Development and Evaluation of a System for the Study of Mineral Nutrition of Sacred Lotus (Nelumbo Nucifera)

Development and evaluation of a system for the study of mineral nutrition of sacred lotus (Nelumbo nucifera).

David. J. Hicks B.Hort.Sci. (Hons.) University of Western Sydney, Hawkesbury

A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

Centre for Horticulture and Plant Sciences University of Western Sydney, Hawkesbury. Australia

July 2005 Acknowledgements

In the capacity of supervisor(s) I would like to thank Dr Tony Haigh (Principal supervisor) for advice and guidance in the areas of experimental design, results interpretation, thesis construction, editing, and patience with a student who in hindsight must have been a frustrating experience. Similarly, Dr Vong Q. Nguyen (Co-supervisor) provided a perspective of the thesis within the Asian vegetable scenario as it is in Australia, helping with employment opportunities in similarly oriented work, patience with my many deadline far misses and his infectious enthusiasm.

On the technical front I would like to note the input of Emma Borchet, Aaron Simmons, Leonie Noakes and Colonel James Sheehy for greasing the wheel with assistance in various trial technical setups and material acquisitions. Further, the staff in Horticulture at UWSH Richmond, too many to identify individually, require recognition for the many small but necessary activities which help to gel the whole, especially CHAPS for funding the tissue analysis. Initially tissue tests were conducted by staff at CSIRO and Agrifoods Technology. Secondary testing was performed by the team at the Waite campus of Adelaide University.

At the industry level, the Rural Industries Research and Development Corporation (RIRDC) deserve recognition for initial funding of the ‘Agronomic and physiological studies of Nelumbo nucifera for export to Asia’ project. Kim and Vicky Jones warrant a mention for allowing the frequent inspection of their fledgling lotus farm and the provision of ‘Green Jade’ rhizomes for planting at Richmond. Thanks to Peter McLaughlin and assorted folk, at the now defunct NORADA, for an unwavering belief in my abilities, encouragement and motivational support.

On the personal side the most thanks are reserved for my family, especially mum and dad for emotional, financial and domestic support including delivery of food preparations, lawn mowing, dishwashing and vacuuming of my seedy hovel. Thanks to brothers Steve and Col for encouragement and motivation. Respect to friends, Dave Gearin, Dean Francis, Matt Barnett, Steve Anderson, Jo Campbell, Matt Carroll, Liz Reichardt, Peter Lister, Jacqui O’Brien and Martin Ayers for enduring support and tolerance. This thesis is dedicated to the lamb of Dog, the Rt. Rev. Dr Jello Fruits, and my lotus flower Imogen.

Statement of Authentication

The work presented in this thesis is, to the best of my knowledge and belief, original except as acknowledged in the text. I hereby declare that I have not submitted this material, either in full or in part, for a degree at this or any other institution.

…………………………………………

David. J. Hicks.

Table of Contents

Volume I Development and Evaluation of a System for the Study of Mineral Nutrition of Sacred Lotus (Nelumbo nucifera).

Abbreviations vi Abstract vii Chapter 1: General Introduction 1 1.1 Background 1 1.1.1 Asian Vegetables 1 1.1.2 Australian Position 2 1.2 Lotus: Old Crop, New Opportunities 3 1.2.1 Lotus Descriptors 3 1.2.2 Uses of Lotus 6 1.2.3 Commercial Potential 7 1.2.4 Crop production: Techniques and Feasibility 8 1.2.5 Constraints to Production 10 1.3 Solution Culture 14 1.3.1 Definitions and History 14 1.3.2 Techniques 15 1.3.3 Media 17 1.3.4 Solutions 17 1.3.5 Uses 19 1.3.6 Rationale for Choice of System for Lotus 20 1.4 Scope of Research 22 1.4.1 Development of a System for Replicated Trials for Lotus 22 1.4.2 Examine the Effects on Growth and Plant Organ Major Nutrient Concentration 23

Chapter 2 Seeds 26 2.1 Introduction 26 2.2 Seed Generation 27 2.2.1 Experiment 1 Observation of the Generation of Lotus (Nelumbo nucifera) Seeds. 27 2.2.3 Materials and Methods 27 2.2.3 Results and Discussion 28 2.3 Seed Germination 29 2.3.1 Experiment 2 Effect of Temperature on the Germination of Lotus (Nelumbo nucifera) Seed.29 2.3.1.2 Materials and Methods 29 2.3.1.3 Results and Discussion 30 2.3.2 Experiment 3 Estimation of the Number of

Seeds to be Sown for the Production of Uniform Lotus (Nelumbo nucifera) Seedlings. 31 2.3.2.2 Materials and Methods 31 2.3.2.3 Results and Discussion 32 2.4 Discussion 34

Chapter 3 Plant Culture 37 3.1 Introduction 37 3.2 Container Trials 38 3.2.1 Experiment 4 Observation Trial on the Effects of N, P and K on Growth and Tissue Composition of Lotus (Nelumbo nucifera) Cultivated in 1 m3 Containers. 38 3.2.1.2 Materials and Methods 38 3.2.1.2 Results and Discussion 39 3.2.2 Experiment 5 Observation of the Growth of Lotus (Nelumbo nucifera) in Containers of Differing Dimensions. 42 3.2.2.1 Materials and Methods 42 3.2.2.2 Results and Discussion 43 3.3 Solution Quality 44 3.3.1 Experiment 6 Effect of Solution Electrical Conductivity on Growth of Lotus (Nelumbo nucifera). 44 3.3.1.1 Materials and Methods 44 3.3.1.2 Results and Discussion 45 3.3.2 Experiment 7 Effect of Solution pH on Growth of Lotus (Nelumbo nucifera). 51 3.3.2.1 Materials and Methods 51 3.3.2.2 Results and Discussion 52 3.3.3 Experiment 8 Observation of Growth of Lotus (Nelumbo nucifera) from Cuttings. 57 3.3.3.1 Materials and Methods 57 3.3.3.2 Results and Discussion 57 3.3.4 Experiment 9 Observation on the effect of Algaecides on the Growth of Lotus (Nelumbo nucifera) and Control of Solution Algae. 59 3.3.4.1 Materials and Methods 59 3.3.4.2 Results and Discussion 59 3.4 Discussion 61

Chapter 4 Analysing the Interaction between Nitrogen and Lotus 64 4.1 Introduction 64 4.1.1 Experiment 10 Effect of Nitrogen on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera) 67 4.2 Materials and Methods 67 4.2.1 Plant Culture 67 4.2.2 Experimental Design 69 4.3 Results 72 4.3.1 Observations of Nitrogen Supply on Visual Growth Expression. 72 4.3.2 Nitrogen Supply Effect on Growth Parameters. 74 4.3.3 Effect of Nitrogen Supply on Organ Nutrient Concentration. 79 4.3.4 Analysis of Major Nutrient Concentration as a Function of Nitrogen Concentration. 84 4.3.5 Analysis of Growth as a Function of Organ Nitrogen Concentration. 90 4.3.6 Analysis of Total Dry Mass as a Function of Nitrogen Affected Growth Parameters. 96 4.3.7 Analysis of Growth Parameters Affected by Nitrogen Concentration, as a Function of Nitrogen Concentration Affected Organ Nutrient Concentration. 98 4.4 Discussion 103

Chapter 5 Analysing the Interaction between Phosphorous and Lotus 116 5.1 Introduction 116 5.1.1 Experiment 11 Effect of Phosphorous on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera) 119 5.2 Materials and Methods 119 5.3 Results 120 5.3.1 Observations of Phosphorous Supply on Visual Growth Expression. 120 5.3.2 Phosphorous Supply Effect on Growth Parameters. 121 5.3.3 Effect of Phosphorous Supply on Organ Nutrient Concentration. 126 5.3.4 Analysis of Major Nutrient Concentration as a Function of Phosphorous Concentration. 131 5.3.5 Analysis of Growth as a Function of Organ Phosphorous Concentration. 138 5.3.6 Analysis of Total Dry Mass as a Function of Phosphorous Affected Growth Parameters. 145

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5.3.7 Analysis of Growth Parameters Affected by Phosphorous Concentration, as a Function of Phosphorous Concentration Affected Organ Nutrient Concentration. 147 5.4 Discussion 152

Chapter 6 Analysing the Interaction between Potassium and Lotus 157 6.1 Introduction 157 6.1.1 Experiment 12 Effect of Potassium on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera) 159 6.2 Materials and Methods 159 6.3 Results 160 6.3.1 Observations of Potassium Supply on Visual Growth Expression. 160 6.3.2 Potassium Supply Effect on Growth Parameters. 161 6.3.3 Effect of Potassium Supply on Organ Nutrient Concentration. 166 6.3.4 Analysis of Major Nutrient Concentration as a Function of Potassium Concentration. 171 6.3.5 Analysis of Growth as a Function of Organ Potassium Concentration. 177 6.3.6 Analysis of Total Dry Mass as a Function of Potassium Affected Growth Parameters. 181 6.3.7 Analysis of Growth Parameters Affected by Potassium Concentration, as a Function of Potassium Concentration Affected Organ Nutrient Concentration. 182 6.4 Discussion 185

Chapter 7 Analysing the Interaction between Calcium and Lotus 189 7.1 Introduction 189 7.1.1 Experiment 13 Effect of Calcium on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera) 192 7.2 Materials and Methods 192 7.3 Results 193 7.3.1 Observations of Calcium Supply on Visual Growth Expression. 193 7.3.2 Calcium Supply Effect on Growth Parameters.194 7.3.3 Effect of Calcium Supply on Organ Nutrient Concentration. 198 7.3.4 Analysis of Major Nutrient Concentration as a Function of Calcium Concentration. 203

7.3.5 Analysis of Growth as a Function of Organ Calcium Concentration. 209 7.3.6 Analysis of Total Dry Mass as a Function of Calcium Affected Growth Parameters. 214 7.3.7 Analysis of Growth Parameters Affected by Calcium Concentration, as a Function of Calcium Concentration Affected Organ Nutrient Concentration. 215 7.4 Discussion 218 Chapter 8 General Discussion and Conclusions 222 8.1 Introduction 222 8.2 Effects of Nutrients 222 8.2.1 Nitrogen 222 8.2.2 Phosphorous 227 8.2.3 Potassium 229 8.2.4 Calcium 232 8.2.5 Other Nutrients 235 8.2.6 Critical Concentrations and Adequate Supply Rates. 236 8.2.7 Organ for Field Testing 240 8.2.8 Nutrient Concentration in Plants, Biomass-Partitioning and Uptake for the Most Effective Treatment. 242 8.3 Analysis of the Effectiveness of the Research 245 8.3.1 Significance of the Research and Results. 247 8.4 Further Lotus Investigations 249 8.5 Potential System Improvements 252 8.6 Conclusions 258

9.1 References 261

Volume II Appendices

Abbreviations

ANOVA Analysis of Variance

CSIRO Commonwealth Scientific and Industrial Research Organisation

F dist. F distribution value

HDPE High density polyethylene

LA Total leaf area

LfNo Number of leaves

LDM Leaf dry mass

N Total nitrogen

NFT Nutrient flow technique

NH4-N Ammonium nitrogen

NO3-N Nitrate nitrogen

NoNo Number of nodes

PDM Petiole dry mass ppm Parts per million

RDM Roots and stolons dry mass

RSS Residual sum of squares

S.E. Standard error

STEM™ Standard Trace Elements Mix

StLgth Total stolon length

StNo Number of stolons

TDM Total dry mass wgt Weight

XRF X-Ray Fluoroscopy

vi Abstract

The sacred lotus (Nelumbo nucifera) is a large aquatic plant endemic to subtropical and tropical Asia and Northern Australia. Lotus has a combination of morphological and anatomical features that make it challenging for research work. The necessity of research on lotus is driven by niche market opportunities identified in Japan during counter seasonal production periods. Several features of lotus are utilised for consumer applications with commercial promise including seeds, young shoots and rhizome production. Further, the flowers and seed pods have value as cut-flower products and religious decoration.

Several challenges have to be overcome before production of adequate products can be realised in Australia. The challenges which can be addressed most immediately are the questions regarding plant nutrition for lotus. Information regarding plant culture and nutritional requirement, has not been adequately reported. Organ critical concentrations for all nutrients, adequate nutrient supply range, identification of an appropriate organ for field sampling, and calibration of field and container-grown nutrition data, require attention. In order to accomplish these objectives, development of a system for growth and analysis of imposed nutrient treatments in replication, which accommodated a plant with unusual and seasonal attributes, was essential. Therefore, a closed solution culture with a coarse gravel media contained in plastic pails under semi-controlled conditions was utilised to study the vegetative period of growth before flowering.

In order to test the system, the major nutrients N, P, K and Ca were trialled to provide indicators of critical concentrations, adequate supply range and suitable

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organs for testing. Concentrations of minor and trace elements in organs were also documented. Tentative critical concentrations at 90% of growth for deficiency of

2.66 % N, 3.9 g kg-1 P, and 9.97 g kg-1 Ca, were estimated. Toxicity concentration values of 4.25 % N, 6.00 g kg-1 P, and 19.30 mg kg-1 Ca were estimated. Adequate supply ranges of 253 to 439 ppm of N, 20 to 60 ppm of P, and 82 to 195 ppm of Ca were extrapolated. The adequate supply range and critical concentration for K could not be determined. Leaves were determined to be the most appropriate organs for field sampling and analysis, having the greatest incidence of sensitivity to nutrient variation. These results, whilst not conclusive, provide a solid reference for any future research on lotus nutrition. Recommendations are made for design and enhancement of the system to provide guidelines for future research.

viii 1

Chapter 1 General Introduction

1.1 Background

1.1.1 Asian Vegetables

Asian vegetables are products which have been defined as either “vegetables which originated from Asia” or “vegetables which are consumed by people of Asian origin”

(Nguyen 1992). They are classed according to edible plant part into leaf, fruit and root types of vegetable (Waters et al. 1992).

In the past 15 years, there has been a plethora of information regarding Asian vegetables. The nature of the information has been both commercial potential

(Nguyen 1992, Pan 1995, Lee 1995, Vinning 1995 and et al. 2003, Midmore 1997,

Midmore and Cahill 1998, and Nguyen 2001) and production methodology (Waters et al. 1992, McVeigh and Tan 2001, Kleinhenz et al. 2000, and Morgan and

Midmore 2002, 2003a, 2003b). However, with a complement of over 300 species and more cultivars (Chen and Zhu 1998), the information generally concerns a select few, leaving a great many aspects to be reported on. Market requirements are constantly changing, identification of which products are required is continually evolving and the production techniques for the exact market requirements of most products are not understood or known to growers in Australia. Therefore, it is necessary to evaluate production in Australia, based upon recognised market requirements for select products.

1.1.2 Australian Position

Australia has several key components to satisfy the market requirements for a wide variety of fresh products (Pan 1995). Essentially, Lee (1995) reports that Australia, as a southern hemisphere producer, can supply fresh products for the northern hemisphere counter season when prices are at a premium due to supply shortfalls.

Australia has an image of being ‘clean and green’ whose fresh products are well produced under strict environmental conditions. Further, as a large body of land incorporating a wide latitudinal range, the growing conditions for any product should be able to be found (Hicks 2001).

One product which has been identified with potential for fresh import replacements of processed imports, and for export to high value markets as a fresh product, are the rhizomes of lotus (Pan 1995, Vinning 1995, Nguyen 2001, Nguyen and Hicks 2004).

1.2 Lotus: Old Crop, New Opportunities.

1.2.1 Lotus Descriptors

An unusual plant by any measure, the Indian or sacred Lotus (Nelumbo nucifera

Gaertner, syn Nelumbium speciosum Willd., Nelumbium nelumbo Druce, Nymphaea nelumbo L.) is a perennial herbaceous plant confined to an aquatic environment

(Hicks and Haigh 2001, Sainty and Jacobs 2003). It is one of the oldest cultivated plants known to mankind (Swarup 1989). It is a plant regarded as sacred in Chinese and Indian cultures and is associated with Buddhism and Hindu religions (Herklots,

1972). Its flowers are often metaphorically depicted in religious symbolism, representing the spiritually pure soul rising from the turgid miasma of existence

(Lovelock et al. 1986).

Lotus is distributed across Asia from Japan to North-East Africa (Borsch and

Barthlott 1996). It covers a broad latitudinal span from Beijing 40o N to as far south as Northern Australia 20o S. Flach and Rumawas (1996) believe it to have been transported to most of these locations and speculate that its true centre of origin is

India.

Lotus has a strikingly distinct morphology. A large plant, which apart from dwarf varieties, grows up to 15 m in stolon length (Liu 1994). Most of the lotus plant is unseen as the stoloniferous stems are anchored in the pond substrate. It is only the large peltate leaves (50-750 mm diam.) and distinct flowers which are visible to the observer. The initial leaves produced from a young stolon are floating before emergent leaves borne on spiny 1-2m petioles dominate (Sainty and Jacobs 2003).

The leaf epidermis is covered by epicuticular wax crystalloids which prevent surface contamination due to the water repellancy known as the ‘Lotus-Effect’ (Barthlott and

Neinhuis 1997). Flowers are solitary (10-20 cm diam.) and rise from leaf axils above emergent leaves (Sainty and Jacobs 2003) and open and close depending upon ambient temperatures (Seymour et al. 1998). The reproductive structures in lotus consist of an obconical receptacle housing a multi-carpellary gynoecium, which looks like an inverted watering can rose, and develops into a head of nutlike achenes

(Swarup, 1989). Numerous 15-20 mm linear stamens subtend the receptacle

(Sculthorpe 1967). The below-ground structures, consist of stolons, internodes with fibrous feeder roots and the overwintering rhizome storage organs. Stolon segments can reach 1m in length and be up to 30 mm diam (Ni 1987). Stolons tend to grow horizontally about 20 cm below the surface of the substrate allowing feeder roots to penetrate into free water. Rhizomes develop as a response to stress in the environment. Rhizomes resemble a chain of sausages approximately 50 cm long divided into 3 to 4 segments, 50 to 150 mm in diameter, with distinct internodes

(Nguyen 2001).

Sacred Lotus is widely reported as one of two species within the Nelumbo genus, the other being N. lutea or North American Lotus. Botanists originally assigned

Nelumbo to its own family, Nelumbonaceae, within the order Nymphaeales

(Sculthorpe 1967). Arguments are currently inconclusive and some taxonomists place the Nelumbo genus to the family Nymphaeaceae (Tivota and Batygina 1996).

The number of varieties is in the hundreds and would be difficult to establish precisely (Ni 1987). Some argue that the Nelumbo genus contains 1 species nucifera, with two sub-species nucifera and lutea (Borsch and Barthlott 1996). A point of

5 view that seems extremely compelling and acceptable. According to Borsch and

Barthlott (1996), the only difference between subspecies is flower colour. Recent developments in gene phylogeny place the genus Nelumbo in the Proteales clade

(APG 1998) quite a significant distance in the evolutionary development of flowering plants from the previous placement amongst the Nymphaeaceae (APG II

2003).

Anatomically, lotus has been the subject of scientific investigation and conjecture for over 120 years. This has included debate over the familial classification and whether lotus is monocotyledonous or dicotyledonous (Esau and Kosokai 1975). Evidence during the latter half of the 20th century focused upon anatomical features to support proposed theories. Esau (1975) found that while “the absence of secondary growth in vascular bundles of lotus is reminiscent of monocotyledons, the specific type of protein-containing plastid uniformly seen in monocotyledons is not found in lotus.”

Rather lotus was found to be rich in a starch-containing plastid common to many dicotyledons. Titova and Batygina (1996) found the lotus embryo to have a single primordium, and was therefore, a monocotyledon. Investigations into the chloroplasts of lotus plumules lead Bao et al. (1992) to argue that lotus could have evolved a special developmental pathway, separate from the accepted taxa of mono or dicotyledons. The most obvious anatomical feature of lotus, displayed in all organs, are the large and small air ducts known as lacuna, structures which facilitate gas exchange (Sculthorpe 1967). The recent reorganisation of the phylogeny of the angiosperms based on gene sequences determined lotus to be a true Eudicot, definitely not a monocot (APG 1998, APG II 2003).

Lotus utilises a special pressurised two-way gas transport system which allows the plant to take its oxygen from the atmosphere rather than the soil (Mevi-Shutz and

Grosse 1988). Control of pressurised internal gases also allows lotus to thermo- regulate. This in turn provides an environmental niche within flowers for example which protects pollinating beetles overnight from low temperatures (Seymour and

Schultze 1996). Seed longevity also singles lotus out from other plants. Lotus has some of the oldest known viable seeds in the world. Shen-Miller et al. (1995) report

1500 year old seeds have been germinated. Maeda et al. (1996) reported that the metabolic activity of 400 and 500 year old lotus seeds was similar to that of fresh seeds. Lotus seeds are highly heterozygous (Yang and Zhou 1998).

1.2.2 Uses of Lotus

Lotus provides a food source, floricultural products and is used as an ornamental feature plant in landscapes (Ni 1983). It also has potential for use in filtering nutrients from water in recycling systems (Nguyen 2001).

Lotus rhizomes are used as a fresh cooked vegetable with 15-16% carbohydrate concentration (Miura 1988). The market requires three to four uniformly sized and shaped segments per rhizome that are creamy white and unblemished in appearance

(Nguyen and Hicks 2004). Rhizomes are also presented as value-added products in frozen, salted and dried forms. Seeds are also consumed raw and cooked with the testa and bitter embryo removed (Flach et al. 1996).

As a fresh cut flower, lotus has a very limited vase life. Flowers must be harvested prior to opening. Green and dried pods are also marketed as products of the flower

7 industry. Green pods have a longer vase life than flowers, and dried pods last for years though are very brittle and easily damaged (Nguyen 2001).

As an ornamental or landscape feature plant, lotus is often found cultivated in temples throughout Asia (Ni 1987). It is increasingly being used for parks and even home gardens where enough space can be provided for adequately sized ponds

(Nguyen 2001).

A future potential use for lotus may be in the filtration of water from commercial situations such as nurseries or other agricultural endeavours where water has been contaminated with nutrients. As a large gross feeding plant it could provide a valuable sink for excess nutrients and provide an alternative source of income through the flowers. Used in combination with a floating aquatic plant such as

Azolla sp., nutrients could be removed from water.

1.2.3 Commercial Potential

New opportunities described by Nguyen (2001) for the Japanese fresh and salted lotus rhizome markets have revealed a niche opportunity for southern hemisphere growers during the months of June to August inclusive. During this time, Japanese and other Northern Hemisphere growers cannot supply adequate amounts of fresh material. Further, due to land constraints and priority for rice in Japan, production of lotus has declined, and lotus was imported from China between 1985 and 2000. New information suggests the quality of Chinese product is inferior to that required in the

Japanese market and fresh exports from China into Japan have been suspended

(Nguyen and Hicks 2004). However in 2003, Japan imported 1 000 tonnes of fresh rhizomes, valued at ¥918, ¥821, and ¥445 per kg for June to August, and more than

10 000 tonne of salted rhizomes (Nguyen and Hicks 2004).

Additionally, the Australian domestic market has a similar requirement for fresh lotus rhizomes estimated at up to 1 000 tonnes (Nguyen 1999). Current supply driven by a sole commercial operator in the Northern Rivers region of NSW, is approximately 120 tonnes. Consumers utilise frozen, salted, and dried product to augment the shortfall.

The quality of the domestic product is affected by varietal choice, difficulties encountered in the production process, and handling practices in the supply chain.

Observations of lotus in retail outlets in the Sydney region reveal a poor quality of product that is often infected by fungal pathogens such as Botrytis sp. The value of lotus at the farm gate has remained reasonably stable for the past 5 years at $4-6 kg-1.

Retail prices are often observed at $8-10 kg-1 (Nguyen and Hicks 2004).

1.2.4 Crop Production: Techniques and Feasibility

The general requirements for growth of lotus are well documented (Ni 1987, Honda

1987, Liu 1994, Nguyen et al. 1998 and Nguyen 2001). However, the specific requirements to grow and crop lotus successfully for a desired product are not well documented or adequately detailed and can at times be contrary to the recommendations for growth. For example the general recommendations state that lotus prefers a sub-tropical to tropical environment in full solar aspect with

9 temperature ranges between 20-30oC, and is frost sensitive (Honda 1987, Sainty and

Jacobs 2003). However, for rhizome production, a temperate environment is preferred and frost has no effect on the rhizomes insulated by the pond substrate. The pond for any lotus growing application should be in a protected, full sun position

(Nguyen and Hicks 2004).

Soil recommendations for growth dictate that organic matter rich in nitrogen should be incorporated into the substrate (Liu 1994). The best soil though for rhizome production is a soft silty loam, 1 m in depth to accommodate the rhizome which forms at greater depth than the stolon. Soft soil which emulsifies and is suspended in the water at the pond bottom and exerts little or no compressional pressure on developing rhizomes is recommended, otherwise rhizomes are produced flat or miss- shapen (Nguyen 2001). Organic matter is best avoided when cropping for rhizomes to reduce host sites for potential pathogens and to prevent the release of unknown chemical residues into the pond (Horne and Goldman 1997). The nutritional balance of fertiliser applications has not been thoroughly investigated (Hicks and Haigh

2003).

The depth of the pond water should be no more than 2.5 m. Again for rhizomes, the depth of the water over the soil should be no greater than 50 cm and even across the pond to mediate pond water temperature and facilitate harvesting (Nguyen 2001).

Land to hold replacement pond water and a catchment area for spent pond water is advisable. Harvesting is undertaken during winter months and is labour-intensive

(Armstrong 2002). Inconsistent yield data have been reported at between 4 to 40 tonnes per hectare (Rubatsky and Yamaguchi 1997, Nguyen 2001), although yield is

10 most likely around 10 tonnes per hectare (Nguyen and Hicks 2004). Lotus rhizomes are highly perishable and should be kept at temperatures between 5 and 10o C

(Nguyen 2001).

The production process should be viewed within a dedicated system with allocated resources that are continuously available during the cropping season (Hicks and

Haigh 2001). Therefore, planning and financial input for setting up is greater than for most other horticultural crops. Land to be used must be flat and have access to adequate volumes of fresh water, commensurate with the operation size available.

Ponds must be constructed specifically for lotus and should be designed on the basis of available resources and harvest method (Nguyen and Hicks 2004). The types of regions within Australia which satisfy all the environmental demands are in limited supply.

It is possible to produce lotus in Australia, though the environmental conditions for adequate production reduce the number of potential locations. Australia is a very dry continent, and substantial volumes of water are not often located where the best land for cropping is located (Hicks and Haigh 2001). Success for any potential grower would rely on careful planning and adequate financial inputs to address the constraints to production.

1.2.5 Constraints to Production

There are a number of constraints to establishing a large-scale lotus industry in

Australia. First of these is choice of variety. An unsuitable variety, labelled

Quandong after its place of origin in China, is currently used in Australia by the sole

11 known commercial rhizome producer (Hicks and Haigh 2003). This variety produces rhizomes with inconsistent shapes and sizes. It is not a variety recognised by the target market in Japan and is regarded as having an inferior flavour (Nguyen

2001). Further development of any industry with this variety cannot be encouraged.

More suitable varieties have been identified though are difficult to obtain.

Importation of Japanese varieties is restricted due to an embargo preventing export of its cultural treasures by Japan. Chinese varieties require approval before release to foreign applicants (Nguyen 2001). Because of Australian quarantine measures to prevent importation of diseased material and aquatic fauna, live plant material importation into Australia has been restrictive. Seed importation is possible and has been achieved (Nguyen 2001). However, seeds are highly variable in their genetic integrity and cannot be relied upon to provide genetically uncompromised material for reproduction (Yang and Zhou 1998).

Research must start with the development of a research methodology in which nutritional requirements can be examined. The lack of information on plant growth and organ response to nutritional applications dictates this starting point. The exact nutritional requirements for particular applications are unknown (Hicks and Haigh

2003). Tissue nutrient concentrations have only been reported twice for lotus (Qu and Zhou 1991, Nguyen 2001). If an industry is to be established for the production of export quality produce then it is vital that the nutritional requirements be determined.

A mechanical harvest technique needs to be developed. Australian harvest labour is reticent to work in ponds during winter (Armstrong 2002). The development of an harvest implement, mechanising the process, would be difficult to justify in the absence of an established industry growing the correct varieties under the correct conditions. A development of this type is an engineering issue rather than a horticultural investigation.

As indicated previously, postharvest parameters for the crop are not known.

Preliminary investigations into storage temperature have been accomplished but provide a starting point only for more intensive research (Nguyen 2001). To be successful in exporting to Japan the postharvest requirements need to be determined.

This can only be accomplished once the quality issues have been resolved.

A lotus growing operation restricts the operator’s options for land usage, most aquatic crops require dedication of resources to the one single activity and change to any other crop type is not easily implemented (Hicks and Haigh 2001). Growers cannot respond to changes in the market place. The greatest impediment to establishing a lotus growing operation, once the other constraints have been satisfied is financial. The cost of setting up a lotus growing operation is very high (Nguyen and Hicks 2004).

The fate of an emerging lotus cultivation industry in Australia is reliant upon the satisfaction of several key events. Firstly, the correct variety must be sourced for the destined market. This has proved difficult as discussed above. Secondly, the method of cultivation, producing the highest quality of product possible at the lowest possible production cost is required. Aspects of this could be satisfied using the

13 current varieties. Thirdly, postharvest investigations into storage conditions and handling of lotus products for market are necessary. For rhizomes this is not possible due to the restricted availability of rhizomes in an emerging industry. Flower products could be studied, though the market size for these products is not of significant importance to follow this line of inquiry. Finally, establishment of market contacts and agreements in the appropriate marketplace should be determined in order to trade rhizome products. However, without a ready supply of suitable quality rhizomes, trade negotiations would be a wasted effort. Therefore, this study concentrated on cultivation methods in the area of plant nutrition. The most appropriate way to make an investigation of this nature is through the use of solution culture techniques.

1.3 Solution Culture

1.3.1 Definitions and History

Solution culture is a term synonymous with soil-less culture and hydroponic culture of plants (Jones 1982). It is a technique of producing plants for a variety of applications where the plant draws all of its mineral nutrition from prepared solutions

(Resh 1978). In contrast, conventional soil-grown plants source their minerals from the media in which they are grown, receive mechanical support, have variable amounts of space for roots, and experience temporal differences in nutrient availability (Asher and Edwards 1983). The definition of solution culture encompasses a wide variety of techniques which incorporates a palette of different media types and solutions. The terms soil-less and hydroponic are inherently confusing as they imply that no media is present in the cultural techniques. This is true of some techniques, and while no minerals are sourced from the media, quite often different techniques require the presence of an inert material to provide physical support and restriction of light to the root organs.

The history of solution culture is relatively long, beginning with documents reporting irrigation of gardens in Babylon during pre-modern times (Resh 1978). Solution cultures have been coupled with plant physiology since experimentation in the 1600s and more significantly from the 1800s to the present (Jones 1982, Asher and

Edwards 1983). Therefore, the considerable volume of available literature is diverse and reflects the developments in plant physiology. Currently, most of the research foci has been on elaboration of the technical and environmental requirements, and evaluation of suitability of species and cultivars. This includes solution formulation,

15 media evaluation and plant physiology interpretation, using the available techniques and materials (Schwarz 1995). There are a number of symposia dedicated to solution culture and related factors, including those held by the International Society for

Soilless Culture and the sub-working group for growth media and hydroponics under the auspices of the International Society for Horticultural Science. The proceedings of these symposia and a number of plant physiological journals house the available literature, a body too large to summarize for this purpose.

Details of the complexity of components for the variety of solution culture techniques, have been documented adequately in the literature (Resh 1979, Asher and Edwards 1983, Schwarz 1995, Jones 1997). A brief summary of the relevant aspects of solution culture is presented along with a rationale for the selection of components of a system for the evaluation of mineral nutrition of lotus.

1.3.2 Techniques

1.3.2.1 Open systems

Also known as the run to waste technique, open systems apply the solution once only

(Jones 1997). The solution is taken up by plants, is adhered to media surfaces for temporally displaced plant uptake or moves beyond the plant root structures into disposal. Media associated with this method typically have high surface area to volume ratios for moisture retention (Resh 1978). The benefits of such a method include low management of nutrients, simplicity of the system with comparatively lower reliance on technical controllers, and a reduction in the possible incidence of

16 pathogens being introduced to the plant roots. Drawbacks include the expense and disposal of resources which are only utilised for a single application (Jones 1997).

1.3.2.2 Closed systems

In the closed system, the solution is utilised and recycled for more than one application. This can be in the form of continually flowing solutions or intermittently delivered solutions. Nutrient flow technique systems (NFT) generally have no apparent applied media and plants are given support from the closed plastic troughs and artificial binding with string for large plants. The solution is delivered continuously or intermittently `in a thin film so that root structures may draw oxygen from the space left in the trough which the roots inhabit (Cooper 1979). The latter includes ebb and flow or flood and drain systems, and employs media which hold solution in between solution delivery (Jones 1997). Solutions are regularly monitored for nutrient strength, electrical conductivity and pH. Inconsistencies with the required solution are amended with additional stock or topping up nutrient solutions and pH adjusters (Jones 1997). Total solution exchanges are made at predetermined frequencies to eliminate solutions with accumulation of nutrients which are not taken up by plants, for example sulphates. The benefit of a closed system is reduced resource inputs. Disadvantages include; the necessity of close monitoring of solutions which have low buffering capacity to nutrient withdrawal, addressing disposal logistics of waste-solutions, the possibility of recirculating pathogens, and the extra complexity and reliance on technology.

1.3.3 Media

The use of media in solution culture is to provide mechanical support to the plant, hold solution nutrients adhered to surfaces, and to exclude light from root structures

(Schwarz 1995). Media should be inert and not provide nutrients (Resh 1978).

Adhesion of solution to media surfaces is necessary depending upon the system in employment (Jones 1997). Types of media most regularly used include sand and gravel which have a low surface area to volume ratio compared to igneous rock derived substrates such as perlite, vermiculite and rock wool (Schwarz 1995).

NFT systems where plant roots are contained within a plastic trough and supplied with a film of nutrients (Cooper 1979), suggest no media is present to support the plant root structures. However, an interpretation could suggest that the plastic troughs are the media with an extremely low surface area to volume ratio. The notion that solution cultures can be discriminated, according to absence of media, is a function of interpretation. This study interprets a view that all plants, soil bound or solution culture, grow in a substrate of some kind, and only the ratio of surface area to volume ratio of the media, the total exchangeable ionic potential, presence of microfauna and unrequired chemicals, and the density of media have a variability according to composition.

1.3.4 Solutions

Composition of solutions has been the subject of conjecture since the advent of solution culture experimentation and imposition. The mineral requirements of plants in general, has been satisfactorily acknowledged and solution cultures contain the

18 identified mineral nutrients determined for plant growth. The ratio of these nutrients is modified for individual plant species and the environments in which the plants are grown.

Solutions must contain the major nutrients N, P and K, the minor nutrients Ca, Mg and S, and the trace elements Fe, Mn, Zn, Cu, B and Mo. The elements N, P, S and

Mo are usually delivered into solution as the compounds NO3 or NH4, PO4, SO4 and

Mo7O24. The concentrations required have been the subject of conjecture since the advent of solution culture and a number of solutions have been proposed. Jones

(1997) provides a comprehensive list of solution variations and cites the importance of the work reported by Hoagland and Arnon (1950). Asher and Edwards (1983) propose the use of dilute solutions in flowing culture systems which require large reservoirs of solution as compensation for the diluting effect of plant nutrient uptake.

This concept allows a method of direct comparison and calibration of plant growth results with those grown in field situations. Questions over the applicability of critical concentrations derived from solution culture have been raised due to the differences between solution cultures and soil solutions, which typically, are not of equal ionic strength.

The balance between nutrients is regarded as a more important aspect of solution composition than overall concentration (Schwarz 1995). Steiner (1984) argues the possibility of a universal solution which can be applied to any crop situation where the plants will selectively take the nutrients they require as needed, provided the nutrients are in a great enough concentration. Commercial preparations of stock solutions employ this argument, providing nutrients in large concentrations of

19 predetermined ratios. Typically, stock solutions are divided into separate A and B

(sometimes C containing trace elements) batches to prevent precipitations of salts with low solubility such as Ca and PO4 and SO4 (Schwarz 1995).

Critical to the solution environment is the pH and its electrical conductivity (EC).

Most plants grow optimally in the range between pH 5.5 to pH 6.5, though a great number of plants have their optimum outside this boundary and many others will tolerate conditions that are not ideal (Islam et al. 1980). The acidity or alkalinity of a solution will influence the interaction of nutrient molecules within and contribute to the availability of certain nutrients (Schwarz 1995). Conversely, the uptake of nutrients will affect the level of pH as the solution changes. Therefore, pH is monitored regularly and adjusted with strong acids and bases consistent with the particular requirement (Jones 1997).

The EC of a solution is an indication of the total amount of salts in the solution measured by the conductivity imparted by nutrient salts in solution and expressed as dS m-1, mmhos cm-1 or cf (Jones 1997). Its measurement does not distinguish between the components in the nutrient solution. Typically, the strength of solutions can vary for different plant species and range in value from 0.5 to 4 dS cm-1.

1.3.5 Uses

Solution cultures are used for the commercial production of food and cut flowers, research and education purposes (Jones 1982). Plants grown in solution culture are used as educational aides in teaching plant nutrition and botany. Demonstrations of nutrient use by plants, and effects on plant growth, are easily solicited through

20 systems in which the correct amount of nutrients can be closely applied and maintained. Similarly, whole plants can be easily produced for study, which under soil grown conditions, root structures would be difficult to obtain (Asher and

Edwards 1983).

It is in the area of research where solution culture was first established and refined.

The use of solution cultures eliminates a large body of unknown factors which may be associated with soil production. The researcher can calculate, then apply nutrients in known concentrations, providing easy evaluation of the response in plant growth and change in solution quality. The isolation and manipulation of one or more elements, pH level, EC, or root temperature for study is possible with solution cultures. Most derived critical concentrations and nutrient requirement evaluations for a large number of plant species have been established using solution cultures

(Asher and Edwards 1983).

1.3.6 Rationale for Choice of System for Lotus

The basis of choice of components to determine a system for study of the nutritional requirements of lotus must recognise a suite of attributes which need to be satisfied.

The system must permit sufficient growth and development of the plant and provide substrate for anchorage of below-ground parts. Therefore, the system must contain a medium which has the physical strength to anchor the growing plant sections allowing for stolons to penetrate, and leaves to emerge over a large surface area.

This stipulation rules out an NFT application.

Lotus is an obligate aquatic plant and needs to be permanently submerged in a solution. Lotus grows in ponds with minimal movement of the solution, so the system must be closed with minimal solution movement. Assuming the Steiner

(1984) theory has relevance, regarding solution quality, a commercially available nutrient was implemented as a constant to evaluate lotus requirements.

Finally, financial restrictions and the need for simplicity (Asher and Edwards 1983) dictate conditions. Initial indicators for requirements of plants and system are necessary before financial outlays on more elaborate systems are operated.

Therefore, the system by necessity should allow for the subterranean growth of stolons, permit leaves to breach the solution surface wherever they may occur, deny the penetration of light, contain the required solution and be of a size adequate for a large plant. The system must have the ability to allow solution change and any manipulation on a regular basis. The system must be able to solicit significant growth differences from imposed treatments.

1.4 Scope of research

The broad aims of this study were to examine the effects on growth and plant tissue composition of major nutrients. This could only be accomplished with the development of a research platform from which lotus could be challenged with nutrient treatments. Therefore, confirmation of the primary objective of this study, could only be distinguished with the first of the two aims. That is, determine the critical concentrations and adequate region of major nutrients in tissues with relation to the growth achieved. These are discussed in further detail.

1.4.1 Development of a System for Replicated Trials for Lotus.

The literature available demonstrates that no adequate platform from which research can be performed has been established. Any knowledge on lotus has been gleaned from crops growing in large ponds. Costs involved in the construction and maintenance of suitable pond structures necessitate that a smaller-scale be used.

Further, extraction of plant parts from ponds, which are usually dug, require expensive machinery, extra labour, and not all plant parts may be recovered.

Therefore, it is vital that a smaller-scaled system for lotus study, which can be operated by a single individual and with low resource inputs, be examined. Hence there is a need to identify a system which will satisfy research objectives in a physical situation and within a defined period of time. However, lotus stolons may grow to 15 m in length, therefore, any research system must accommodate or consider the physical requirements of the plant and be capable of expressing the treatment impositions in a consistent and expected way.

To confirm the hypothesis that a system can be developed for lotus study which has pertinence to a larger commercial activity, the aims to satisfy this objective were

1. Establish that any results obtained in small scale system can be extrapolated

to larger-scaled situation.

2. Establish that any proposed system can be implemented and treatments

imposed will generate consistent and significantly different results on a

replicated basis.

3. Establish that the proposed system can perform the function of solving a

problem.

This leads to the detail for the system justification, in this case, nutritional responses by lotus.

1.4.2 Examine the Effects on Growth and Plant Organ Major Nutrient Composition.

In a closed system such as a pond or container, there is a need for tight nutrient management. All nutrients added to the system, mostly remain within the system and are in direct contact with plant sub-surface organs. Nutrients do not leach through the soil like nitrogen for example and not all nutrients will bind to soil particles as phosphorous does. Further, plant roots in a pond cannot grow in a direction away from high nutrient concentrations as a terrestrial plant can. Pond water during times of growth for lotus is in a state of equilibrium due to small-scale water movements (Horne and Goldman 1997, Sculthorpe, 1967).

The current information available in the literature on lotus nutrition is limited, or inadequate in its scientific rigour. Details of tissue composition or nutrient supply levels have not been properly investigated. Hence, the critical concentrations for

24 maximum growth are not fully understood and growers in a commercial operation have only rudimentary guidelines for lotus nutrition. This has led to present inconsistencies in crops and signs of disorder appearing (Jones K 2001 pers. comm.

11 November).

Response to nutrient, by other ‘Asian vegetables’, similarly, has not had thorough investigation. For some Asian vegetables, such as those belonging to the

Brassicaceae, some estimation of nutrient requirement may be able to be based upon established relationships for well studied relatives. Lotus has no close relatives from which to draw information on nutritional requirements. The closest plants in morphology and aspect, Nymphaea spp., or water-lilies, provide no information. For indications of potential nutrient requirements, allocation within the plant, choice of organ or part for sampling and stage of growth at sampling, it is necessary to cross- reference crop plants which have similar characteristics. Waterchestnut (Eleocharis dulcis Burm. f.) is similar to lotus in that it is aquatic, herbaceous and forms an overwintering storage organ (Kleinheinz et al. 2000). It is widely dissimilar in plant form and significantly different in size, which could affect uptake and partitioning of nutrients in a way anomalous to lotus requirements. Terrestrial crops such as sweetpotato (Ipomoea batatas (L.) Lam.) and yam (Dioscorea alata L.) could offer greater insight as these plants have a similar biomass, grow via spreading runners, and produce large storage organs (Onwueme and Charles 1994; O’Sullivan et al.

1997). The common or ‘Irish’ potato (Solanum tuberosum) has had extensive work reported and as such will provide a comparison with well established information.

The recent inclusion of Nelumbonaceae in the Proteales (APG 1998) suggests comparison with other members of this order is necessary. The morphology and

25 strata upon which the sister members of the Proteales clade are endemic, suggest the comparison is unnecessary. Therefore, for comparison of the effect of nutrients on lotus organs, this study utilised available information for species with similar characteristics. Species which were different were also used to contrast the wide variety of effects nutrients can have on plant tissues and organs.

This study attempted to address the nutritional requirements of lotus during the vegetative growth phase. The central aims were to:

1. Determine the projected correct nutrient regime for lotus for the vegetative

growth stage;

2. Define the critical concentrations for major nutrients

3. Establish the most appropriate organ(s) for field sampling

4. Provide an index of (nutrient) disorders of the major elements so that growers

and agronomists can approximate the relative health of their plants and then

calculate the amount of whichever particular fertiliser is needed for

rectification (assuming a deficiency or imbalance).

5. Compare the outcome of nutrition in a small scale closed system with tissue

collected from commercial situations.

In order to accomplish these objectives, plant material was sourced (Chapter 2), indications of the general requirements for growth of lotus in containers were investigated (Chapter 3), leading to the ability to challenge lotus with single major nutrient treatments (Chapters 4-7). A general discussion (Chapter 8) assessed the success of the objectives and provided direction for further activity.

Chapter 2 Seeds

2.1 Introduction

In this chapter, the principle objectives will be to document the generation of plant material for trial purposes and investigate the basic requirements for germination of lotus seeds. Seeds are the easiest and quickest method to provide a large amount of plant material for use within trials. The alternatives are to either source growing material from plants in situ or establish plants in vitro. Both of these options have significant disadvantages. Established plants will only yield a certain amount of material, will compromise the asexual reproduction of rhizomes for the following season, be of differing size and developmental attributes, will only be available at select opportunities, and contain unknown inputs of nutrient and or other chemical differences. Plants from in vitro would ultimately be superior in that they would have the closest uniformity possible, however, the difficulty of establishment and maintenance of lotus (Nelumbo lutea) in culture has been documented (Frankco

1986). Further, a large amount of resources are required for such an enterprise.

Therefore, the use of seed material for any investigations was chosen for expediency of collection, ease of production, continual production potential, convenience in manipulation and the ability to utilise great numbers if required. In order to implement any trials on lotus, ponds which generated a source of seed were required to be planted and basic seed germination requirements to provide plants needed addressing.

2.2 Seed Generation

2.2.1 Experiment 1 Observation of the Generation of Lotus (Nelumbo nucifera ) Seeds.

The objective of this experiment was to determine if it was possible to generate seeds at a temperate inland location, and estimate the quantity of seed which could be expected from a known pond area, providing the ability to design potential future experiments.

2.2.2 Materials and Methods

A pond measuring approximately 30 m x 10 m, located at UWSH Richmond campus

(33o21’S 150o28’E), containing 40 tonnes of silty loam soil, was sown with lotus rhizomes of the ‘Green Jade’ variety at a spacing of 2 m x 2 m in early October 1998.

The pond was flooded with water to a depth of approximately 20 to 50 cm above the soil surface. Water level was controlled by a 50 mm float valve, supported by star pickets and located centrally within the pond. Fertiliser was applied as two split applications by hand, in the form of Hydrosol™ pellets (Table A1.1) at a rate of approximately 5 kg per pond and CaNO3 at a rate of 2 kg per pond.

Leaf emergence occurred by late October and the first flowers appeared towards late

December. Pollination was provided by locally kept bees. Flower receptacles (pods) were monitored for seed development and pods harvested when desiccation of the majority of pod tissues occurred and seeds turned black from late February to early

April. Observations for harvest were undertaken every 3 days though actual harvests were intermittent, depending upon pod availability. Pods were dried further under

20oC ventilated conditions. The number of pods and seeds per harvest were recorded for each harvest.

2.2.3 Results and Discussion

Table 2.1 Seed production of lotus (Nelumbo nucifera) at UWSH Richmond in a 300 m2 pond.

Total Av. Av. No.days from No. No. Seed wgt No. Seed No. Seed Date 1st harvest seeds pods (g) Seed day-1 pod-1 Wgt (g) 18-Jan 0 274 52 333.83 274.00 5.27 1.22 21-Jan 3 156 22 188.27 52.00 7.09 1.21 23-Jan 5 482 63 525.29 241.00 7.65 1.09 25-Jan 7 678 65 544.53 339.00 10.43 0.80 28-Jan 10 602 54 806.74 200.67 11.15 1.34 4-Feb 17 1398 122 1716.2 199.71 11.46 1.23 7-Feb 20 290 31 337.04 96.67 9.35 1.16 11-Feb 25 1128 87 1371.43 225.60 12.97 1.22 22-Feb 36 2049 141 2548.35 186.27 14.53 1.24 6-Mar 47 1308 72 1507.24 118.91 18.17 1.15 21- Mar 62 1553 94 2021.23 103.53 16.52 1.30

Mean 901.64 73.00 1081.83 160.55 11.33 1.18

Total 9918.00 803.00 11900.15

Seeds were available for harvest for a period of approximately 60 days from mid

January to mid March (Table 2.1). The total number of seeds was approximately 9

900 seeds, sufficient for the purposes of future trials. The number of seeds produced per day was greatest in the beginning of production and decreased with time.

Conversely, the average number of seeds per pod increased with time, though the average seed weight remained relatively consistent.

2.3 Seed Germination

2.3.1 Experiment 2 Effect of Temperature on the Germination of Lotus (Nelumbo nucifera ) Seed.

The aim of this experiment was to find the most appropriate temperature at which seeds of lotus (Nelumbo nucifera) germinated. Criteria specifying appropriateness was the length of time to germination and the maximum percentage germination for each replicate within a treatment. The outcomes of this experiment would allow for future trial considerations into the required germination temperature.

2.3.1.2 Materials and Methods

During March of 1998, the testas of seeds of the lotus variety ‘Townsville’ were scarified at the hilum using a bench grinder until the cotyledon could be seen. The seeds were then surface sterilised using a 1% solution of NaOCl for 10 min. Then seeds were divided into groups of five treatments with five replicates in 100 ml specimen containers holding approximately 75 ml deionised distilled H2O. Each container was then placed into an incubator with temperature treatments set to 15, 20,

25, 30 and 40oC for germination. Water was changed daily with water kept at the appropriate temperature in the incubator separate from the trial container.

Inspections for germination were conducted over a 20 day period. Data were analysed using the ANOVA procedure of Statistica 6.0 software and graphed using

SigmaPlot 2000.

2.3.1.3 Results and Discussion

Time to Maximum Germination (days) 2

0 15 20 25 30 40

Incubation Temperature (oC)

Figure 2.1 Time to maximum germination for seeds of lotus (Nelumbo nucifera) as a function of incubation temperature. Values are means and bars represent S.E. (n=5). (Table A2.1).

Temperature of the solution significantly affected (P<0.0000) seed germination

(Figure 2.1, Table A2.1). At 15oC, only one seed germinated after 15 days. As temperature increased to 20oC, the germination decreased in the time required to approximately 9 days. At temperatures between 25 to 40oC, the response time for germination decreased to approximately 6 days where the amount of variation also decreased. At 40oC, the emerging tissues appeared vitrified. Therefore, the 25 and

30oC temperatures were regarded as the most adequate to germinate healthy seedlings.

The variation in time to maximum germination displayed for all treatments except for 40oC, suggested that sowing a large number of seeds would result in the production of seedlings of variable size. For experimental purposes, uniform seedlings were required. Therefore, a trial was performed to estimate the number of seeds that needed to be sown to produce a specific number of uniform seedlings.

2.3.2 Experiment 3 Estimation of the Number of Seeds to be Sown for the Production of Uniform Lotus (Nelumbo nucifera) Seedlings.

The aim of this experiment was to provide an index of the number of lotus seeds which will germinate at a particular day within the germination period. In the previous experiment, it was observed that seeds varied in the time which they took to germinate. If future trials were to be conducted with any uniformity, the basic requirement of the plant material was that it should have the same chronological age.

Therefore, an experiment was conducted to determine the percentage of seeds which germinated each day.

2.3.2.2 Materials and Methods

During June of 1999, 230 seeds of lotus, variety ‘Green Jade’, were given pre- treatment as per the method described in section 2.3.1.2. The seeds were then divided into groups of five and transferred to 46 x 100 ml specimen containers

o holding 75 ml deionised distilled H2O. All 46 containers were placed into a 25 C incubator for germination. The number of seeds germinating per day was recorded over a 20 day period. The experiment was replicated twice and the results are presented as the mean.

2.3.2.3 Results and Discussion

100 100

No. Seeds % of Total 80 80

60 60

40 40 % Total Seeds Sown Numberseeds of Germinated 20 20

0 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DNG

Time (days) Figure 2.2 Distribution of the number of seeds of lotus (Nelumbo nucifera) and the percentage of the total number of seeds germinating relative to time. DNG denotes – did not germinate.

The heterozygous nature of the lotus seed was illustrated by the wide variation in seed germination over a 10 day period (Figure 2.2). The greatest amount of germination was 3 to 4 days after sowing, 3 days having the greatest number at approximately 32.6% of the total sown. Germination continued at a consistent though reduced rate for the next 3 days before less than 10% of seeds were left to germinate from day 8 to 12. Approximately 5.5% of the seeds failed to germinate and appeared to be infected with an unknown pathogenic organism. Francko (1986) found a high infection rate of micro-organisms in germinating Nelumbo lutea seeds which required extensive incubations in antibiotics leaving many seeds sterile.

These results provide an estimating multiplication factor for the approximate number of seeds to be sown for a particular application. For example, if 50 uniformly germinated plants were required for a trial, then using the Figures for day 3, an approximate total of 154 seeds would need to be sown. Therefore, a large number of supply seeds for experimentation were necessary for plant cultural experiments.

2.4 Discussion

The aims of this chapter were to investigate the possibility of seed production in a non-recognised region for lotus, and determine the appropriate conditions for the germination of seeds providing uniform seedlings adequate for experimentation. A full, detailed investigation of lotus seed physiology was not an objective. Rather, the basic ability to proceed with consecutive stages, was the primary thrust of this exercise.

Seed production was confirmed to be an achievable goal with almost 10 000 seeds produced annually in a 300 m2 area. When extrapolated this amounts to approximately 330 000 seeds per hectare. Comparative values with seed production for consumption, known to be conducted in Asian centres, were not readily available.

Comparison with other species was not a real possibility due to the highly individualistic nature of lotus seed production, and the huge variation in seed production found for other species. While comparisons were not possible, the number of seeds produced in a single 300 m2 pond was more than adequate for subsequent experimental work.

The temperature conditions for germination were satisfied, with the optimum temperature recorded between 25 and 30oC. Temperature plays a major role regulating embryo growth and radical emergence or in breaking physical dormancy by dislodging the seed water-plug allowing imbibition (Baskin and Baskin 2005).

Germination was achieved without the necessity to manipulate any other environmental conditions, therefore, satisfying this line of inquiry.

The experiment on temperature requirement revealed a variation in the germination rate, in some instances up to 5 days difference. As uniformity in seedlings for future experimentation was desired, an experiment for the estimation of the germination rate using a larger number of seeds was required. This enabled prediction of the quantity of seeds to be sown for a particular number of required uniformly germinated seedlings. The results of this experiment suggest approximately 30% of any lot of seeds sown will germinate at the same time. With a greater sample set, the experiment also revealed that germination can take place over a 10 day period producing highly variable stages of seedling maturity. The use of a plant germinated

10 days apart in a trial was undesirable due to the observed developmental differences between seedlings.

Lotus seed genetic variation has been reported by others. Yang and Zhou (1998), found seeds produced plants with large variations in the floral organs. They then used this variation to breed new varieties. As lotus reproduces both asexually and sexually, the seeds provide a long-lived means of ensuring genetic diversity. Lotus seeds have been shown to be amongst the longest lived (Shen-Miller et al. 1995).

Therefore, it could be speculated that if conditions deteriorated beyond the ability for asexual rhizomes to propagate, then any variability in the germinating seeds could provide an adaptation to changed environmental conditions.

The potential for study of seeds to achieve an absolute optimum of germination was not exhausted, but conducted to the point of necessity. Extensive literature on seed ecology and physiology has been documented providing information on the direction of other possibilities for lotus seed investigations to improve germination (Heydecker

1973, Fenner 1992, McDonald and Kwong 2005). Future experimentation could include trials involving environmental parameters such as light/dark conditions, pH,

EC, oxygen concentration and nutrient composition of the germinating solution.

Unresolved seed issues include the physiological changes in the seed as germination progresses, the differences in viability of seeds from different harvest periods and the possibility of internal circadian rhythms delivering temporal dormancy. Further, viability due to storage conditions, age of seeds, and the influence of micro- organisms on seed germination has not been addressed adequately.

The outcomes of the experiments reported in this chapter were successful with reference to the objectives and allow for continuity of the overall aspects of this project. Therefore, the next stage investigating the basic requirements for plant growth was conducted.

Chapter 3 Plant Culture

3.1 Introduction

The objectives of this chapter are to investigate the parameters required to grow lotus adequately. These parameters include the size of the container for growth and the quality of the solution in which growth is to occur. Once these aspects to growth were standardised, the potential imposition of singular nutrient treatments could be realised. Current recommendations for the growth of lotus appear to be based upon cursory observations without scientific rigour (Honda 1987, Liu 1994). Moreover, recommendations for growth are for field grown plants and not adapted towards plants grown in restricted containers or for specific periods of time (Liu 1994,

Nguyen 2001).

The experiments reported in this chapter addressed the requirements for container size, pH, EC, suitable plant parts for culture, and the control of algal blooms. The intention behind these inquiries was to provide a reference of values for more specific single factor trials regarding individual nutrient influences on growth and yield.

3.2 Container Trials

3.2.1 Experiment No 4 Observation Trial on the Effects of N,P and K on Growth and Tissue Composition of Lotus (Nelumbo nucifera ) Cultivated in 1 m3 Containers.

This experimental investigation took into account the large size of the plant, the need for nutritional evaluation, and the need to determine tissue composition. Therefore, a trial utilising large 1 m3 containers was conducted where treatments for N, P and K could be imposed and tissues analysed for nutrient concentrations and the full cycle of development from seedling to rhizome formation could be observed. It was expected that containers of this size, could adequately house a plant which grows up to 15 m in length. Other expectations included the ability to determine a range of possible values for nutrient composition within samples and to compare samples of tissues produced from the trial and from a commercial lotus growing operation.

3.2.1.2 Materials and Methods

During October of 1998, twelve 1 m3 HDPE produce bins each containing Sydney sand (grains of approx. 0.5 mm), a centrally positioned 24 cm dia. by 1 m deep plastic conduit with uniformly spaced (~ 5 cm apart vertically and horizontal) leakage holes (8 mm φ) confined in ladies hosiery to exclude sand internally, were each transplanted with four replicates of 25 day old lotus seedlings. The conduit was utilised for the exchange of solution, drawing liquid from the sand into the cavity upon siphoning via a hose and also housed a 300 W aquarium heater to maintain solution temperature at a minimum of 20oC.

Solutions were made up of three nutrient factors with four treatments each. A single container was used for a treatment which included 75, 250, 350, and 450 ppm of N,

5, 20, 25, and 30 ppm of P and 50, 250, 350, and 450 ppm of K. Solutions were devised using an adapted Excel spreadsheet developed by Cresswell (1997) (Tables

A1.2-4). Solutions also contained STEM, Scotts Australia. Monitoring of solution pH and EC was performed with an Orion™ multi-parameter meter, Orion Pacific.

The trial duration was six months and solution treatments were exchanged every month. In the first month, solutions supplied were conducted at ¼ strength, ½ strength for the next two months and full strength for the final three months.

During February of 1999, tissue samples were taken from leaves (hereafter differentiated into leaf and petioles to distinguish between leaf lamina and leaf petiole) for the newest fully open leaf in each treatment and from a commercial lotus farm in the Alstonville area of Northern NSW. A soil sample was also taken from the commercial pond and the grower’s estimate of fertiliser application was recorded.

Analysis of tissue for N was performed by Agrifoods Technology using technical procedure No. TP029, and by CSIRO using XRF techniques for other minerals including P, K, Ca, Mg, S, Fe, Mn, B, Cu, Zn, Si, Al and Mo.

3.2.1.2 Results and Discussion

The size of the containers and the fine consistency of the sand prevented easy observation of plant parts and manipulation of solutions. In the containers where plants grew adequately, it was impossible to differentiate the individual plant from which a leaf emerged. At harvest, the density and weight of the sand prevented recovery of the below-ground organs in identifiably replicate form, resulting in an

amorphous mass of indistinguishable stolons and roots which could not be separated

as replicates and hence statistically analysed. Moreover, the sand density prevented

an adequate dissemination of nutrients throughout the solution and when solution

exchanges were conducted, a great deal of solution was left adhered to sand surfaces,

thus influencing the nature of the next batch of solution. Further, the integrity of

some of the containers was compromised by the weight of the sand and solution

concentrations resulting in cracked containers and rapid loss of solution. Therefore,

the possibility of evenly distributed solution treatments and independent

measurement of plants was impossible under this particular system.

Table 3.1 Estimated range of nutrient application rates per hectare and the range of nutrient concentration within soils and in leaf lamina and petioles of the youngest open healthy lotus (Nelumbo nucifera) leaves from container grown and pond grown plants.

Nutrient Application Alstonville Soil Nutrient Nutrient Range Nutrient Concentration in Concentration in (kg ha-1) Concentration Young Leaf Petiole Pond Grown Container Pond Grown Container Grown Grown N (%) 200 – 400 0.75 – 1.0 mg kg-1 2.20 3.40 0.80 2.00 P (%) 40 – 200 20 – 25 mg kg-1 0.20 0.40 0.08 0.40 K (%) 250 – 500 0.15 – 0.24 meq/100g 1.16 3.07 1.89 3.91 Ca (%) 100 – 150 2.5 – 3.5 meq/100g 0.23 1.24 0.28 0.83 Mg (%) 60 – 100 1.90 – 2.54 meq/100g 0.31 0.90 0.23 0.67 S (%) 30 – 50 mg kg-1 0.22 0.33 0.13 0.37 Cl (%) 20 – 70 mg kg-1 0.91 1.633 1.09 2.86 Fe (ppm) 400 – 450 mg kg-1 35.30 110.10 22.40 75.60 Mn (ppm) 80 – 260 mg kg-1 1 364.00 8 380.00 602.00 2 511.00 Na (%) 0.46 meq/100g 0.035 0.142 0.17 0.82 Al (ppm) 0.28 meq/100g 10.00 92.00 19.00 204.00 Cu (ppm) 0.8 – 1.0 mg kg-1 7.50 22.50 9.40 20.90 Zn (ppm) 1.8 – 2.5 mg kg-1 14.20 28.10 13.60 25.80 B 1.1 – 1.2 mg kg-1 Si (%) 0.007 0.047 0.003 0.017

The inability to maintain solution consistency and retrieve plant parts from individual

replicates meant that the tissue nutrient composition could only be used as an

approximate guide (Table 3.1). However, trends emerged from differences in

41 nutrient concentrations between leaf and petiole. For example, leaf N was always higher than petiole N and petiole K was always greater than leaf K for any given sample. Further, the samples taken from the commercial crop of lotus provided tissue nutrient concentrations similar to those from the trial plants. Therefore, an assumption can be made predicting the relative values of the major nutrients required for growth. The values of N and P will always be higher in leaves, while the values for K will always be greater in petioles. The values for roots and stolons were not tested and require investigation. The inability to measure growth of the experimental plants prevented the identification of an organ suitable for determining nutrient requirements.

The limitations encountered in this experiment precipitated the need to focus on an adequately exploitable container size before the plant nutritional requirements could be addressed. The entire scope of the lotus cycle of growth of seedling to rhizome formation was deemed impractical as a research proposal at this stage and thus the vegetative stage during the cropping season was chosen for the initial experimental purposes. Therefore, the following experiment to determine a suitable container size was conducted.

3.2.2 Experiment 5 Observation of the Growth of Lotus (Nelumbo nucifera ) in Containers of Differing Dimensions.

3.2.2.1 Materials and Methods

During January of 2000, 25 days old lotus seedlings were transplanted to four different types of containers as single plants. The container treatments replicated four times, included 200 L and 25 L cylindrical containers, 20 L washing baskets, and 2.5 L cylindrical pails. All containers except the 2.5 L had a 40 mm conduit with holes drilled uniformly along the length to allow for drainage of solutions. The conduits were covered in ladies hosiery to prevent sand entering the drainage cavity.

The 2.5L containers were entirely replaced with fresh container and sand when a nutrient exchange occurred.

The duration of the trial was 30 days and all plants were grown using a commercially available stock solution (Table A1.5) which was maintained at the recommended EC of 220 mS cm-1 and pH 5.8 to 6.5. Plants grown in the 2.5 L containers had coarse 5 mm quartz gravel for media, while the other containers all had a finer 0.5 mm washed Sydney sand. All containers were filled so that 10 cm of solution was free above the media. The weight of media was measured at 1 695 g using a Toledo balance for the 2.5 L containers and used as a constant for each 2.5 L container thereafter. The mass of other containers was too great for manual manoeuvring onto scales.

3.2.2.2 Results and Discussion

The physicality of operating 20 to 200 L containers was beyond the potential of a single operator and immediately discounted their possibility for utilisation in further trials. The trial was discontinued after two solution exchanges because of the difficulty in managing a large operation. These containers were all very difficult to manipulate and changing solutions presented the same problems experienced in the previous experiment. Further, the amount of resources required to operate the 20 to

200 L units was not sustainable and a large amount of waste was produced. Also at the planned harvest date, a time discrepancy of several days would have existed between the plants harvested initially and those harvested last.

The ease of operation in manipulating 2.5 L containers, relative to the other container treatments, was considerable. Using fresh containers and gravel upon solution exchange reduced old solution residue and algae. Moreover, frequent release of the plants from the media allowed regular inspection of the subterranean parts and the time from the start of the harvest of plants to finishing was 5 hours. Therefore, the

2.5 L containers were assessed to be superior for the purposes of studying lotus nutrition within a specific period of time.

3.3 Solution Quality

Experiments 6 and 7 were carried out simultaneously to define the optimum electrical conductivity (E.C.) and pH of solutions. They were conducted using a commercially available A and B nutrient stock solution (Table A1.5) with general recommendations stating solutions should have an EC of 220 mS cm-1 and pH between 5.8 and 6.5 for optimum performance. The objectives of these two experiments were to define the most appropriate EC and pH ranges for maximum growth of lotus.

3.3.1 Experiment 6 Effect of Solution Electrical Conductivity on Growth of Lotus (Nelumbo nucifera).

3.3.1.1 Materials and Methods

During November of 2000, 25 day old seedlings of lotus were transplanted in 2.5 L pails containing 1 695 g of 5 mm washed gravel. Initial solutions were held at half strength EC treatments for 20 days before increasing the EC treatments to full strength for a further 30 days. The eight EC treatments imposed were 0, 25, 50, 75,

150, 200, 275, and 300 mS cm-1 with four replicates each. The treatments were indicated by the codes EC0, EC25, EC50, EC75, EC150, EC200, EC275 and EC300.

Solutions were monitored for EC and pH and adjusted daily with either deionised

H2O, fresh solution or 1M NaOH, depending upon the requirement as determined by an Orion multiparameter meter model 1230. Fresh solution, gravel and containers were replaced at 10 day intervals.

Total dry mass, organ dry mass, the number of organs, total stolon length and internode length were recorded at harvest. Data were analysed using ANOVA techniques and differences found between treatments were assessed (α = 0.05) using

Tukey’s Honestly Significant Difference test in Statistica 6.0 software (Statsoft

2003). Data were represented by graphs constructed using SigmaPlot 8.02 (SPSS

2002).

3.3.1.2 Results and Discussion

The E.C. of the nutrient solution had significant effects on the total dry mass

(P<0.0000) and organ dry mass (P<0.0000) for leaves, petioles and roots and stolons

(Figure 3.1, Tables A3.1-4). Total dry mass increased from approximately 0.77 g

-1 -1 plant at EC0 to a maximum peak of approximately 12.68 g plant at EC200 before

-1 declining sharply to 3.27 g plant at EC300. Individual organ dry mass followed the same pattern as total dry mass with roots and stolons consistently having the greatest mass followed by leaves then petioles. There was negligible change in pH of the solutions throughout the experiment.

The number of organs significantly changed with increasing E.C. (Figure 3.2a,

Tables A3.5-7). The number of leaves increased (P<0.0000) from approximately 17 leaves at EC0 to a peak of 57 leaves at EC150 before declining to 21 leaves at EC300.

The number of nodes sharply increased (P<0.0000) from approximately 6 nodes at

EC0 to 50 nodes at EC50 to EC150 before increasing to a maximum of 66 at EC200.

Node numbers then decreased to approximately 33 nodes at EC275 to EC300. The number of stolons also increased (P<0.0000) from approximately 1.25 stolons at EC0 to between 8.50 and 11.5 stolons at EC25-75 before peaking at 17.67 stolons for EC150

to EC200. The number of stolons then decreased to around 10 stolons for EC275 to

EC300.

Total stolon length sharply increased (P<0.0000) from approximately 178 mm at EC0 to between 947 and 1 554 mm at EC25 to EC150 before peaking at 1 788 mm at EC200.

Total stolon length then sharply decreased to around 900 mm for EC275 to EC300

(Figure 3.2b, Table A3.8). There was no change in internode length (P>0.18) due to increasing EC and was steady at approximately 25 mm (Figure 3.3, Table A3.9).

The results demonstrated some large growth changes due to the nutrient loading in solutions. Large changes were expected between EC0 and EC50, however, the magnitude of change from EC200 to EC275 was unexpected. The plants of EC150-200 were physically larger, created greater amounts of dry mass and were considered to be optimal. Therefore, any post EC or pH experimentation was conducted with the nutrient levels of the 200 mS cm-1 EC level as the constant treatment. Visually, signs of nutrient disorder were observed in older leaves of all treatments as marginal chlorosis followed by necrosis of tissues which superficially resembled potassium deficiency. In the lower EC treatments, an even yellowing across the lamina of older leaves could also be detected and was assumed to be due to a low supply of nitrogen.

These speculations could only be confirmed with single nutrient trials isolating particular nutrient supply evaluated against tissue composition and measured growth.

A wide amount of variation between seedlings after 25 days initial growth, even though they were germinating on the same day, was observed. This not only reinforced the evidence for claims made by Frankco (1986) regarding heterosis of

47 seed material, but illustrated a need for further inquiry into establishing a method to easily, cheaply and quickly produce plant material for trials which had a greater level of uniformity. Uneven stages of growth and development within plant material and between plants will inevitably create disproportionate responses to treatments and thus affect results. Therefore, a trial to evaluate plant pieces of relatively equal dimension and development, to narrow the variation in plant material at the start of experiments, was undertaken before any imposition of single nutrient trials. This trial is reported after the pH trial details as Experiment 8. Further, an algal problem was evident which could influence the overall availability of nutrient to the trial plants. Hence, a trial to eradicate algae was initiated and was reported as Experiment

16 A 14

) 12 -1

Total Dry Mass (g plant Dry Mass Total 4

Leaf B Petiole 5 Roots & Stolons

2 Organ Dry Mass (g) Mass Dry Organ

0 0 25 50 75 150 200 275 300

E.C. (mS cm-1)

Figure 3.1 Effect of nutrient solution electrical conductivity on dry mass of lotus (Nelumbo nucifera): a) Total; b) Organ. Values are means and bars represent S.E. (n=4). (Tables A3.1-4).

80 A Leaf Node Stolons

40 Number of Organs of Number

0 B 2000

1500

1000 Total Stolon Length (mm) Length Stolon Total 500

0 0 25 50 75 150 200 275 300

-1 E.C. (mS cm )

Figure 3.2 Effect of nutrient solution electrical conductivity on: a) Number of organs per plant of lotus (Nelumbo nucifera); b) Total stolon length per plant of lotus. Values are means and bars represent S.E. (n=4). (Table A3.5-8).

20 Internode Length (mm) Length Internode 10

0 0 25 50 75 150 200 275 300

-1 E.C. (mS cm )

Figure 3.3 Effect of nutrient solution electrical conductivity on internode length per plant of lotus (Nelumbo nucifera). Values are means and bars represent S.E. (n=4). (Table A3.9).

3.3.2 Experiment 7 Effect of Solution pH on Growth of Lotus (Nelumbo nucifera).

3.3.2.1 Materials and Methods

During November of 2000, 25 day old seedlings of lotus were transplanted in 2.5 L pails containing 1 695 g of 5 mm washed gravel. Initial solutions using a commercially available stock solution (Table A1.5) were held at ECs from 1.0 to 1.2 dS cm-1 for 20 days before increasing the EC to 2.0 to 2.2 dS cm-1 for a further 30 days. Solution EC increased slightly with treatments. The eight pH treatments imposed during the entire 50 days were 5.5, 6.0, 6.25, 6.5, 7.0, 7.5, 8.0, and 9.0, identified as pH5.5 to pH9.0 respectively. Treatment pH was adjusted in 20 L batches of treatment solution using 1 M NaOH (Table 1.5a). Solutions were monitored for

EC and pH and adjusted daily with either deionised H2O, fresh solution or a few drops of 1M NaOH, depending upon the requirement as determined by an Orion multiparameter meter model 1230. Solution EC tended to rise slightly each day, presumably due to the reduced volume of solution to dissolved salts ratio. Fresh solution, gravel and containers were replaced at 10 day intervals.

Tukey’s Honestly Significant Difference test in Statistica 6.0 software (Statsoft

2003). Data were represented by graphs constructed using SigmaPlot 8.02 (SPSS

2002).

3.3.2.2 Results and Discussion

Dry mass of lotus was significantly affected by the pH of the nutrient solution

(Figure 3.4, Tables A3.10-13). Total dry mass increased sharply (P<0.0000) from approximately 3.17 g at pH5.5 to a maximum of 13.18 g at pH6.25. Total dry mass then decreased with increasing solution alkalinity to a low of 1.28 g at pH8.0. Leaves

(P<0.0000) had the greatest dry mass and petioles (P<0.0000) the lowest dry mass, followed similar trends to the total. In roots and stolons (P<0.0000), the trend was mostly similar, however, the maximum dry mass was achieved at pH6.5.

The number of organs was significantly affected by pH with nodes having the most frequent occurrence followed by leaves then stolons (Figure 3.5a, Tables A3.14-16).

The number of nodes increased (P<0.0005) from approximately 24 nodes at pH5.5 to a maximum of 52 nodes at pH6.25. Node number then decreased slightly but remained similar from pH6.5 to pH7.0, after which the number of nodes fell significantly through pH8.0 to pH9.0 where it was least. The number of leaves displayed similar trends (P<0.0000) increasing from approximately 13 leaves at pH5.5 to a maximum of 36.5 leaves at pH6.25. The number of leaves then decreased but the only significant differences were between pH9.0 and pH6.25 to pH7.0. The number of leaves counted was compromised by a mite infestation towards the end of the trial, explaining the 21 leaf discrepancy between this trial and the EC maximum leaf count which was conducted at a pH of 6.3. The number of stolons (P<0.0006) showed little change across the pH range except at pH6.5 where a maximum of approximately 14.5 stolons were recorded.

Total stolon length was significantly (P<0.0000) changed with pH (Figure 3.5b,

Table A3.17). Total stolon length increased from approximately 675 mm at pH5.5 to a maximum of 1835 mm at pH6.25. Total stolon length then decreased between pH6.25 and pH9.0. Internode length (P<0.0000) was relatively unaffected by pH (Figure 3.6,

Table A3.18), ranging between 23 to 38 mm except for pH9.0 where the mean internode length was calculated at approximately 5 mm. It should be noted that the results for pH9.0 were skewed by the fact that only one plant survived the treatment.

Visually, there were signs of nutrient disorder which were described previously in

Experiment 6 as older leaf marginal symptoms. At the high pH a slight, even, interveinal chlorosis was apparent. This could be due to an Fe deficiency as found by Islam et al. (1980) in pH trials with wheat and maize. The concentrations of Na due to NaOH treatments (Table 1.5a) were less than the concentration reported by

Marschner (1995) as being toxic to plants, approximately 50 ppm, and were considered potentially influential to growth but not the major influencing factor.

Without tissue analysis, this can only be speculation and therefore, requires experimental investigation.

The results demonstrate very clearly that pH6.25 was an obvious optimum for the growth of lotus. All measured parameters except stolon dry mass, which was greatest at pH6.5, peaked at pH6.25. The sharpness of the response to pH suggests a narrow range where lotus is tolerant to pH fluctuations. Similar narrow, well defined pH tolerance to low acid soils was observed by Edwards and Kang (1978) in cultivars of Cassava. Therefore, all trials conducted after this trial, were carried out with nutrient solutions maintained at pH 6.25.

16 A

) 12 -1

Total Dry Mass (g plant 4

6 B Leaf Petiole Roots & Stolons 5

Organ Mass (g) Dry 2

0 5678910

Figure 3.4 Effect of nutrient solution electrical pH on dry mass per plant of lotus (Nelumbo nucifera): a) Total; b) Organ. Values are means and bars represent S.E. (n=4). (Table A3.10-13).

60 A Leaves Nodes 50 Stolons

Number of Organs Number 20

0 2000 B

1500

1000

Total Stolon Length (mm) 500

0 5678910

Figure 3.5 Effect of nutrient solution pH on: a) Number of organs per plant of lotus (Nelumbo nucifera); b) Total stolon length per plant of lotus. Values are means and bars represent S.E. (n=4). (Table A3.14-17).

20 Internode Length (mm) Length Internode

0 5678910

Figure 3.6 Effect of nutrient solution pH on average internode length per plant of lotus (Nelumbo nucifera). Values are means and bars represent S.E. (n=4). (Table A3.18).

3.3.3 Experiment 8 Observation of Growth of Lotus (Nelumbo nucifera) from Cuttings.

3.3.3.1 Materials and Methods

During November of 2001, apical stolon plant pieces approximately 120 mm in length and 5 mm in diameter were excised after the 4th node from 25 day old lotus seedlings. Each plant piece comprised three internodes, one open leaf and one unopened emerging leaf. The cut surfaces were treated with an acrylic gap sealant,

Blutack or building adhesive pressed into the lacunae to seal the open end. A non- treated cut surface was included for comparison. Excised plant pieces were then transplanted into separate 2.5 L containers with 1 695 g of 5 mm gravel as a single replicate. The four treatments had four replicates. Solutions consisted of the commercial stock A and B nutrients (Table A1.5) maintained at pH 6.25 and an EC of 150 mS cm-1 initially for 20 days before increasing to 200 mS cm-1 for a further 50 days. Solutions, containers and gravel were exchanged every 10 days. Solutions were monitored daily and topped up with either fresh solution or tap water.

3.3.3.2 Results and Discussion

Non-sealed cuttings immediately leaked gas from the cut surface and deteriorated after one week in culture. The acrylic sealant and building adhesive appeared to be toxic to plant condition and plants did not grow adequately. Also, the initial liquid state of these sealants was difficult to manipulate correctly and required the plants to be out of solution until the sealant cured, approximately five minutes. The Blutack putty adequately sealed the cut surface of the plants which grew satisfactorily. The subsequent decay of plants, which deteriorated under treatment conditions, prevented

58 the possibility of statistical analysis of measured data. However, it was clearly observed that plants treated with Blutack sealant, were the most uniformly superior of any plants yet produced.

Propagation of non-rhizome vegetative stolon material, taken from germinating rhizomes, has been reported to grow adequately and in some varieties hasten the time from transplanting to flowering (Katori et al. 2002). Traditionally, only rhizomes have been used as propagation material. Stolons were considered as not suitable for propagation due to the disturbance of feeder roots attached to nodes, loss of turgor due to the transpiration activity of attached leaves and low nutrient concentration compared to rhizomes (Katori et al. 2002). However, the results of Katori et al.

(2002), using large stolon pieces (~500 mm x 20 mm) to successfully grow plants and produce lotus flowers, and the results from this experiment using small stolon and leaf material, suggested the traditional opinion was incorrect.

It was determined that any further work would be complimented by cuttings from the primary stolon after the fourth node from the apical meristem with one open and one unopened leaf. The cut surface should be sealed with Blutack. It should be noted that even though the uniformity of plants via cuttings had been improved by restricting the quantity of the number of nodes and leaves to equal numbers on each cutting, there was still obvious though slight variation in stolon lengths and thicknesses between cuttings.

3.3.4 Experiment 9 Observation on the effect of Algaecides on the Growth of Lotus (Nelumbo nucifera) and Control of Solution Algae.

The potential of algaecides for use in lotus trials was investigated. Two types of algaecide, with different active constituents, Coptrol (chelated Cu compound) and

Simazine (6-chloro-N,N’-diethyl-1,3,5-triazine-2,4-diamine), were assessed for the control of algae in lotus nutrient trials.

3.3.4.1 Materials and Methods

During November of 2001, cuttings of 25 day old lotus seedlings were taken after the

4th node and sealed with Blutack putty as described in section 3.3.3.1. They were then transplanted into 2.5 L pails containing 1 695 g of coarse 5 mm washed gravel.

Solutions contained nutrients of a commercially available product (Table A1.5) and were maintained at an EC of 200 mS cm-1 and a pH of 6.25. Algaecide treatments included 0.5, 1, and 2 times the recommended application rate of 2 L ha-1 of Coptrol in rice paddies and 1 ml L-1 of Simazine generally. A control treatment without algaecide was also included and each treatment contained four replicates. The trial was conducted for 20 days.

3.3.4.2 Results and Discussion

The presence of algaecide proved detrimental to the growth of lotus with every plant under both types of algaecide treatments becoming necrotic within 20 days. The double strength algaecides completely controlled the presence of any algae though the lotus plants were also destroyed within 5 days after application. At the recommended rate of application, algae were not completely eradicated with traces

60 remaining in the solution and plants survived for approximately 10 days before all tissues were necrotic. The half strength applications did not adequately control algae and plants survived for 20 days. The control treatment plants grew adequately, with the same signs of nutrient disorder witnessed in the EC and pH trials, although the algae were not controlled without solution changes.

Similar effects for Simazine have been recorded by Frank (1995), who reported negative effects on some species of plant and no effect on others. The product used in this trial made no statements about its effect on aquatic flora other than algae, however, Frank (1995) points out that the manufacturer of the chemical has cautioned against use with waterlillies. The adverse effect due to Coptrol was surprising, given the manufacturers claim that ornamental or crop plants would not be affected.

It was concluded that the use of algaecide was of no benefit to the growth of lotus at the strength required to control algae and amounted to a waste of all resources.

Therefore, subsequent trials relied upon the systematic regular exchange of solutions to keep the presence of algae to a minimum. Until a greater amount of resources can be acquired to initiate a more complex system of solution management, and a greater understanding of the nutrient requirements and tissue composition is identified, the presence of algae would have to be viewed as a an uncomfortable though moderately acceptable reality.

3.4 Discussion

The objectives of this chapter were to standardise a container system for the growth of lotus, determine the solution EC and pH optimum, and identify the most appropriate plant part for experiments involving lotus. These aims were adequately satisfied as outlined below.

The container with the most functionality was the 2.5 L cylindrical pail. It could be easily manipulated by one operator within an acceptable time period for exchange of solutions, gravel and container. More importantly, the plants were able to grow and develop within the experimental time period. Therefore, the standard container to be used in subsequent experimentation was identified as a 2.5 L cylindrical pail containing 1 695 g of washed 5 mm coarse quartz gravel.

Best EC value and range for critical limits were found to be 200 mS cm-1 for EC and a pH of 6.25. These values had a narrow range regarding dry matter production though for total stolon length and organ numbers the range was not as acute. As these results present the first documentation of EC and pH for lotus no absolute definitive values are claimed, however, these results provide an adequate set of measurements for the purpose of single nutrient evaluations.

Using 4th node cuttings from 25 day old seedlings provided uniform starting material that did not produce the large variations in plant size and development seen for whole seedlings used in Experiments 6 and 7. Further, plant parts from cuttings were

62 easily managed at the early stages of growth. Therefore, cuttings were chosen as the most appropriate plant material for use in the 2.5 L container system.

To reduce the effects of plant-to-plant variation, the number of replicates was increased from four to five. Although eight replicates would be desirable (Poorter and Garnier 1996), this number is impractical in a system which is labour-intensive and time-dependant; it would minimise the potential number of treatments or increase the time required for solution changes and harvesting of plant material.

Plant assessments to evaluate growth would have been better served with LA analysis, and tissue composition analysis comparisons with growth, as further indications or confirmation of treatment effectiveness. Tissue analysis was not undertaken for the experiments in this chapter as no nutrient treatments were in effect and the likelihood of tissues delivering results with differences was low. The need to identify which organ is most appropriate for field analysis remains unresolved and can only be answered through challenging lotus with a number of nutrient treatments.

The other unresolved problem is the algae situation. Treating algae with algaecide affects lotus plants, lotus appeared to be more sensitive to algaecides than algae (both are obligate hydrophytes). Regular changing of the solutions ensured the growth of the algae did not deny the trial plants of nutrients, this was evident by the plants not indicating N stress or other stress, N most likely to appear during growth as it is required in the largest amounts by plants. Algae are present in commercial crop situations, therefore, the presence within the trial plants was deemed as an acceptable inconvenience.

Chapter 4 Analysing the Interaction between Nitrogen and Lotus

4.1 Introduction

Nitrogen has been well established as the most important nutrient for plant growth, and the most abundant mineral nutrient in plant tissues (Taiz and Zeiger 1991). It is an important component in amino acids, hence enzymes and other proteins contain large fractions of N (Mengel and Kirkby 2001). It is a part of DNA as a nucleotide base component, and plays a role in the regulation of the TCA and Calvin-Benson cycles as well as other metabolic processes (Marschner 1995).

The nitrogen requirements of lotus have not been reported. Organ nutrient concentration and distribution within the plant have not been documented in requisite detail (Nguyen 2001). Consequently, critical concentrations and the adequate range of tissue nitrogen concentrations required for maximum growth of lotus have not been established. Although Nguyen (2001) reported critical concentrations and adequate range estimates, based upon the results of tissue analysis from Experiment

1, the data were shown to be potentially compromised by the inadequacy of the research system in which the trial was conducted. Therefore, it is necessary to determine organ nutrient concentration as a function of nitrogen supply within a well defined trial system.

Indications of suitable treatments from solution culture experiments for many traditional crop species have revealed differences in the response and sensitivity to amount and type of nitrogen supplied. For example, while culture solutions used

65 during the last 50 years have varied the nitrogen concentration from 126 to 210 ppm,

Schwartz (1995) recommends 175 ppm as satisfactory for most species. High concentrations of nitrogen have been shown to suppress yield in root crop species such as sweetpotato (Ipomoea batatas) and Chinese waterchestnut (Eleocharis dulcis) (O’Sullivan et al. 1997, Kleinhenz et al. 2000). Limitations to N supply in general for most plants is expressed as slowed or stunted growth, uniform light green chlorosis of younger to mid-mature leaves and yellow chlorosis followed by necrosis of oldest leaves as the highly mobile N is utilised elsewhere in the plant under low supply conditions (Grundon et al. 1997).

Chlorotic symptoms developing evenly across mature leaf laminas, resembling nitrogen deficiency, were observed in the lower EC treatments of Experiment 7. The symptoms could not be solely attributed to a lack of nitrogen supply as all elements were in low supply for these treatments. Additionally, symptoms expressed, such as the marginal chlorosis followed by necrosis, were not consistent with typical signs of

N deficiency. Therefore, to distinguish nitrogen symptoms, critical concentrations, and adequate range for nitrogen supply, a trial was necessary to challenge lotus with varying nitrogen levels, yet maintaining consistent supply of all other nutrients required for plant growth. It was expected that by restricting nitrogen alone, the symptoms of deficiency would be expressed through differences in growth measurements and visual cues. Further, the dry matter yield as a function of organ concentration should reveal the critical concentrations and adequate range of nitrogen in tissues.

This chapter aims to determine the efficacy of utilising the proposed system by challenging lotus with a range of N treatments. Establishment of organ critical nutrient concentrations outside the adequate range of N supply for lotus and documentation of nutritional disorder symptoms that may be expressed, are the objectives with which to confirm the effectiveness of the system.

The experiment reported in this chapter attempted to analyse the response of lotus to variable nitrogen supply within the proposed container system. In the absence of reliable experimental precedents, concentrations of nutrients were based upon the calculated nutrient concentrations (Table A1.5) found within the commercially available nutrient formulation trialled in Experiment 7. The treatment applied at an

EC level of 225 µS cm-1, and corresponding to a nitrogen concentration of 275 ppm, was chosen as the initial estimate of appropriate supply concentration. Hence the upper mid-point, or constant, for nitrogen concentration in the following treatments was recognised at 275 ppm of nitrogen. Similarly, the supply levels for the other nutrients were also determined as the constant throughout each treatment class. All other N treatments were proportionally assigned relative to the constant with the exception of the extreme low and high treatments. The objective of using extreme high and low treatments was to capture the critical concentrations in tissues where growth is limited due to supply. Within the range of critical concentrations lies the adequate region of concentration and this can be used to extrapolate back to the corresponding supply level for grower’s recommendations.

By analysing all organs, those that were responsive to the applied treatments would be identified as being suitable index tissues that would be useful for field sampling in

67 commercial situations. By comparing the relationships between nutrient concentrations and growth parameters for the organs, it was possible using the method of Mead et al. (1993) to determine whether the organs showed the same response or responded differently to the imposed treatments. To determine the response to nitrogen the following experiment was carried out.

4.1.1 Experiment 10 Effect of Nitrogen on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera ).

A trial involving eight nitrogen treatments with five replications per treatment was undertaken over a 50 day period of growth. The effect of nitrogen supply on growth parameters and tissue concentrations of major nutrients were analysed.

4.2 Materials and Methods

4.2.1 Plant Culture

During September of 2002, the testas of 100 lotus seeds (var. Green Jade) were scarified using a Ryobi bench grinder before surface sterilisation with a 0.04% solution of sodium hypochlorite for 15 minutes. Four seeds were then sown per one standard container (SC described in section 3.4) and saturated with 1 500 ml tap water for germination. After a 7 day germination period and 10 days subsequent growth, plants were selected for uniformity and cultivated for 25 to 30 days individually in a new SC with a solution containing nutrients at 25% the concentration of the constant treatment (see below). Forty plants were then selected for uniformity based upon the number of leaves and nodes, and cuttings were excised from the emerging stolon after the 4th node from the apical meristem using a sharp knife. Each explant had three intact stolon sections, one open functioning leaf, one

68 emerging unopened leaf, and one to two emerging side stolons. The cut surface was sealed using water-proof adhesive putty (Blutack™) pressed into the exposed internal surfaces of the lacunae to support adhesion. The explant pieces were then transplanted into a new SC, and solutions containing 50% concentration of the total treatment solution were imposed for 20 days, after which full strength solution treatments were used for a duration of 30 days. Treatments were imposed for a total of 50 days.

Pre-treatment and treatment solutions were prepared in bulk 20 L portions prior to application from stock solutions (Table A1.6) and the EC measured for each working solution in order to monitor subsequent batches of working solution. Concentration of constant nutrients in treatment solutions were calculated using Nutron 2000+ software (Lennard 2000), other treatments were calculated using the values obtained for the constants in an adapted Excel 2000 spreadsheet developed by Creswell

(1997). Concentrations of all nutrients other than N treatments, Cl and S, remained constant at 45 ppm P, 350 ppm K, 230 ppm Ca, 60 ppm Mg, and between 40 and 205 ppm S. KNO3 concentrations were varied and the K equilibrated with K2SO4. For the two highest N treatments, N concentration was increased by the addition of

NH4NO3. Trace elements were included at concentrations of 0 to 70 ppm Cl, 10 ppm

Fe, 0.4 ppm Cu, 0.1 ppm Zn, 2 ppm Mn, 0.3 ppm B, and 0.1 ppm Mo. pH was adjusted to pH 6.25 with 10 M NaOH where necessary. Trial container solution volumes were adjusted daily, alternatively with fresh treatment solution appropriate to the required treatment supply or fresh tap water. Entire solution and SC changes were conducted at 10 day intervals.

Containers were located on a 1 000 mm x 2 500 mm bench within a semi-controlled environment with temperatures maintained between 20 and 30oC. Supplemental lighting was delivered by suspending two high-pressure sodium lamps 1 m over the bench, time controlled for 16 hr day-1 of artificial light. All plants when not under manipulative processes were kept in holding containers with appropriate solutions to avoid desiccation of the plant tissues.

4.2.2 Experimental Design

The eight different N treatments 50, 150, 200, 225, 250, 275 (the constant), 325, and

400 ppm of N (Table A1.6), identified as N50 to N400 respectively, were replicated five times. Observations for expressed disorder symptoms were taken at day 20 and

40 during the change of container and media. Additional data were collected at final harvest. The numbers of leaves, nodes and stolons were counted. The lengths of stolons were measured using a Toledo™ 1 000 mm steel rule. Total leaf area was determined by photocopying leaves onto 80 g m-2 sheets of A4 sized paper, weighing the leaf images for each plant, then calculating LA based upon the known physical parameters in Excel XP software (Microsoft 2001). Internode length was calculated from the total stolon length divided by the number of nodes. The masses of leaves, petioles and stolons were measured using a Mettler PB 3002 Delta Range™ balance after drying at 80oC for 14 days in Thermoline™ ovens. Tissue analysis for nitrogen concentration was undertaken by combustion techniques using a Carlo Erba

Instrument at the University of Adelaide, Waite campus. Phosphorous, potassium, calcium, magnesium, sulphur, iron, manganese, zinc, copper, boron, molybdenum, sodium, and aluminium concentrations were measured by adequate range inductively

70 coupled atomic emission spectrometry (ICPAES) at the University of Adelaide,

Waite campus.

Analysis of growth and tissue composition data as a function of treatment application was tested for homogeneity then computed according to analysis of variance techniques (ANOVA) using Statistica 6.0 software. ANOVA differences were estimated using Tukey’s Honestly Significant Difference protocol (Statsoft Inc.,

2003). Concentration of all nutrients with significant differences (P<0.01) were assessed against the nitrogen concentration in organs. The relationship between dry mass and growth parameter, and growth parameter and organ nutrient concentration which demonstrated a significant effect (P<0.01), were then assessed using regression protocols in Tablecurve 2D v.4 (Jandel Scientific, 1996). Regression equations were selected on the basis of rank of F statistic, a positive intercept of the y axis, retention of similar shape between zero and the data range, and passage centrally through the data range.

To test whether one or more equations were required to describe the relationships between tissue nutrient concentration and the growth parameters, regression equations were tested for similarity using Mead’s method (Mead et al. 1993). This method involves the comparison of residual sums of squares of fitted equations for separate and combined data sets. The method is able to be used irrespective of the form of the equations involved unlike methods that are used to compare the coefficients derived when the same equation is fitted to each data set. F distribution tables from Bluman (1992) were employed for comparisons. The conversion of F values to corresponding p values was performed using the web-based probability

71 distribution function calculator (Pezzullo 2005). Critical concentrations and extrapolated adequate supply values were estimated using the evaluation function in

Tablecurve 2D v.4 (Jandel Scientific, 1996). SigmaPlot 8.0 (SPSS Inc., 2002) and

Excel XP (Microsoft, 2001) were utilised for the construction and presentation of graphs.

4.3 Results

4.3.1 Observations of Nitrogen Supply on Visual Growth Expression.

Nitrogen supply had an obvious effect on overall plant growth. The differences were most notable at the extreme N supply treatments of N50 and N400 and were more pronounced at 40 days than at 20 days (Table 4.1). Treatments in between appeared relatively similar in size and development for both times of observation.

Signs of disorder were observed over all classes of treatment and were seen in the oldest floating leaves followed by the oldest emergent leaves. At day 20, the oldest leaf in every replicate and treatment appeared to display symptoms associated with transplant shock and was disregarded as a reliable indicator. Leaf tissue of plants in the N50 treatment displayed a marginal chlorosis followed by necrosis in approximately 50% of the older leaves (Table 4.1). Chlorosis began interveinally at leaf margins, travelled inward, before consuming veinal tissue at the margins. The necrosis followed chlorosis. The degree of chlorosis/necrosis increased with leaf age and the oldest necrotic leaves curled upwards. Across the leaf lamina, older leaves also had a distinct though lighter green compared to younger leaves. This lighter shade of green was not observed in the chlorosis/necrosis affected leaf tissue in the leaves of higher N treatments. The chlorosis/necrosis was present in all treatments although only approximately 10% of the leaves were affected from N150 to N325.

Affected leaves of the N400 treatment had the strongest display of these symptoms in approximately 50% of the older leaves. There was a greater degree of the interveinal chlorosis for this treatment. The shade of green across laminas of all plants from

N400, was darker than those of plants from N150 to N325.

At day 40, complete necrosis of 25% of older leaves of plants in the N50 treatment had occurred and a further 25% were showing symptoms of chlorosis. Plants from

N150 to N325 had approximately 10% of leaves completely necrotic, and a further 25% showed varying degrees of chlorosis/necrosis depending on leaf age. The plants in

N400 were similar to N150 to N325, appearing to have overcome the earlier heavy signs of disorder.

The visual appearance of roots and stolons was affected by N supply. At day 20, roots connected to leaves with signs of disorder appeared blackened in all treatments.

Healthy roots were either white when mature, or had a purplish tinge when emerging from an apical node. At day 40, 10% of the oldest stolon and connected tissues were necrotic and rotting for plants in the N50 treatment. A further 50 to 75% of the roots also were blackened but not necrotic. Blackening of roots of plants in other treatments continued though it corresponded to leaves displaying symptoms.

Table 4.1 Estimated observations for lotus (Nelumbo nucifera) on: a) the percentage of leaves per plant showing signs of disorder at day 20; b) the percentage of leaves per plant showing signs of disorder at day 40; c) the percentage of total leaf area per plant affected by disorder at day 40; d) the below-ground plant parts affected by disorder at day 20; e) below-ground plant parts affected by disorder at day 40. Values followed by different letters are significantly different at P<0.01 within each column (Tables A4.1-5).

Treatment A B C E (ppm) D 50 41.25a 57.50a 3.39a 35.00ac 57.50a 150 52.50a 45.00a 5.41a 50.00a 57.50a 225 25.25a 32.50a 4.46a 42.50a 37.50a 250 45.00a 37.50a 4.98a 32.50abc 37.50a 275 27.50a 46.25a 5.77a 27.50abc 25.00a 300 30.00a 32.50a 4.90a 30.00abc 47.50a 325 6.25a 33.75a 4.90a 6.25b 32.50a 400 12.50a 30.00a 4.41a 12.50bc 27.50a

4.3.2 Nitrogen Supply Effect on Growth Parameters.

Dry mass, organ numbers, organ dimensions and leaf area were significantly affected by nitrogen supply. Total dry mass (P<0.0009), dry mass of all leaves (P < 0.002) and petioles (P<0.0000) generally increased with increasing N supply, however, the re were no significant increases with treatment for roots and stolons (P>0.01)

(Figures 4.1a-b, Tables A4.6-9). Maximum total dry mass was approximately 25 g

-1 plant and occurred at treatment N400. Total dry mass increased steadily from N50 to

N225 after which treatments were not significantly different. Though not significantly different, total dry mass decreased from N225 to N275 before increasing to the highest yielding treatment for total dry mass from N275 to N400. Maximum leaf dry mass was approximately 5.5 g and occurred from N325 and N400. Maximum petiole dry mass was approximately 4.5 g and occurred at N400. Maximum roots and stolons dry mass was approximately 6.5 g and occurred at N400. The pattern of dry mass accumulation in the organs was similar to total dry mass (Figures 4.1a-b).

The number of leaves (P<0.0006), nodes (P<0.0000) and stolons (P<0.003) generally increased with increasing N supply across the full range of treatments (Figures 4.2a- c, Tables A4.10-12). The exception to this was the number of leaves which plateaued at approximately 35 leaves between the N300 and N400. The maximum number of nodes, approximately 95, occurred at N400. The maximum number of stolons was approximately 25 and occurred at N400.

Total leaf area was least at the lowest rate of N supply and increased significantly

2 2 (P<0.0000) from approximately 3.55 dm at N150 to 13.32 dm at N225 (Figure 4.3a,

Table A4.13). Total leaf area continued to increase through N250 to a maximum of

2 15.74 dm at N400 but was not significantly different from N225 ppm. There was no effect (P>0.25) of N supply on total stolon length (Figure 4.3b, Table A4.14). Mean internodal length (P>0.05) displayed a negative trend from low to high N supply but was not significant (Figure 4.3c, Table A4.15).

25 A ) -1 20

10 Total Dry Mass (g plant

3 Organ Dry Mass (g) Mass Organ Dry 2 Leaf 1 Petiole Root & Stolon

0 0 50 100 150 200 250 300 350 400 N Supply (ppm)

Figure 4.1 Dry mass of lotus (Nelumbo nucifera): a) Total dry mass; b) Organ dry mass for leaf, petiole, and roots and stolons; as affected by nitrogen supply. Values are means and bars represent S.E. (n=5). (Tables A4.6-9).

40 A

15 Number of Leaves of Number 10

0 B 100 N Supply (ppm)

80 es d o N

f 60 er o b

um 40 N

0 C 25

10 Number of Stolons

0 0 50 100 150 200 250 300 350 400 N Supply (ppm) Figures 4.2 Effect of nitrogen supply on lotus (Nelumbo nucifera) organ numbers: a) Leaf no. b) Node no. c) Stolon no. Values are means and bars represent S.E. (n=5). (Tables A4.10-12).

18 A 16

14 ) 2 12

6 Total Leaf AreaTotal (dm

0 B 2500

2000

1500

1000 Total Stolon Length (mm) Length Stolon Total 500

0 C

150

100

Internode Length (mm) Internode 50

0 0 50 100 150 200 250 300 350 400 N Supply (ppm)

Figure 4.3 Effect of nitrogen supply on lotus (Nelumbo nucifera) organ dimensions: a) Total leaf area; b) Total stolon length; c) Average internode length. Values are means and bars represent S.E. (n=5). (Tables A4.13-15).

4.3.3 Effect of Nitrogen Supply on Organ Nutrient Concentration.

Organ nitrogen concentration was least for the lowest rate of supply N and increased consistently without peak with N supply through all treatments to a maximum N concentration of approximately 4.6, 4.1 and 3.25 % for leaves (P<0.0002), petioles

(P<0.0000) and roots and stolons (P<0.0000) respectively, at the N400 treatment (Figure

4.4a, Tables A4.16-18).

Nitrogen supply had no effect on leaf (P>0.28) or petiole (P>0.01) phosphorous concentration though it had significant effects on roots and stolons (P<0.004) (Figure

4.4b, Tables A4.19-21). P concentration in roots and stolons increased with increasing

-1 N and achieved a maximum of approximately 11.00 g kg between treatments N150 to

-1 N400. P concentration was approximately 6.00 and 8.00 g kg in leaves and petioles respectively.

Supply of N had no effect on concentration of potassium in leaves (P>0.7) which contained approximately 30.00 g kg-1 K. Petiole K concentration was affected by N

-1 supply (P<0.005) with a maximum peak of approximately 60.00 g kg between N50 to

N325, before dropping away significantly at N400. Similar trends for K in roots and stolons (P<0.0000) had a maximum of approximately 45.00 g kg-1 (Figure 4.5a, Tables

A4.22-24).

Supply of N had a significant effect on the concentration of calcium in leaves

(P<0.0000) but not petioles (P>0.02) or roots and stolons (P>0.42) (Figure 4.5b, Tables

A4.25-27). Calcium concentration in the leaf increased to a peak of approximately

-1 25.00 g kg from N50 to N250 before declining sharply at N400. Petioles and roots and stolons contained approximately 11.00 and 13.00 g kg-1 Ca respectively.

When N supply increased, concentration of Zn in leaves and petioles, and Fe and Al concentration in leaves increased (Figures A4.2a, 3a & 5a). Conversely, S and Mo decreased with increasing N supply (Figures A4.1b & 4b). Concentration of Mn in leaves and Al in leaves and petioles decreased with increasing N supply at lower N, before increasing sharply with higher applications of N (Figures A4.2b & 5b).

Concentration for Cu and Mo in petioles, roots and stolons, and B in roots and stolons and leaves, tested significant though were considered anomalous due to the spike achieved at N275 (Figures A4.3b, 4b & 4a respectively). Removal of this treatment resulted in no significance for these elements. N supply had no effect on Mg and Na concentration for all organs (Figures A4.1a & 5a). A summary of the appropriate statistics of significance can be found in Table 4.2.

5 A

2 Organ N Conc. (%) Conc. N Organ

B 10000 ) -1 8000

6000

4000 Organ P Conc. (mg kg P Conc.Organ (mg

Leaf 2000 Petiole Roots & Stolons

0 0 50 100 150 200 250 300 350 400

N Supply (ppm)

Figure 4.4 Effect of nitrogen supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Nitrogen; b) Phosphorous. Values are means and bars represent S.E. (n=5). (Tables A4.16-21).

60000

) 50000 -1

40000

30000

20000 Organ K Conc.kg (mg

10000

0 25000

) 20000 -1

15000

10000 Organ Ca Conc. (mg kg (mg Conc. Ca Organ

5000 Leaf Petiole Roots & Stolons

0 0 50 100 150 200 250 300 350 400 N Supply (ppm)

Figure 4.5 Effect of nitrogen supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Potassium; b) Calcium. Values are means and bars represent S.E. (n=5). (Tables A4.22-27).

Table 4.2 List of F and P values for lotus (Nelumbo nucifera) organ minor and trace element nutrient concentration as a function of nitrogen supply (Figures A-4.1-5; Tables A4.28-57).

Nutrient Organ F P value Mg Leaf 1.71 0.143 Petiole 3.10 0.014 Roots & Stolons 2.18 0.065 S Leaf 6.40 0.000* Petiole 1.71 0.145 Roots & Stolons 1.08 0.399 Fe Leaf 9.73 0.000* Petiole 2.51 0.037 Roots & Stolons 1.12 0.376 Mn Leaf 9.57 0.000* Petiole 3.61 0.006* Roots & Stolons 1.29 0.287 Zn Leaf 7.64 0.000* Petiole 3.61 0.006* Roots & Stolons 3.09 0.014 Cu Leaf 1.49 0.209 Petiole 6.53 0.000* Roots & Stolons 2.53 0.036 B Leaf 3.30 0.009* Petiole 2.06 0.079 Roots & Stolons 4.18 0.003* Mo Leaf 14.6 0.000* Petiole 6.37 0.000* Roots & Stolons 9.25 0.000* Na Leaf 1.53 0.193 Petiole 1.53 0.195 Roots & Stolons 2.15 0.068 Al Leaf 10.1 0.000* Petiole 10.2 0.000* Roots & Stolons 5.88 0.000* * Denotes significance at P<0.01

4.3.4 Analysis of Major Nutrient Concentration as a Function of Nitrogen Concentration.

Organ nitrogen concentration was significantly increased by N supply in all three organs

(Tables A4.58-60), however, a single fitted regression equation described combined leaves and petioles (P < 0.0000) and combined petioles, roots and stolons (P<0.0000)

(Figure 4.6, Tables A4.172-175 & 188-191). Concentration in leaves and petioles increased steadily from approximately 2% at N50 to 4.3% at N400. Concentration in petioles, roots and stolons combined also increased steadily though at lower concentrations from 1.5% at N50 to 3.75% at N400.

Phosphorous concentration in all organs rose steadily with increased N concentration

(Figure 4.7, Tables A4.61-63). Concentration was highest in roots and stolons (P <

0.0000), petioles (P < 0.0000) then leaves (P < 0.0000) and ranged without peaking from approximately 7.30 to 10.40, 6.80 to 8.80, and 4.90 to 6.50 g kg-1 respectively.

Individual organ equations were significantly different from each other (Tables A4.176-

179 & 192-195).

Concentrations of K in petioles (P < 0.0003) displayed an inverse parabolic relationship with increasing N concentration, a maximum of approximately 60.00 g kg-1 K concentration was achieved at approximately 2.5% petiole N before increased N concentration depressed petiole K. (Figure 4.8a, Tables A4.64-66). Roots and stolons

(P < 0.008) K concentration decreased from approximately 46.00 to 32.00 g kg-1 with increasing N, whereas leaf (P < 0.004) K concentration remained stable until higher N concentration was imposed and K increased. Fitted equations were found to be different from each other (Tables A4.180-183 & 196-199).

Calcium concentration in leaves increased with an inverse-parabolic trend (P<0.005) from approximately 18.30 at 2.45 % N concentration to a peak of 22.80 g kg-1 at 3.78 %

N. The Ca concentration then decreased to approximately 18 000 mg kg-1 at 4.90 % N.

No significant changes were recorded for Ca concentrations in petioles (P>0.33) or roots and stolons (P>0.72), with approximately 15.00 and 11.00 g kg-1 respectively

(Figure 4.8b, Tables A4.67-69). Fitted regression equations for leaves and for petioles and roots and stolons were significantly different from each other (Tables A4.184-187

& 200-203).

Of the minor and trace elements (Table 4.3), only Mg (P<0.001) concentration in roots and stolons and Mo (P<0.001) in leaves, were negatively affected by increased N concentration (Figures A4.8a & 9a, Tables A4.72 & 91). Conversely, Fe concentration in leaves (P<0.001) and petioles (P<0.01), and Al concentration in all organs (P<0.001 for leaves and P<0.01 for petioles and roots and stolons) resulted in an increase with increased N concentration (Figures A4.8b & 9b, Tables A4. 76-77 & 97-99). All other minor and trace elements had no significant change with increasing N concentration

(Tables A4.70-71, 73-75, 78-90 & 92-96).

3 N Conc. (%) N Conc. 2

1 Leaves & Petioles Petioles, Roots & Stolons

0 0 100 200 300 400 500

N Supply (ppm)

Figure 4.6 Nitrogen concentration in organs of lotus (Nelumbo nucifera) as a function of nitrogen supply. Regression equations are: y = 1.88exp(x/486.22) (r2 = 0.47) and y = 1.35exp(x/403.67) (r2 = 0.73), for leaves and petioles (____) and for petioles, roots and stolons (…..) respectively. (Tables A4.58-60, 172-175 & 188-191).

14000

12000

) 10000 -1

8000

6000

Organ P Conc. (mg kg (mg Conc. P Organ 4000

Leaf 2000 Petiole Roots & Stolons

0 0123456

Organ N Conc. (%)

Figure 4.7 Phosphorous concentration in organs of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration. Regression equations are: y = 3819.77 + 24.84x3 (r2 = 0.64), y = 4861.81 + 491.35x1.5 (r2 = 0.46), and y = 6841.7 + 346.77x2 (r2 = 0.49) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A4.61-63, 176-179 & 192-195).

80000 AA

60000 ) -1

40000

Organ K Conc. (mg kg Conc. (mg Organ K 20000 Leaf Petiole Roots & Stolons

0 B 25000 )

-1 20000

15000

10000 Organ Ca Conc. (mg kg Conc. (mg Organ Ca

5000

0 0123456 Organ N Conc. (%)

Figure 4.8 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration a) Potassium, regression equations are y = 26 482 + 55.56x3 (r2 = 0.17), y = 37 513.34 – 16 150.97x2lnx + 11 640.84x2.5 (r2 = 0.45), and y = 48 539.05 - 894.29x2 (r2 = 0.13) for leaves (____), petioles (…..) and roots and stolons (----) respectively; and b) Calcium, regression equation is y = 6 560.24 + 5 775.26x2 - 2383.36x2.5 (r2 = 0.31) for leaves. (Tables A4.64-69, 180-187 & 196-203).

Table 4.3 List of F and P values for the relationship between organ nitrogen concentration and minor and trace element concentration (Figures A4.6-10, Tables A4.70-99).

Nutrient Organ F value P Mg Leaf 0.15 0.93 Petiole 3.39 0.07 Roots & Stolons 17.52 0.0002* S Leaf 1.67 0.20 Petiole 0.61 0.44 Roots & Stolons 3.16 0.08 Fe Leaf 17.63 0.0002* Petiole 10.80 0.002* Roots & Stolons 4.12 0.05 Mn Leaf 0.79 0.38 Petiole 0.02 0.88 Roots & Stolons 5.11 0.03 Zn Leaf 3.81 0.06 Petiole 1.57 0.22 Roots & Stolons 2.68 0.11 Cu Leaf 1.48 0.23 Petiole 1.22 0.28 Roots & Stolons 1.32 0.26 B Leaf 5.65 0.02 Petiole 3.58 0.06 Roots & Stolons 2.26 0.14 Mo Leaf 30.71 0.0000* Petiole 0.29 0.60 Roots & Stolons 0.22 0.64 Na Leaf 1.31 0.28 Petiole 0.30 0.59 Roots & Stolons 0.06 0.81 Al Leaf 14.79 0.0005* Petiole 7.64 0.009* Roots & Stolons 12.29 0.002* *Denotes significance at P<0.01

4.3.5 Analysis of Growth as a Function of Organ Nitrogen Concentration

Increased N concentration in all organs resulted in increased total dry mass (Fig 4.9a).

The change was most pronounced for N concentration in roots and stolons (P<0.0004).

Leaf (P<0.0000) and petiole (P<0.002) N concentration increases, similarly, produced a greater total dry mass response though the change was more gradual (Tables A4.100-

102).

Individual organ dry mass responses to N concentration within individual organs, were significant in leaf (P<0.0000) and roots and stolons (P<0.01) tissues but not in petioles

(P>0.39) (Figure 4.9b). Root and stolon dry mass approximately doubled for a four fold increase in N concentration. Leaf dry mass initially doubled at lower N concentration from approximately 2.5 to 4.0 % N before levelling out at N concentration greater than

4.5% (Tables A4.103-105).

Leaf and node numbers were both sharply increased with rising N concentration in all organs (Figure 4.10). The number of leaves (P<0.006) and nodes (P<0.0000) approximately tripled with an increase in leaf N concentration from 2.5 to 5.2%. An increase in N concentration in petioles from approximately 1.2 to 4.5% N resulted in three-fold increase in the number of leaves (P<0.0001) and 2.5 fold increase in the number of nodes (P<0.0000). In roots and stolons, an increase from 1.2 to 3.7% N produced similar increases in leaf (P<0.0001) and node number (P<0.0004) as in petioles (Tables A4.106-111).

The number of stolons was increased significantly as N concentration increased in petioles (P<0.0003) and roots and stolons (P<0.002), but not in leaves (P>0.01) (Figure

4 11a). A petiole N concentration change from 1.2 to 4.5 % N resulted in a doubling in the number of stolons. As N concentration increased from approximately 1.2 to 3.7 %

N in roots and stolons, similarly, the stolon number doubled (Tables A4.112-114).

Total leaf area was highly responsive to N concentration in organs (Figure 4.11b). An increase from 2.5 to 5.2 % N concentration in leaf tissue caused an approximate 2.5 fold steady increase in LA (P<0.0000). An increase in petiole N concentration (P<0.0009) from 1.2 to 2.4% N approximately doubled the LA. The response, after 2.4% N, plateaued at around 3.2% N after increasing leaf area another 50% to 14 dm2. Total leaf area declined as a function of N concentration in petioles above 3.2% N. Root and stolon N concentration (P<0.004) from 1.2 to 2.5% N gradually doubled the leaf area, before appearing to plateau at the higher range of 2.4 to 3.7% N (Tables A4.115-117).

There was no change to total stolon length (P>0.1) due to N concentration in any organ

(Tables A4.118-120). Internode length however, increased from approximately 200 to

300 mm, with an increase in petiole N from 1.2 to 4.5% N (P<0.001). Conversely, internode length was reduced significantly from 150 to 100 mm with an increase 1.2 to

3.7 % N in roots and stolons (P<0.001) and 2.5 to 5.0 % N in leaves (P<0.008) (Figure

4.12, Tables A4.121-123).

A 20 ) -1

10 Total Dry Mass (g plant 5 Leaf Petiole Roots & Stolons 0 10

B 8

4 Organ Dry Mass (g)

0 0123456

Organ N Conc. (%)

Figure 4.9 Dry mass of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration: a) Total dry mass, regression equations are y = (1.95 + 0.44x)2 (r2 = 0.50), y = 3.75 + 2.8x (r2 = 0.23) and y = 1.13 + 4.38x (r2 = 0.26) for leaves (____), petioles (…..) and roots and stolons (----) respectively; b) Individual organ dry mass, regression equations are y = (2.54 - 6.52/x2)2 (r2 = 0.55) for leaves and y = 2.84 + 0.29x2 (r2 = 0.13) for roots and stolons. (Tables A4.100-105).

50 A

20 Number ofLeaves

0 120 B

100

Number of Nodes of Nodes Number 40

20 Leaf Petiole Roots & Stolons 0 0123456 Organ N Conc. (%)

Figure 4.10 Organ numbers of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration: a) number of leaves, the regression equations are y = 3.63 + 2.75x1.5 for leaf (r2 = 0.16), y = 6.96 + 3.77x1.5 for petioles (r2 = 0.37), and y = 4.84 + 4.75x1.5 for roots and stolons (r2 = 0.36); b) number of nodes, regression equations are y = 5.02 + 8.35x1.5 (r2 = 0.48), y = 40.08 + 10.19xlnx (r2 = 0.58) and y = 1.13 + 4.38x2 (r2 = 0.26) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A4.106-111).

35 A

15 Number of Stolons of Stolons Number

20 ) 2

10 Total Leaf Area (dm Total

5 Leaf Petiole Roots & Stolons 0 0123456 Organ N Conc. (%)

Figure 4.11 Organ numbers and dimensions of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration: a) Number of stolons, regression equations are y = 12.67 + 0.17x3 (r2 = 0.28) for petioles and y = 10.23 + 1.008x2 (r2 = 0.22) for roots and stolons; b) Total leaf area, regression equations are y = 2.10 + 1.37x1.5 (r2 = 0.47), y = 14.7exp(-0.5((x-3.56)/1.72)2) (r2 = 0.29) and y = 4.97 + 2.88x (r2 = 0.18) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A4.112-117).

500 Petiole Roots & Stolons Leaf 400

300

200 Internode Length (mm) Length Internode

100

0 0123456 Organ N Conc (%)

Figure 4.12 Internode length of lotus (Nelumbo nucifera) as a function of organ nitrogen concentration, regression equations are y = 160.02 - 8.37xlnx (r2 = 0.14), y = 173.43exp(- 0.15x) (r2 = 0.24) and y = 220.77/(1 + 0.38x) (r2 = 0.26) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A4.121-123).

4.3.6 Analysis of Total Dry Mass as a Function of Nitrogen Supply Affected Growth Parameters.

Total leaf area was the growth parameter with the greatest effect and hence limit on the creation of dry mass for lotus (Figure 4.13, Tables 4.3 & A4.124). Total dry mass increased uniformly to approximately quadruple for a five-fold LA change. Stolon numbers also contributed to increasing dry mass, though the F statistic was considerably less than for LA. Leaf number, node number, and total stolon length increases, also had significant F values (Tables A4.125-129), though again were lower than for LA and number of stolons and perceived as having less importance to dry matter production.

Conversely, increasing internode length resulted in a decline of dry mass.

10 Total Dry Mass (g)

0 0 5 10 15 20 25

2 Total Leaf Area (dm )

Figure 4.13 Total dry mass of lotus (Nelumbo nucifera) as a function of total leaf area. Linear regression is y = 1.68 + 0.83x (r2 = 0.83, Table A4.124).

Table 4.4 Total dry mass of lotus (Nelumbo nucifera) F statistic and coefficient of determination as a function of growth parameter (Figures 4.13 & A4.8-10, Tables A4.124-129).

Parameter F stat. P r2 Total leaf 159.1 0.0000 0.83 area Stolon No. 64.9 0.0000 0.63 Node no. 32.7 0.0000 0.45 Total stolon 31.95 0.0000 0.44 length Leaf no. 28.3 0.0000 0.41 Internode 10.26 0.003 0.18 length

4.3.7 Analysis of Growth Parameters Affected by Nitrogen Concentration, as a Function of Nitrogen Concentration Affected Organ Nutrient Concentration.

Increasing P concentration in leaves and roots and stolons had no significant effects on growth (Tables A4.130, 132-3, 135-6, 138-9, 141-2, 144-5 & 147). Similarly, changing levels of leaf K and Ca concentration had no effects on growth (Tables A4.148, 151,

154, 157, 160, 163 & 166-171). Doubling the P concentration in petioles resulted in a significant increase in leaf numbers (P<0.008) from 20 to 40 leaves (Figure 4.14, Table

A4.137), but not any other growth parameter (Tables A4. 131, 134, 140, 143 & 146).

Total dry mass (P<0.002) decreased from approximately 15 to 5 g plant-1 and stolon numbers (P<0.003) from 25 to 10 stolons with an increase of K in petioles from 45.00 to 70.00 g K kg-1 (Figures 4.15a-b, Tables A4.149 & 161). No other growth parameter was affected by petiole K concentration (Tables A4.152, 155, 158, & 164). Leaf, node and stolon numbers were reduced 3.5, 2.5 and 2.5 times respectively with increasing K concentration from 25.00 to 55.00 g kg-1 in roots and stolons (Figures 4.16-17a, Tables

A4.156, 159 & 162). Conversely, internode length increased by 50% with the same K concentration rise in roots and stolons (Figure 4.17b, Table A4.165). Total dry mass and LA were unaffected by variation of K concentration in root and stolon tissue

(Tables A4.150 & 153).

Number of Leaves Number 20

0 0 2000 4000 6000 8000 10000 12000

-1 Petiole P conc. (mg kg )

Figure 4.14 Number of leaves for lotus (Nelumbo nucifera) as a function of petiole phosphorous concentration. Regression equation is y = 16.16 + 1.85*10-11x3 (r2 = 0.13). (Tables A4.137).

100

20 ) -1

10 Total Dry Mass (g plant 5

0 35

B 30

15 Number of Stolons of Stolons Number

0 20000 40000 60000 80000

Petiole K conc. (mg kg-1)

Figure 4.15 a) Total dry mass of lotus (Nelumbo nucifera) as a function of petiole potassium concentration. Regression equation is y = 23.89 - 3.51*10-9x2 (r2 = 0.22); b) Number of stolons of lotus as a function of petiole potassium concentration. Regression equation is y = 29.94 - 1.62*10-11x2.5 (r2 = 0.19). (Tables A4.149 & 161).

101

50 A

Number of Leaves 20

120 B

100

Number of Nodes Number 40

0 0 10000 20000 30000 40000 50000 60000

-1 Roots & stolons K conc. (mg kg )

Figure 4.16 Organ numbers of lotus (Nelumbo nucifera) as a function of roots and stolon potassium concentration a) Number of leaves, regression equation is y = 42.43 - 8.88*10-10xlnx (r2 = 0.15); b) Number of nodes, regression equation is y = 117.97 - 5.36*10-6x1.5 (r2 = 0.14). (Tables A4.156 & 159).

102

35 A 30

15 Number of Stolons of Stolons Number 10

0 250 B

200

150

100 Internode Length (mm) Length Internode

0 0 10000 20000 30000 40000 50000

-1 Roots & stolons K conc. (mg kg )

Figure 4.17 a) Number of stolons of lotus (Nelumbo nucifera), regression equation is y = 32.61 - 1.77*10-6x2 (r2 = 0.22); b) Internode length of lotus, regression equation is y = 81.36 + 4.11*10-13x2.5 (r2 = 0.19); both as a function of roots and stolon potassium concentration. (Tables A4.162 & 165).

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4.4 Discussion

The objective of the experiment reported in this chapter was to determine the critical concentrations of N required for adequate growth of lotus. Varying the supply of nitrogen to lotus in the research system has an effect on all growth parameters except for total stolon length. Dry mass and leaf area appear to be the strongest indicators of a change in growth due to changes in supply of N (Figures 4.1 & 4.3a). It is not clear from these results where the supply range exhausts growth as the greatest growth was seen at the highest supply rate of N400. This result raises further questions over the upper limit of supply on growth and the consequential effect this may have on rhizome formation. Nitrogen suppression of tuberisation in potato (Solanum tuberosum L.) has been frequently reported (Ewing 1997). While the supply level of N400 resulted in the greatest growth, this was not significantly greater than the growth achieved at rates of

N225 to N350. The results can be used to provide an estimate of the lower critical supply rate. The results at the lower end of the supply, though different, are not sensitive enough to determine absolutely a lower critical level, but are coarse enough to provide a working estimate.

Positive identification of N symptoms of deficiency was marred by the presence of the chlorosis/necrosis of margins on older leaves, described in the previous chapter. These symptoms are not consistent with N deficiency. Nitrogen toxicity was not recorded either as the highest treatment provided the greatest amount of actual growth, though only significantly different from treatments N50 and N150. The inadequacy of symptomology and a greater identification of the region where N is most sensitive,

104

between N0 and N225, is a strong argument for further trialling of N, after analysis of the other trials in order to design trials with more appropriate treatments.

The range of concentration for N due to supply was between 2.0 to 4.3% for leaves and petioles, and between 1.5 to 3.75% for petioles, roots and stolons (Figure 4.6). The trend was to increase with increasing N supply. Comparisons with sweetpotato young mature leaves, 28 days after transplant, critical limits at 4.2% and 4.3%, and 4.5% as adequate, suggest this range is acceptable at the higher level. Leaves of Irish potatoes however, have a much lower adequate range (1.8 to 3.0 % c.v. Atlantic) and critical limit (1.4 to 1.7%) (Huett et al. 1997).

Dry mass and organ numbers all increased with the corresponding increase in N concentration for all organ types (Figures 4.9, 10, & 11a). The characteristic curve required for estimating the correct level of N in tissues or where its adequate growth lies was not established for dry mass or organ numbers. This could only be determined for leaf area as a function of N in petioles (Figure 4.11b) which provided data showing the expected curvilinear relationship. Given that leaf area can be shown to be the single most important growth factor dictating the amount of dry mass produced (Figure 4.13,

Table 4.3), and that leaf area is restricted by the concentration of N in petioles at lower and higher N%, then the petioles may prove to be the most suitable organ for tissue analysis. Further, the results obtained for petioles and leaf area may be used as an indication of the next step required to resolve the critical concentration objectives.

There are several models available from which estimations of critical concentrations of various species have been deduced. Historically, nutrient calibration curves were fitted

105 by freehand to assess a particular growth measurement against nutrient concentration, based on the assumption that any nutrient concentration below 90% growth is either in the zone of deficiency or toxicity (Macey, 1936; Ulrich, 1952; Smith, 1962; Bates,

1971). Before the advent of powerful computational methods from which to pick the most appropriate line for the data, researchers proposed a variety of statistical and computational methods from which to determine critical concentrations.

Cate-Nelson (1971) suggested partitioning data into two classes based on tentative critical levels and using the means of the two groups to ascertain correlation coefficients to maximise the overall predictive ability. Similar to the imposition of a line designated free-hand on points plotted for growth as a function of nutrient concentration, this method is still quite arbitrary and has no ability to account for error (Lewis et al. 1993).

A statistical technique designed to overcome any arbitrary factors is known as the

- Mitscherlich model (Ware et al. 1982). This method utilises the equation y = β(1 - γe x α ) to characterize deficiency levels. Based upon the estimates for β the asymptotic maximum growth, γ the decrement of the asymptote and the y value at x = 0 (the assumption being that some yield is to be expected at 0 nutrient input), α the constant of proportionality, and measured parameters y and x being growth or yield and nutrient concentration respectively. The problem with this method as pointed out by Parks et al.

(2000) was that it could only be applied to the zone of deficiency, thereby discounting all points measured in a possible toxic region. Further, the estimates still have arbitrary elements, because they are based on observed data, and no ability to account for the amount of error (Lewis et al. 1993).

106

Pinkerton et al. (1989) argued the use of substituting the corresponding nutrient supply concentration for rapeseed plants in shoots which had 90% of the shoot dry mass. This method fails to acknowledge the possibility of error by way of ‘healthy’ plants containing similar nutrient concentration, or difference in growth or yield, is a product of some other influencing factor.

Another plant analysis interpretive model is the DRIS or diagnosis and recommendation integrated system (Jones 1993 citing Beaufils 1973). A system which compares calculated nutrient ratio indices with prior accepted standards. In the absence of standards with which to compare against, this system could not be considered for analysis of lotus data. Questions over the efficacy of this method have also been raised regarding the lack of standard data (Reuter and Robinson 1986). Jones (1993) points out the inadequacy of this method in the sufficiency range, though considers it useful for analyses of data close to the critical concentrations.

The generally accepted standard for plant analysis is a hybrid of those developed in the past and is known broadly as the critical range concentrations. These are not regarded as absolutes as there are many influencing factors governing the plants growth and yield responses such as environmental interactions, plant part, plant age, culture system, and genotype (Lewis et al. 1993). The critical range is the zone of sufficiency, determined by species, as having a yield of dry matter above 90 to 99% of the total dry matter production or other appropriate measurement of growth (Jones 1993). With the advent of computer technology and software, models can be fitted which not only accurately describe fitted regression curves but which include estimates of the associated error

(Smith and Loneragan 1997). The most powerful computational equipment is of no

107 use if the data do not demonstrate the typically expected response. Many examples have been reported for all elements associated with plants, and a wide variety of species, that provide indicative criteria for a response curve to be acceptable (Jones 1993, Lewis et al. 1993, Smith and Loneragan 1997). The results generated from this experiment mostly do not show the expected differentiation of deficient, adequate and toxic ranges desired of plant analysis curves. The curves selected, which were the most appropriate fit for the data, largely did not resemble those expected of plant growth response as a function of nutrient content. Further, the scatter of individual data points around the curve, reflected in consistently low coefficients of determination, reduced the likelihood of being able to achieve the expected response.

Due to the spread of the yield dry mass data generated from this experiment and its failure to achieve a plateau (Figure 4.9), it is necessary to resolve the estimation of a critical concentration using the response of LA to N concentration in petioles (Figure

4.11). The demonstration of LA giving the most influence on the production of dry matter (Figure 4.13) further compels the argument for adoption of these data in accepting a position from which future investigation can be designed. The estimated adequate range and critical concentration in petioles can be found from Figure 4.11b

(Table A4.116) by using the evaluation function in Tablecurve v.2.0 with the corresponding equation y=14.7exp(-0.5((x-3.46)/1.72)2) (Table A4.116):

Ü The maximum LA = y = ~ 14.68 dm2.

2 Ü 90% of the maximum LA (y1) = 14.68 * 0.9 = 13.21 dm .

2 Ü At 13.21 dm , the lower limit (x1) was 2.66% and the upper limit (x2) was 4.25% for petioles (Figure 4.11b, Table A4.116).

108

Ü As there was not a unique relationship for petioles alone, the relationships for N concentration in petioles, leaves and petioles, and petioles, roots and stolons

with LA were evaluated by calculating the adequate supply rates for each petiole

relationship (Figure 4.6, Tables A4.59, 173 & 175).

Ü Using the relationship for leaves and petioles shown in Figure 4.6 (Table A4.173), the adequate supply rate ranges from 168 to 395 ppm.

Ü Using the relationship for petioles, roots and stolons shown in Figure 4.6 (Table A4.175), the adequate supply rate ranges from 275 to 464 ppm.

Ü Using the relationship for petioles (Table A4.59), the adequate supply rate ranges from 253 to 439 ppm.

When using these relationships it is apparent that inconsistencies occur within the calculated adequate supply rates. They do not calibrate with growth responses of 90 % of the maximum when observing Figures 4.1-3, and do not transpose amongst relationships, producing extrapolated calculated growth estimates of unequal value.

For example, when the adequate supply rate minimum of 168 ppm from the relationship for leaves and petioles, is extrapolated by the other two relationships which express N concentration in petioles (Tables A4.59 & 175), the corresponding calculated petiole N concentrations differ considerably. When these calculated petiole N concentrations are applied back to the relationship between LA and petiole N concentration (Figure 11b,

Table A4.116), the values achieved should be equivalent. The value of the calculated

LA, or any growth parameter suitable for analysis, ideally should be 90 % of the maximum LA, any value calculated that is outside a nominated ± 5 % tolerance should be considered invalid as an indicator of a relationship’s integrity to represent critical

109 concentration and adequate supply rates. A list of calculated values for LA based on the extrapolated adequate supply from all three relationships expressing petiole N concentration is presented (Table 4.5). The values for the petiole only relationship would be expected to return exact values due to the direct connection with the original petiole LA and N concentration relationship. However, the cross-referencing of adequate supply rates through associated relationships revealed all but one of the calculated values (the lower N supply value N275 for combined petioles, roots and stolons) for LA at 90 % of the maximum are outside the stated tolerance (Table 4.5).

The physical implications for sampling of roots and stolons of field specimens for organ nutrient content, precludes their selection as an organ for analysis. Hence, the use of these combined relationships for the establishment of adequate supply range (Figure

4.6, Tables A4.173 & 175), based on tentative critical concentrations drawn from the relationship between LA and petiole N concentration (Figure 4.11b, Table A4.116), should be avoided. In the context of this experiment, the adequate supply range should be defined by the relationship for petioles alone (Table A4.59). Therefore, the adequate supply rate ranges from 253 ppm to 439 ppm N (Table 4.5), corresponding to estimated petiole N critical concentration values of 2.66 % and 4.25 % N for deficient and toxic limits respectively, were adopted. Further, these derived adequate supply rates can be assessed against the relationships for leaves and for roots and stolons (Tables A4.58 &

60) to quantify extrapolated critical limit estimates for these organs. Therefore, the extrapolated critical limits were calculated to be 3.71 to 4.98 % N and 2.45 to 3.47 % N for leaves and roots and stolons respectively. Estimates of major element concentrations in organs were also derived using the appropriate relationships and are discussed in below.

110

Table 4.5 The critical concentration, extrapolated 90% maximum total leaf area, and percentage maximum total leaf area for lotus (Nelumbo nucifera), calculated from adequate supply rates substituted into the relationships involving petiole nnitrogen concentration and total leaf area (Figures 4.6 & 11b, Tables A4.59, 173 & 175).

Relationship N s upply N (%) LA 90 (dm2) % max LA (ppm) Leaf & Petiole-Def 168 2.09 10.74 73.16 Petiole/Roots & 275 2.8 2 13.7 3 93.5 3 Stolons-Def Petiole-Def 253 2.66 13.18 89.78

Leaf & Petiole-Tox 395 3.83 14.35 97.75 Petiole/Roots & 464 4.49 12.28 83.65 Stolons-Tox Petiole-Tox 439 4.25 13.21 89.99 Def-deficient critical conc., Tox-toxicity critical conc.

The results obtained from this experiment suggest that only petioles should be taken during sampling procedures and used to estimate the limiting concentration of N in lotus. While the accuracy of determining the best supply is drawn from the petiole alone relationships, the combined organs single line relationships can be used to describe both leaf and roots and stolon N concentration from petiole N concentration data. Therefore, a field sample of petioles would provide estimates for leaf, petiole and root and stolon organ N concentration.

The extrapolated adequate supply rates suggest that the upper treatment supply concentration N400 was close to the margin upon which growth would be limited at the toxic region. A future experiment to satisfy this speculation and discern the critical range should be sensitive to the lower and higher ends of the supply spectrum. A greater number of replicates per treatment may also reduce the effects of any variation within each treatment. To capture the upper transition zone and toxic region for nitrogen concentration in lotus, treatments in an experiment should range between N350

111

to N500. The lower end of the supply range needs greater clarification through a greater number of treatments across the range of N25 to N300. A zero treatment is an improbability as a treatment in soil-less culture systems, as N in the NO3 form is a co- carrier of K and Ca, therefore a certain amount of N is inevitable.

The quantity and ratio of NO3-N to NH4-N should also be considered. The variation in total and organ dry mass from N225 to N275, and subsequent increase in dry mass from

N275 to N400 where it was the maximum dry mass for all treatments, suggest the additions of NH4-N at N325 and N400 (Table A1.6) could be responsible for the increased production of dry mass.

The variable amounts of S across the treatments (Table A1.6) were largely discounted as having any influences on growth parameters, as the concentration of S found in organs did not significantly change across treatments (Figure A4.1, Tables A4.31-33).

The exception was leaf S concentration which had a strong relationship with LA

(P<0.0000, r2=0.50, Table A4.205), and a weaker though still significant relationship with total dry mass (P<0.006, r2=0.15, Table A4.204). The relationship of leaf S concentration with LA is less significant than the relationship for N concentration in leaves (P<0.0000, r2=0.47), though the co-efficient of determination for the S argument is higher (Tables A4.115 & 205). These results suggest that experimental work should be undertaken with S as the treatment variable.

The critical concentration approximations can be used to indicate the possible concentrations for P, K, and Ca that would be found. The estimates will be challenged in the following chapters, against the data resulting from the subsequent single factor

112 trials using P, K, and Ca. Using the assumed calculated adequate supply range for N, P concentrations of 6.89 to 5.09 g kg-1 for leaf, 6.99 to 9.17 g kg-1 for petioles, and 8.92 to

11.02 g kg-1 for roots and stolons were extrapolated using the relationships from Figure

4.7 (Tables A4.61-69). These concentrations, highest in roots and stolons then petioles followed by leaf tissue, changed due to supply of N (Figure 4.4b) and organ N concentration (Figure 4.7). This indicates that any of these three organs could be used to determine P concentration as they all demonstrate an ability to express a range of P concentrations.

However, the increases in P concentration as a result of increased N% seem to be artefactual as no significant differences, other than an increase in leaf number (P<0.008) with increasing petiole P (Table A4.137), were observed for growth in relation to changing P concentration (Tables A4.130-136, 138-147). According to Kleinheinz et al. (2000) increases in P uptake as a result of increasing N supply have been documented for many crop plants. Based upon these statistics it could be predicted that

P concentrations in organs in subsequent work, would be in a similar range as found by this experiment. It is difficult to predict any growth outcomes as a function of P as the reliance on N appears to be an over-riding influence on this data set. Kleinhenz et al.

(2000) report a decrease in photosynthetic activity as a result of increased P and subsequent yield in waterchestnut trials. The results of a trial undertaken where phosphorous supply was varied are reported in the next chapter.

Nitrogen limited K uptake in petioles and roots and stolons (Figure 4.8a) but conversely seemed to increase K in leaves. In petioles, low N and high N depressed K uptake whereas for roots and stolons K uptake was only reduced by increasing N. Using the

113 assumed N adequate range, extrapolation from Figure 4.8a, the results yield K concentration levels of 29.32 to 33.34 g kg-1 for leaves, 60.08 to 48.50 g kg-1 for petioles, and 43.17 to 38.77 g kg-1 for roots and stolons. Comparing with sweetpotato at an adequate concentration range for leaves lying between 47.00 to 60.00 g kg-1 K at 28 days after transplanting, and 40.00 g kg-1 K listed as critical, the level for lotus seems quite low (Huett et al. 1997).

It was observed (Figures 4.15-17a) that increased concentrations of K in petioles and roots and stolons were detrimental to growth. The data suggests either a nutrient balance correction between N and K was necessary, or high K levels were a limiting factor to growth. It could be predicted from this set of results that increasing K beyond a certain concentration level would depress growth. The results of an experiment in which supply of K was varied are reported in Chapter 5. A trial with N as a second factor would be necessary to establish the relationship between N and K further.

Insufficient K could not be ascribed to the marginal chlorosis/necrosis as was proposed in the last chapter as the presence of this symptom was evident for all treatments and as has been shown, increasing K concentration had a negative effect on growth. Therefore, adequate if not too much K was present in the supply solution. An imbalance with another element may produce an expression of K deficiency. Such an imbalance is noted by Mott (1988) in regard to the interaction of cations in solution, especially Ca which may dominate solutions.

Calcium was only of significance in leaves, as a function of N supply and in relation to leaf N concentration. Nitrogen concentration became limiting to Ca concentrations after

114 a peak at 3.75 % N (Figure 4.8a), though this limitation was not related to any changes in growth (Tables A4.166-171). Further, there were no limits achieved for leaf growth associated with any one nutrient to calculate critical concentration limits. Therefore, indications of critical concentration limits for Ca in leaves were derived from the critical concentrations and corresponding adequate supplies determined from the relationships between petiole N concentration and LA, and N supply and petiole N concentration. No concentration range was found for Ca in petioles or roots and stolons, and therefore, could not be estimated from a graph in the same manner as P and K approximations.

However, the actual Ca concentration at the adequate supply rates could be calculated.

The resulting concentrations for organ Ca using the relationships for Figure 4.8b

(Tables A4.67-69), indicate Ca concentration limits of 22.86 to 17.88 g kg-1 for leaves, and concentration ranges of 19.92 to 22.13 g kg-1 for petioles and 18.83 to 22.64 g kg-1 for roots and stolons.

This is high in comparison to sweetpotato with 7.30 to 9.50 g kg-1 reported for mid- growth young mature leaves (Huett et al. 1997). The trend indicated by N supply on organ Ca concentration (Figure 4.5b) suggests either N has little or no interaction, or, as the sweetpotato example indicates, the concentration in the supply was far too large for the N treatments to solicit any response. High Ca may also be the explanation for the marginal chlorosis/necrosis which is being observed in the older leaf tissue.

Partitioning of the immobile Ca in quantities too great to be absorbed by the required number of binding sites in the tissue may be having a negative effect causing the

‘burning’ of leaf tissue (Schwarz 1995). Alternatively, competition for binding sites by positively charged Ca2+ molecules may be inhibiting K+ charged molecules, soliciting a pseudo-potassium deficiency (Schwarz 1995, Jones 1997).

116

Chapter 5 Analysing the Interaction between Phosphorous and Lotus

5.1 Introduction

Phosphorous, in the form of orthophosphate, is one of the major soil derived nutrients essential for plant growth and function (Mengel and Kirkby 2001). It is a vital component of nucleic acids, a variety of proteins, lipid membranes and carbohydrate structures (Taiz and Zeiger 1991). In the ionic form, P is a regulator and participant of chemical reactions utilised by the energy exchanging compounds ATP and ADP during the photosynthesis and respiration cycles of plant metabolism (Marschner 1995). The importance of P to plants is perhaps best illustrated by the magnitude of the gradient between P concentration in the plant cell cytosol and in the supply of available P.

Mengel and Kirkby (2001) report a thousand fold gradient for which plants have adapted an active uptake system in order to acquire P.

The availability of P is dependent upon several factors most importantly the reservoir of

P concentration, chemistry of the media, and the presence of symbiotic micro-organisms which specifically assist P uptake. It is not known if lotus, an obligate anaerobe, has any such associations. However, it is widely known that P is often restricted by pH in soils and solution cultures. In soils, a slightly acid pH is required or P is restricted through binding to other particles, primarily Fe and Al particles as hydrous oxides

(Moody and Boland 1999). In solution culture PO4 precipitates with Ca ions at pH levels greater than pH 7 (Weast 1966, Schwartz 1995). As reported in Chapter 2,

Experiment 7 showed that pH affects the amount of growth of lotus, and any system for growing lotus should be in the range of pH 6.25 to pH 7.0, with pH 6.25 for optimum

117 growth. It was not established that differences in pH affected P availability, or if the growth response to pH was a function of P availability or uptake. Therefore, it is necessary to evaluate the response of lotus to P in a pH steady environment to observe the growth.

Critical concentrations and symptoms of deficiency for P, caused by low supply or pH imbalance, have been widely reported for a number of species (Reuter and Robinson

1997). Deficiencies often manifest in plants as stunted growth, accompanied by dark green discolouration yielding to purplish tinges in leaves due to the excessive production of anthocyanins, and thin non-woody stems (Grundon et al. 1997).

Symptoms generally appear in older leaves first when P deficiency stress is encountered, reflecting the mobility of P within plant tissues (Mengel and Kirkby 2001).

Phosphorous toxicity, generally occurs when plant parts contain greater than 1%

(Marschner 1995), symptoms can display interveinal chlorosis resembling Fe deficiency in young leaves and marginal and interveinal scorching of mature leaves leading to abscission (Grundon et al. 1997).

The role of P, critical P concentrations, the organ required for plant sampling and symptoms of deficiency of P in relation to lotus, have not been adequately documented.

Similar to N, there has been no report beyond those advised by Nguyen (2001).

Comparative analysis may be derived from other crops with similar morphological features to lotus as was performed for N. In Experiment 10, the supply level of P was constant at 45 ppm and a range of test results were achieved for growth parameters and nutrient tissue concentration as a function of N supply. Phosphorous was found in varying concentrations in all tissues due to N supply and it was clear an interaction

118 between N and P was manifest. The concentrations of P had no significant effect on any growth parameter, except for the amount of P in petioles, which were shown to influence the number of leaves. This influence was not as strong as for N supply or N concentration (Tables A3.5, and 101-103).

The actual physical ranges for P in each tissue for the most favourable growth results were 4.29 to 5.73 g kg-1, 6.99 to 9.176 g kg-1, and 9.30 to 13.10 g kg-1 for leaves, petioles, and roots and stolons, respectively. The previous and next experiment were conducted simultaneously and with the same supply constant treatment as the upper mid-level treatment, P45 (Table 1.6-7). This is the corresponding N supply constant treatment in Experiment 10 (N275), which was equivalent in nutrient composition, EC and pH. The growth response results of N275 were similar to and within the treatments

N225 to N400 which produced the maximum growth. It could be predicted that the results in the following experiment will be similar in nutrient concentration range and plant growth response. Further, it is expected that the highest concentrations for P will be in the order roots and stolons, petioles and leaves and that leaf numbers and N concentration in tissues will be affected by P supply.

This chapter aimed to determine the efficacy of utilising the proposed system by challenging lotus with a range of P treatments. The ability to establish organ critical nutrient concentrations, adequate supply rates for P, identify the most appropriate organ for field sampling, and documentation of expressed nutritional disorder symptoms, were the objectives. The following experiment was conducted.

119

5.1.1 Experiment 11 Effect of Phosphorous on Growth and Tissue Nutrient Concentration of Lotus (Nelumbo nucifera ).

During September of 2002, a trial involving seven phosphorous treatments with five replications per treatment was undertaken over a 50 day period of growth. Analysis of growth parameters, effect of P supply and effect of major nutrient concentrations with significant differences were performed.

5.2 Materials and Methods

The conditions for plant growth, harvest, and statistical procedures were as per section

4.2 except for treatment imposition.

Phosphorous treatments comprised 5, 15, 25, 40, 45, 50, and 100 ppm of P and were identified as P5 to P100 respectively (Table A1.7). A t-test for the comparison of samples means with equal variances was used to discriminate between calculated critical concentration estimates.

120

5.3 Results

5.3.1 Observations of Phosphorous Supply on Visual Growth Expression.

At day 20 all plants showed signs of disorder (Table 5.1). The marginal chlorosis/ necrosis symptoms found in previous experiments were present for all treatment classes. Blackening of roots from the oldest node was also present. Signs of disorder typical of phosphorous deficiency were seen in one replicate of the P5 treatment only. A slight purple hue could be distinguished in one leaf only. Signs of P toxicity were not seen. It was obvious that P treatments caused an effect on plant growth, plants appeared to be of smaller size at low and high treatments compared to mid-range treatments.

At day 50, the same symptoms of disorder were evident except for the P deficiency seen at day 20. It was clear that the amount of blackening of the roots had a gradient from P5 to P100 (Table 5.1).

Table 5.1 Estimated observations for lotus (Nelumbo nucifera) on: a) the percentage of leaves per plant showing signs of disorder at day 20; b) the percentage of leaves per plant showing signs of disorder at day 40; c) the percentage of total leaf area per plant affected by disorder at day 40; d) the below-ground plant parts affected by disorder at day 20; e) below-ground plant parts affected by disorder at day 40. Values followed by different letters are significantly different at P<0.01 within each column (Tables A5.1-5).

Treatment A B C (ppm) D E 5 57.50ab 71.25a 2.17a 42.50a 75.00a 15 42.50ab 42.50a 4.87a 37.50a 50.00ab 25 27.50ab 32.50a 4.46a 40.00a 57.50ab 40 25.00ab 55.00a 6.77a 42.50a 57.50ab 45 25.00ab 47.50a 6.81a 17.50a 42.50ab 50 5.00b 62.50a 5.98a 28.75a 42.50ab 100 41.25a 60.00a 3.32a 22.50a 25.00b

121 5.3.2 Phosphorous Supply Effect on Growth Parameters.

Dry mass, organ numbers, organ dimensions and leaf area were significantly affected by phosphorous supply. Total dry mass and dry mass of all leaves, petioles, and roots and stolons generally increased, plateaued, then decreased (P<0.001) with increasing P supply, respectively (Figures 5.1a-b, Tables A5.6-9). Total dry mass

-1 -1 increased from approximately 6 g plant at P5 to a peak and plateau of 20 g plant at

-1 P40 to P50, before decreasing to approximately 10 g plant at P100. All organs displayed the same pattern as that shown for total dry mass. Leaves increased from approximately 2 g at P5 to a peak of 7.5 g at P40 before decreasing to 4 g at P100.

Petioles showed the least change by increasing from approximately 2 g at P5 to a maximum of 5g over P40 to P50 before decreasing to 3g at P100. Roots and stolons had the greatest change over the range of treatments and greatest amount of dry mass in all treatment classes. They increased from approximately 3 g at P5 to a maximum of 8 g where it plateaued to P50 before decreasing to 4 g at P100.

The number of leaves increased, but the effect was not significant (P>0.01) from approximately 8 leaves at P5 to 22 leaves at P25 before decreasing gradually to 14 leaves at P100 (Figure 5.2a, Table A5.10). The number of nodes increased significantly (P<0.0000) from approximately 38 nodes at P5 to 82 nodes at P25 before decreasing to 50 nodes at P100 (Figure 5.2b, Table A5.11). The number of stolons had a similar pattern of significant increase (P<0.001), rising from approximately 8 to 23 stolons over P5 to P25 before decreasing to 12 stolons from P25 to P100 (Figure

5.2c, Table A5.12).

2 Total leaf area increased significantly (P<0.001) from approximately 3 dm at P5 to

2 14 dm at P25 where it plateaued for the next 3 treatments (Figure 5.3a, Table A5.13).

122 2 Total leaf area then fell to approximately 7 dm at P100. Total stolon length demonstrated the same trends but the effect of the treatment was not significant

(P>0.01) (Figure 5.3b, Table A5.14). Internode length did not show any significant differences due to treatment, nor in the pattern of response of growth (Figure 5.3c)

(P>0.7, Table A5.15).

123

20 ) -1

10 Total Dry Mass (g plant 5

0 B Leaf Petiole 8 Roots and Stolons

4 Organ Dry Mass (g)

0 0 20406080100

P Supply (ppm)

Figure 5.1 Dry mass of lotus (Nelumbo nucifera): a) Total dry mass; b) Organ dry mass for leaf, petiole, and roots and stolons as affected by phosphorous supply. Values are means and bars represent S.E. (n=5). (Tables A5.6-9).

124

10 Number of Leaves Number

80 B

40 Number of Nodes

0 20 C

10 Number of Stolons of Number

0 0 20406080100 P Supply (ppm) Figure 5.2 Effect of phosphorous supply on lotus (Nelumbo nucifera) organ numbers: a) Leaf no. b) Node no. c) Stolon no. Values are means and bars represent S.E. (n=5). (Tables A5.10-12).

125

18 A 16

14 ) 2 12

6 Total Leaf Area (dm Area Leaf Total

2500 B

2000

1500

1000 Total Stolon Length (mm) Length Stolon Total

500

35 C

Internode(mm) Length 10

0 0 20406080100 P Supply (ppm) Figure 5.3 Effect of phosphorous supply on lotus (Nelumbo nucifera) organ dimensions: a) Total Leaf Area; b) Total Stolon length; c) Internode length. Values are means and bars represent S.E. (n=5). (Tables A5.13-15).

126 5.3.3 Effect of Phosphorous Supply on Organ Nutrient Concentration.

Supply of P had a highly significant effect on P concentration in leaves (P<0.0000), petioles (P<0.0000), and roots and stolons (P<0.0000) (Figure 5.4a, Tables A5.19–

-1 21). In leaves, P concentration was approximately 2.00 g kg at P5 and increased

-1 - steadily to approximately 8.00 g kg at P100. Petioles had approximately 1.50 g kg

1 -1 of P at P5 and increased to 10.50 g kg P at P100. Roots and stolons had

-1 -1 approximately 1.40 g kg at P5 and increased to 13.50 g kg at P100. Petiole P concentration was greater than in leaves after P25. Roots and stolon concentration was greater than in petioles at P25 and greater than in leaves thereafter.

Supply of P had no significant effect on N concentration in leaves (P>0.01), petioles

(P>0.05), roots and stolons (P>0.05) (Figure 5.4b, Tables A5.16–18). Leaves contained approximately 3.5 % N, petioles had between 2 to 3 % N, while roots and stolons contained between 2 to 2.5 % N.

Supply of P had no significant effect on K concentration in leaves (P>0.03), petioles

(P>0.3), and roots and stolons (P>0.07) (Figure 5.5a, Tables A5.22–24). In leaves, approximately 26.00 g kg-1 of K was found, in petioles approximately 55.00 g kg-1 and between 40.00 to 45.00 g kg-1 of K was found in roots and stolons.

There was no significant response for calcium concentration in leaves (P>0.02) and petioles (P>0.2) due to P supply (Figure 5.5b, Tables A5.25-26). In leaves approximately 18.00 to 25.00 g kg-1 of Ca was found, whilst in petioles approximately 10.00 to 12.00 g kg-1 of Ca was found. Calcium concentration differences in roots and stolons due to P supply, were significant (P>0.01) (Figure

5.5b, Table A5.27). Roots and stolons contained approximately 10.00 g kg-1 of Ca at

127 -1 P5 and decreased to around 9.00 g kg at P40 to P50 before increasing to

-1 approximately 11.00 g kg at P100.

There were no significant differences in the organs as a function of P supply for Mg,

S, Fe, Cu, B, and Al (Tables 5.2). Further, no differences were found for Mn, Zn and

Na in leaves as well as Zn and Na in petioles (Table 5.2). Concentration of Mn in petioles and roots and stolons was significantly affected by P supply. In petioles,

-1 -1 approximately 28 mg kg of Mn was found at P5 which decreased to 15 mg kg at

-1 P40 to P50 before increasing to 20 mg kg at P100 (Figure A5.2a). Approximately 20

-1 -1 mg kg of Mn was found in roots and stolons which decreased to 14 mg kg at P40 to

-1 P50 before increasing to 20 mg kg . The concentration of Zn in roots and stolons

-1 was steady at approximately 80 mg kg from P5 to P50 before sharply increasing to

-1 130 mg kg at P100 (Figure A5.3a). Root and stolon concentration for Mo decreased

-1 -1 significantly from approximately 8.5 mg kg Mo at P5 to a minimum of 5.5 mg kg

-1 at P25 before increasing to 6.5 mg kg at P100 (Figure A5.4b). The concentration of

Mo in leaves and petioles was considered not significant, the anomalous result for

P45 was considered artefactual. Root and stolon Na concentration increased from

-1 approximately 2.50 g kg at P5 to 4.00 g kg Na at P15 to P50 before increasing to 4.50

-1 g kg at P100 (Figure A5.5a).

128

14000 A

12000 ) -1 10000

8000

6000

Organ P Conc.kg (mg 4000

Leaf 2000 Petiole Roots & Stolons

4 )

-1 3

2 Organ N Conc. (mg kg (mg N Conc. Organ 1

0 020406080100

P Supply (ppm)

Figure 5.4 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Phosphorous; b) Nitrogen. Values are means and bars represent S.E. (n=5). (Tables A5.16-21).

129

60000

50000 ) -1

40000

30000

20000 Organ K Conc. (mg kg (mg K Conc. Organ

10000 A

0 B 25000 )

-1 20000

15000

10000 Organ Ca Conc. (mg kg (mg Conc. Ca Organ

5000 Leaf Petiole Roots & Stolons

0 020406080100

P Supply (ppm)

Figure 5.5 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Potassium; b) Calcium. Values are means and bars represent S.E. (n=5). (Tables A5.22-27).

130 Table 5.2 List of F and P values for lotus (Nelumbo nucifera) organ minor and trace element nutrient concentration as a function of phosphorous supply (Figures A5.1-5, Tables A5.28-57).

Nutrient Organ F value P Mg Leaf 1.5 >0.2 Petiole 0.87 >0.5 Roots & Stolons 2.05 >0.05 S Leaf 1.73 >0.1 Petiole 0.68 >0.6 Roots & Stolons 0.49 >0.8 Fe Leaf 0.27 >0.9 Petiole 1.17 >0.3 Roots & Stolons 2.52 >0.01 Mn Leaf 2.73 >0.01 Petiole 7.88 <0.0000* Roots & Stolons 16.48 <0.0000* Zn Leaf 3.50 >0.01 Petiole 2.99 >0.02 Roots & Stolons 6.04 <0.005* Cu Leaf 0.99 >0.4 Petiole 0.86 >0.5 Roots & Stolons 1.27 >0.3 B Leaf 2.49 >0.05 Petiole 2.19 >0.07 Roots & Stolons 1.22 >0.3 Mo Leaf 12.99 <0.0000* Petiole 14.27 <0.0000* Roots & Stolons 6.00 <0.0004* Na Leaf 0.33 >0.9 Petiole 3.57 >0.01 Roots & Stolons 4.05 <0.001* Al Leaf 0.97 >0.4 Petiole 0.74 >0.6 Roots & Stolons 2.21 >0.07 * Denotes significance at P<0.01

131 5.3.4 Analysis of Major Nutrient Concentration as a Function of Phosphorous Concentration.

Organ P concentration was significantly increased in all three organs, however, there was no difference found between the relationships for petioles and roots and stolons

(Figure 5.6, Tables A5.58-60, 163–166, 179–182). Concentration in leaves increased

-1 -1 from approximately 2.00 g kg of P at P5 to 8.00 g kg of P at P100 (P<0.0000).

Concentration in petioles, roots and stolons increased from approximately 0.80 g kg-1

-1 of P at P5 to 12.00 g kg of P at P100 (P<0.0000).

Nitrogen concentration in leaves (P<0.01) was significantly affected by P concentration (Figure 5.7, Table A5.61). Approximately 3.5 % N was found in leaves when P concentration was 2.00 g kg-1 and increased to 4.1 % N at 10.00 g kg-1

P; leaf concentration was significantly different (P<0.01) from other organs (Tables

A5.159-161 & 175-177). Petiole N concentration and roots and stolons N concentration were able to be described by a single equation rather than by separate equations (P>0.05, Tables A5.178 & 182). The combined N concentration in petioles, roots and stolons did not change (P> 0.4) with increasing P concentration and was steady at approximately 2 to 2.5 % N (Figure 5.5, Table A5.162).

Individually, roots and stolons N concentration was found to increase with increasing

P (P<0.01, Table A5.63), but petioles did not (P>0.2, Table A5.62).

There was no relationship between K concentration in leaves and P concentration

(P>0.4) which was steady at between 20.00 to 30.00 g kg-1 (Figure 5.8a, Table

A5.64). Leaf K concentration was significantly different to other organ K concentrations (Tables A5.167–169 & 183–185), but petioles and roots and stolons were found to have similar K concentrations (Tables A5.170 & 186). Combined

132 petiole, roots and stolons K concentration, approximately 50.00 g kg-1, was not significantly (P>0.2) affected by P concentration (Figure 5.8a, Table A5.170).

Individually, K concentrations in petioles and roots and stolons were significantly increased by increased P concentration (P<0.0000, P<0.01 respectively) (Tables

A5.65-66).

The relationship describing leaf Ca concentration was similar to that for petiole Ca

(P>0.05) but different to combined organs (P<0.0001) and roots and stolons

(P<0.006) (Tables A5.173, 187-189). Similarly, petiole Ca concentration was found to be similar to that for roots and stolons (P>0.06) (Tables A5.190). Combined Ca concentration in leaves and petioles was significantly affected by P (P<0.0002)

(Figure 5.8b, Table A5.172). Increasing from approximately 10.00 to 20.00 g kg-1

Ca concentration at a P concentration of between 2.00 to 4.50 g kg-1, where it peaked, before falling to around 10.00 g kg-1 Ca concentration at a P concentration of

11.00 g kg-1. Combined petiole and roots and stolons Ca concentration was not significantly affected by P concentration (P>0.1) and remained around 10.00 g kg-1

(Figure 5.6b, Table A5.174). Individually, leaf and petiole Ca concentrations were not significantly affected (P>0.4 for both) by changes in P concentration (Table

A5.67 & 68), while roots and stolons Ca concentration was significantly affected

(P<0.001) by increasing P (Table A5.69).

Of the minor and trace elements there was no significant effect on Mg, Fe, Mn, Cu,

B, Mo, Na and Al concentration in leaves due to changes in P concentration (Tables

5.3). There were no significant differences in petiole Mg, S, Fe, Cu, Mo, Na, and Al concentrations due to changes in P concentration (Tables 5.3). In roots and stolons,

133 Fe and Cu were the only elements not to have a significant relationship with P concentration (Table 5.3).

In leaves, the minor nutrient S (P<0.01) and the trace element Zn (P<0.0005) had slight increases with increasing P concentration (Figures A5.6b, 8, & 9b, Tables

A5.73 & 81-82). Zinc concentration was a combination of results with petioles as there was no difference between the Zn concentration in these organs (Tables

A5.193-199). In combined petioles, roots and stolons Mn concentration (P<0.0000) was high at low P concentration, declined with increasing P before levelling at P 7.00 g kg-1, then increasing in concentration at the highest P concentration (Figure A5.7,

Tables A5.80-81, 191). A similar but not as pronounced effect (P<0.01) was found for Mg concentration in roots and stolons (Figure A5.6, Table A5.72). Also of significance in roots and stolons S (P<0.005), B (P<0.005), Na (P<0.002), and Al

(P<0.0002) concentrations increased slightly with increasing P concentration

(Figures A5.6b, 9a, & 10a-b, Tables A5.75, 90, 96 & 99). Concentration of Zn in roots and stolons had a marked increase (P<0.0000) with increasing P (Figure A5.8,

Table A5.84), whereas Mo concentration, decreased (P<0.01) before remaining steady (Figure A5.9b, Table A5.93).

134

16000

14000

) 12000 -1

10000

8000

6000

Organ(s) P Conc. (mg kg (mg Conc. Organ(s) P 4000

2000 Leaf Petioles, Roots & Stolons

0 0 20 40 60 80 100 120 P Supply (ppm)

Figure 5.6 Phosphorous concentration in organs of lotus (Nelumbo nucifera) as a function of phosphorous supply. Regression equations are: y2 = 1.22 * 106 + 672290.79x (r2 = 0.92) and y = 189.09x - 0.70x2 (r2 = 0.90) for leaves (____) and petioles, roots and stolons (…..) respectively. (Tables A5.61-63, 159-162 & 175-178).

135

2 Organ N Conc. (%) Organ N Conc.

1 Leaf Petioles, Roots & Stolons

0 0 2000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg kg-1)

Figure 5.7 Nitrogen concentration in organs of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration. Regression equation is: y = (1.88 + (1.67 * 10-13)x3)0.5 (r2 = 0.22) for leaves (____). Petioles, roots and stolons (…..). (Tables A5.58-60, 163-166 & 179-182).

136

70000

60000 )

-1 50000

40000

30000

20000 Organ K Conc. (mg kg (mg Conc. K Organ

10000 Leaf Petioles, Roots & Stolons A 0 30000 Leaves & Petioles B Petioles, Roots & Stolons 25000 )

-1 20000

15000

Organ Ca (mg kg (mg Ca Organ 10000

5000

0 0 2000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg kg-1)

Figure 5.8 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration: a) Potassium, leaves (____) and petioles, roots and stolons (…..); b) Calcium, regression equation is y=20053.53exp(-exp(-((x- 4778.02)/3912.24))-((x-4778.02)/3912.24)+1) (r2 = 0.20) for leaves and petioles (Tables A5.64-69, 167-174 & 183-190).

137 Table 5.3 List of F and P values for the relationship between organ phosphorous concentration and minor and trace element concentration (Figures A5.6-10, Tables A5.70-99).

Nutrient Organ F value P Mg Leaf 6.83 0.05 Petiole 1.15 0.29 Roots & Stolons 6.00 0.005* S Leaf 8.58 0.01* Petiole 0.98 0.33 Roots & Stolons 10.12 0.005* Fe Leaf 4.41 0.05 Petiole 2.71 0.11 Roots & Stolons 2.08 0.16 Mn Leaf 2.60 0.12 Petiole 25.63 0.00000* Roots & Stolons 33.06 0.00000* Zn Leaf 16.02 0.001* Petiole 7.94 0.01* Roots & Stolons 63.06 0.00000* Cu Leaf 0.75 0.39 Petiole 0.26 0.61 Roots & Stolons 4.96 0.05 B Leaf 0.34 0.56 Petiole 1.70 0.005* Roots & Stolons 9.25 0.005* Mo Leaf 4.89 0.04 Petiole 0.42 0.52 Roots & Stolons 8.00 0.01* Na Leaf 0.14 0.71 Petiole 0.71 0.41 Roots & Stolons 11.57 0.002* Al Leaf 0.16 0.69 Petiole 0.69 0.41 Roots & Stolons 19.10 0.0002* *Denotes significance at P<0.01

138

5.3.5 Analysis of Growth as a Function of Organ Phosphorous Concentration.

Increased P concentration in organs resulted in significant changes to total dry mass

(Figure 5.9a). The P concentration in leaves increased total dry mass sharply

(P<0.0000) from approximately 5 g plant-1 at 2.00 g kg-1 P to a peak of 7.5 g plant-1 at 5.50 g kg-1 P before decreasing just as sharply to below 5 g plant-1 at 10.00 g kg-1.

Concentration of P in petioles (P<0.0000) effected total dry mass in the same trend as for P in leaves, although total dry mass increased to a similar mass over a greater change of P concentration. Total dry mass responded initially to roots and stolons P concentration increases (P<0.0000) similar to the petiole response in mass and trend, the decrease in total dry mass to 7 g plant-1 over a greater range of P at approximately

14.00 g kg-1 differentiating the two relationships (Tables A5.100-102).

Individual organ response to increased P was similar in trend for the total dry mass organ response (Figure 5.9b). Leaves (P<0.0000) and roots and stolons (P<0.0000) achieved the same dry mass though petioles (P<0.0000) generated markedly lower dry mass (Tables A5.103-105). The number of organs produced by increased P concentration in organs also had the same response over the P range. The number of leaves increased from between 7 to 10 at low P concentration, to a peak of 20 leaves at a mid range P concentration around 5.00 to 6.00 g kg-1 P, before decreasing at higher P concentration (P<0.001 all organs) (Figure 5.10a, Tables A5.106-108). The number of nodes increased from approximately 30 to 80 nodes for leaf changes in P concentration (P<0.0000) and 30 to 90 nodes for changes in petiole P concentration

(P<0.0000) and in roots and stolons (P<0.0000). The number of nodes then decreased above P concentrations of approximately 4.00 g kg-1, to around 10, 50 and

40 nodes for leaf, petiole, and roots and stolons P concentrations respectively (Figure

139

5.10b, Table A5.109-111). Stolon numbers increased from approximately 8 to a peak of 18 stolons for all organs before declining to 6 for leaves (P<0.0000) and 10 stolons for petioles (P<0.0000) and roots and stolons (P<0.0000) (Figure 5.11a,

Tables A5.112-114).

The total stolon length (Figure 5.11b) and LA (Figure 5.12) both showed the same trend across P concentration as seen for mass and organ numbers. Total stolon length increased from 750 to 1 000 mm at low P to a peak of approximately 2 000 mm before declining to an estimated response of 500 mm for leaf (P<0.0001), 1 000 mm for petioles (P<0.004), and 1 200 mm for roots and stolons which were not significant (P>0.01) (Tables A5.115-117). Total leaf area increased from around 5 dm2 at low P concentration to a peak of approximately 12 dm2 for all organs at mid P concentration, before declining to estimates of 2, 6, and 5 dm2 for leaf (P<0.0000) , petioles (P<0.0000) and roots and stolons (P<0.0000) respectively (Tables A5.118-

120). There was no change in internode length (P>0.1) due to P concentrations in the organs tested (Tables A5.121-123).

Critical concentrations, determined from the means of growth estimates are approximately 3.93 to 6.08, 3.66 to 7.20, and 3.67 to 7.87 g kg-1 of P in leaf, petioles and roots and stolons respectively (Table 5.4). The lower critical concentrations were found to be similar (P<0.01) though different to the higher critical concentrations. The leaf upper critical concentration was found to be different from petioles and roots and stolons (P<0.01).

140

30 Leaf Petiole Roots & Stolons 25 ) -1

10 Total Dry Mass(g plant

0 12

Organ Dry Mass (g) 4

0 0 2000 4000 6000 8000 10000 12000 14000 16000

-1 Organ P Conc. (mg kg ) Figure 5.9 Dry mass of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration: a) Total dry mass, regression equations are y = 18.68/(1+((x-5370.53)/2655.69)2) (r2 = 0.53), y = 1.0 + 0.00074xlnx -5.84 * 10-7x2 (r2 = 0.55) and y = 19.03exp(-exp(-((x-6183.58)/4361.79))-((x-6183.58)/4361.79)+1) (r2 = 0.53) for leaves (____), petioles (…..) and roots and stolons (----) respectively; b) Individual organ dry mass, regression equations are y=28.52exp(-(x- 5528.62)/1359.21/(1+ exp(-(x-5528.62)/1359.21)2 (r2 = 0.59), y=20.76exp(-(x- 6056.35)/2097.11)/(1+exp(-(x-6056.35)/2097.11)2 (r2 = 0.74) and y=7.04exp(-exp(-((x- 6434.54)/4767.11))-((x-6434.54)/4767.11)+1) (r2 = 0.51) for leaf, petioles and roots and stolons respectively. (Tables A5.100-105).

141

A 25

10 Number of Leaves Number

0 B

40 Number of Nodes Number

20 Leaf Petiole Roots & Stolons

0 0 2000 4000 6000 8000 10000 12000 14000

-1 Organ P Conc. (mg kg ) Figure 5.10 Organ numbers of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration: a) number of leaves, the regression equations are y=20.90exp(- exp(-((x-5036.10)/2735.65)-((x-5036.10)/2735.65)+1) for leaves (r2 = 0.40), y = 0.27 + 0.012x -0.00010x1.5 for petioles (r2 = 0.41), and y=21.89exp(-exp(-((x-5680.38)/4456.73))- ((x-5680.38)/4456.73)+1) for roots and stolons (r2 = 0.39); b) number of nodes, regression equations are y=78.35/(1+((x-4659.18)/2326.89)2) (r2 = 0.72), y-1 = 0.055 -5.10/x0.5 + 150.27/x (r2 = 0.60) and y-1 = 0.00025 + (1.93 * 10-7)xlnx + 1138.75/x1.5 (r2 = 0.83) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A5.106-111).

142

A Leaf Petiole 25 Roots & Stolons

Number of Number Stolons 10

40000

3500 B

3000

2500

2000

1500 Stolon Length (mm) Length Stolon

1000

500

0 0 2000 4000 6000 8000 10000 12000 14000 16000

-1 Organ P Conc. (mg kg ) Figure 5.11 Organ numbers and dimensions of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration: a) Number of Stolons, regression equation is y=3.94*1015x-3.51/(1.51+x-2.51*4.76*1010)2 for leaf (r2 = 0.47), y= 1.95*1013x-2.94/(0.94+ x-1.94*42627213.68)2 petioles (r2 = 0.51), and y=1564874716x-2.82/(0.82+ x-182*17310947.81)2 roots and stolons (r2 = 0.51) ; b) Total Stolon Length, regression equations are y=2004.62exp(-exp(-((x- 4844.19)/2697.10))-((x-48.44.19)/2697.10)+1) (r2 = 0.40), y = 155.81 + (-0.0060)x1.5 + 6.67x/lnx (r2 = 0.35), and y=1.28*1014x-2.60/(0.60+ x-1.60*2839196.27)2 (r2 = 0.19) for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A5.112-117).

143

20 Leaf Petiole Roots & Stolons

15 ) 2

10 Total Leaf Area (dm 5

0 0 2000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg kg-1)

Figure 5.12 Total leaf area of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration, regression equations are y=12.99exp(-0.5((x- 5637.06)/2224.90)2) (r2 = 0.57), y=(1.58+0.00066x-5.22*10-8x2)2 (r2 = 0.49) and y=2.25*1014x-3.17/(1.17+ x-2.17 * 489849375.7)2 (r2 = 0.45), for leaves (____), petioles (…..) and roots and stolons (----) respectively. (Tables A5.118-120).

144

Table 5.4 Calculated phosphorous critical concentrations for lotus (Nelumbo nucifera) organs determined by the relationship between growth parameter and organ phosphorous concentration (Figures 5.7-10). All units are mg kg-1.

Growth Leaf Petiole Roots & Stolons Parameter Deficiency Toxicity Deficiency Toxicity Deficiency Toxicity TDM 3 815.94 5 941.33 4 254.30 8 061.99 4 404.99 8 669.22 LA 4 522.85 6 625.07 4 393.66 8 303.64 4 143.83 8 214.32 LfNo 3 854.86 6 415.66 3 504.32 7 542.12 3 658.97 7 237.95 NoNo 3 803.26 5 374.46 2 517.50 5 029.81 2 706.10 5 950.26 StNo 3 564.14 6 145.71 3 066.16 6 756.71 3 366.08 8 039.47 StLgth 3 538.63 5 682.03 3 334.59 7 817.55 3 290.78 8 265.91 LDM 4 402.39 6 335.99 PDM 4 539.16 6 957.99 RDM 4 111.83 8 700.50

Mean 3 928.87a 6 074.32b 3 658.53a 7 209.97c 3 668.94a 7 868.23c s.e. 146.09 165.82 286.71 420.42 224.95 368.96 Letters denote differences at P<0.01

145

5.3.6 Analysis of Total Dry Mass as a Function of Phosphorous Supply Affected Growth Parameters.

Total leaf area was the growth parameter with the strongest correlation (r2=0.93) for dry matter production when under P treatment conditions (Figure 5.13, Tables 5.5 &

A5.124). Total dry mass increased from approximately 5 to 25 g plant-1 over a corresponding change in LA from approximately 2 to 20 dm2. Total stolon length followed by the number of stolons, leaves then nodes respectively, were also related with dry matter production (Figures A5.11-13, Tables 5.5 & 125-128).

146

30 )

-1 25

10 Total Dry Mass (g plant

0 0 5 10 15 20 25 30

Total Leaf Area (dm2)

Figure 5.13 Total dry mass of lotus (Nelumbo nucifera) as a function of total leaf area. Regression equation is y = 3.002 + 1.66x0.5 lnx (r2 = 0.93, Table A5.124).

Table 5.5 Total dry mass of lotus (Nelumbo nucifera) F statistic and coefficient of determination as a function of growth parameter (Tables A5.124-128).

Parameter F stat. P r2 Total leaf 391.26 0.0000 0.93 area Total stolon 73.20 0.0000 0.69 length Stolon No. 41.53 0.0000 0.54 Leaf no. 41.52 0.0000 0.54 Node no. 28.47 0.0000 0.44

147

5.3.7 Analysis of Growth Parameters Affected by Phosphorous Concentration, as a Function of Phosphorous Concentration Affected Organ Nutrient Concentration.

Increasing concentrations of P caused increases in N concentration from 3 to 4 % in leaf tissue and were related to a decrease in total dry mass (P<0.0000) of approximately 15 g plant-1 (Figure 5.14a, Table A5.129). Total leaf area, numbers of leaves and stolons, and total stolon length similarly had decreases of approximately 8 dm2 (P<0.0000), 10 leaves (P<0.007), 8 stolons (P<0.006) and 1000 mm (P<0.006) respectively for the same increase in N concentration (Figures 5.14b-16, Tables

A5.130-131 & 133-134). There was no effect on node number (P>0.06) by leaf N concentration (Table A5.132).

In roots and stolons, the increasing concentrations of P caused increases in N concentration from 2 to 3% had a negative effect on total dry mass (P<0.0008) only

(Figure 5.17, Table A5.135). Increasing concentrations of P caused increases in N concentration but these were not related to any changes in LA (P>0.01), numbers of leaves (P>0.01), nodes (P>0.02), stolons (P>0.04), and total stolon length (P>0.04)

(Tables A5.136-140).

Changes in P concentration did not result in any significant changes in K concentration in petioles and no growth change was recorded (Tables A5.141-146).

Similarly, K concentration in roots and stolons had no influence on growth (Tables

A5.147-152). Further, increases of Ca concentration in roots and stolons had no response in growth (Tables A5.153-158).

148

30 )

-1 25

10 Total Dry Mass (g plant

25 )

2 20

10 Total Leaf Area (dm

012345 Leaf N Conc. (%)

Figure 5.14 Effect of lotus (Nelumbo nucifera) leaf nitrogen concentration on: a) Total dry mass, regression equation is y=31.25-0.34x3 (r2 = 0.51); b) Total leaf area, regression equation is y=18.79-0.23ex (r2 = 0.40). Tables A5.129-130).

149

Number of Leaves Number 10

0 25

10 Number of Stolons of Stolons Number

0 012345 Leaf N Conc. (%)

Figure 5.15 Effect of lotus (Nelumbo nucifera) leaf nitrogen concentration on: a) Number of leaves, regression equation is y=26.21-0.23ex (r2 = 0.16); b) Number of stolons, regression equation is y=21.26-0.16ex (r2 = 0.17). (Tables A5.131 & 133).

150

5000

4000

3000

2000 Total Stolon Length (mm) Length Stolon Total 1000

0 012345 Leaf N Conc. (%)

Figure 5.16 Effect of lotus (Nelumbo nucifera) leaf nitrogen concentration on total stolon length y=2808.55-22.67x3 (r2 = 0.17). (Table A5.134).

151

30 )

-1 25

10 Total Dry Mass (g plant Mass Total Dry

0 01234 Roots and Stolons N (%)

Figure 5.17 Effect of nitrogen concentration in lotus (Nelumbo nucifera) roots and stolons on total dry mass, regression equation is y=30.44-3.11x2 (r2 = 0.26). (Table A5.135).

152

5.4 Discussion

The objectives of the experiment reported in this chapter were to record symptoms of treatment disorder, establish the adequate supply range of P and the critical concentrations for the optimum growth of lotus, in addition to identifying an appropriate organ for field testing. Symptoms typical of P disorder were not expressed satisfactorily. Symptoms of disorder expressed in previous experiments, the blackening of roots and marginal chlorosis/necrosis, were still present across all treatment classes and could not be attributed to P. However, the symptoms did seem to be greater at lower P treatments (Table 5.1). This Indicates that P may have a secondary effect on mitigating any imbalance.

Treatments varying the supply of P to lotus had an effect on all growth parameters except for internode length (Figures 5.1-3). Similarly, supply of P created a proportional P concentration gradient in all three organs tested (Figure 5.4a).

Increasing P concentration in organs had an inverse parabolic effect on growth from which estimates of critical concentrations at 90% of the maximum growth could be drawn (Figures 5.9-10). The means of these critical concentrations were calculated to obtain a more accurate estimate (Table 5.4) and these were tested for difference.

The lower critical concentration was found to be the same for the three organs tested and could be consolidated further into a single Figure of approximately 3.75 g kg-1 of

P in any organ. Similarly, the higher critical concentration for petioles and roots and stolons could be combined at approximately 7.54 g kg-1 of P, however P in leaves was found to be different at approximately 6.08 g kg-1. Although all organs could be sampled for field testing, from these results the preliminary indicator for P sensitivity in the organs is the leaves. Roots and stolons are not a practical option due to their

153 location in the pond substrate. Petioles are a possibility for testing and depending on the results for other nutrients may be the organ of choice for field sampling.

From these critical concentrations, supply concentrations for adequate growth could be extrapolated. Using the calculated mean values of the critical concentrations found for organs and Figure 5.6, approximate supply rates are in the range of 20 to

57 ppm for the leaf P concentration curve and 22 to 48 ppm for the combined petiole, roots and stolons P concentration curve. While the difference between both range estimates at the lower P supply, around 20 ppm is negligible, the discrepancy of 9 ppm for the higher supply value is considerable. If the individual critical concentrations for organs in Table 5.4 were to be used in conjunction with Figure 5.4 to extrapolate estimates of the appropriate supply range, then supply range concentrations of 20 to 56, 20 to 60, and 20 to 43 ppm are determined for leaves, petioles, and roots and stolons respectively. Roots and stolons have the narrowest supply range.

Comparisons of these critical concentration results concur with some species but not others; a great diversity of response to P supply between species has been reported

(Asher and Loneragan 1967). There is little purpose in comparing within the

Proteales order. Parks et al. (2000) found critical concentrations of 0.49 to 0.79 g kg-

1 and 0.46 to 1.36 g kg-1 in leaves and stems respectively of Banksia ericifolia, obviously far more sensitive to P than most other species. The average concentration of P in organs of waterchestnut have been reported as 3.30, 2.70 and 4.50 g kg-1 for corms, stems and roots respectively (Kleinhenz et al. 2001). These values differ greatly with lotus, the only similarity with lotus is the order of magnitude for organs where root organs contain a greater amount of P than leaf (stem) organs. O’Sullivan

154 et al. (1997) report an adequate range of 2.60 to 4.50 g kg-1 of P for 28 day old 7th to

9th open leaf blades of sweetpotato. The upper end of these values overlaps with the minimum of the lotus value found in this experiment. In potatoes, P concentration will vary widely according to age and plant part but at a similar physiological and chronological age 35 days after transplanting, whole shoots of potato were found to contain 7.90 to 8.80 g kg-1 of P for adequate growth (Huett et al. 1997). However, these results were gravel culture derivative and Huett et al. (1997) also list adequate

P as 2.00 to 4.00 g kg-1 after 42 days in field grown potatoes. Roberts and Dow

(1982) report petiole P in potato to have critical concentrations between 3.80 and

4.50 g kg-1 which decreased to 1.40 to 1.70 g kg-1 as the plants aged. Therefore, it can be demonstrated that P concentration in organs is widely variable and the values found from this experiment have preliminary merit.

The adequate ranges established for organs in this experiment were lower than the P range estimated in Experiment 10. There was considerable overlapping of the values reported for leaves, but for petioles and roots and stolons the overlap of values was very narrow. The order of magnitude of P within organs was the same as found in

Experiment 10. These results demonstrate further that N has some sort of interactive role in facilitating the uptake of P in lotus. This question should be addressed in the future with a two-factorial trial to establish the correct balance between these nutrients during the vegetative growth phase.

Supply of P had no effect on the uptake of N however (Figure 5.4b). Concentration of P in leaves however had a significant affect on leaf N (Figure 5.7), as P increased so did N. The leaf N at the corresponding P critical concentrations was found to be approximately 3.6 to 3.7 % N, values which concur with those found in Experiment

155

10 for the optimum leaf area. In combined petioles, roots and stolons, there was no change in N at approximately 2.35 % due to P concentration (Figure 5.7). This value, while within the acceptable limits calculated for roots and stolons in the discussion of Chapter 3 was lower than the 2.4 to 4.0 % N range estimated in petioles. These disparate results solidify the requirement for further investigation into the N and P balance.

Phosphorous supply and concentration in organs had no effect on K uptake. A dichotomy existing between combined petiole, roots and stolons concentrations of K and for organs individually was observed. These differences were considered inconsequential, a function of a minor difference between two mean values and wide spread of data, supported by low co-efficients and therefore, were absorbed by the combined relationship. This example validates the approach used for combined relationships. Concentration of K in organs was similar to that found in Experiment

10. Concentration of Ca in leaves was affected by P supply and P concentration

(Figures 5.5b & 8b). An inverse parabolic relationship was found between rising P concentration and Ca in combined leaves and petiole Ca concentration and P supply.

A similar relationship was found between leaf concentration of Ca and P supply, but not for petioles. It would be expected that some relationship occurs between P and

Ca and that the relationship would be expressed most definitively in the leaves. It is well established that after xylem transport Ca is relatively immobile in plants

(Mengel and Kirkby 2001). Therefore, any accumulation of Ca, which has a strong affinity for P, would be in the leaves of lotus.

Minor nutrients of interest were Mn and Zn. A parabolic relationship for Mn was found with increasing P supply and concentration in petioles and roots and stolons

156

(Figures A5.2b & 7, Tables A5.80-81 & 191-192). Mn toxicity, prevalent in anaerobic conditions (Mengel and Kirkby 2001) could be a contributing factor to the decreased growth at extremes of P concentration and supply. Gonzalez and Lynch

(1997) found that toxic levels of Mn in bean leaves suppressed CO2 assimilation.

Increasing P supply and concentration increased the uptake of Zn into roots and stolons (Figures A5.3a & 8, Tables A5.82-84 & 193-200). Mengel and Kirkby

(2001) list concentrations of Zn in the range of 150 to 200 mg Zn kg-1 dry matter to be in the zone of toxicity for most plants. This also may be a contributing factor to the decrease in growth at high P supply and concentration.

It could be speculated that the effect on growth of P is relatively indirect. At low supplies, the plant cannot function due to the lack of energy required via the P+ driving many of the physiological functions. At high levels of P, the actual P concentration is not the agent for suppression of plant growth but rather facilitates the uptake of other metal ions which have a negative effect on growth. It is clear from these results that a P interaction with 2+ cations is functioning. This argument fuels the requirement for greater investigation into P analyses in conjunction with other cations and anions. However, the results of trials examining K and Ca require primary attention and are the subject of Chapters 5 and 6 respectively.

157

Chapter 6 Analysing the Interaction between Potassium and Lotus

6.1 Introduction

Potassium is the most important cation to plants in regard to concentration, biochemistry and physiological functions (Mengel and Kirkby 2001). Potassium is utilised for enzyme activation and protein synthesis during photosynthesis and respiration (Peoples and Koch 1979). Highly mobile within all plant tissues, K is the principal cation for compensation of charge for immobile and mobile anions in the cytosol. It is a regulator of osmotic potential, essential for pH control in sieve tubes allowing sucrose loading, providing a charge gradient across membranes and the control of stomatal aperture (Outlaw 1983, Marschner 1995).

The availability of K is generally not restricted by pH in soils and solution culture but rather total K in the reservoir, cation exchange capacity, and K buffering capacity in soils (Gourley 1999). Potassium uptake by plants is by one of two transporters driven by the proton pump embedded in the root cell plasma membrane, whose functional dominance is determined by supply (Mengel and Kirkby 2001). Diurnal fluctuations in uptake have also been reported (MacDuff and Dhanoa 1996).

Critical concentrations and symptoms of deficiency for K have been widely reported for a number of species (Reuter and Robinson 1997). Deficiencies of K in plants are generally reflected by marginal chlorosis followed by necrosis in older leaf tissues, shortened internodal lengths and weak stems (Taiz and Zeiger 1991). Excess supply of K has been reported to reduce yield and/or quality for some crops (Gourley 1999).

158

The role of K and the most appropriate sampling organ for K concentration in relation to lotus has not been adequately documented. As with N and P, there has been no report beyond those advised by Nguyen (2001). Comparative analysis may be derived from other crops with similar morphological features to lotus as was performed for N and P. In Experiments 10 and 11, the supply level of K was constant at 350 ppm. In Experiment 10, K was found in varying concentrations in all organs in response to changes in N supply. In Experiment 11 only petioles and roots and stolons expressed a range of K concentrations in response to changes in P supply. It was clear that an interaction between N and K was functioning, but not as apparent for P and K. The concentration of K in roots and stolons from Experiment

10 had significant effects on growth parameters such as dry mass, organ numbers and mean internodal length. In petioles, K concentration influenced total dry mass, node and stolon numbers, and mean internodal length. Potassium levels for leaf tissue had no apparent relationship with growth.

The concentrations for K in each organ found in the previous experiments were approximately 30.00 g kg-1 of K for leaves, 50.00 to 60.00 g kg-1 of K for petioles, and 30.00 to 45.00 g kg-1 of K for roots and stolons in Experiment 10, and between

20.00 to 30.00 g kg-1 of K for leaves and 40.00 to 60.00 g kg-1 for petioles, roots and stolons respectively in Experiment 11. It could be predicted that the results from the following experiment will not be in a similar concentration range and plant growth response. This is due to the supply constant treatment (K350) growth responses in

Experiment 10 and 11, being lower than for the corresponding growth parameter results found at lower K supplies. Further, it is expected that the concentration for K will be highest in petioles, lower in roots and stolons, and lowest in leaves. The results of Experiment 10 suggest that K concentration in petioles will be the most

159 important factor on subsequent growth results, as petiole K was found to be limiting to total dry mass (Figure 4.15a).

This chapter aimed to determine the efficacy of utilising the proposed system by challenging lotus with a range of potassium treatments. Establishment of organ critical nutrient concentrations, adequate supply rates of K, and documentation of nutritional disorder symptoms that may be expressed for lotus, were the objectives.

The following experiment was conducted.

6.1.1 Experiment 12 Effect of Potassium on Growth and Organ Nutrient Concentration of Lotus (Nelumbo nucifera ).

During September of 2002, a trial involving eight potassium treatments with five replications per treatment was undertaken over a 50 day period of growth. Analyses of growth parameters, effect of K supply and effect of major nutrient concentrations with significant differences were performed.

6.2 Materials and Methods

The conditions for plant growth, harvest, and statistical procedures were as per section 4.2 except for treatment imposition.

Potassium treatments comprised 50, 225, 300, 325, 350, 375, 400, 500 ppm of K and were identified as K50 to K500 respectively (Table A1.8).

160

6.3 Results

6.3.1 Observations of Potassium Supply on Visual Growth Expression.

At day 20, symptoms of marginal chlorosis/necrosis were present in approximately

50% of all leaves across all treatment classes except for the K225. These values were not significantly different (P>0.01) from each other (Tables 6.1 & A6.1). In roots, blackening of tissues appeared to have a gradient both from root age and from treatment concentration. The least blackening occurred for K50 and the greatest for

K500. Treatments in between these extremes however, were not significantly different from either extreme treatment (P<0.0001) (Table A6.4).

At day 40, symptoms remained the same in appearance but had become even across all treatments for affected leaf number (P>0.1) and roots (P>0.05) (Table 6.1 & A6.2

& 5). Total affected leaf area was least at K50 and greatest at K375 (P<0.002), at other treatments total affected leaf area was variable and showed no trend (Table A6.3).

Table 6.1 Estimated observations for lotus (Nelumbo nucifera) on: a) the percentage of leaves per plant showing signs of disorder at day 20; b) the percentage of leaves per plant showing signs of disorder at day 40; c) the percentage of total leaf area per plant affected by disorder at day 40; d) the below-ground plant parts affected by disorder at day 20; e) below-ground plant parts affected by disorder at day 40. Values followed by different letters are significantly different at P<0.01 within each column (Tables A6.1-5).

Treatment A B C (ppm) D E 50 48.75a 35.00a 0.64a 3.75a 37.50a 225 26.25a 48.75a 1.92ab 13.75ab 52.50a 300 50.00a 35.00a 0.80ab 45.00b 40.00a 325 52.50a 41.25a 2.12ab 32.50ab 47.50a 350 50.00a 38.75a 1.70ab 42.50b 37.50a 375 55.00a 46.25a 2.66b 27.50ab 52.50a 400 47.50a 43.75a 1.36ab 40.00ab 57.50a 500 57.50a 58.75a 2.51b 47.50b 52.50a

161

6.3.2 Potassium Supply Effect on Growth Parameters.

Dry mass, organ numbers, organ dimensions and LA were significantly affected by potassium supply. Total dry mass and dry mass of all leaves, petioles, and roots and stolons generally increased slightly, then decreased (P<0.0004) with increasing K supply (Figures 6.1a-b, Tables A6.6-9). Total dry mass increased from

-1 -1 approximately 20 g plant at K50 to peak of 25 g plant at K225, decreased to

-1 -1 approximately 12 g plant at K375, before increasing slightly to 15 g plant at K500.

All organs displayed the same pattern as total dry mass except after K400 where only roots and stolons increased. Leaves increased (P<0.004) from approximately 6.5 g at

K50 to a peak of 8 g at K225 before decreasing to 4 g at between K300 to K500. Petiole dry mass remained steady at a maximum of approximately 4 to 5 g at K50 to K225, before decreasing (P<0.0007) to 2.5 g at K375 to K500. Roots and stolons increased

(P<0.002) from approximately 7 g at K50 to a maximum of 8 g at K225 then decreased to 3 g at K375 before increasing to 4.5 g at K500.

The number of leaves was not significantly affected by K supply (P>0.2), and ranged approximately between 30 leaves at K50 to 22 leaves at K500 (Figure 6.2a, Table

A6.10). The number of nodes did not change as a function of K supply (P>0.1) and ranged between 60 to80 nodes from K50 to K500 (Figure 6.2b, Table A6.11). The number of stolons similarly did not change due to K supply (P>0.4), and numbered approximately 15 to 20 stolons from K50 to K500 (Figure 6.2c, Table A6.12).

2 Total leaf area plateaued (P<0.001) from approximately 16 dm at K50 to K225 before

2 decreasing to 9 dm at between K375 to K500 (Figure 6.3a, Table A6.13). Total stolon length did not significantly change due to supply K (P>0.06) though it fluctuated

162 between 1 500 and 2 500 mm (Figure 6.3b, Table A6.14). Internode length similarly did not change significantly (P>0.7) and was between 22 to 30 mm in length (Figure

6.3c, Table A6.15).

163

25 A

20 ) -1

10 Total Dry Mass (g plant

0 Leaf B Petiole Roots & Stolons 8

4 Organ Dry Mass (g) Mass Dry Organ

0 0 100 200 300 400 500 K Supply (ppm)

Figure 6.1 Dry mass of lotus (Nelumbo nucifera): a) Total dry mass; b) Organ dry mass for leaf, petiole, and roots and stolons as affected by potassium supply. Values are means and bars represent S.E. (n=5). (Tables A6.6-9).

164

40 A

15 Number of Leaves of Number

0 B 100

Number of Nodes Number 40

25 C

10 Number of StolonsNumber

0 0 100 200 300 400 500 K Supply (ppm) Figure 6.2 Effect of potassium supply on lotus (Nelumbo nucifera) organ numbers: a) Leaf; b) Node; c) Stolon no. Values are means and bars represent S.E. (n=5). (Tables A6.10-12).

165

14 ) 2 12

6 Total Leaf Area (cm Total Leaf Area (cm

4 A 2

30000 B 2500

2000

1500

1000 Total Stolon Length (mm)

500

30 C

10 Internode Length (mm)

0 0 100 200 300 400 500 K Supply (ppm) Figure 6.3 Effect of potassium supply on lotus (Nelumbo nucifera) organ dimensions: a) Total Leaf Area; b) Total Stolon length; c) Internode length. Values are means and bars represent S.E. (n=5). (Tables A6.13-15).

166

6.3.3 Effect of Potassium Supply on Organ Nutrient Concentration.

Supply of K had a highly significant effect on K concentration in leaves (P<0.0000), petioles (P<0.0000), and roots and stolons (P<0.0000) (Figure 6.4a, Tables A6.16–

-1 18). In leaves, K concentration was approximately 20.00 g kg at K50 and increased

-1 - steadily to 40.00 g kg between K375 to K500. Petioles had approximately 30.00 g kg

1 -1 of K at K50 and increased to a plateau of 60.00 g kg K at K375 to K500. Roots and

-1 stolons had approximately 20.00 g kg at K50 and increased to a peak plateau of 40

-1 .00 g kg at K300 to K500

Supply of K had no significant effect on N concentration in leaves (P>0.19), petioles

(P>0.25), roots and stolons (P>0.35) (Figure 6.4b, Tables A6.19–21). Leaves contained approximately 3.5 to 4 % N, petioles had between 3 to 3.5 % N, as did roots and stolons contain between 3 to 3.5 % N.

Supply of K had no significant effect on P concentration in leaves (P>0.36), petioles

(P>0.84), and roots and stolons (P>0.18) (Figure 6.5a, Tables A6.22 – 24). In leaves, approximately 6.00 g kg-1 of P was found, in petioles approximately 7.00 g kg-1 and between 9.00 to 12.00 g kg-1 of K was found in roots and stolons.

There was a significant response in Ca concentration in leaves (P<0.001) and roots and stolons (P<0.002) due to K supply but not petioles (Figure 6.5b, Tables A6.25-

-1 27). In leaves Ca increased from approximately 20.00 g kg at K50 to a peak plateau

-1 -1 of 25.00 g kg of Ca at K225 to K400 before decreasing to 20.00 g kg at K500. In petioles approximately 12.00 to 15.00 g kg-1 of Ca was found. Roots and stolons

167

-1 contained approximately 9.00 g kg of Ca at K50 and gradually increased to a peak

-1 plateau of around 14.00 g kg at K325 to K500.

There were no significant changes in nutrient concentration in leaves as a function of

K supply for S, Mo and Na (Table 6.2). In petioles, nutrient concentration was constant for Mg, S, Fe, Mn, Cu, B and Al (Table 6.2). Root and stolons Mg, S, Fe,

Zn, Ns and Al concentrations were unaffected by K supply. Leaf Mg, Zn, and Cu generally increased while Fe, Mn, and B decreased with increasing K supply. In petioles Zn concentration generally decreased whereas Mo and Na concentration increased with rising K supply. Increasing supply of K in roots resulted in decreased

Mn and Mo concentration and increased Cu and B concentration.

168

A 60000

) 50000 -1

40000

30000

20000 Organ K Conc. (mg kg (mg K Conc. Organ

10000

2 Organ N Conc. (%) N Conc. Organ

1 Leaf Petiole B Roots & Stolons 0 0 100 200 300 400 500

-1 K Supply (mg kg )

Figure 6.4 Effect of potassium supply on nutrient organ concentration in lotus (Nelumbo nucifera) for: a) Potassium; b) Nitrogen. Values are means and bars represent S.E. (n=5). (Tables A6.16-21).

169

12000 A

10000 ) -1

8000

6000

4000 Organ P Conc. (mg kg (mg P Conc. Organ

2000

0 B 30000

) 25000 -1

20000

15000

10000 Organ Ca Conc. kg (mg Leaf 5000 Petiole Roots & Stolons

0 0 100 200 300 400 500

K Supply (ppm)

Figure 6.5 Effect of potassium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Phosphorous; b) Calcium. Values are means and bars represent S.E. (n=5). (Tables A6.22-27).

170

Table 6.2 List of F and P values for lotus (Nelumbo nucifera) organ minor and trace element nutrient concentration as a function of potassium supply (Figures A6.1- 5, Tables A6.28-57).

Nutrient Organ F value P Mg Leaf 11.53 0.0000* Petiole 1.11 0.38 Roots & Stolons 1.95 0.10 S Leaf 3.21 0.014 Petiole 2.15 0.07 Roots & Stolons 1.68 0.15 Fe Leaf 6.34 0.0000* Petiole 0.82 0.5 Roots & Stolons 1.59 0.1 Mn Leaf 4.19 0.004* Petiole 2.28 0.06 Roots & Stolons 7.61 0.0000* Zn Leaf 13.29 0.0000* Petiole 8.02 0.0000* Roots & Stolons 2.51 0.04 Cu Leaf 11.13 0.0000* Petiole 1.67 0.1 Roots & Stolons 4.05 0.005* B Leaf 5.71 0.0005* Petiole 3.12 0.01 Roots & Stolons 4.67 0.002* Mo Leaf 3.20 0.01 Petiole 5.73 0.0005* Roots & Stolons 9.67 0.0000* Na Leaf 2.37 0.05 Petiole 19.05 0.0000* Roots & Stolons 1.51 0.2 Al Leaf 7.36 0.0000* Petiole 1.53 0.2 Roots & Stolons 3.17 0.01 *Denotes significance at P<0.01

171

6.3.4 Analysis of Major Nutrient Concentration as a Function of Potassium Concentration

Concentrations of potassium were significantly affected by K supply for all organs

(Figure 6.6, Tables A6.58-60). Concentration was highest in petioles (P < 0.0000)

-1 which increased steadily from approximately 30.00 g kg of K at K50 to a maximum

-1 of 60.00 g kg of K at K500 and did not peak. Roots and stolons (P < 0.0000) K

-1 -1 concentration increased from approximately 20.00 g kg of K at K50 to 40.00 g kg of K where a peak and plateau was achieved from K225 to K500. Leaf K concentration increased (P < 0.0000) steadily from approximately 20.00 g kg-1 of K to 40.00 g kg-1 of K and did not peak. Fitted equations were found to be different from each other

(Tables A6.135-138 & 151-154).

Organ nitrogen concentration was significantly decreased by increasing K concentration in all three organs, however, there was no difference found between leaves and petioles and between leaves and roots and stolons which were best represented by combined fitted curves (Figure 6.7a, Tables A6.61-63, 139-142 &

155-158). Concentration in leaves and petioles (P<0.0000) decreased steadily from approximately 4.00% of N at 20.00 g kg-1 K to 2.75% of N at 70.00 g kg-1 K.

Concentration of N in leaves, roots and stolons (P< 0.0000) combined also decreased steadily though at lower concentrations from approximately 3.5% at 20.00 g kg-1 K to 2.5% at 40.00 g kg-1 K.

Phosphorous concentration in all organs rose steadily with increased K concentration; leaves and petioles were best represented by a single combined curve

(Figure 6.7b, Tables A6.64-66, 143-146, & 159-162). Concentration of P was

172 highest in roots and stolons (P<0.01) and ranged without peaking from approximately 9.00 to 12.00 g kg-1 of P at 20.00 g kg-1 to 50.00 g kg-1 of K. In leaves and petioles, P concentration increased (P<0.0000) steadily from approximately 5.00 g kg-1 of P at 20.00 g kg-1 K to 8.00 g kg-1 of P at 70.00 g kg-1 K without peaking.

Calcium concentration in roots and stolons (P<0.0000) was significantly affected by an increase in K concentration but not in leaves (P>0.2) or petioles (P>0.06) (Figure

6.8, Tables A6.67-69). Increasing K concentration produced a gradual increase in the roots and stolons Ca concentration from approximately 9.00 to 13.00 g kg-1 Ca.

Leaves contained approximately 22.00 to 25.00 g kg-1 Ca, while petioles contained between 12.00 to 15.00 g kg-1 of Ca on average. Each organ was best represented by individual fitted curves (Tables A6.147-150 & 163-166).

Of the minor and trace elements, only Mg (P<0.001) concentration in roots and stolons and Mo (P<0.001) in leaves were negatively affected by increased N concentration (Table 6.3, Figure A6.8a & 9a, Tables A6.72 & 91). Conversely, Fe concentration in leaves (P<0.001) and petioles (P<0.01) only, and Al concentration in all organs (P<0.001 for leaves and 0.01 for petioles and roots and stolons), resulted in an increase with N concentration (Figures A6.8b & 9b, Tables A6.76-77 & 97-99).

All other minor and trace elements had no significant change with increasing N concentration (Tables A6.70-71, 73-75, 78-90 & 92-96).

173

80000

60000 ) -1

40000

Organ K Conc. (mg kg (mg K Conc. Organ 20000 Leaf Petiole Roots & Stolons

0 0 100 200 300 400 500 600 K Supply (ppm)

Figure 6.6 Potassium concentration in organs of lotus (Nelumbo nucifera) as a function of potassium supply. Regression equations are: y = 12 838.75 + 194.70x0.5 (r2 = 0.65), y = 6 183.04 + 1 568.01(lnx)2 (r2=0.80) and y = 43 350.17(1-exp(- 0.012x)) (r2 = 0.80) for leaves (____), petioles (…..), roots and stolons (- - - ) respectively. (Tables A6.58-60).

174

2 Organ N Conc. (%) Organ N Conc.

A Leaves & Petioles Leaves, Roots & Stolons 0

12000 B

10000 ) -1

8000

6000

4000 Organ P Conc. (mg kg P (mg Organ Conc.

2000 Leaves & Petioles Roots & Stolons 0 0 20000 40000 60000 80000

Organ K Conc. (mg kg-1)

Figure 6.7 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentration a) Nitrogen, regression equations are y = 4.08 – 7.3*10-8x1.5 (r2 = 0.45) and y = 3.79 – 7.3*10-15x3 (r2 = 0.24) for leaves and petioles (_ . _ . _) and leaves, roots and stolons (_ .. _ .. _) respectively; b) Phosphorous, regression equations are y = 5179.96 + 6.19*10-8x2lnx (r2 = 0.62) and y = 8998.56 + 1.78*10-11x3 (r2 = 0.25) for leaves and petioles (_ . _ . _), roots and stolons (- - -) respectively. (Tables A6.140, 156, 144 & 160).

175

35000

Leaf 30000 Petiole Roots & Stolons )

-1 25000

20000

15000

10000 Organ Ca Conc. (mg kg (mg Conc. Ca Organ

5000

0 0 20000 40000 60000 80000

-1 Organ K Conc (mg kg )

Figure 6.8 Calcium concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentration. Regression equation is: y = 5.74 + 0.35lnx (r2 = 0.55) for roots and stolons (- - -). Leaves (____) and petioles (…..). (Tables A6.67-69).

176

Table 6.3 List of F and P values for the relationship between organ potassium concentration and minor and trace element concentration (Figures A6.6-10, Tables A6.70-99).

Nutrient Organ F value P Mg Leaf 25.33 0.0000* Petiole 0.75 0.3 Roots & Stolons 5.29 0.01 S Leaf 4.86 0.03 Petiole 1.66 0.2 Roots & Stolons 13.69 0.0009* Fe Leaf 16.82 0.0003* Petiole 5.27 0.02 Roots & Stolons 4.08 0.05 Mn Leaf 21.66 0.0000* Petiole 4.57 0.04 Roots & Stolons 4.16 0.04 Zn Leaf 7.61 0.01* Petiole 2.64 0.1 Roots & Stolons 0.24 0.6 Cu Leaf 27.50 0.0000* Petiole 5.80 0.02 Roots & Stolons 0.92 0.3 B Leaf 0.86 0.3 Petiole 2.72 0.1 Roots & Stolons 11.93 0.002* Mo Leaf 6.65 0.01 Petiole 6.27 0.01 Roots & Stolons 14.72 0.0006* Na Leaf 13.36 0.001* Petiole 92.01 0.0000* Roots & Stolons 10.58 0.003* Al Leaf 45.48 0.0000* Petiole 43.81 0.0000* Roots & Stolons 19.01 0.0002* *Denotes significance at P<0.01

177

6.3.5 Analysis of Growth as a Function of Organ Potassium Concentration.

Total dry mass generally decreased with increasing K concentration (Figure 6.9a,

Tables A6.100-102). Leaves (P<0.0000) demonstrated the sharpest decline dropping from approximately 20 to 5 g with increasing K concentrations of 20.00 to 40.00 g kg-1. Petioles (P<0.0000) had a similar magnitude of decline though over a greater range of K increase from 20.00 to 60.00 g kg-1 of K. Roots and stolons (P>0.02) also had a negative trend with increasing K concentration but was not significant.

Individual organ dry mass demonstrated similar trends to total dry mass response

(Figure 6.9b, Tables A6.103-105). Leaf dry mass (P<0.0000), dropped from approximately 7 to 3 g, over a K increase from 20.00 to 40.00 g kg-1 of K. Petiole dry mass (P<0.0000) declined from approximately 6 to 2 g over a K range increase from 20.00 to 60.00 g kg-1. Roots and stolons dry mass declined but was not significant (P>0.01).

The LA response to increasing K concentration also demonstrated a negative relationship (Figure 6.10, Tables A6.106-108). Leaf concentration (P<0.0000) decreases from 20.00 to 40.00 g kg-1 of K resulted in a sharp decline from approximately 16 to 6 dm2 in LA. Petiole K concentration solicited a drop from approximately 16 to 6 dm2 over a K increase range of 20.00 to 60.00 g kg-1. Roots and stolons K concentration (P>0.01) did not affect LA.

There was no response in organ numbers or stolon dimensions to increasing K concentration (Tables A6.109-123). Leaf (P>0.1, P>0.06, P>0.5), node (P>0.1,

P>0.1, P>0.7) and stolon numbers (P>0.3, P>0.3, P>0.8) were not affected by K

178 concentration in leaf, petiole and roots and stolon respectively. Total stolon length

(P>0.01, P>0.1, P>0.7) and internode length (P>0.7, P>0.5, P>0.5) showed no response to increased K concentration in leaves, petioles and roots and stolons respectively.

179

A Leaf 25 Petiole Roots & Stolons ) -1 20

10 Total Dry Mass (g plant

0 B 10

Organ Dry Mass (g) Dry Mass Organ 4

0 20000 40000 60000 80000

Organ K Conc. (mg kg-1)

Figure 6.9 Dry mass of lotus (Nelumbo nucifera) as a function of organ potassium concentration: a) Total dry mass, regression equations are y = 22.05 – 7.4*10-9 x2 (r2 = 0.61) for leaves (____) and y = 22.51 – 1.01*10-11x2.5 (r2 = 0.57) for petioles (…..); b) Individual organ dry mass, regression equations are y= 7.68 – 2.09*10-10x2lnx (r2 = 0.42) for leaves and y=5.78 – 2.78*10-12x2.5 (r2 = 0.58) for petioles. Roots and stolons (----). (Tables A6.100-105).

180

15 ) 2

10 Total Leaf Area (dm 5

Leaf Petiole

0 0 20000 40000 60000 80000

Organ K Conc. (mg kg-1)

Figure 6.10 Total leaf area of lotus (Nelumbo nucifera) as a function of organ potassium concentration, regression equations are y = 19.00 – 5.89x2 (r2 = 0.45) and y = 18.62 – 1.84*10-9x2 (r2 = 0.32), for leaves (____) and petioles (…..) respectively. (Tables A6.106-107).

181

6.3.6 Analysis of Total Dry Mass as a Function of Potassium Supply Affected Growth Parameters.

Total dry mass increased (P<0.0000) from approximately 6 to 20 g over an increase of LA from 6 to 18 dm2 (Figure 6.11, Table A6.124). The increase in total dry mass was highly related to increasing leaf area (r2=0.83).

25 ) -1 20

10 Toatl Dry Mass (g plant

0 0 5 10 15 20

Total Leaf Area (dm2)

Figure 6.11 Total dry mass of lotus (Nelumbo nucifera) as a function of total leaf area. Regression equation is y = 7.13 + 0.011x2.5 lnx (r2 = 0.83). (Table A6.124).

182

6.3.7 Analysis of Growth Parameters Affected by Potassium Concentration, as a Function of Potassium Concentration Affected Organ Nutrient Concentration.

Concentration of N in roots and stolons had no significant growth response in relation to total dry mass (P>0.8) and LA (P>0.7) (Tables A6.125-126).

Concentration of P in petioles (P>0.1) did not affect LA (Table A6.127). Similarly, roots and stolons P concentration did not have any effect on total dry mass (P>0.2) or

LA (P>0.3) (Tables A6.128-129). Further, concentrations of Ca in leaves did not affect total dry mass (P>0.9) and LA (P>0.7) (Tables A6.130-131).

Increasing petiole P concentration (P<0.003) did have a negative effect on total dry mass (Figure 6.12, Table A6.132). Total dry mass decreased from approximately 18 to 10 g plant-1 as P increased from 6.00 to 9.00 g kg-1. Increasing concentrations of

Ca in roots and stolons caused a decline in total dry mass and in LA (Figure 6.13,

Tables A6.133-134). Total dry mass dropped from 20 to 5 g plant-1 over a Ca increase from 8.00 to 18.00 g kg-1 of Ca, while LA decreased from approximately 15 to 6 dm2 over the same Ca increase.

183

25 ) -1 20

10 Total Dry Mass (g plant

0 0 2000 4000 6000 8000 10000

Petiole P Conc. (mg kg-1)

Figure 6.12 Effect of lotus (Nelumbo nucifera) petiole phosphorous concentration on dry mass, regression equation is y=26.93 – 1.86*10-5x1.5 (r2 = 0.21). (Table A6.132).

184

30 A

25 ) -1 20

10 Total DryTotal Mass (g plant

0 B

15 ) 2

10 Total Leaf Area (dm Total 5

0 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

-1 Roots & Stolons Ca Conc. (mg kg )

Figure 6.13 Effect of lotus (Nelumbo nucifera) root and stolon calcium concentration on a) total dry mass, regression equation is y= 21.82 – 4.97*10-8x2 (r2 = 0.52); b) Total leaf area, regression equation is y=17.47 – 2.46*10-10x2.5 (r2 = 0.38). (Tables A6.133-134).

185

6.4 Discussion

The central intentions of the experiment reported in this chapter were to investigate the effects K supply treatments have on signs of nutritional disorder, the growth of lotus, the critical K concentrations for 90% of maximum growth, and identification of the most appropriate organ for field testing for K imbalance. These results refute any speculation of the marginal necrosis and root blackening being attributed to K deficiency. The disorder was equally present in approximately 50% of leaves for all treatment classes and similarly for roots at the day 40 observation. Further, the results found for growth indicate that treatments did not capture the relevant range of supply concentrations to examine deficiency or establish critical concentrations for

K. These results suggest that the supply treatments were mostly too high and those within the correct range, were not appropriately sensitive.

Supply of K resulted in a brief increase in response for most growth parameters from

K50 to K225, before decreasing to K375. After K375 most growth remained stable to

K500 though for total dry mass and petiole dry mass a slight increase was recorded.

The results suggest that more treatments were required between K0 to K225, specifically to clarify the zone of deficiency with greater precision. Increasing the number of treatment supply rates between K0 to K225 would result in more data that could be represented by a curve that may be characteristic of a nutrient concentration and growth response relationship. Supply rates of K225 and K375 would also be appropriate to define the critical concentration for toxicity.

Potassium supply increased organ K concentration steadily at K50 to K300 where a plateau was achieved for roots and stolons only (Figure 6.6). In leaves and petioles,

186

K concentration was not exhausted with supply. The speculated order of magnitude of K in organs, was confirmed, with petioles consistently containing the highest amount of K, then roots and stolons followed by leaves. The expected contrast in K concentration range from previous experiments was only apparent briefly at low K.

The higher K levels for all organs tested were similar to those found in Experiments

10 and 11.

The K concentration plateau for roots and stolons, and the continual rise in leaves and petioles, coincided with a negative response in growth. Total dry mass, individual dry mass and LA all decreased with increasing K concentration but no other growth parameter was affected (Figures 6.9 & 10). The response of growth was most acute for leaf K concentration. The lower K concentrations corresponded to the highest growth. The highest growth of approximately 20 g plant-1 total dry mass was similar to that achieved in the previous two experiments where the K supply was in the higher zone. However, the highest amount of total dry mass in

Experiment 10 was achieved when K concentration was suppressed at high N concentrations. Explanations for these results might be drawn from comparisons with other species.

Data reported for sweetpotato leaves at mid-growth with an adequate concentration of 29.00 to 50.00 g K kg-1 dry weight (Huett et al. 1997) suggest the result obtained for lotus in this Experiment to be low. However, when the dry mass of lotus is negatively affected by the increasing K concentration, the adequate amount of K for lotus could not possibly be in a similar range. The presence of Na has been reported to lower the critical concentration level of K for sweet potato (O’Sullivan et al.

1997), though at 26.00 g K kg-1 dry matter, this is still in the range of growth

187 suppression for lotus. Other species also contained more K than lotus, leaves of taro

50.00 to 60.00 g K kg-1 (O’Sullivan et al. 1996), and petioles of potato 80.00 to

130.00 g K kg-1 (Huett et al. 1997). Uptake of K in waterchestnuts was much lower and reasonably comparable to lotus with a reported 9.70 g K kg-1 dry mass found in stems (Kleinhenz et al. 2000). Waterchestnut, like lotus is found in anaerobic conditions within ponds, therefore, the uptake of K may have a specific consequence, such as lower requirement of K, when growing in aquatic environments. This question requires greater definition through future experimentation.

Design of future experiments looking at K influence on lotus should focus on lower supply inputs in order to capture the lower critical value and to identify where the supply of K begins to impede growth. Response to K in a variety of plants was shown to have a greater sensitivity than the wide discrepancies previously reported

(Asher and Ozanne 1967). Disorder expression attributed to a specific K concentration also remains to be deduced. It would be appropriate to conduct the necessary trials in conjunction with a second factor such as N or Ca.

Supply of K had no influence on the uptake of N or P but had a response with Ca concentrations in leaves and roots and stolons. Low K supply appeared to facilitate

Ca uptake but suppress Ca uptake at higher K. At very high K the suppression of Ca uptake may be responsible for the turnaround in total dry mass from a negative trend.

Similar responses were found for Mg, Zn and Cu, cations with similar charge to Ca

(Figures A6.1a, 3a, & 3b).

Concentration of K however, had a slight negative effect on N concentration which remained at similar levels to those found for organs in Experiment 10 where total

188 leaf area was highest, and so had no effect on growth. Increased uptake of P in petioles and Ca in roots and stolons did have a negative relationship with growth. As

P levels increased, beyond 6.00 g kg-1 in petioles, the level at the lowest K for this experiment, the total dry mass decreased (Figure 6.12), the same effect was found in

Experiment 11 (Figure 4.7a). Conversely, as P levels in petioles from Experiment 10 increased so did the number of leaves (Figure 3.14). Calcium increases due to increased K concentration similarly depressed total dry mass and leaf area (Figure

6.13). Without a similar precedent to compare Ca effect on lotus growth, the trial investigating the effect of Ca on lotus in the following chapter must be analysed.

189

Chapter 7 Analysing the Interaction between Calcium and Lotus

7.1 Introduction

Calcium is required by plants for a wide range of functions. It has a role in cell wall stability, through strengthening of cell walls by cross-linking pectins in the middle lamella, and cell extension facilitated by auxin induced acidification of the cell wall releasing Ca from the pectate cross-links (Mengel and Kirkby 2001). The release of

Ca decreases cell wall permeability, allowing for secretory processes of a variety of substances. Calcium serves as a cation balancing anions, particularly in the vacuole and is important for osmoregulation through salt accumulation, particularly oxalates, without increasing cell osmotic pressure (Marschner 1995). As a second messenger,

Ca is responsible for the activation of proteins and enzymes, most notably calmodulin (Bush 1995). Phosphorylation processes are also influenced, particularly the provision of charge stimulation for membrane bound enzymes, for example the

ATPase proton pump (Gonzalez et al. 1999). Indirectly, the provision of a stable membrane also serves to maintain membrane bound enzymes in a functional environment (Fageria et al. 1997).

Availability of Ca from soils is generally adequate, Ca being the third most abundant metal in the Earth’s crust (Bruce 1999). In solution culture, care must be taken to

- avoid precipitates with anions, particularly PO4 (Schwartz 1995). Uptake of Ca is limited to young unsuberized roots and can be depressed by the presence of other cations (Mengel and Kirkby 2001). Movement of Ca within the plant is restricted to the xylem sap, and once deposited within meristematic cells where concentrations of

Ca are highest in the plant, Ca is relatively immobile (Marschner 1995). Within the

190 cell, Ca is found mostly bound to the cell wall, membranes and in the vacuole as free

Ca2+ or as salt precipitates. The concentration of Ca in the cytosol is comparatively low during normal metabolism though fluctuates with signal transduction functions

(Bush 1995).

The amount of Ca in plants varies with species and is between 5 to 30 mg Ca per g of dry matter (Mengel and Kirkby 2001). Plant part and age also dictate concentration of Ca (Marschner 1995) though concentrations are typically higher in dicotyledons than in monocotyledons (Islam et al. 1987). The deficiency critical concentration for a wide number of species has been documented (Reuter and Robinson 1997).

Loneragan and Snowball (1969) found the Ca concentration remained stable at low supply with yield consequences, but at luxury supply, yields stabilise and Ca concentration in tissues increase. Toxicity due to Ca has not been reported as a major problem. Deficiencies are most often seen in new emerging shoots due to the immobility of Ca in older plant parts, where the growing point is affected and expanding leaves often become marginally necrotic and curl under (Grundon et al.

1997). Disorders in fruits related to the breakdown of membrane integrity are also common due to Ca deficiency or immobility of Ca through the phloem sap (Bangerth

1979). Consistency of supply has implications on functional requirements and expression of deficiency (Loneragan and Snowball 1969).

Typical adequate concentrations of Ca for healthy plants have been reported as 9.00 to 12.00 g kg-1 in young leaf blades of sweetpotato (O’Sullivan et al. 1997). In

‘Irish’ potato, Ca concentrations were 6.00 to 9.00 g kg-1 for similar leaves though older plants (Huett et al. 1997). Waterchestnuts were reported as containing 8.60 g kg-1 of Ca in stems (Kleinhenz et al. 2001), while eddo taro second-youngest open

191 leaf blades contained between 2.60 and 4.00 g kg-1 for adequate growth (O’Sullivan et al. 1995).

The Ca requirement and partitioning for lotus has not been adequately reported. In

Experiments 10 to 12, an indication of the Ca concentrations and range was determined. In leaves, Ca concentration was consistently higher than in other organs at concentrations between 20.00 to 30.00 g kg-1 (Figures 4.5b, 5.6b and 6.5b). In petioles, the Ca concentration found at between 10.00 to 15.00 g kg-1 was marginally higher than for roots and stolons at approximately 10.00 g kg-1. In Experiment 11, no difference was found between the Ca concentration of petioles and Ca concentration of roots and stolons (Figure 5.6b). Therefore, it was necessary to challenge lotus with a varying supply range of Ca treatments to establish the critical concentrations, the best organ for assessment of Ca in tissues and to determine the optimum supply range for adequate growth. The system used for observation of Ca trials is important due to the location of the growing point of lotus beneath the media.

Based on the report of Loneragan and Snowball (1969) and the results from the previous experiments, it was expected that concentration of Ca in tissues would be relatively stable except at higher treatments. Expression of the effects of Ca at lower supply should be seen in the suppression of yields. At higher Ca supply yields should be relatively even.

The objectives of this chapter were to solicit a set of nutrient and growth responses in relation to a variety of Ca treatments in order to evaluate the effectiveness of the trial system. Identification of the most appropriate organ for analysis, establishment of critical concentrations and determination of optimum supply concentration would

192 provide a measure of confirmation. The following experiment was undertaken to substantiate the vigour of these propositions.

7.1.1 Experiment 13 Effect of Calcium on Growth and Organ Nutrient Concentration of Lotus (Nelumbo nucifera ).

During September of 2002, a trial involving eight calcium treatments with five replications per treatment was undertaken over a 50 day period of growth. Analyses of growth parameters, effect of Ca supply and effect of major nutrient concentrations with significant differences were performed.

7.2 Materials and Methods

The conditions for plant growth, harvest, and statistical procedures were as per section 4.2 except for treatment imposition.

Calcium treatments comprised 50, 100, 150, 175, 200, 230, 250, 350 ppm of Ca, and were identified as Ca50 to Ca350 respectively (Table A1.9).

193

7.3 Results

7.3.1 Observations of Calcium Supply on Visual Growth Expression.

At day 20, symptoms of disorder on leaves were approximately 10% of leaf surfaces at low supply treatments from Ca50 to Ca175, though not statistically different from higher Ca supply treatments (Table 7.1). Marginal chlorosis followed by necrosis on older leaves was most pronounced at treatments higher than Ca200 where approximately 40% of leaf surfaces were affected. Similarly, blackening of roots was least at low supply treatments from Ca50 to Ca175 and the incidence increased with higher treatments between Ca200 to Ca350.

At day 40, the incidence of symptoms on leaves had increased for Ca50 to Ca175 to a point of parity with Ca200 to Ca350 which remained at day 20 symptom levels, though only Ca100 and Ca350 were significantly different. The exception was Ca100, which although doubling in symptoms with time, was noticeably lower than other treatments (Table 7.1). Similarly, root blackening was least for Ca100, this treatment was significantly different from all other treatments except Ca50.

Table 7.1 Estimated observations for lotus (Nelumbo nucifera) on: a) the percentage of leaves per plant showing signs of disorder at day 20; b) the percentage of leaves per plant showing signs of disorder at day 40; c) the percentage of total leaf area per plant affected by disorder at day 40; d) the below-ground plant parts affected by disorder at day 20; e) below-ground plant parts affected by disorder at day 40. Values followed by different letters are significantly different at P<0.01 within each column (Tables A7.1-5). Treatment A B C E (ppm) D 50 12.50a 36.25ab 1.25a 5.00a 42.50ab 100 6.25a 15.00a 0.41a 3.75a 25.00a 150 10.00a 23.75ab 1.46a 6.25ab 50.00b 175 12.50a 33.75ab 1.74ab 6.25ab 55.00b 200 37.50ab 38.75ab 2.70ab 15.00abc 60.00b 230 32.50ab 47.50ab 2.25ab 32.50c 52.50b 250 40.00ab 45.00ab 3.15ab 22.50abc 62.50b 350 57.50b 52.50b 4.52b 25.00bc 50.00b

194

7.3.2 Calcium Supply Effect on Growth Parameters.

Total dry mass (P<0.001) and dry mass of leaves (P<0.003) generally increased, plateaued, then decreased with increasing Ca supply, petioles (P>0.01) and roots and stolons (P>0.02) showed no significant change in dry mass due to Ca supply (Figures

7.1a-b, Tables A7.6-9). Total dry mass increased from approximately 15 g plant-1 at

-1 Ca50 to a peak and plateau of 30 g plant at Ca100 to Ca200, before decreasing to

-1 approximately 20 g plant at Ca225 to Ca350. All organs displayed the same pattern as total dry mass. Leaves increased from approximately 4 g at Ca50 to a peak of 10 g at

Ca100 to Ca200 before decreasing to 6 g at Ca225 to Ca350.

The number of leaves remained at approximately 25 for treatments Ca50 to Ca225 before dropping to less than 20 at Ca250 to Ca350, but there was no significant effect

(P<0.06) of Ca supply (Figure 7.2a, Table A7.10). The number of nodes was not significantly affected by Ca supply (P<0.02) and fluctuated between 60 and 90 nodes

(Figure 7.2b, Table A7.11). The number of stolons similarly was not significantly affected by increasing Ca supply (P<0.03), and was approximately between 15 and

25 stolons (Figure 7.2c, Table A7.12).

Total leaf area was increased significantly (P<0.005) from approximately 10 dm2 at

2 Ca50 to 25 dm at Ca100 where it plateaued for the next three treatments (Figure 7.3a,

2 Table A7.13). Total leaf area then fell to approximately 15 dm at Ca225 to Ca350.

Total stolon length varied between 1 700 and 3 000 mm but was not significantly affected (P>0.01) by Ca supply (Figure 7.3b, Table A7.14). Internode length ranged between 22 to 40 mm (P>0.05) but was not significantly affected by Ca supply

(Figure 7.3c, Table A7.15).

195

35 AA

30 ) -1 25

Total Dry Mass (g plant (g Dry Mass Total 10

0 14 BB

6 Organ Dry Mass (g) Mass Organ Dry 4 Leaf 2 Petiole Roots & Stolons

0 0 50 100 150 200 250 300 350

Ca Supply (ppm)

Figure 7.1 Dry mass of lotus (Nelumbo nucifera) as affected by calcium supply: a) Total dry mass; b) Organ dry mass for leaf, petiole, and roots and stolons. Values are means and bars represent S.E. (n=5). (Tables A7.6-9).

196

A 30

15 Number of Leaves of Number 10

0 B 100

40 Number of Nodes Number

0 C

10 Number of StolonsNumber

0 0 50 100 150 200 250 300 350 Ca Supply (ppm) Figure 7.2 Effect of calcium supply on lotus (Nelumbo nucifera) organ numbers: a) Leaf; b) Node; c) Stolon. Values are means and bars represent S.E. (n=5). (Tables A7.10- 12).

197

A 25 )

2 20

10 Total Leaf Area (cm Leaf Total

0 3500 B

3000

2500

2000

1500

Total Stolon Length(mm) Stolon Total 1000

500

0 C 40

20 Internode Length (mm)

0 0 50 100 150 200 250 300 350 Ca Supply (ppm) Figure 7.3 Effect of calcium supply on lotus (Nelumbo nucifera) organ dimensions: a) Total Leaf Area; b) Total Stolon length; c) Internode length. Values are means and bars represent S.E. (n=5). (Tables A7.13-15).

198

7.3.3 Effect of Calcium Supply on Organ Nutrient Concentration.

Calcium concentration in leaves (P>0.0000), petioles (P>0.0000) and roots and stolons (P>0.0000) had significant responses due to Ca supply (Figure 7.4a, Tables

-1 A7.16-18). In leaves approximately 5.00 g kg of Ca was found at Ca50 and

-1 increased steadily to a peak of 25.00 g kg at Ca350. Petioles contained

-1 approximately 5.00 g kg of Ca at Ca50 and increased to a peak and plateau of 10.00

-1 -1 g kg of Ca at Ca200 to Ca350. Roots and stolons contained approximately 5.00 g kg

-1 of Ca at Ca50 and increased to around 8.00 g kg at Ca150 to Ca200 before increasing

-1 to approximately 10.00 g kg at Ca250 to Ca350.

Supply of Ca had significant effects on N concentration in leaves (P<0.0000), petioles (P<0.0000), and roots and stolons (P<0.0000) (Figure 7.4b, Tables A7.19–

21). Leaves contained approximately 4.6 % N at Ca50 before decreasing to around

4.0% between Ca100 to Ca350. Petioles contained approximately 3.5 % N at Ca50 then dropped sharply to around 2 % at Ca100 to Ca350. Roots and stolons demonstrated similar concentration and trend to petioles.

Supply of Ca had a highly significant effect on P concentration in leaves (P<0.006), petioles (P<0.007), and roots and stolons (P<0.0003) (Figure 7.5a, Tables A7.22–

-1 24). In leaves, P concentration was approximately 7.50 g kg at Ca50 and decreased

-1 -1 to 6.00 g kg across Ca100 to Ca350. Petioles had approximately 10.00 g kg of P at

-1 Ca50 and decreased to 7.50 g kg P at Ca100 to Ca350. Roots and stolons had

-1 -1 approximately 11.00 g kg of P at Ca50 and decreased to 8.50 g kg of P at Ca100 to

Ca350.

199

Supply of Ca had no significant effect on K concentration in leaves (P>0.13) and petioles (P>0.33), though roots and stolons (P<0.003) responded with a slight increase (Figure 7.5b, Tables A7.25–27). In leaves, approximately 30.00 g kg-1 of K was found, and in petioles, K concentration was approximately 60.0 g kg-1. Roots

-1 and stolons K concentration increased from approximately 35.00 g kg at Ca50, then

-1 increased to a peak and plateau of 41.00 g kg of K at Ca150 to Ca350.

There were no significant responses in leaves as a function of Ca supply for Mo and

Na (Table 7.2, A7.49 & 52). A negative response was found for Mg, Fe, Mn, Zn, B,

Na and Al in leaves (Tables 7.2, A7.28-57, Figures A7.1a, 2, 3a & 4a). Conversely, an increase in Cu concentration in leaves was found while S concentration decreased over three treatments before increasing at higher Ca (Figure A7.3a & 1b). Petioles were mostly unresponsive to Ca treatments (Tables 7.2, A7.28-57). Exceptions were a decrease in Mn and Zn while S demonstrated a similar trend to leaves and Na increased, peaked then decreased (Figures A7.2b, 3a, 1b & 5a). Large responses to

Ca treatments were found for Mg, S, Mn, Zn, Mo and Al concentrations in roots and stolons (Tables 7.2, A7.28-57). The general trend for S, Zn, Mo and Al was to decrease, level then increase (Figures A7.1b, 3a, 4b & 5b). Concentration of Mg increased slightly with increasing Ca while Mn decreased with increasing Ca

(Figures A7.1a & 2b). No response was found for Fe, Cu, B and Na in roots and stolons.

200

25000 A

20000 ) -1

15000

10000 Organ Ca Conc. (mg kg (mg Conc. Organ Ca

5000 Leaf Petiole Roots & Stolons

0 B

4 ) -1

2 Organ N Conc. (mg kg (mg OrganN Conc.

0 0 50 100 150 200 250 300 350

Ca Supply (ppm)

Figure 7.4 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Calcium; b) Nitrogen. Values are means and bars represent S.E. (n=5). (Tables A7.16-21).

201

A 10000 )

-1 8000

6000

4000 Organ P Conc. (mg kg (mg Organ P Conc.

Leaf 2000 Leaf Petiole Roots & Stolons

0 B 60000

50000 ) -1

40000

30000

20000 Organ K Conc. (mg kg Conc. (mg Organ K

10000

0 0 50 100 150 200 250 300 350

Ca Supply (ppm)

Figure 7.5 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Phosphorous; b) Potassium. Values are means and bars represent S.E. (n=5). (Tables A7.22-27).

202

Table 7.2 List of F and P values for lotus (Nelumbo nucifera) organ minor and trace element nutrient concentration as a function of calcium supply (Figures A7.1-5, Tables A7.28-57).

Nutrient Organ F value P Mg Leaf 4.18 0.003* Petiole 2.45 0.04 Roots & Stolons 7.24 0.0000* S Leaf 5.01 0.0008* Petiole 4.91 0.0009* Roots & Stolons 5.32 0.0005* Fe Leaf 18.35 0.0000* Petiole 1.32 0.27 Roots & Stolons 2.44 0.04 Mn Leaf 4.18 0.003* Petiole 8.03 0.0000* Roots & Stolons 25.27 0.0000* Zn Leaf 3.79 0.0005* Petiole 4.26 0.003* Roots & Stolons 7.80 0.0000* Cu Leaf 23.23 0.0000* Petiole 1.36 0.25 Roots & Stolons 1.47 0.21 B Leaf 6.53 0.0000* Petiole 1.74 0.13 Roots & Stolons 1.67 0.15 Mo Leaf 2.53 0.03 Petiole 2.23 0.05 Roots & Stolons 9.71 0.0000* Na Leaf 2.25 0.05 Petiole 4.98 0.0008* Roots & Stolons 1.44 0.22 Al Leaf 4.17 0.003* Petiole 1.03 0.43 Roots & Stolons 4.43 0.002* *Denotes significance at P<0.01

203

7.3.4 Analysis of Organ Calcium Concentration on Organ Nutrient Composition.

Calcium supply increased Ca concentration for all organs; petioles and roots and stolons were best represented as a combined fitted curve (Figure 7.6, Tables A7.58-

60, 141-144, 157-160). Concentration of Ca in leaves (P<0.0000) increased steadily

-1 without peak or plateau from approximately 5.00 to 25.00 g kg of Ca at Ca50 to

Ca350. In petioles, roots and stolons (P<0.0002) Ca concentration also increased without peak or plateau, though the magnitude of change was not as great over the same range of supply. Concentration of Ca in petioles, roots and stolons increased from approximately 5.00 to 10.00 g kg-1.

Concentration of N in all organs was suppressed with increasing Ca concentration; petioles and roots and stolons were best represented as a single fitted curve (Figure

7.7, Tables A7.61-63, 145-148, 161-164). In leaves, N concentration decreased

(P<0.0000) from approximately 4.5 to 3.9 % N with an increase from 5.00 to 25.00 g kg-1 of Ca. Petioles, roots and stolons (P<0.002) had a greater decline, approximately 3.7 to 1.9 % N, over a narrower Ca increment, ranging from 5.00 to

10.00 g kg-1.

Phosphorous concentration in organs was best represented by all organs combined

(Figure 7.8a, Tables A7.64-66, 149-152, 165-168). Concentration of P declined

(P<0.0000) from approximately 9.00 to 5.00 g kg-1 of P over a range of 5.00 to 25.00 g kg-1 of Ca.

Organ concentrations of K were best represented by individual fitted curves (Figure

7.8b, Tables 7.67-69, 153-156, 169-172). No change was found for leaves (P>0.05)

204 with increasing Ca and was steady at between 25.00 to 30.00 g kg-1 of K. Similarly, petiole (P>0.33) K concentration had no response in relation to Ca increase and was approximately 55.00 to 60.00 g kg-1 of K. Roots and stolons (P<0.0002) K concentration increased from approximately 35.00 to 45.00 g kg-1 over an increment from 5.00 to 15.00 g kg-1 of Ca.

In leaves, minor and trace elements Cu and Mo had increases in concentration with

Ca increase while Fe, Mn, and Al decreased with Ca increase (Tables 7.3, A7.65-94,

Figures A7.8, 9b, 7a-b & 10b). Concentrations of Mg, S, Zn, B, and Na showed no response to Ca increases (Tables 7.3, A7.65-94). In petioles, Mg, Cu and Mo concentrations increased with Ca, and conversely, Mn concentration was depressed

(Table 7.3, A7.65-94, Figures A7.6a, 8 & 9b). There was no response to Ca for S,

Fe, Zn, B, Na, and Al concentrations in petioles (Table 7.3). Roots and stolons concentrations for Mg, S, Fe, B, Mo and Na all increased with increasing Ca concentration, whereas only Mn decreased (Tables 7.3, A7.65-94, Figures A7.6a-b,

7a, 9a-b & 10a). No response to Ca was found for Zn, Cu and Al concentrations in roots and stolons.

205

30000

25000 ) -1 20000

15000

10000 Organ Ca Conc. (mg kg (mg Conc. Ca Organ

5000 Leaf Petioles, Roots & Stolons

0 0 50 100 150 200 250 300 350 400 Ca Supply (ppm)

Figure 7.6 Calcium concentration in organs of lotus (Nelumbo nucifera) as a function of calcium supply. Regression equations are: y = (24 385.97 + 0.87x- 0.89x2)0.5 (r2 = 0.87) and y = 1454.06x0,36 (r2 = 0.61) for leaves (____) and petioles, roots and stolons (…..) respectively. (Tables A7.58 & 144).

206

Organ N Conc. (%) Organ N Conc. 2

1 Leaf Petioles, Roots & Stolons 0 0 5000 10000 15000 20000 25000 30000

Organ Ca Conc. (mg kg-1)

Figure 7.7 Nitrogen concentration in organs of lotus (Nelumbo nucifera) as a function of organ calcium concentration. Regression equations are: y = 8.28 – 0.43x3 (r2 = 0.55) and y = 3.82 – 0.017x0.5 (r2 = 0.11) for leaves (____), and petioles, roots and stolons (…..) respectively. (Tables A7.61 & 148).

207

12000 A

10000

) 8000 -1

6000

P Conc. (mg kg P Conc. (mg 4000

2000

Leaves, Petioles, Roots & Stolons

0 70000 B Leaf Petiole 60000 Roots & Stolons )

-1 50000

40000

30000

20000 Organ K Conc. (mg kg (mg K Conc. Organ

10000

0 0 5000 10000 15000 20000 25000 30000

-1 Organ Ca Conc. (mg Kg )

Figure 7.8 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ calcium concentration a) Phosphorous, regression equation is y = 283299379.3 /(27 584.79 + x) (r2 = 0.26) for combined leaves, petioles, roots and stolons; b) Potassium, regression equation is y = 25 142.38 + 19.22x0.5lnx (r2=0.32) for roots and stolons (---). Leaves (___) and petioles (….). (Tables A7.65, 66 & 149).

208

Table 7.3 List of F and P values for the relationship between organ calcium concentration and minor and trace element concentration (Figures A7.6-10, Tables A7.70-99).

Nutrient Organ F value P Mg Leaf 1.57 0.21 Petiole 27.58 0.00001* Roots & Stolons 51.57 0.0000* S Leaf 0.71 0.41 Petiole 6.90 0.01 Roots & Stolons 9.37 0.005* Fe Leaf 80.99 0.0000* Petiole 0.19 0.66 Roots & Stolons 13.28 0.0009* Mn Leaf 10.78 0.0023* Petiole 15.43 0.0004* Roots & Stolons 18.94 0.0001* Zn Leaf 0,03 0.87 Petiole 0.43 0.51 Roots & Stolons 0.44 0.51 Cu Leaf 28.70 0.00001* Petiole 8.29 0.0068* Roots & Stolons 3.79 0.05 B Leaf 5.23 0.03 Petiole 5.32 0.02 Roots & Stolons 39.66 0.0000* Mo Leaf 34.32 0.0000* Petiole 19.67 0.0002* Roots & Stolons 16.19 0.0003* Na Leaf 1.43 0.23 Petiole 0.73 0.39 Roots & Stolons 11.85 0.002* Al Leaf 18.63 0.0002* Petiole 2.39 0.13 Roots & Stolons 0.93 0.34 *Denotes significance at P<0.01

209

7.3.5 Analysis of Growth as a Function of Organ Calcium Concentration.

Increasing concentrations of Ca had responses for total dry mass in relation to leaves

(P<0.0000) and roots and stolons (P<0.0005) but not petioles (P>0.1) (Figure 7.9a,

Tables A7.100-102). Leaf Ca concentration increases from 5.00 to 12.00 g kg-1 of

Ca resulted in a rise from approximately 10 to 30 g where a peak and plateau was achieved. Total dry mass then decreased to around 15 g plant-1 with a Ca increase to

25.00 g kg-1. The response to Ca increases in roots and stolons was a narrow increase in total dry mass from 20 to 30 g plant-1 where it peaked before sharply declining to approximately 10 g plant-1 over a Ca range from 5.00 to 13.00 g kg-1.

Individual organ dry mass was responsive to Ca concentration for leaves (P<0.0003) and roots and stolons (P<0.0000) but not petioles (P>0.04) (Figure 7.9b, Tables

A7.103-105). Leaf dry mass increased from approximately 4 to 10 g where a peak plateau was achieved for a corresponding Ca increase from 4.00 to 12.00 g kg-1 of

Ca. Leaf dry mass then decreased to around 5.00 g kg-1 from Ca concentrations of

16.00 to 25.00 g kg-1. Dry mass of roots and stolons decreased sharply from approximately 12 to 5 g over a Ca concentration range of 5.00 to 13.00 g kg-1.

The number of stolons was significantly affected by leaf (P<0.003) Ca concentration and petiole (P<0.0006) Ca concentration but not Ca concentration in roots and stolons (P>0.2) (Figure 7.10a, Tables A7.106-108). In response to leaf Ca concentration, the number of stolons increased from approximately 11 to a peak plateau of 24 stolons over a Ca range of 5.00 to 15.00 g kg-1. The number of stolons then decreased to approximately 11 stolons with Ca concentration increasing to

25.00 g kg-1 of Ca. Response to Ca concentration was more acute, stolon numbers

210 increased from approximately 15 to a peak of 24 over a Ca concentration range of

5.00 to 10.00 g kg-1 before declining to 10 stolons at 15.00 g kg-1.

Total stolon length was influenced by leaf (P<0.007) Ca concentration, but not petiole (P>0.1) or roots and stolons (P>0.1) Ca concentration (Figure 7.10b, Tables

A7.109-111). Total stolon length increased from approximately 1 500 mm to a peak plateau of 3 000 mm over a leaf Ca concentration range of 5.00 to 15.00 g kg-1 before dropping to 2 000 mm at 25.00 g kg-1 of Ca. Total leaf area was affected by leaf

(P<0.0005) and roots and stolons (P<0.005) Ca concentrations, but not petiole

(P>0.2) Ca concentration (Figure 7.11, Tables A7.112-114). In leaves, an increase in

Ca concentration from 5.00 to 15.00 g kg-1 resulted in LA increasing from approximately 10 dm2 to a peak plateau of 24 dm2 before falling to 12 dm2 at 25.00 g kg-1 of Ca. In roots and stolons, the Ca concentration range from 5.00 to 13.00 g kg-1 resulted in an increase in LA to a peak of approximately 22 dm2 at 9.00 g kg-1 of Ca before declining to 10 dm2 LA.

Concentration of Ca did not influence the number of leaves (P>0.1, P>0.09, P>0.07), the number of nodes (P>0.09, P>0.02, P>0.2) or internode length (P>0.03, P>0.4,

P>0.3) for leaf, petiole and roots and stolon Ca concentrations respectively (Tables

A7.115-123). The critical concentrations determined from the means of growth responses corresponding to Ca concentration are approximately 9.97 to 19.32, 7.63 to

11.46, and 6.57 to 9.21 g kg-1 of Ca for leaves, petioles and roots and stolons respectively (Table 7.4). There were insufficient data to perform a t-test for analyses of differences between means.

211

A 40 ) -1

20 Total (g Dry Mass plant 10

B LeafLeaf PetiolePetiole RootsRoots & & Stolons Stolons 15

10 Organ Dry Mass (g) 5

0 0 5000 10000 15000 20000 25000 30000

-1 Organ Ca Conc. (mg kg )

Figure 7.9 Dry mass of lotus (Nelumbo nucifera) as a function of organ calcium concentration: a) Total dry mass, regression equations are y=32.97exp(-exp(-((x-13 932.88)/8 735.56))-((x-13 932.88)/8 735.56)+1) (r2 = 0.40) for leaves (____), and y = 30.31/ (1+((x – 7718.89)/3723.08)2 (r2 = 0.30) for roots and stolons (----), petioles (…..); b) Individual organ dry mass, regression equations are y=10.16exp(-exp(-((x- 14 152.93)/9 172.04))-((x-14 152.93)/9 172.04)+1) (r2 = 0.59) and y = 30/(1 + ((x – 7718.89)/3723.08)2) (r2 = 0.30) for leaves and roots and stolons respectively. (Tables A7.100-103 & 105).

212

40 A Leaf Petiole Roots & Stolons 30

20 Number of StolonsNumber

0 B 4000

3000

2000 Total Stolon Length (mm) Length Stolon Total 1000

0 0 5000 10000 15000 20000 25000 30000

-1 Organ Ca Conc. (mg kg )

Figure 7.10 Effect of calcium concentration in organs of lotus (Nelumbo nucifera) on: a) Number of stolons, regression equations are y = 2.92 – 7.46*10-8x2 +0.024x/lnx (r2=0.22), y = 2.64 +6.90*10-7x2 – 4.76*10-11x3 (r2=0.30), for leaves and petioles respectively; b) Total stolon length, regression equations are y=2931.44exp(- exp(-((x-14 608.40)/11 527.19))-((x-14 608.40)/11 527.19)+1) (r2=0.19) for leaves (___), petioles (….) and roots and stolons (----). (Tables A7.106-107 &109-111).

213

) 25 2

Total Leaf Area (dm Total 10

Leaf 5 Petiole Roots & Stolons 0 0 5000 10000 15000 20000 25000 30000

-1 Organ Ca Conc. (mg kg )

Figure 7.11 Total leaf area of lotus (Nelumbo nucifera) as a function of organ calcium concentration, regression equations are y= 24.31exp(-exp(-((x-14 240.44)/9 587.32))-((x-14 240.44)/9 587.32)+1) (r2 = 0.30) for leaves (____), petioles (…..), and y=22.29/(1+((x – 8 055.09/ 4 154.86)2) (r2 = 0.19) for roots and stolons (----). (Tables A7.112-114).

Table 7.4 Calculated calcium critical concentrations for lotus (Nelumbo nucifera) organs, determined by the relationship between growth parameter and organ calcium concentration (Figs 7.9-11). All units (mg kg-1)

Leaf Petiole Roots & Stolons Deficiency Toxicity Deficiency Toxicity Deficiency Toxicity TDM 10 205.70 18 277.18 nc nc 6471.10 8966.69 LA 10 117.22 19 052.71 nc nc 6665.49 9444.69 LfNo nc nc nc nc nc nc NoNo nc nc nc nc nc nc StNo 9 700.14 20 541.19 7624.47 11 453.71 nc nc StLgth 9 656.99 20 386.07 nc nc nc nc LDM 10 177.42 18 315.63 PDM nc nc RDM nc nc

Mean 9 971.49 19 314.56 7624.47 11 453.71 6 568.29 9 205.69 s.e. 101.95 413.84 nc nc 51.95 127.75 nc not calculated

214

7.3.6 Analysis of Total Dry Mass as a Function of Calcium Supply Affected Growth Parameters.

Total dry mass increased (P<0.0000) from approximately 10 to 40 g plant-1 over an increase of LA from 7 to 33 dm2 (Figure 7.12, Table A7.124). The increase in total dry mass was highly related to increasing LA (r2=0.89).

40 ) -1

20 Total Dry Mass (g plant 10

0 0 5 10 15 20 25 30 35

Total Leaf Area (dm2)

Figure 7.12 Total dry mass of lotus (Nelumbo nucifera) as a function of total leaf area. Regression equation is y = 4.82 + 0.34xlnx (r2 = 0.89). (Table A7.124).

215

7.3.7 Analysis of Growth Parameters Affected by Calcium Concentration, as a Function of Calcium Concentration Affected Organ Nutrient Concentration.

Addition of variable concentrations of Ca causing a reduction in N concentration in leaves (P<0.0007) resulted in a total dry mass response (Figure 7.13a, Table A7.125-

127). Total dry mass was higher at lower leaf N concentration and was reduced from approximately 30 to 10 g plant-1 as N concentration increased from approximately 3 to 5% of N. The response for N in leaves (P<0.0005) for LA was similar to total dry mass (Figure 7.13b, Table A7.128-130). There was no influence for N concentration in leaves on the number of stolons (P>0.1) and total stolon length (P>0.02) (Tables

A7.131-132).

Variable concentrations of Ca causing a reduction in P in leaves from 8.00 to 4.00 g kg-1 resulted in a decrease (P<0.002) in total dry mass from approximately 30 to 10 g plant-1 (Figure 7.14a, Table A7.133). The same response was observed for LA

(P<0.0009), decreasing from approximately 25 to 5 dm2 for the same P concentration

(Figure 7.14b, Table A7.134). There was no response to P concentration in leaves for the number of stolons (P>0.2) or total stolon length (P>0.01) (Tables A7.135-

136).

Addition of variable concentrations of Ca causing an increase in root and stolon K concentration had no influence on total dry mass (P>0.1), LA (P>0.3), number of stolons (P>0.9) or total stolon length (P>0.8) (Tables A7.137-140).

216

50 Leaf A Petiole Roots & Stolons 40 ) -1

20 Total Dry Mass (g plant Mass Dry Total 10

0 B 30

25 ) 2

Total Leaf Area (dm 10

0 0123456 N Conc. (%)

Figure 7.13 Effect of lotus (Nelumbo nucifera) leaf nitrogen concentration on: a) Total dry mass, regression equation is y=37.00 – 0.21ex (r2 = 0.23), y = 35.06 – 3.19x1.5 (r2=0.22), y = 38.44 – 4.24x1.5 (r2=0.21) for leaves, petioles and roots and stolons respectively; b) Total leaf area, regression equations are y=28.63 – 0.16ex (r2 = 0.26), y = 27.23 – 2.42x1.5 (r2=0.25) and y = 29.83 – 3.22x1.5 (r2=0.25) for leaves (___), petioles (….) and roots and stolons (----) respectively. (Table A7.125-130).

217

40 ) -1

20 Total Dry Mass (g plant Total Dry 10

B 30

25 ) 2

Total Leaf Area (dm Area Leaf Total 10

0 0 2000 4000 6000 8000 10000

Leaf P Conc. (mg kg-1)

Figure 7.14 Effect of lotus (Nelumbo nucifera) leaf phosphorous concentration on: a) Total dry mass, regression equation is y= 39.00 – 3.9*10-7x2 (r2 = 0.21); b) Total leaf area, regression equation is y= 29.68 – 2.8*10-7x2 (r2 = 0.22). (Tables A7.133- 134).

218

7.4 Discussion

The objectives of the experiment reported in this chapter were to observe the visual effect of Ca on plant parts, identify the critical Ca concentrations in tissues, determine the adequate supply range of Ca for lotus and identify the most appropriate organ for field testing. The symptoms of marginal chlorosis/necrosis expressed in previous experiments were comparatively negligible at the lower Ca supplies though present with increasing Ca supply and time. It is clear that higher supplies of Ca have a negative effect on symptomology which are supported by a negative response in growth.

The growth results as a function of Ca concentration allow for the tentative proposal of critical Ca concentrations for all organs tested (Table 7.4). Leaf responses to Ca concentration had the greatest number of significant growth incidences and a mean critical concentration for the deficient and toxic values were established. The values determined for petioles were not as reliable as they were a single value calculated from the number of stolons. Organ numbers have been shown in Experiments 10, 11 and 12, to be not as closely associated with dry mass as parameters such as LA and total stolon length. The critical values determined for the roots and stolons were derived from the means of total dry mass and LA responses. Therefore, critical values associated with organ number growth parameters such as for petioles, are not as robust as those for total dry mass itself, or measured responses such as LA or total stolon length.

Comparisons with the values reported for other crops suggest the lotus results were high. Loneragan et al. (1968) found a number of species of plants grew favourably

219 at lower Ca concentrations than had previously been reported. O’Sullivan et al.

(1997) list a critical deficiency of 7.60 g kg-1 of Ca in the 7th to 9th youngest leaf blades of sweetpotato, with healthy plants containing 9.00 to 12.00 g kg-1 of Ca. In waterchestnuts, 8.60 g kg-1 and 7.80 g kg-1 were reported for stems and roots respectively (Kleinhenz et al. 2000). In cassava, concentrations of Ca greater than

8.80 g kg-1 were reported to be toxic (Howeler 1996). Taro however, was reported to have an adequate range between 26.00 and 40.00 g kg-1 of Ca in the second emerged leaf blade with a critical value for deficiency at 20.00 g kg-1 of Ca (O’Sullivan et al.

1996). It can be seen that a large range of Ca concentrations for a wide selection of species has been observed and the values for lotus have a similar concentration or are just outside the values of some species.

From the means of the critical concentrations found for various growth parameters

(Table 7.4), an adequate supply range can be estimated using the equations from the curve in Figure 7.6 and the evaluation function in the Tablecurve software. A supply range of approximately 82 to 195 ppm Ca is extrapolated from the critical concentrations for leaves. Similarly, roots and stolons extrapolate to approximately

60 to 195 ppm Ca supply. Both of these sets of values fall in the region of least incidence of leaf disorder, though for roots and stolons the lower 60 ppm value, if substituted for the leaf results, determines total dry mass and LA to be approximately half that of the 90% critical levels. In petioles, only the single critical values estimated for the number of stolons could be used to estimate the adequate supply range and these were found to be approximately 100 to 260 ppm Ca. These values were deemed to be inappropriate, the lower value has very little margin for adjustment and the upper value was in the range where disorders were common and

220 growth impeded. Therefore, the values of 82 to 195 ppm of Ca for leaf critical concentrations were assumed to be the most functional supply range.

These calculated supply levels imply the commercial nutrient levels used as the constant throughout the four individual nutrient trials are inappropriate for lotus.

Calcium in high supply is generally not a problem as a non toxic divalent cation

(Clarkson 1980) and supplies of between 200 and 300 ppm have been recommended

(Jones 1997). However, it is known to be implicated in suppression of the uptake of

K and Mg (Bangerth 1979, Jones 1997). In this case, disorder symptoms and growth suppression would have to be a sensitivity to total salt loading or an unbalanced

Ca:K:Mg ratio or a combination of these postulations. It is known, that voltage operated K+ channels embedded in membranes have been reported to be blocked by

Ca2+ and in some instances permeate K+ channels (Bush 1995). At high K supply, a low affinity mechanism operates for the uptake of K, which is competitively inhibited by Ca (Johansen et al. 1968). The level of K supply in this trial was not in the range for adequate growth estimated in the previous experiment, where K was analysed and the constant K350 was assessed as high. Therefore, the high level K350 could potentially activate low affinity mechanisms for K uptake and facilitate the uptake of Ca through permeable channels or block uptake channels. However, uptake of K increased slightly in roots and stolons with increased Ca concentration

(Figure 7.8b). Beyond the roots and stolons, K concentration in petioles and leaves was similar to the levels found for the equivalent K350 treatment in Experiment 12.

This suggests that high affinity channels for K were operating when an equilibrium of K was established in tissues (Johansen et al. 1968). It is not known however, what ratio of K is absorbed by low and high affinity mechanisms in lotus.

221

While variable concentrations of Ca influencing roots and stolons K concentration had no effect on growth (Tables A7.137-140), variable concentrations of Ca influencing N concentrations saw reduced growth as N increased up to 5% (Figure

7.13), beyond the levels found in previous experiments. Variable concentrations of

Ca, reducing combined organ P concentrations saw reduced growth as P decreased from 8.00 to 4.00 g kg-1 (Figure 7.14). Phosphorous concentrations lower than 6.00 g kg-1 were related to a reduction in growth in Experiment 11. Reduced concentrations of P, as Ca supply concentration increased, could be a function of the high affinity Ca and P have for each other (Schwarz 1995) and may have formed precipitates in the supply solution. Calcium had influence over minor and trace elements, though Ca supply or concentration did not influence any of these to levels of deficiency or toxicity generally recognised for plants (Marschner 1995).

Apart from nutrient influences, Ca also has influence as a second messenger for enzyme activation. These results suggest re-evaluation for the major minerals need addressing at lower Ca supplies. Future trials involving Ca and lotus should focus on the relationships with N and K as 2nd or 3rd factors to resolve speculation over influence of levels or ratio between 2 nutrients. Three-factorial trials may be advantageous in soliciting the critical values as Ca critical concentrations are known to be variable with respect to other nutrient availability, especially K and Mg (Jones

1997). Definition of the lower critical value with less scatter in the results giving a greater correlation coefficient is essential. These results do not provide that outcome, though they do provide indicators for future work to pinpoint exact treatments to solicit the required outcome.

222

Chapter 8 General Discussion and Conclusions

8.1 Introduction

The objectives of this chapter were to bring together the information gleaned from the previous chapters to address the overall thesis aims. This includes a perspective comparison of each of the major nutrients trialled with respect to results found in trials where the nutrient was not under the scrutiny of treatment, analysis of the effectiveness of the research system and whether the central objectives of the thesis were satisfied, clarify future work to rectify or give greater definition to the current suite of available nutrient information, and improvement of the system. A list of conclusions was drawn from the reconciliation of information.

8.2 Effects of nutrients

8.2.1 Nitrogen

Variable concentrations of N in the supply were shown to have significant effects on growth (Figures 4.1-3) and organ N concentration (Figure 4.4a). Growth differences were also strongly related to the N concentration of organs (Figures 4.9-12). Uptake of N appears to be related to variable supplies of P (Figure 5.4b) and Ca (Figure

7.4b), concentrations of P in leaves (Figure 5.7), K in leaves and petioles (Figure

6.7a), K in leaves, roots and stolons (Figure 6.7a), and Ca in leaves (Figure 7.7). The strength of these relationships varies considerably between nutrients and organs, but also within a specific relationship. An example was the N concentration in leaves as a function of P supply and concentration. P supply only appeared to have been an influencing factor at supplies P5 and P100, the two treatment extremes (Figure 5.4b).

223

Phosphorous concentration in leaves appears to have only been influential at P concentrations beyond 6.00 g kg-1 P (Figure 5.8), where the trend occurred and the data points fit closer than P concentrations of less than 6.00 g kg-1. In general, the uptake of N in plants is driven by a physiological need (Mengel and Kirkby 1995) rather than ionic gradient. Therefore, the organ concentrations of P, K and Ca which have been associated with influencing N uptake in the results are assumed to be indirect. Speculation suggests that P, K, and Ca concentrations were a function of physiological processes.

The critical limits for deficiency and toxicity were not adequately defined for N and require further investigation. At the deficiency tail of the N concentration versus growth curve, the treatments were too far apart to capture the characteristic sharp decline from the 90% adequate region. At the toxic critical concentration, the treatments were not high enough to define an estimate for the maximum amount of N in tissues before a plateau was achieved, suggesting that higher supplies of N may have resulted in greater N concentrations in tissues.

The concentration of N found in all three organ tissues for Experiments 11-13 were within the limit values found in Experiment 10, except for the deficiency N concentration in relation to Ca concentration (Table 8.1). An explanation for the high N deficiency concentration as a function of Ca concentration in leaves, may be that the Ca175 to Ca350 rates of supply oppressed growth and N concentration (Table

7.4 & 8). The N concentrations drawn from Experiments 10-12 may be affected by the use of the Ca230 constant. This has implications over the absolute critical concentration values for N in organs as a function of the ratio of N:Ca, which should be investigated using a two-factorial experiment. The N concentrations in organs

224 from the constant treatments across all four nutrient trials were mostly similar, only

N concentrations in leaves in relation to P and Ca concentrations, and roots and stolons in relation to P and K concentrations, showed significant differences (Table

A8.1). Further, the constant treatment N275 was inside the estimated supply range, between 253 and 439 ppm N, calculated in Experiment 10. These arguments support the suggestion, that the extrapolated critical concentrations estimated for leaves and for roots and stolons have merit as indicators of the true critical concentrations for these organs. This corresponded to leaf N concentration limits of between 3.71 and 4.98% N, and root and stolon N concentration limits of between

2.45 and 3.47% N when using the relationships for N in organs as a function of LA.

The levels of N found in organs were similar to those reported for other species

(Reuter and Robinson 1997). Therefore, the critical concentrations of N for lotus are considered to be close to the absolute. These need to be confirmed through further experimentation.

Comparisons with the field sample tissue analysis data reported in Experiment 1

(Table 3.1), 2.2% N in leaves and 0.8% N in petioles, suggest the corresponding concentrations obtained in Experiments 10-13 are high (Table 8.1). However, N supply rates in pond solution for N were approximately 0.75 to 1.00 ppm N (Table

3.1) when sampled for the field-grown plants, compared to the N275 constant across

Experiments 10-13, approximately less than 1% of that available to the container- grown plants. Given that an estimated 200 to 400 kg ha-1 N (Table 3.1) was applied as fertiliser, it must be assumed that the applied N was taken up and distributed throughout the large plants or lost from the pond system due to nitrification processes. Consideration must be given to the age of the plants when sampling was undertaken for Experiment 1, the field-grown samples were taken approximately 100

225 days from planting, compared to 50 days for Experiment 10-13. It has been shown for several species of crop and ornamental plant that levels of certain nutrients, especially N, decrease in concentration with age (Reuter and Robinson 1997).

Another mitigating factor is the specificity of the sample from Experiment 1, only young fully opened leaves and petioles were taken, whereas for Experiments 10-13 the individual organs of an entire replicate were homogenised, without distinction between organ age and development, for nutrient composition analysis. This may explain the variation in N concentration displayed by individual replicates from the fitted curve, resulting in relatively low r2 values. Bates (1971) argues convincingly for the need to discriminate within organ type on the basis of age due to the mobility or immobility of different nutrients which may give differing concentration results due to treatment imposition. These results, subject to available resources for testing procedures, reinforce that argument through the variation reported.

The relative concentrations of N in each of the organs, were established convincingly. In all analyses, the concentration of N was highest in leaves then petioles followed by roots and stolons. In some trials no difference was found between the concentrations of N in leaves and petioles (Figures 4.6 & 6.7) or between petioles and roots and stolons (Figures 4.6, 5.7, 6.7 & 7.7), though the N concentration of leaves was always greater than that of roots and stolons.

Attention must be given to the NH4-N and NO3-N fractions which can be taken up by plants. Both moieties have been shown to be required by a number of plant species in differing quantities and proportions (Marschner 1995). Availability of type of N in the media is dependent upon the presence and response of N-cycle bacteria to the prevailing soil oxygen concentration (Harris 1988). Low O2 tension promotes the

226

activity of denitrifying facultative-bacteria which in the absence of O2, substitute negatively charged NO3-N as a final electron accepter (Tortora et al. 1992).

Effectively converting the solution mobile NO3-N to N2 and N2O gases, which escape into the atmosphere (McKenzie et al. 2004). Positively charged NH4-N frequently binds with the negative surface of clay particles, immobilising the cation from the soil solution (Harris 1988). Under anaerobic conditions, the bacteria responsible for the nitrification of NH4-N to NO3-N have a reduced capacity to operate (Ibekwe et al. 2003, Kantawanichkul and Somprasert 2005). Therefore, in a pond environment the concentration of NH4-N compared to NO3-N would be expected to be higher.

Secondary influences on initial N uptake are pH, root temperature, plant NH4-N concentration and the carbohydrate status of the plant (Mengel and Kirkby 2001).

Nitrate-N after uptake has considerable mobility in the plant compared to NH4-N, which is absorbed into the roots and utilised in the construction of carbon skeletons

(Marschner 1995). Ammonium-N is favoured by plants when conditions such as low root temperature, neutral pH, and high carbohydrate concentration occur.

Conversely, if root temperatures rise, pH decreases or carbohydrate concentration is low stimulating a shift in the stoichiometry, then NO3-N uptake increases (Mengel and Kirkby 2001).

Consideration of the N fraction status is especially important for a species such as lotus. Lotus occupies an anaerobic environmental niche and has high carbohydrate concentration. It could be speculated that lotus has adapted to higher NH4-N supply and therefore, requires a lower ratio of NH4-N to NO3-N. Preliminary evidence could be drawn from Experiment 10, where the plant growth reaction was

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consistently highest for the N400 treatment. Treatments N325 to N400 were supplemented with NH4-N (Table A1.6) to satisfy the N treatment requirements and produced the highest amount of total dry mass (Figure 4.1a-b). These maxima were recorded after a non-significant depression in total dry mass from N225 to N275, treatments without NH4-N. This suggests that the ratio of N type is as equally important to plant growth and development as total N supplied. Therefore, in order to evaluate this, a two-factorial experiment comprising NH4-N and NO3-N as factors would be necessary to determine the optimum supply concentrations, ratios and rates under controlled conditions.

8.2.2 Phosphorous

The sensitivity of lotus to P supply was much more narrow than for the other major nutrients and was reflected by the limitation to growth and organ concentrations of P.

This was consistent with the limited amounts of P available to plants in general from soils (Moody and Bolland 1997). Variable supply rates of P (Figure 5.4a), N

(Figure 4.4b), and Ca (Figure 7.5a) were shown to be related to P uptake. Similarly, concentrations of N in all organs (Figure 4.7), K in leaves and petioles and roots and stolons (Figure 6.7b), and Ca concentrations in combined organs (Figure 7.8a), were shown to be related to P concentrations in organs. The level of uptake for P due to supply was not exhausted and did not reach a plateau (Figure 5.6). Therefore, the maximum amount of P which lotus can tolerate in its tissues has not been resolved and requires further investigation.

The critical limits for P concentration in organs were consistently defined by a number of different growth attributes with similar trends and critical values (Table

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5.4). Individually, the curves from which the critical concentration values were determined had a similar degree of replicate scatter to those obtained in Experiment

10, reducing the value of the coefficient of determination. The adequate supply range for P was able to be calculated using corresponding critical concentrations determined for organs at between; 20 to 56 ppm P for leaves, 21 to 55 ppm P for petioles, and 40 to 50 ppm P for roots and stolons. The expectation of extrapolated adequate supply limits, is that differing critical concentrations between organs for the same nutrient resolve into adequate supply rates which are equivalent. These extrapolated adequate supply rates conform to this hypothesis. Adequate supply rates for leaves and petioles were equal, and the supply rate calculated for roots and stolons was within the supply rates for leaves and for petioles. Further, the constant treatment in non-P trials conforms to this range at 45 ppm of P, thus the level of P supply employed was considered acceptable and appropriate.

From Experiment 1, comparisons with pond-grown plants of the P concentrations found in leaves (2.03 g kg-1) and petioles (0.80 g kg-1) (Table 3.1) with those found in Experiment 11, leaves (3.93 to 6.07 g kg-1), petioles (3.66 to 7.21 g kg-1), and roots and stolons (3.67 g kg-1), suggest the concentrations from Experiment 11 and similar results from Experiments 10, 12 and 13 are disproportionately high (Table 8.1).

However, supply rates for P were approximately 20 to 25 ppm in pond solution for the field-grown plants compared to the P45 constant across Experiments 10 to 13, approximately 50 % of that available to the container-grown plants. Application rates of approximately 40 to 200 kg ha-1 to pond soil do not reflect in the available P supply, suggesting P may have bound to soil particles or precipitated with other molecules. However, the values of P found for the critical limits and range, were consistent with other species (Reuter and Robinson 1997). Therefore, the values

229 determined in Experiment 11 were considered moderately accurate, pending confirmation with rigorous evaluation involving further experimentation. A wider range of treatments, longer durations of experimentation, and calibration with field- grown plants is necessary.

The distribution of P in organs was consistent through Experiments 10-13, except for low supply rates of P in Experiment 11. Generally, P accumulated in the highest quantities in roots and stolons, then petioles, followed by leaves. The exception saw leaves containing the highest P concentration at low P supply levels (Figure 5.4a).

This may be due to a minimum requirement of P for leaves to function. The concentrations of P in organs were also consistently similar across non-P treatments.

The variations in P concentration tended to occur at extremes of other nutrient treatments. The concentration of P in plants, is known to be much greater than in supply (Marschner 1985) and the sensitivity of the range displayed by the critical values, suggest P in lotus is highly regulated.

8.2.3 Potassium

The response of lotus to K was dramatic. Growth was shown to be severely restricted by high K supplies and organ concentrations. Organ concentrations of K were saturated at low treatment supplies of K300 achieving a plateau well before the nominated constant treatment of K350 used in the non-K trials (Figure 6.4). The corresponding fitted relationships for organ K as a function of K supply (Figure 6.6), only reach a plateau for roots and stolons, effectively eliminating the ability to extrapolate toxic critical concentration estimates from growth responses. Therefore, the values of any estimates may be improved in future through trials with K supply

230

rates centralised around the K225 treatment, which provided the maximum growth response in Experiment 12.

The coarse range of treatments in Experiment 12, around the critical regions, resulted in the restricted ability to accurately define critical values. The region of adequate supply of K has been identified at approximately 225 ppm of K, this suggestion requires validation through further experimentation with a narrowly defined treatment focus. The actual concentration of K in organs, relative to each other, was consistent for all four single nutrient trials. Petioles had the highest concentration of

K, followed by roots and stolons, then leaves.

Comparisons with the analyses for Experiment 1 (Table 3.1), where K levels were

11.63 g kg-1 for leaves and 18.94 g kg-1 for petioles, suggested Experiments 10-13 provided high results. The arguments outlined previously for N for the possible explanations for the variation, also have relevance to K. However, comparison of the

Experiment 1 values with those of treatment K225 show that the mean concentration

-1 -1 of K in leaves at 26.50 g kg and the mean for petioles from K225 at 49.00 g kg was far higher than the corresponding values of Experiment 1. Comparisons with leaves of other species such as potato and sweetpotato (Reuter and Robinson (1997) reveal these K concentrations to be within the range of values reported for other crops.

Compared to values reported for Chinese waterchestnuts at 20.60 g kg-1 (Kleinhenz et al. 2000), and sweetpotato at 26.00 g kg-1 of K in leaves (O’Sullivan et al. 1997), the values found in these experiments are marginally high. However, O’Sullivan

(1997) qualifies her critical value with the presence of Na being a regulatory factor.

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The field analysis results from Experiment 1 confirm that the K350 supply constant is high, and the appropriate supply rate should be around 225 ppm of K. However, supply concentrations for K were approximately 15 to 24 ppm in pond solution for the field-grown plants compared to the K350 constant across Experiments 10 to 13, approximately 6 to 11 % of that available to the container-grown plants. Application rates of K were approximately 250 to 500 kg ha-1, suggesting a large amount had been taken up by plants or bound to exchangeable cation sites on soil surfaces. It is possible that petioles act as a regulating storage sink for K during vegetative growth.

Support for this argument, are the results of K in petioles from Experiment 10. It appears a relationship exists between N concentration and K concentration in petioles, as N increases beyond 2.8%, K concentrations decrease (Figure 4.8a).

When K concentrations in petioles decrease, total dry mass and the number of stolons increase (Figure 4.15). Developmental processes such as flowering or rhizome initiation, are known to increase the requirements for K in plants (Marschner

1995) and may trigger the release and transfer of mobile K from petioles. This speculation requires confirmation through rigorous experimentation.

The expression of symptoms of disorder superficially resembling K deficiency in older leaves of plants from Experiments 8-13, was not alleviated at high K supplies.

Further, the high K supplies were shown to have a negative influence on growth.

Therefore, if a K imbalance was responsible for the expression of these symptoms, it had to be due to the influence of interacting nutrients. The K50 treatments for K supply were not low enough to produce K symptoms of deficiency.

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8.2.4 Calcium

Concentration of Ca in all organs drew a growth response for a number of different growth parameters (Figures 7.9-11). Increasing Ca concentration in leaves was related to significant increases in all measures of growth, before decreasing with further Ca increase. The fitted curves were able to be used to generate critical concentrations and subsequent corresponding adequate supply range. However, the scatter of individual data was large, reflected in low r2 values. Petioles and roots and stolons had fewer useable fitted curves with which to make critical concentration estimates. All organs showed similar scatter of data.

Similar to K, the levels of Ca employed as treatments in Experiment 13 and as the constant rate Ca230 in Experiments 10, 11, and 12, were too high (Tables A1.6-9).

Variable supplies of Ca significantly affected the Ca concentrations in all organs

(Figure 7.4a). Variable supplies of Ca negatively affected N and P concentrations in organs and positively affected K concentration in roots and stolons (Figures 7.6-8).

Similarly, variable supplies of N (Figure 4.5b), P (Figure 5.5b) and K (Figure 6.5b) affected Ca concentration in leaves, while K supply also affected Ca concentration in roots and stolons (Figure 6.5b). Concentrations of N in leaves (Figure 4.8b), P

(Figure 5.8b) in combined leaves and petioles and K (Figure 6.8) in roots and stolons had significant effects on Ca concentration. These interactions strongly suggest Ca concentrations in organs are a function of both availability of Ca and the influence of other ions in plant tissues. The relationship between leaf N and Ca concentrations appears to be strongly related to growth. As Ca concentration in leaves increases, N concentration decreases (Figures 7.4b & 7). Similarly, as Ca concentrations in leaves increase beyond the level corresponding to maximum LA, the LA decreases (Figure

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7.11). It could be speculated from the evidence of the results from Experiments 10-

13, that once the lower critical concentration for a nutrient is satisfied, the concentration ratio with other nutrients becomes the limiting factor to growth.

The critical concentrations for Ca were able to be estimated, from results gathered in

Experiment 13, but not absolutely defined. Growth response curves (Figures 7.9-11) as a function of Ca concentration provided a number of opportunities to estimate the critical concentrations (Table 7.4). These curves whilst highly significant, have a wide spread of data and hence low r2 values, similar to the other experiments.

Critical concentrations of approximately 9.97 to 19.30 g kg-1 for leaves, 7.60 to 11.45 g kg-1 for petioles and 6.57 to 9.20 g kg-1 for roots and stolons extrapolated to adequate supply ranges of 82 to 194 ppm Ca, 104 to 261 ppm Ca, and 61 to 194 ppm

Ca, respectively. Since 261 ppm Ca was outside the optimum for growth, and petioles were found to be of similar concentration to roots and stolons (Figure 7.6), the values for petioles were disregarded. The initial Ca treatment of Ca50 had the lowest growth response of all treatments, therefore, the 61 ppm supply calculated for roots and stolons data appears too low. Hence the adequate supply range for Ca was accepted as 82 to 194 ppm of Ca.

Concentrations of Ca in organs were consistently higher in leaves than other organs for all experiments. The concentration of Ca in petioles and roots and stolons in all trials, was similar. This result further validates the claim that excess Ca was being sequestered into leaf marginal tissues, the most distant tissues on the plant from the growing meristem tissues located at the ends of stolons where uptake of other ions may have been hindered by charge imbalance due to excess Ca ions.

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Comparisons of these values with those found from field analysis of laminas and petioles from the youngest fully expanded leaves again suggest the experimental values obtained are high. Field-grown plants were found to contain 2.23 g kg-1 Ca in young leaves, compared to a deficient critical concentration of 9.97 g kg-1 Ca for homogenised leaves from container-grown plants. Petioles had the same magnitude of difference for Ca concentration. However, supply rates for Ca were approximately 25 to 35 ppm in pond solution for the field-grown plants compared to the Ca230 constant across Experiments 10 to 13, approximately 10% of that available to container-grown plants. Application rates for Ca were approximately 100 to 150 kg ha-1, indicating an unknown amount of applied Ca was bound to soil particles or negatively charged ions and forming insoluble precipitates.

The loading of excess Ca in container-grown plants into older leaves may have raised the Ca concentration values for healthy leaves. Comparisons with other root crop species suggest the levels of Ca in lotus organs are high (O’Sullivan et al. 1997,

Kleinhenz et al. 2000). Therefore, verification of these results requires further experimental work with a narrower set of treatments, and greater scrutiny of analysis of organs with differing ages and developmental stages, based on the results obtained from this study.

Expression of symptoms, attributable to Ca at deficiency were not found, due to the treatments used in Experiment 13. Treatments with rates of supply well below the optimal growth treatment of Ca100 should be included in future experimentation to cause the expression of deficiency symptoms. At the toxic level, it appears Ca either superficially resembles a K deficiency or suppresses K from tissues in older leaves.

The concentrations of K found in leaves (Figure 7.8b) do not support the second

235 hypothesis. Therefore, it was assumed that excess Ca loaded into older leaves simply provided an imbalance of cationic charge.

8.2.5 Other Nutrients

Lotus appears to be very sensitive to imbalances of nutrients caused by supply and uptake. The number of times a particular nutrient was affected by the treatments from Experiments 10-13 is shown in Table 8.4. The greatest variations were recorded for Mn, Mo, Zn and Al followed by Mg, S, Fe, B, and Na. The least number of non-treatment variations was observed in the major nutrients in the order of P, N, K, and Ca as well as Cu. The anaerobic environment, soil properties, applied nutrients and pH may have been the influencing factors on pond solution nutrient availability. Iron and Mn concentrations were very high in pond solutions at 400 to 450 ppm Fe and 80 to 200 ppm Mn, without application (Table 3.1), compared to 10 ppm and 0.1 ppm for container solutions (Table A1.5). Exchange of positively charged Fe and Mn from cation exchange sites with applied cations in fertiliser may the explanation for the large discrepancy.

The evaluation of the minor and trace elements requires attention due to the absence of information on growth response, and the great variation of concentration found in organs as a result of varying the supply of major nutrients. The critical concentrations and adequate supply rates require identification, however, estimates of minor and trace nutrients can be drawn from Experiments 10-13 and used for working values in supply planning and field testing of tissues.

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8.2.6 Critical Concentrations and Adequate Supply Rates.

The critical concentrations drawn directly from limited growth due to nutrient concentration and the subsequent extrapolated adequate supply rates from

Experiments 11-13 are presented (Tables 8.1-2). Estimated extrapolated critical concentrations where a nutrient expressed a significantly different range of values, and actual concentrations of nutrients extrapolated from relationships where no range was recorded, are also presented. Experiment 12 yielded no reliable fitted-curve to represent the relationship between K nutrient concentration and growth, hence, no adequate supply rate could be extrapolated from which calculated estimates of critical concentrations in other organs could be obtained. Therefore, concentrations of K were estimated from the extrapolations drawn for K in experiments 10-11 & 13.

The critical concentration values for organs, the estimated critical concentrations, and actual concentrations in organs found at extrapolated adequate supply rates were not uniformly within organs. Most values found or calculated were outside the S.E. of a difference values surrounding any particular concentration mean (Table 8.1).

Moreover, the values were not within a nominated ± 5 % tolerance of each other, confirming variation amongst derived concentration limits (Table 8.1). The adoption of any values representing lotus critical concentration limits for nutrients within an organ should be drawn from the relationships between the subject nutrient and the dry mass yield, LA or total stolon length growth response to a range of supply treatments. However, the actual concentration values give estimates of the possible limits and levels of concentrations found in organs, the ratio of major nutrients in organs relative to other major nutrients, and the ratio of individual nutrients between organs.

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Table 8.1 Critical concentrations and actual concentration of major nutrients in organs of lotus (Nelumbo nucifera) derived from extrapolated calculations. (Figures 4.6-8 & 11, 5.6-12, 6.6-8 & 7.6-11; Tables A4.58-60, A5.4, 58-60, 6.58-60 & 7.4-59- 61).

Trial/ N P K Ca Organ (%) (mg kg-1) (mg kg-1) (mg kg-1) Def Tox Def Tox Def Tox Def Tox N-Leaf 3.71# 4.98# 6 890# 5 090# 29 320# 33 340# 22 860# 17 880# P-Leaf 3.57# 3.68# 3 930* 6 075* 27 120^ 27 290^ 21 780# 22 240# K-Leaf NC NC NC NC NC NC NC NC Ca-Leaf 4.28# 3.99# 6 490# 5 800# 27 380^ 26 350^ 9 970* 19 310* Mean 3.85 4.22 5 770 5 655 27 940 28 993 18 203 19 810 S.E. 0.22 0.39 927 293 694 2 190 4 128 1 283 N-Petiole 2.66* 4.39* 6 990# 9 170# 60 080# 48 500# 19 920^ 22 130^ P-Petiole 2.50^ 2.40^ 3 660* 7 200* 53 010^ 55 150^ 11 790^ 11 650^ K-Petiole NC NC NC NC NC NC NC NC Ca-Petiole 2.40^ 1.97^ 7 910# 6 950# 57 300^ 58 580^ 7 620* 11 450* Mean 2.52 2.92 6 186 7 773 56 796 54 076 13 076 15 076 S.E. 0.08 0.75 1 290 702 2 056 2 958 3 636 3 527 N-Roots & 2.45# 3.47# 8 920# 11 020# 43 170# 38 770# 18 830^ 22 640^ Stolons P-Roots & 2.12^ 2.17^ 6 670* 7 879* 43 110^ 43 870^ 9 880^ 10 090^ Stolons K-Roots & NC NC NC NC NC NC NC NC Stolons Ca-Roots 2.37^ 2.17^ 8 560# 8 410# 38 840# 41 970# 6 570* 9 200* & Stolons Mean 2.31 2.60 8 050 9 103 41 706 41 536 11 760 13 976 S.E. 0.10 0.43 697 970 1 433 1 488 3 661 4 339 NC – Not calculated due to lack of growth; Def – deficiency zone below; Tox – toxicity zone above. * Original critical conc. based on growth and nutrient relationship; # – critical concentration calculated from expressed range. ^ – actual concentration at estimated adequate supply.

The concentrations found were similar to nutrient concentrations reported for other crop species with morphological features similar to lotus (Reuter and Robinson

1997). It would be expected that some variation occurs when the concentrations are derived on changing individual nutrient treatments where each individual nutrient has different interactions and concentration balance requirements. Supporting this argument was the interaction between N and Ca.

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The concentration of each major nutrient was similar in all experiments and were similar to those reported for other species. Exceptions were the critical concentrations drawn from direct growth relationships for P and Ca in leaves and Ca in roots and stolons (Table 8.1). These critical concentrations were approximately 50

% of the concentrations derived from extrapolation. Similarly, the values presented for concentrations satisfied the expected ratio of particular nutrients between organs.

The exception was the unusually high levels of Ca in organs, the result of inappropriately high Ca supplies. The large difference between some growth-based critical concentrations and derived concentrations based on extrapolations, recorded for P and Ca in leaves and Ca in roots and stolons, reinforce the requirement to adopt critical concentrations from direct nutrient growth relationships.

Table 8.2 Adequate supply rates for major nutrients, extrapolated from organs with critical concentrations established from the relationships between organ nutrient content and growth parameter (all units ppm). (Table 8.1).

Nutrient N P K Ca

Organ Def Tox Def Tox Def Tox Def Tox Leaves NC NC 20 55 NC NC 80 195 Petioles 255 440 20 55 NC NC 105 260 Roots & NC NC 40 50 NC NC 60 200 Stolons NC – Not calculated due to lack of growth; Def – deficiency zone below; Tox – toxicity zone above.

Adequate supply rates could be determined from growth-based critical concentrations in all organs for P and Ca, and for N in petioles (Table 8.2).

Adequate K supply rates were not able to be determined. The expectation that extrapolated adequate supply rates should be equivalent for all organs was satisfied for corresponding P concentrations (Table 8.2). The adequate supply rates

239 determined for the Ca critical concentrations in organs were not equivalent and three separate supply rates were found (Table 8.2). When the individual adequate Ca supply rates for an organ are substituted into the relationship equations for the other two organs, a wide range of values is produced (Table 8.3). This was undesirable as the calculated estimates should be equivalent within an organ.

The definition of critical concentration limits and adequate supply rates for lotus are also dependent upon a satisfactory calibration of container-grown plants with field- grown plants. The establishment of values for plants, which have relevance beyond the context in which they were grown is crucial, otherwise those values become artefactual.

Table 8.3 Evaluation of the calculated critical concentrations for calcium found for organs, when adequate supply rates are substituted within the relationships for the relevant two organs. (Tables 8.2, A7.A58-60).

Organ Substituted Substituted Ca Ca Ca Supply Organ Supply Rates Lower C.C. Upper C.C. (ppm) (mg kg-1) (mg kg-1) Leaf Leaf 85 & 195* 9 970 19 310 Leaf Petiole 105 & 260 12 165 22 600 Leaf Roots & Stolons 60 & 200 7 680 19 730 Petiole Leaf 85 & 195 6 890 10 020 Petiole Petiole 105 & 260* 7 620 11 450 Petiole Roots & Stolons 60 & 200 6 090 10 180 Roots & Stolons Leaf 85 & 195 7 200 9 210 Roots & Stolons Petiole 105 & 260 7 730 9 960 Roots & Stolons Roots & Stolons 60 & 200* 6 570 9 200 * Original calculated supply rates and critical concentrations in italics.

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8.2.7 Organ for Field Testing

At this stage of lotus nutrition evaluation, the best organ for field testing appears to be leaf lamina. This is based upon the number of occurrences in which significantly different levels of nutrients could be found for all the elements tested in Experiments

10-13 (Table 8.4). Leaf laminas had the greatest number of nutrient range expressions due to supply and concentration, followed by roots and stolons then petioles. The degree of difficulty in sampling roots and stolons in a crop situation would also limit the use of these organs for routine sampling.

The need to differentiate the concentrations of nutrients in organs across a developmental spectrum remains. Such sample discrimination would be best performed in conjunction with trials which seek to define more accurately the critical limits and adequate supply range.

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Table 8.4 Number of occurrences of significant nutrient ranges in organs of lotus (Nelumbo nucifera). (Tables A4.58-99, A5.58-99, A4.58-99 A7.58-99).

Leaves Petioles Roots & Total Rank Stolons

Nutrient Supply Conc. Supply Conc. Supply Conc.

N 2 1 2 1 2 1 9 (6) 6

P 2 1 2 1 3 1 10 (7) 5

K 1 1 2 1 3 1 9 (6) 6

Ca 3 0 1 0 3 0 7 (4) 13

Mg 2 1 0 1 1 3 8 9

S 2 1 1 0 1 3 8 9

Fe 4 2 0 1 0 1 8 9

Mn 4 2 3 2 3 2 16 1

Zn 4 1 3 1 2 1 12 4

Cu 3 1 1 1 1 0 7 13

B 3 0 0 1 2 3 9 6

Mo 2 1 3 1 4 4 15 2

Na 0 1 2 1 1 3 8 9

Al 3 3 1 2 2 3 14 3

Total 35 16 21 14 28 26 140

Numbers in parenthesis represent non-treatment differences.

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8.2.8 Nutrient Concentration in Plants, Biomass-Partitioning and Uptake for the Most Effective Treatment.

Estimations of the concentration of nutrients in plants, the biomass partitioning and uptake ratio are best calculated from a set of values that has direct relevance to each other. The construction of such values from the best of all the treatments combined would give a relatively inaccurate indication, due to the influencing nature of nutrients on each other. Therefore, Ca100 which was the treatment that resulted in plants with the highest dry mass accumulation and greatest LA, was used for the estimation of biomass partitioning and calculation of an uptake ratio for the first 50 days of vegetative growth. It should be noted, the limitation of the value of such an exercise is really only relevant to container based plants. A summary of the concentration of nutrients found in organs of lotus from treatment Ca100 in

Experiment 13 is presented in Table 8.5. From these values and the dry mass of each organ, an indication of the amount of each nutrient required per hectare can be calculated (Table 8.6). From the total biomass for the major elements (NPK) 107:

28: 155 kg ha-1 or an uptake ratio of approximately 1: 0.25: 1.45 is calculated. This ratio is applicable to plants grown in soilless culture under protected semi-controlled environmental conditions. Extrapolation to a commercial situation should account for the influences of climate, soil nutrient components, and stage of growth of crop.

The results obtained provide limited estimates with which lotus growers and agronomic advisors can work, and provide a good basis upon which greater clarity of critical limits can be established. The type of organ for field testing for nutrient concentrations has been adequately satisfied, although an obvious need to discriminate between organs at different physiological developmental stages remains.

Therefore, the argument for further investigation into the role of the major nutrients

243 in lotus nutrition is strengthened by the need to resolve between anomalies reported in this thesis.

Table 8.5 Nutrient concentration in dry plant parts for the vegetative stage of growth of lotus (Nelumbo nucifera). (source of values Experiment 13, Ca100).

Parameter Unit Leaf Petiole Roots & Stolons

N % 4.04 2.18 2.26

P g kg-1 6.22 7.38 8.46

K g kg-1 26.00 56.60 41.60

Ca g kg-1 10.46 7.22 7.06

Mg g kg-1 6.92 4.00 3.98

S g kg-1 4.02 3.86 5.70

Fe mg kg-1 292.00 221.00 590.00

Mn mg kg-1 46.34 24.27 20.86

Zn mg kg-1 42.10 35.39 82.70

Cu mg kg-1 14.20 15.14 31.97

B mg kg-1 38.09 24.27 22.72

Mo mg kg-1 1.13 1.26 4.43

Na g kg-1 2.27 4.66 4.34

Al mg kg-1 54.86 57.01 155.38

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Table 8.6 Extrapolated biomass partitioning of lotus (Nelumbo nucifera) per hectare (source of values: Experiment 13 Ca100).

Parameter Unit Leaf Petiole Roots & Total Stolons

Dry Biomass Tonnes ha-1 1.24 1.07 1.50 3.82

N kg ha-1 50.01 23.33 33.90 107.24

P kg ha-1 7.71 7.89 12.69 28.30

K kg ha-1 32.24 60.56 62.4 155.20

Ca kg ha-1 12.97 7.73 10.59 31.29

Mg kg ha-1 8.58 4.28 5.97 18.83

S kg ha-1 4.98 4.13 5.97 15.08

Fe kg ha-1 0.36 0.24 0.89 1.48

Mn g ha-1 57.00 26.00 31.00 11.00

Zn g ha-1 52.00 38.00 120.00 210.00

Cu g ha-1 18.00 16.00 48.00 82.00

B g ha-1 47.00 26.00 34.00 110.00

Mo g ha-1 1.40 1.30 6.60 9.40

Na kg ha-1 2.81 4.99 6.51 14.31

Al g ha-1 68.00 61.00 230.00 360.00

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8.3 Analysis of the Effectiveness of the Research

The effectiveness of the research system can be measured by the ability of the system to achieve the desired objectives. The aims of the research platform were to produce consistent, significantly different growth and tissue concentration results.

Additionally, from the data generated, the critical concentrations and the adequate supply ranges were to be calculated for N, P, K and Ca. Further, resolution of problems should be addressed with certainty. The expression of disorder symptoms were to be drawn from the imposed treatments. Finally, a clear indication of the direction of research beyond the objectives outlined for this project should be able to be clarified.

The system that was developed allowed for consistency to be established across the four single nutrient trials. Analysis of the constant treatments for Experiments 10 to

13 show very few differences except for N in leaves (P trial is different to Ca trial)

(Table A8.1), N in roots and stolons (K trial is different to P trial) (Table A8.3), Ca in leaves and petioles (K trial is different to Ca trial) (Tables A8.10-11), Ca in roots and stolons (K trial is different to P trial) (Table A8.12). All other constant treatments resulted in similar nutrient concentrations (Tables A8.2, 4 & 9). The production of dry mass as a function of dimensional change compared to the production of organ numbers (Figures 4.13, 5.13, 6.11 & 7.12, Tables 4.4 & 5.5) also demonstrated an expected response of plants. In Experiments 11 and 13, where critical concentrations were established as a direct function of the relationships between nutrient concentration and growth for all three organs, calculated adequate supply rate matched only the P trial of Experiment 11 (Table 8.2). The calculated

246 adequate supply rates based on Ca trial critical concentrations from Experiment 13 overlapped in range, but the limits did not match (Table 8.2). Further, when the Ca adequate supply calculated for each individual organ was substituted by the adequate supply rates of the other two organs, the critical concentrations extrapolated have a wide variation (Table 8.3). Therefore, from a consistency perspective, the system was moderately successful.

The research system could be successfully used to challenge lotus with a variety of nutrient treatments and partially resolve the objective of determining nutrient parameters. Adequate nutrient supply rates and organ critical concentrations were not sharply defined, but were able to be estimated for use in field interpretation and as a basis for further investigation. The calculated values compare favourably with other species and no unusual values were recorded. The comparison in nutrient concentrations between plant material analysed from a commercial situation and container-grown plants, was not equitable. Discrepancies between field and container grown plants existed and could sufficiently account for nutrient concentration differences. These included the 50 day difference in age of organ for sampling, large variation in solution volume between field and container (larger solutions have a greater buffering capacity to EC and pH changes as nutrient is removed), and low solution strength of the field-grown plants. Therefore, the relevance of the system results were accepted as pertinent.

Symptoms of nutrient disorders were not present during experimentation, though this was not a function of the production system but rather a product of experimental design. The method employed for the nutrient trials was conducive to soliciting growth and tissue nutrient concentration differences but not the display of symptoms

247 for lotus. This argument was supported by Asher and Edwards (1983) who maintain that research designs should serve either objective, but not both. The expression of a marginal chlorosis/necrosis observed on older leaves was resolved as a function of excessive Ca. Thus, a research question which presented itself, was able to be solved satisfactorily and a viable explanation could be offered for the relative absence of desired symptoms of disorder expected from the treatment imposition.

The number of research questions that require solving was much greater than a project of this scope and size could possibly address. The information available prior to this investigation was scant and large gaps remain in our knowledge of lotus nutrition. Great potential remains for completing a plethora of plant-related inquiries and system adaptations. Improvements to the system are possible and mandatory.

No system should remain static. It should be improved with the advances in technology available to the researcher. This system was deliberately confined to a manual operation to satisfy the basic requirements of growth and subsequent information generation before the commitment of expensive automation equipment.

These two themes are discussed in greater detail in section 8.4.

8.3.1 Significance of the Research and Results

The research results reported in this thesis have increased the available knowledge on lotus cultivation in several respects. It was established that plant cuttings of seedling material could be successfully transplanted. The optimal EC and pH values were suggested, pending greater clarification of nutrient supply requirements which may influence EC and pH values. The mostly consistent concentrations of nutrients in

248 organs and the corresponding supply estimates allow for the design of future experiments which will accurately define critical nutrient limits. An appropriate organ for field sampling was identified as the leaf lamina. Growers of lotus cannot yet confidently sample leaves and precisely base their nutrient applications on the interpretation of the sample analysis with reference to the organ nutrient content found in these experiments. The nutrient concentrations found in these experiments can be used in conjunction with field samples for nutrient application estimates, provided the operator takes into consideration the differences between field and container-grown plants reported here. The calibration of adequate nutrient supply rates and critical limits between pot-trials and plants cultivated in ponds was not achieved with these preliminary investigations. This could largely be attributable to the enormous discrepancies between pond and container nutrient supplies and the age and developmental stages of the plants sampled. This objective requires urgent attention and design of experiments to address this issue will be enhanced by the results reported for the container trials. Field samples of all stages of plant development should also be taken from plants grown in a planned nutrition program for greater accuracy of organ nutrient concentrations.

From a research perspective, these results allow for a greater number of questions over lotus nutrition and physiology to be addressed from a referenced and logical position. Arguments outlining the research possibilities for lotus are discussed in greater detail in Section 8.4 and for system improvements in Section 8.5. The techniques and outcomes of these experiments demonstrate that conventions can be challenged, modified, and adapted to different situations and requirements. As a template for research into the nutrition of water plants, these methods can be adapted to other water plant species for which the information is unavailable.

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8.4 Further Lotus Investigations

The need to document the expression of nutrient disorder symptoms may be exclusive to the requirement of trials to express critical concentrations in organs.

Asher and Edwards (1983) recommend different approaches to trial design for the purpose of illustrating these dissimilar outcomes. The sensitivity of lotus to nutrient imbalance may first be seen in growth rather than as signs of disorder, as the results from these experiments suggest, except for Ca excess. These results suggest treatments outside the ranges tested for are required to solicit disorder symptoms. It would be recommended that plants grown in adequately supplied nutrient solutions be transferred to solutions with the absence of the particular nutrient desired for expression. Plant parts expressing different degrees of disorder can be described and analysed for nutrient concentration.

Absolute critical concentrations using impartial methods of calculation such as the

Mitscherlich (Ware et al. 1982) or Smith-Dolby (Smith and Dolby 1977) techniques should be compared and calibrated to the critical concentrations determined with direct growth effects. The nuances of environmental niche influences may skew the growth rate and hence alter the outcome of the critical concentrations determined from analysis with direct growth. To do these impartial analyses, trials must be designed to accommodate treatments around a particular critical concentration, usually deficiency. The trials in this study could not accommodate the use of impartial techniques due to the spread of treatments over a range designed to capture both critical concentrations. These results do provide an excellent reference for treatment supply concentrations clustered around the estimated critical concentrations found in this study. Investigations into the major nutrient designed

250 with impartial calculation of critical concentration should be the next logistical step, followed by two-factorial trials analysing the ratio or balance of nutrients, especially

N with K or Ca.

A full understanding of lotus nutrition would not be complete until the minor and trace elements have undergone treatment imposition and analysis of those challenges.

The results for minor and trace elements found from these investigations could be adequately used for designing treatment range. Trials could be single or multi- factorial, depending upon the perceived importance of the nutrient(s) under question and available resources. For example, based upon the sensitivity displayed in tissues for the uptake of Mo and Mn, single trials with a greater number of treatments may be advantageous. Conversely, low responses from nutrients like Mg and Fe suggest that two-factorial trials with a lower treatment range for both elements may be suitable.

The uptake and distribution of Na and heavy metal contaminants not required for growth should also be assessed. Knowledge of the degree to which lotus is tolerant to salinity could be an advantage if Na replaces K for some functions and lotus is able to be grown in water with high Na concentrations. Similarly, water plants have been suggested as vehicles for the removal of contaminants of water resources; information regarding the uptake capacity for these elements may be beneficial to waste water management. The use of lotus in such applications could not be recommended for food products, though flowers and overall biomass production, providing a secondary function to the process is a strong argument worthy of consideration.

251

The trials in this project concentrated on early vegetative growth of one variety of lotus; the suite of over 200 known varieties may have particular nutrient requirements. Additionally, the influence of nutrient concentration, balance and timing of application at other developmental stages such as flowering and rhizome development are crucial for the full picture of lotus nutrition to be realised. This is especially important in the N and K ratio. Nitrogen has been reported to suppress flowering in tomatoes (Kinet and Peet 1997) and affect development of overwintering organs such as tubers in potato (Ewing 1997). A higher requirement for K supply during the formation of overwintering organs has been reported

(Marschner 1995). Therefore, the balance of nutrients rather than the overall concentration supplied may prove to be more important to the overall development of the crop.

Given the nature of the environment and plant form, the timing of applications of nutrients in a commercial operation is a large logistical challenge and an engineering conundrum. Trials to evaluate nutrition effects on the flowering and rhizome stages need to accommodate a much larger plant than the system utilised in this project. An overhaul of the system requirements would need to be performed for the delivery of these outcomes. These results provide solid indicators with which to design and implement such a system.

Solution culture environments have much higher ECs than soil culture environments, due to the soil reservoir binding nutrient (Asher and Edwards 1983). The soil reservoir may require nutrient application adjustment according to soil type as different soils bind different nutrients and at differing concentrations. Transferral of the results generated in solution cultures need to be shown to be possible through comparison with soil trials where supplied nutrients are in a similar proportion to

252 those found in solution culture. Analysis of tissues from such trials could then be directly compared or calibrated to solution test situations. Adaptation of the system to a recirculating solution with a much larger external reservoir as proposed by Asher and Edwards (1983), may overcome the large discrepancies of EC and nutrient supply loading through continual exposure to fresh supply of lower concentrated nutrients. This would effectively supply the same amount of nutrients to all treatment replicates, whilst exposing the plant to a lower EC gradient. A system operating in this approach would be closer to mimicking a soil environment.

Interaction of in situ applications in soil environments on larger scales for all nutrients, lotus varieties, climate niches and all stages of organ development define the final phases of the process started with the trials in this project. The scale of such an endeavour is beyond a single operator and would require large inputs of resources, time and industry cooperation. With the industry in its infancy and supplying the relatively small domestic market with import replacements, the prospect of resource funding for lotus research remains narrow, however the potential remains.

8.5 Potential System Improvements

No system for analysis of plants is infallible and is subject to enhancement with newly available improved technologies, evolving evaluation techniques, increased knowledge base of the subject and resource availability. The system described and evaluated for the study of mineral nutrient effects on lotus plants is no exception.

The system has enormous potential for fine tuning and improvement as a result of the information generated in this project. Changes in the solution management,

253 container logistics and level of technology employed would be necessary to produce data which are more accurate and useful to workers involved with lotus and other aquatic plants.

The solution could be managed more effectively by using a slowly circulating technique where the plant is continually submerged in solution pumped into the bottom of the container, drained from an outlet in the top and then returned to a relatively large central treatment reservoir. The solution can either be continually circulated, or managed through timers and solenoid devices.

The benefits of such a technique, an adaptation of Asher et al. (1965), are to provide a continually homogenised solution to all replicate plant roots, allow filtering, oxygenation and movement of solution to control algae and homogenise the reservoir and return solutions, external monitoring of the solution for quality, quantity and temperature, and lower continued labour inputs. Plants grown in this way would not require changes of container and media when exchanging solutions, therefore, no disruption of the root system would occur, any number of replicates can be attached to a treatment (provided the reservoir is of adequate size), and harvest of plants can be as required for any type of destructive analysis. Different applications can be drawn from such a setup such as determining relative growth rate and production of plant parts for a number of uses. The drawbacks include initial higher resource inputs, reliance upon technology increasing the probability of error due to technology failure, and higher initial labour inputs.

Assuming an adequately sized reservoir was utilised, larger containers to accommodate plants at later stages of growth could be employed as research tools.

254

They would require greater space, media, nutrients, and other resources to maintain a sufficient equilibrium between solution requirement, delivery and maintaining homogeneity. Labour inputs would also be greater.

255

8.6 Conclusions

The complexity of simulating an aquatic environment for a large plant in replicate, for the commitment of designed treatments, is extremely challenging. The system developed for researching lotus is capable of achieving the objectives of critical concentration determination for any nutrient, determining the adequate supply range for maximum growth and expressing signs and symptoms of nutrient disorder. The system is adaptable to other objectives and improvements.

The conditions for plant material production for the system have been adequately addressed for the purposes of utility within the system developed. Significant gaps in our knowledge remain regarding seed physiology, production of clonal material, and genetic variation of heterozygous seeds.

The optimum pH and EC for lotus growing in soilless cultures has been identified.

Extrapolation of these values to soil grown plants requires careful consideration.

Values for critical nutrient concentrations and adequate nutrient supply range for lotus have been documented and are satisfactory for field estimations of plant materials and pond soil water analysis. Determination of absolute values requires further experimentation based on the results of this work. The effects of major nutrients on the growth response of lotus and expression of nutrient disorder have been attempted but require further definition. Different approaches in experimental design are necessary for these two objectives.

The leaf lamina has been recognised as the most appropriate organ for field testing of plant nutrient status. Leaves displayed the ability to express a range of nutrient

256 concentrations for all elements required for growth. Leaves are also the most convenient organ to sample from the plant and such an action does not compromise the plant’s below ground structures.

It is necessary to relate results obtained for container-grown plants, to those of field- grown plants. Calibration requires that plants should be of an equal age, be grown under similar conditions (eg environment and applied nutrients), and samples taken from corresponding organs, in equivalent measures, and concurrently at predetermined time intervals.

The sensitive response of lotus to concentrations of particular nutrients during growth stages, reveal lotus as a crop plant which must be carefully managed in terms of nutrition. This is especially important as the current crop recommendations are for the application of large amounts of most nutrients prior to transplanting the propagation material (Nguyen and Hicks 2004). Specialised crop environments like ponds, require delicate handling of nutrient management. Due to the degree of homogeneity of nutrients in the pond soil water continuum. Plants within the pond environment cannot escape high concentrations of nutrients through the direction of root growth away from these concentrations. The adherence of nutrients to soil particles in the media reservoir may offset the concentration of nutrients in the pond water solution compared to the inert media of soilless cultures and remove nutrients directly available to plants from the pond solution.

The basis for continued study of nutrition of lotus has been outlined in terms of an improved system within which to impose treatments and a nutrient range platform

257 from which to work. The entire tapestry of lotus nutrition will take a dedicated, staged approach to experimentation and significant resources.

258

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Volume II Appendices

Development and evaluation of a system for the study of mineral nutrition of sacred lotus (Nelumbo nucifera Gaertn.).

David . J. Hicks B.Hort.Sci. (Hons.) University of Western Sydney, Hawkesbury

A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

Centre for Horticulture and Plant Sciences University of Western Sydney, Hawkesbury. Australia

July 2005

Table of Contents

Volume II Appendices: Development and evaluation of a system for the study of mineral nutrition of sacred lotus (Nelumbo nucifera Gaertn.)

Appendix 1 Miscellaneous Information 1

Appendix 2 Seed ANOVA Tables 17

Appendix 3 Plant Culture ANOVA Tables 18

Appendix 4 Nitrogen ANOVA Tables and Miscellaneous Graphs 27

Appendix 5 Phosphorous ANOVA Tables and Miscellaneous Graphs 108

Appendix 6 Potassium ANOVA Tables and Miscellaneous Graphs 187

Appendix 7 Calcium ANOVA Tables and Miscellaneous Graphs 253

Appendix 8 ANOVA Tables for Constant Treatments 324

Appendix 1 Miscellaneous Information

Table A1.1 Composition of Hydrosol as per label.

6% N as NO3 7% P water soluble 29.9% K water soluble 1.8% Mg

0.05% B 0.015% Cu as EDTA 0.29% Fe as DTPA 0.05% Mn as EDTA 0.008% Mo 0.016% Zn as EDTA

Recommended rates: continuous feeding 0.8-1.0 g L-1 occasional feeding 0.8-3.0 g L-1

EC value 1.1 mS cm-1 at 1g L-1

-1 o Max. solubility 30 kg 100 L H2O @ 25 C

Table A1.2 Solution composition spreadsheet for N treatments in experiment 1.

Amount Used for Growing Compound Stock Soln Solutions (ml/L)

N (ppm) 50 250 350 450 (g/L) NaH2PO4.2H2O 30.90 KH2PO4 30.00 3.600 3.600 3.600 3.600 Ca(NO3)2.4H2O 250.00 1.000 3.500 3.500 3.500 KNO3 25.00 K2SO4 65.00 8.000 6.300 6.300 6.300 MgSO4 62.50 4.500 3.000 3.000 3.000 CaCl2 112.00 2.600 NH4NO3 5.00 K2CO3 34.50 NaNO3 18.25 Mg(NO3)2.6H2O 65.00 2.000 2.000 2.000 KNO3 130.00 1.000 2.000 2.000 2.000 NH4NO3 100.00 2.500 5.300 8.200 STEM 6.07 1.000 1.000 1.000 1.000

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 0.250 0.875 0.875 0.875 KNO3 N 0.130 0.260 0.260 0.260 NH4NO3 N 0.000 0.250 0.530 0.820 Mg(NO3)2 N 0.000 0.130 0.130 0.130 NaH2PO4.2H2O P 0.000 0.000 0.000 0.000 KH2PO4 P 0.108 0.108 0.108 0.108 KH2PO4 K 0.108 0.108 0.108 0.108 K2SO4 K 0.520 0.410 0.410 0.410 K2SO4 S 0.520 0.410 0.410 0.410 KNO3 K 0.130 0.260 0.260 0.260 Ca(NO3)2.4H2O Ca 0.250 0.875 0.875 0.875 CaCl2 Ca 0.291 0.000 0.000 0.000 MgSO4 Mg 0.281 0.188 0.188 0.188 Mg(NO3)2 Mg 0.000 0.130 0.130 0.130 MgSO4 S 0.281 0.188 0.188 0.188 NaH2PO4.2H2O Na 0.000 0.000 0.000 0.000 CaCl2 Cl 0.291 0.000 0.000 0.000

Nutrient Concentration in Growing Solution (ppm) N 29.653 103.785 103.785 103.785 N 18.012 36.025 36.025 36.025 N 0.000 87.506 185.513 287.020 N 0.000 24.554 24.554 24.554 P 0.000 0.000 0.000 0.000 P 24.589 24.589 24.589 24.589 K 21.438 21.438 21.438 21.438 K 233.299 183.723 183.723 183.723 K 47.460 94.921 94.921 94.921 Ca 42.422 148.476 148.476 148.476 Ca 105.147 0.000 0.000 0.000 Mg 56.811 37.874 37.874 37.874 Mg 0.000 21.348 21.348 21.348 S 74.905 49.937 49.937 49.937 S 95.664 75.336 75.336 75.336 Na 0.000 0.000 0.000 0.000 Cl 46.500 0.000 0.000 0.000

Nutrient Concentration in Growing Solution (ppm) N 48 252 350 451 P 25 25 25 25 K 302 300 300 300 Ca 148 148 148 148 Mg 57 59 59 59 S 171 125 125 125 Na 0 0 0 0 Cl 47 0 0 0

Table A1.3 Solution composition spreadsheet for P treatments in experiment 1.

Amount Used for Growing Compound Stock Soln Solutions (ml/L)

P (ppm) 5 20 25 30 (g/L) NaH2PO4.2H2O 30.90 KH2PO4 30.00 0.800 3.000 3.600 4.400 Ca(NO3)2.4H2O 250.00 3.500 3.500 3.500 3.500 KNO3 25.00 K2SO4 65.00 2.000 2.000 2.000 2.000 MgSO4 62.50 5.000 5.000 5.000 5.000 CaCl2 112.00 NH4NO3 5.00 K2CO3 34.50 NaNO3 18.25 Mg(NO3)2.6H2O 65.00 KNO3 130.00 4.800 4.700 4.600 4.500 NH4NO3 100.00 4.500 4.600 4.600 4.700 STEM 6.07 1.000 1.000 1.000 1.000

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 0.875 0.875 0.875 0.875 KNO3 N 0.624 0.611 0.598 0.585 NH4NO3 N 0.450 0.460 0.460 0.470 Mg(NO3)2 N 0.000 0.000 0.000 0.000 NaH2PO4.2H2O P 0.000 0.000 0.000 0.000 KH2PO4 P 0.024 0.090 0.108 0.132 KH2PO4 K 0.024 0.090 0.108 0.132 K2SO4 K 0.130 0.130 0.130 0.130 KNO3 K 0.624 0.611 0.598 0.585 K2SO4 S 0.130 0.130 0.130 0.130 Ca(NO3)2.4H2O Ca 0.875 0.875 0.875 0.875 CaCl2 Ca MgSO4 Mg 0.313 0.313 0.313 0.313 Mg(NO3)2 Mg 0.000 0.000 0.000 0.000 MgSO4 S 0.313 0.313 0.313 0.313 NaH2PO4.2H2O Na 0.000 0.000 0.000 0.000 CaCl2 Cl 0.000 0.000 0.000 0.000 5

Nutrient Concentration in Growing Solution (ppm) N 103.785 103.785 103.785 103.785 N 86.459 84.658 82.856 81.055 N 157.511 161.011 161.011 164.512 N 0.000 0.000 0.000 0.000 P 0.000 0.000 0.000 0.000 P 5.464 20.491 24.589 30.053 K 4.764 17.865 21.438 26.202 K 58.325 58.325 58.325 58.325 K 227.810 223.063 218.317 213.571 Ca 148.476 148.476 148.476 148.476 Ca 0.000 0.000 0.000 0.000 Mg 63.123 63.123 63.123 63.123 Mg 0.000 0.000 0.000 0.000 S 83.228 83.228 83.228 83.228 S 23.916 23.916 23.916 23.916 Na 0.000 0.000 0.000 0.000 Cl 0.000 0.000 0.000 0.000

Nutrient Concentration in Growing Solution (ppm) N 348 349 348 349 P 5 20 25 30 K 291 299 298 298 Ca 148 148 148 148 Mg 63 63 63 63 S 107 107 107 107 Na 0 0 0 0 Cl 0 0 0 0 6

Table A1.4 Solution composition spreadsheet for K treatments in experiment 1.

Amount Used for Growing Compound Stock Soln Solutions (ml/L) K (ppm) (g/L) 50 250 350 450 (NH4)2HPO4 30 NaH2PO4.2H2O 30.90 KH2PO4 30.00 3.600 3.600 3.600 3.600 Ca(NO3)2.4H2O 250.00 3.500 3.500 3.500 3.500 KNO3 25.00 K2SO4 65.00 3.000 MgSO4 62.50 2.500 5.000 5.000 3.000 CaCl2 112.00 NH4NO3 5.00 K2CO3 34.50 NaNO3 18.25 Mg(NO3)2.6H2O 65.00 5.500 4.000 KNO3 130.00 0.400 4.400 6.300 7.500 NH4NO3 100.00 5.700 4.800 3.800 2.400 STEM 6.07 1.000 1.000 1.000 1.000

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 0.875 0.875 0.875 0.875 KNO3 N 0.052 0.572 0.819 0.975 NH4NO3 N 0.570 0.480 0.380 0.240 (NH4)2HPO4 N 0.000 0.000 0.000 0.000 Mg(NO3)2 N 0.358 0.000 0.000 0.260 NaH2PO4.2H2O P 0.000 0.000 0.000 0.000 KH2PO4 P 0.108 0.108 0.108 0.108 (NH4)2HPO4 P 0.000 0.000 0.000 0.000 KH2PO5 K 0.108 0.108 0.108 0.108 K2SO4 K 0.000 0.000 0.000 0.195 KNO3 K 0.052 0.572 0.819 0.975 K2SO4 S 0.000 0.000 0.000 0.195 Ca(NO3)2.4H2O Ca 0.875 0.875 0.875 0.875 CaCl2 Ca 0.000 0.000 0.000 0.000 Mg(NO3)2 Mg 0.358 0.000 0.000 0.260 MgSO4 Mg 0.156 0.313 0.313 0.188 MgSO4 S 0.156 0.313 0.313 0.188 NaH2PO4.2H2O Na 0.000 0.000 0.000 0.000 CaCl2 Cl 0.000 0.000 0.000 0.000 7

Nutrient Concentration in Growing Solution (ppm) N 103.785 103.785 103.785 103.785 N 7.205 79.254 113.477 135.092 N 199.514 168.012 133.009 84.006 N 0.000 0.000 0.000 0.000 N 39.063 0.000 0.000 28.409 P 24.582 24.582 24.582 24.582 P 0.000 0.000 0.000 0.000 P 0.000 0.000 0.000 0.000 K 31.030 31.030 31.030 31.030 K 0.000 0.000 0.000 37.704 K 20.109 221.197 316.713 377.040 Ca 148.476 148.476 148.476 148.476 Ca 0.000 0.000 0.000 0.000 Mg 31.561 63.123 63.123 37.874 Mg 33.910 0.000 0.000 24.661 S 41.614 83.228 83.228 49.937 S 0.000 0.000 0.000 35.874 Na 0.000 0.000 0.000 0.000 Cl 0.000 0.000 0.000 0.000

Nutrient Concentration in Growing Solution (ppm) N 350 351 350 351 P 25 25 25 25 K 51 252 348 446 Ca 148 148 148 148 Mg 65 63 63 63 S 42 83 83 86 Na 0 0 0 0 Cl 0 0 0 0 8

Table A1.5 Commercial solution stock composition (%w/v).

A B Neutron 2000+ Conversion (ppm)

N as NO3 3.66 0.90 N as NH4 0.25 ----- N Total 3.91 0.90 275 P as P water soluble ----- 0.80 45 K as NO3 2.50 2.50 K as PO5 ----- 1.00 K Total 2.50 3.51 350 CaNO3 3.6 ----- 230 S as SO4 ----- 2.00 120 Mg as SO4 ----- 1.50 60 Fe as EDTA 0.10 ----- 10 Mn as EDTA ----- 0.01 0.1 Zn as EDTA ----- 0.02 2 Cu as EDTA ----- 0.004 0.4 B as Borax ----- 0.003 0.3 Mo as Na Molybdate ----- 0.001 0.1 Water 85.10 87.20

Table 1.5a Volume of 0.01 M NaOH used to adjust pH in Experiment 7 (Treatment solutions made in 20 L batches).

- • pH Treatment • 1 M NaOH volume (ml L 1) • 5.50 • 0 • 6.00 • 0.022 • 6.25 • 0.045 • 6.50 • 0.067 • 7.00 • 1.79 • 7.50 • 3.46 • 8.00 • 5.34 • 9.00 • 15.12

Table A1.6 Solution composition spreadsheet for N treatments in experiment 10.

Compound Stock Soln Amount Used for Growing Solutions (ml/L)

N (ppm) 50.00 150.00 200.00 250.00 275.00 300.00 325.00 400.00 (g/L)

KH2PO4 100.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 Ca(NO3)2.4H2O 200.00 2.10 4.00 6.00 6.50 6.75 6.75 6.75 6.75 K2SO4 40.00 17.00 15.00 13.00 8.60 5.50 2.00 MgSO4 150.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 CaCl2 112.00 3.90 2.35 0.65 0.25 Mg(NO3)2.6H2O 200.00 0.93 0.93 0.93 0.93 0.93 0.93 KNO3 100.00 0.00 1.00 2.00 4.40 5.80 7.50 8.50 8.50 NH4NO3 100.00 0.00 0.00 0.35 2.50 STEM 12.14 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 0.42 0.80 1.20 1.30 1.35 1.35 1.35 1.35 KNO3 N 0.00 0.10 0.20 0.44 0.58 0.75 0.85 0.85 NH4NO3 N 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.25 Mg(NO3)2 N 0.00 0.00 0.19 0.19 0.19 0.19 0.19 0.19 KH2PO4 P 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 KH2PO4 K 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 K2SO4 K 0.68 0.60 0.52 0.34 0.22 0.08 0.00 0.00 K2SO4 S 0.68 0.60 0.52 0.34 0.22 0.08 0.00 0.00 KNO3 K 0.00 0.10 0.20 0.44 0.58 0.75 0.85 0.85 Ca(NO3)2.4H2O Ca 0.42 0.80 1.20 1.30 1.35 1.35 1.35 1.35 CaCl2 Ca 0.44 0.26 0.07 0.03 0.00 0.00 0.00 0.00 MgSO4 Mg 0.30 0.30 0.15 0.15 0.15 0.15 0.15 0.15 Mg(NO3)2 Mg 0.00 0.00 0.19 0.19 0.19 0.19 0.19 0.19 MgSO4 S 0.30 0.30 0.15 0.15 0.15 0.15 0.15 0.15 CaCl2 Cl 0.44 0.26 0.07 0.03 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 49.82 94.89 142.33 154.19 160.13 160.13 160.13 160.13 N 0.00 13.86 27.71 60.96 80.36 103.92 117.77 117.77 N 0.00 0.00 0.00 0.00 0.00 0.00 12.25 87.51 N 0.00 0.00 35.13 35.13 35.13 35.13 35.13 35.13 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 39.70 39.70 39.70 39.70 39.70 39.70 39.70 39.70 K 305.08 269.19 233.30 154.34 98.70 35.89 0.00 0.00 K 0.00 36.51 73.02 160.63 211.75 273.81 310.32 310.32 Ca 71.27 135.75 203.62 220.59 229.08 229.08 229.08 229.08 Ca 157.72 95.04 26.29 10.11 0.00 0.00 0.00 0.00 Mg 60.60 60.60 30.30 30.30 30.30 30.30 30.30 30.30 Mg 0.00 0.00 30.54 30.54 30.54 30.54 30.54 30.54 S 79.90 79.90 39.95 39.95 39.95 39.95 39.95 39.95 S 125.10 110.38 95.66 63.29 40.47 14.72 0.00 0.00 Cl 69.75 42.03 11.63 4.47 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 49.82 108.74 205.18 250.29 275.62 299.17 325.28 400.54 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 344.78 345.40 346.01 354.67 350.15 349.40 350.02 350.02 Ca 228.99 230.79 229.91 230.70 229.08 229.08 229.08 229.08 Mg 60.60 60.60 60.84 60.84 60.84 60.84 60.84 60.84 S 205.00 190.28 135.61 103.24 80.42 54.67 39.95 39.95 Cl 69.75 42.03 11.63 4.47 0.00 0.00 0.00 0.00 11

Table A1.7 Solution composition spreadsheet for P treatments in experiment 11.

Compound Stock Soln Amount Used for Growing Solutions (ml/L)

P (ppm) 5.00 15.00 25.00 40.00 45.00 50.00 100.00 (g/L)

KH2PO4 100.00 0.25 0.66 1.10 1.76 2.00 2.20 4.40 Ca(NO3)2.4H2O 200.00 6.75 6.75 6.75 6.75 6.75 6.75 6.75 K2SO4 40.00 7.50 7.00 6.50 5.80 5.50 5.30 2.85 MgSO4 150.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 CaCl2 112.00 Mg(NO3)2.6H2O 200.00 0.93 0.93 0.93 0.93 0.93 KNO3 100.00 5.80 5.80 5.80 5.80 5.80 5.80 5.80 NH4NO3 100.00 1.00 1.00 0.00 0.00 STEM 12.14 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 1.35 1.35 1.35 1.35 1.35 1.35 1.35 KNO3 N 0.58 0.58 0.58 0.58 0.58 0.58 0.58 NH4NO3 N 0.10 0.10 0.00 0.00 0.00 0.00 0.00 Mg(NO3)2 N 0.00 0.00 0.19 0.19 0.19 0.19 0.19 KH2PO4 P 0.03 0.07 0.11 0.18 0.20 0.22 0.44 KH2PO4 K 0.03 0.07 0.11 0.18 0.20 0.22 0.44 K2SO4 K 0.30 0.28 0.26 0.23 0.22 0.21 0.11 K2SO4 S 0.30 0.28 0.26 0.23 0.22 0.21 0.11 KNO3 K 0.58 0.58 0.58 0.58 0.58 0.58 0.58 Ca(NO3)2.4H2O Ca 1.35 1.35 1.35 1.35 1.35 1.35 1.35 CaCl2 Ca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 MgSO4 Mg 0.30 0.30 0.15 0.15 0.15 0.15 0.15 Mg(NO3)2 Mg 0.00 0.00 0.19 0.19 0.19 0.19 0.19 MgSO4 S 0.30 0.30 0.15 0.15 0.15 0.15 0.15 CaCl2 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 160.13 160.13 160.13 160.13 160.13 160.13 160.13 N 80.36 80.36 80.36 80.36 80.36 80.36 80.36 N 35.00 35.00 0.00 0.00 0.00 0.00 0.00 N 0.00 0.00 35.13 35.13 35.13 35.13 35.13 P 5.69 15.03 25.04 40.07 45.54 50.09 100.18 K 4.96 13.10 21.83 34.94 39.70 43.67 87.34 K 134.60 125.62 116.65 104.09 98.70 95.11 51.15 K 211.75 211.75 211.75 211.75 211.75 211.75 211.75 Ca 229.08 229.08 229.08 229.08 229.08 229.08 229.08 Ca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mg 60.60 60.60 30.30 30.30 30.30 30.30 30.30 Mg 0.00 0.00 30.54 30.54 30.54 30.54 30.54 S 79.90 79.90 39.95 39.95 39.95 39.95 39.95 S 55.19 51.51 47.83 42.68 40.47 39.00 20.97 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 275.49 275.49 275.62 275.62 275.62 275.62 275.62 P 5.69 15.03 25.04 40.07 45.54 50.09 100.18 K 351.30 350.47 350.23 350.77 350.15 350.53 350.23 Ca 229.08 229.08 229.08 229.08 229.08 229.08 229.08 Mg 60.60 60.60 60.84 60.84 60.84 60.84 60.84 S 135.09 131.41 87.78 82.63 80.42 78.95 60.92 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13

Table A1.8 Solution composition spreadsheet for K treatments in experiment 12.

Compound Stock Soln Amount Used for Growing Solutions (ml/L)

K (ppm) 50.00 225.00 300.00 325.00 350.00 375.00 400.00 500.00 (g/L)

KH2PO4 100.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 Ca(NO3)2.4H2O 200.00 6.75 6.75 6.75 6.75 6.75 6.75 6.75 6.75 K2SO4 40.00 2.80 4.10 5.50 6.90 8.30 13.90 MgSO4 150.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 CaCl2 112.00 Mg(NO3)2.6H2O 200.00 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 KNO3 100.00 0.30 5.10 5.75 5.80 5.80 5.80 5.80 5.80 NH4NO3 100.00 2.15 0.25 0.00 0.00 STEM 12.14 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 1.35 1.35 1.35 1.35 1.35 1.35 1.35 1.35 KNO3 N 0.03 0.51 0.58 0.58 0.58 0.58 0.58 0.58 NH4NO3 N 0.22 0.03 0.00 0.00 0.00 0.00 0.00 0.00 Mg(NO3)2 N 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 KH2PO4 P 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 KH2PO4 K 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 K2SO4 K 0.00 0.00 0.11 0.16 0.22 0.28 0.33 0.56 K2SO4 S 0.00 0.00 0.11 0.16 0.22 0.28 0.33 0.56 KNO3 K 0.03 0.51 0.58 0.58 0.58 0.58 0.58 0.58 Ca(NO3)2.4H2O Ca 1.35 1.35 1.35 1.35 1.35 1.35 1.35 1.35 CaCl2 Ca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 MgSO4 Mg 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 Mg(NO3)2 Mg 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 MgSO4 S 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 CaCl2 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 160.13 160.13 160.13 160.13 160.13 160.13 160.13 160.13 N 4.16 70.66 79.67 80.36 80.36 80.36 80.36 80.36 N 75.26 8.75 0.00 0.00 0.00 0.00 0.00 0.00 N 35.13 35.13 35.13 35.13 35.13 35.13 35.13 35.13 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 39.70 39.70 39.70 39.70 39.70 39.70 39.70 39.70 K 0.00 0.00 50.25 73.58 98.70 123.83 148.95 249.45 K 10.95 186.19 209.92 211.75 211.75 211.75 211.75 211.75 Ca 229.08 229.08 229.08 229.08 229.08 229.08 229.08 229.08 Ca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mg 30.30 30.30 30.30 30.30 30.30 30.30 30.30 30.30 Mg 30.54 30.54 30.54 30.54 30.54 30.54 30.54 30.54 S 39.95 39.95 39.95 39.95 39.95 39.95 39.95 39.95 S 0.00 0.00 20.60 30.17 40.47 50.78 61.08 102.29 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Nutrient Concentration in Growing Solution (ppm) N 274.67 274.67 274.93 275.62 275.62 275.62 275.62 275.62 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 50.65 225.89 299.87 325.02 350.15 375.27 400.40 500.90 Ca 229.08 229.08 229.08 229.08 229.08 229.08 229.08 229.08 Mg 60.84 60.84 60.84 60.84 60.84 60.84 60.84 60.84 S 39.95 39.95 60.55 70.12 80.42 90.73 101.03 142.24 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15

Table A1.9 Solution composition spreadsheet for Ca treatments in experiment 13.

Compound Stock Soln Amount Used for Growing Solutions (ml/L)

Ca (ppm) 50.00 100.00 150.00 175.00 200.00 230.00 250.00 350.00 (g/L)

KH2PO4 100.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 Ca(NO3)2.4H2O 200.00 1.50 2.95 4.40 5.16 5.90 6.75 6.75 6.75 K2SO4 40.00 2.50 5.50 5.50 5.50 MgSO4 150.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 CaCl2 112.00 0.52 3.00 Mg(NO3)2.6H2O 200.00 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 KNO3 100.00 8.50 8.50 8.50 8.50 7.25 5.80 5.80 5.80 NH4NO3 100.00 2.50 1.50 0.50 STEM 12.14 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Concentration in Growing Solution (g/L) Ca(NO3)2.4H2O N 0.30 0.59 0.88 1.03 1.18 1.35 1.35 1.35 KNO3 N 0.85 0.85 0.85 0.85 0.73 0.58 0.58 0.58 NH4NO3 N 0.25 0.15 0.05 0.00 0.00 0.00 0.00 0.00 Mg(NO3)2 N 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 KH2PO4 P 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 KH2PO4 K 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 K2SO4 K 0.00 0.00 0.00 0.00 0.10 0.22 0.22 0.22 K2SO4 S 0.00 0.00 0.00 0.00 0.10 0.22 0.22 0.22 KNO3 K 0.85 0.85 0.85 0.85 0.73 0.58 0.58 0.58 Ca(NO3)2.4H2O Ca 0.30 0.59 0.88 1.03 1.18 1.35 1.35 1.35 CaCl2 Ca 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.34 MgSO4 Mg 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 Mg(NO3)2 Mg 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 MgSO4 S 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 CaCl2 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.34

Nutrient Concentration in Growing Solution (ppm) N 35.58 69.98 104.38 122.41 139.96 160.13 160.13 160.13 N 117.77 117.77 117.77 117.77 100.45 80.36 80.36 80.36 N 87.51 52.50 17.50 0.00 0.00 0.00 0.00 0.00 N 35.13 35.13 35.13 35.13 35.13 35.13 35.13 35.13 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 39.70 39.70 39.70 39.70 39.70 39.70 39.70 39.70 K 0.00 0.00 0.00 0.00 44.87 98.70 98.70 98.70 K 310.32 310.32 310.32 310.32 264.68 211.75 211.75 211.75 Ca 50.91 100.12 149.32 175.12 200.23 229.08 229.08 229.08 Ca 0.00 0.00 0.00 0.00 0.00 0.00 21.03 121.32 Mg 30.30 30.30 30.30 30.30 30.30 30.30 30.30 30.30 Mg 30.54 30.54 30.54 30.54 30.54 30.54 30.54 30.54 S 39.95 39.95 39.95 39.95 39.95 39.95 39.95 39.95 S 0.00 0.00 0.00 0.00 18.40 40.47 40.47 40.47 Cl 0.00 0.00 0.00 0.00 0.00 0.00 9.30 53.65

Nutrient Concentration in Growing Solution (ppm) N 275.99 275.39 274.78 275.31 275.55 275.62 275.62 275.62 P 45.54 45.54 45.54 45.54 45.54 45.54 45.54 45.54 K 350.02 350.02 350.02 350.02 349.25 350.15 350.15 350.15 Ca 50.91 100.12 149.32 175.12 200.23 229.08 250.11 350.40 Mg 60.84 60.84 60.84 60.84 60.84 60.84 60.84 60.84 S 39.95 39.95 39.95 39.95 58.35 80.42 80.42 80.42 Cl 0.00 0.00 0.00 0.00 0.00 0.00 9.30 53.65

Appendix 2 Seed ANOVA Tables

Table A2.1 Analysis of variance of the number of days to germinate lotus (Nelumbo nucifera) seeds as a function of temperature. (Figure 2.1).

Univariate Tests of Significance for No. Days Germn (seeds_temp) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 998.7556 1 998.7556 1024.365 0.000000 Treatment 110.2095 4 27.5524 28.259 0.000000 Error 15.6000 16 0.9750

Tukey HSD test; variable No. Days Germn (seeds_temp) Homogenous Groups, alpha = .01000 Error: Between MS = .97500, df = 16.000 Treatment No. Days Germn 1 2 3 4 30oC 5.40000 **** 5 40oC 6.00000 **** 3 25oC 6.60000 **** 2 20oC 9.40000 **** 1 15oC 15.00000 ****

Appendix 3 Plant Culture ANOVA Tables

Table A3.1 ANOVA of the total dry mass of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.1a).

Univariate Tests of Significance for total dm (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition

SS Degr. of MS F p

Intercept 1062.446 1 1062.446 259.1970 0.000000 Treat 472.454 7 67.493 16.4659 0.000000

Error 131.168 32 4.099

Tukey HSD test; variable total dm (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 4.0990, df = 32.000 Treat total dm 1 2 3 4 1 0 0.77250 **** 3 50 2.94000 **** **** 8 300 3.27667 **** **** 2 25 3.77750 **** **** 4 75 4.50000 **** **** **** 7 275 5.32750 **** **** 5 150 7.95333 **** 6 200 12.68250 ****

Table A3.2 ANOVA of the leaf dry mass of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.1b).

Univariate Tests of Significance for leaf dm (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 111.2361 1 111.2361 196.3670 0.000000 Treat 76.3944 7 10.9135 19.2658 0.000000 Error 18.1271 32 0.5665

Tukey HSD test; variable leaf dm (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = .56647, df = 32.000 Treat leaf dm 1 2 3 4 1 0 0.037500 **** 2 25 0.762500 **** **** 3 50 0.870000 **** **** 8 300 1.026667 **** **** 4 75 1.280000 **** **** **** 7 275 1.885000 **** **** 5 150 2.746667 **** 6 200 4.732500 **** 19

Table A3.3 ANOVA of the petiole dry mass of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.1b).

Univariate Tests of Significance for petiol dm (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 54.52225 1 54.52225 198.1325 0.000000 Treat 26.11105 7 3.73015 13.5553 0.000000 Error 8.80578 32 0.27518

Tukey HSD test; variable petiol dm (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = .27518, df = 32.000 Treat petiol dm 1 2 3 1 0 0.102500 **** 3 50 0.642500 **** 2 25 0.820000 **** 8 300 0.860000 **** 4 75 0.973333 **** **** 7 275 1.105000 **** **** 5 150 1.956667 **** **** 6 200 2.880000 ****

Table A3.4 ANOVA of the roots and stolons dry mass of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.1b).

Univariate Tests of Significance for root dm (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 215.0447 1 215.0447 305.8252 0.000000 Treat 64.7890 7 9.2556 13.1628 0.000000 Error 22.5012 32 0.7032

Tukey HSD test; variable root dm (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = .70316, df = 32.000 Treat root dm 1 2 3 1 0 0.632500 **** 8 300 1.390000 **** 3 50 1.427500 **** 2 25 2.195000 **** **** 4 75 2.246667 **** **** 7 275 2.337500 **** **** 5 150 3.250000 **** 6 200 5.070000 ****

Table A3.5 ANOVA of the number of leaves of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.2a).

Univariate Tests of Significance for leaf No. (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 51960.07 1 51960.07 734.3639 0.000000 Treat 7729.44 7 1104.21 15.6060 0.000000 Error 2264.17 32 70.76

Tukey HSD test; variable leaf No. (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 70.755, df = 32.000 Treat leaf No. 1 2 3 4 5 1 0 16.75000 **** 8 300 21.00000 **** 2 25 26.00000 **** **** 3 50 30.00000 **** **** **** 7 275 39.25000 **** **** **** 4 75 46.33333 **** **** **** 6 200 52.00000 **** **** 5 150 57.00000 ****

Table A3.6 ANOVA of the number of nodes of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.2a).

Univariate Tests of Significance for Node No. (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 66049.48 1 66049.48 487.9846 0.000000 Treat 11269.37 7 1609.91 11.8943 0.000000 Error 4331.25 32 135.35

Tukey HSD test; variable Node No. (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 135.35, df = 32.000 Treat Node No. 1 2 3 1 0 5.75000 **** 2 25 32.50000 **** 7 275 33.00000 **** 8 300 39.33333 **** 4 75 45.66667 **** **** 3 50 50.25000 **** **** 5 150 52.33333 **** **** 6 200 66.25000 ****

Table A3.7 ANOVA of the number of stolons of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.2a).

Univariate Tests of Significance for stolon No. (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 4245.317 1 4245.317 348.1105 0.000000 Treat 844.787 7 120.684 9.8959 0.000002 Error 390.250 32 12.195

Tukey HSD test; variable stolon No. (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 12.195, df = 32.000 Treat stolon No. 1 2 3 1 0 1.25000 **** 2 25 8.50000 **** 4 75 8.66667 **** 8 300 9.33333 **** 7 275 10.25000 **** 3 50 11.50000 **** **** 6 200 15.25000 **** **** 5 150 17.66667 ****

Table A3.8 ANOVA of the total stolon length of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.2b).

Univariate Tests of Significance for Stolon lgth (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 46015613 1 46015613 249.3595 0.000000 Treat 8320879 7 1188697 6.4416 0.000090 Error 5905129 32 184535

Tukey HSD test; variable Stolon lgth (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 1845E2, df = 32.000 Treat Stolon lgth 1 2 3 1 0 178.000 **** 7 275 866.750 **** **** 8 300 936.000 **** **** **** 2 25 947.250 **** **** **** 3 50 1034.000 **** **** **** 4 75 1276.000 **** **** 5 150 1554.000 **** **** 6 200 1788.500 ****

Table A3.9 ANOVA of the internode length of lotus (Nelumbo nucifera) as a function of E.C. (Figure 3.3).

Univariate Tests of Significance for Internode lgth (EC_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 28314.25 1 28314.25 944.2501 0.000000 Treat 327.77 7 46.82 1.5615 0.182761 Error 959.55 32 29.99

Tukey HSD test; variable Internode lgth (EC_a1) Homogenous Groups, alpha = .05000 Error: Between MS = 29.986, df = 32.000 Treat Internode lgth 1 3 50 20.71911 **** 8 300 24.22782 **** 7 275 25.87202 **** 6 200 26.59439 **** 4 75 27.37218 **** 5 150 28.81550 **** 1 0 28.89892 **** 2 25 30.34460 ****

Table A3.10 ANOVA of the total dry mass of lotus (Nelumbo nucifera) as a function of pH (Figure 3.4a).

Univariate Tests of Significance for total dm (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1551.663 1 1551.663 353.5800 0.000000 NewVar 446.924 7 63.846 14.5488 0.000000 Error 105.322 24 4.388

Tukey HSD test; variable total dm (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = 4.3884, df = 24.000 NewVar total dm 1 2 3 4 8 8 1.28250 **** 1 1 3.12750 **** **** 7 7 4.13000 **** **** 2 2 6.68750 **** **** 6 6 7.41000 **** **** 5 5 9.86000 **** **** 4 4 10.03000 **** **** 3 3 13.18000 ****

Table A3.11 ANOVA of the leaf dry mass of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.1b).

Univariate Tests of Significance for leaf dm (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 285.7644 1 285.7644 314.9270 0.000000 NewVar 88.1986 7 12.5998 13.8856 0.000000 Error 21.7776 24 0.9074

Tukey HSD test; variable leaf dm (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = .90740, df = 24.000 NewVar leaf dm 1 2 3 4 5 8 8 0.497500 **** 1 1 1.335000 **** **** 7 7 1.650000 **** **** **** 2 2 3.002500 **** **** **** 6 6 3.226667 **** **** **** 4 4 3.805000 **** **** **** 5 5 4.540000 **** **** 3 3 5.850000 ****

Table A3.12 ANOVA of the petiole dry mass of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.4b).

Univariate Tests of Significance for petiole dm (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 59.31420 1 59.31420 246.1440 0.000000 NewVar 21.85143 7 3.12163 12.9542 0.000001 Error 5.78337 24 0.24097

Tukey HSD test; variable petiole dm (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = .24097, df = 24.000 NewVar petiole dm 1 2 3 4 8 8 0.285000 **** 7 7 0.522500 **** **** 1 1 0.650000 **** **** 6 6 1.326667 **** **** **** 2 2 1.402500 **** **** **** 4 4 1.585000 **** **** 5 5 2.270000 **** **** 3 3 2.850000 ****

Table A3.13 ANOVA of the roots and stolons dry mass of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.4b).

Univariate Tests of Significance for root dm (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 218.5966 1 218.5966 412.6381 0.000000 NewVar 60.0432 7 8.5776 16.1917 0.000000 Error 12.7141 24 0.5298

Tukey HSD test; variable root dm (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = .52975, df = 24.000 NewVar root dm 1 2 3 4 5 8 8 0.500000 **** 1 1 1.142500 **** **** 7 7 1.957500 **** **** **** 2 2 2.282500 **** **** 6 6 2.856667 **** **** 5 5 3.050000 **** **** **** 3 3 4.480000 **** **** 4 4 4.640000 ****

Table A3.14 ANOVA of the number of leaves of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.5a).

Univariate Tests of Significance for leaf No. (pH_a4) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 15576.12 1 15576.12 320.4689 0.000000 NewVar 3107.37 7 443.91 9.1332 0.000017 Error 1166.50 24 48.60

Tukey HSD test; variable leaf No. (pH_a4) Homogenous Groups, alpha = .01000 Error: Between MS = 48.604, df = 24.000 NewVar leaf No. 1 2 3 8 8 5.00000 **** 1 1 13.00000 **** **** 7 7 17.25000 **** **** **** 6 6 18.00000 **** **** **** 2 2 27.00000 **** **** 4 4 27.75000 **** **** 5 5 32.00000 **** **** 3 3 36.50000 ****

Table A3.15 ANOVA of the number of nodes of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.5a).

Univariate Tests of Significance for node no. (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 45150.13 1 45150.13 339.4215 0.000000 NewVar 5439.37 7 777.05 5.8416 0.000487 Error 3192.50 24 133.02

Tukey HSD test; variable node no. (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = 133.02, df = 24.000 NewVar node no. 1 2 3 8 8 10.25000 **** 1 1 24.00000 **** **** 7 7 35.75000 **** **** **** 5 5 42.00000 **** **** 4 4 44.00000 **** **** 2 2 44.50000 **** **** 6 6 48.00000 **** **** 3 3 52.00000 ****

Table A3.16 ANOVA of the number of stolons of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.5a).

Univariate Tests of Significance for stolon no. (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1995.014 1 1995.014 259.9837 0.000000 NewVar 307.597 7 43.942 5.7264 0.000556 Error 184.167 24 7.674

Tukey HSD test; variable stolon no. (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = 7.6736, df = 24.000 NewVar stolon no. 1 2 8 8 2.50000 **** 1 1 6.00000 **** 6 6 7.66667 **** 7 7 7.75000 **** 5 5 8.00000 **** 2 2 8.25000 **** **** 3 3 8.50000 **** **** 4 4 14.50000 ****

Table A3.17 ANOVA of the total stolon length of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.5b).

Univariate Tests of Significance for stolon lgth. (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 38659890 1 38659890 259.9335 0.000000 NewVar 7778207 7 1111172 7.4711 0.000084 Error 3569519 24 148730

Tukey HSD test; variable stolon lgth. (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = 1487E2, df = 24.000 NewVar stolon lgth. 1 2 3 8 8 202.500 **** 1 1 674.500 **** **** 7 7 941.250 **** **** **** 5 5 974.000 **** **** **** 2 2 1226.750 **** **** 6 6 1260.667 **** **** 4 4 1678.000 **** 3 3 1835.500 ****

Table A3.18 ANOVA of the internode length of lotus (Nelumbo nucifera) as a function of pH. (Figure 3.6).

Univariate Tests of Significance for Int. lgth. (pH_a3) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 21801.41 1 21801.41 500.1490 0.000000 NewVar 2750.19 7 392.88 9.0132 0.000019 Error 1046.16 24 43.59

Tukey HSD test; variable Int. lgth. (pH_a3) Homogenous Groups, alpha = .05000 Error: Between MS = 43.590, df = 24.000 NewVar Int. lgth. 1 2 8 8 4.93902 **** 5 5 23.17309 **** 7 7 25.88502 **** 6 6 26.87596 **** 1 1 26.91028 **** 2 2 27.71260 **** 3 3 35.18775 **** 4 4 38.12917 ****

Appendix 4 Nitrogen ANOVA Tables and Miscellaneous Graphs

Table A4.1 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 20 days of nitrogen treatments. (Table 4.1).

Univariate Tests of Significance for No.Lf.d20 (Spreadsheet1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 2.886003 1 2.886003 283.4916 0.000000 Treat 0.702772 7 0.100396 9.8619 0.000009 Error 0.244325 24 0.010180

Table A4.2 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of nitrogen treatments. (Table 4.1).

Univariate Tests of Significance for No.Lf.d40 (Spreadsheet1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 4.961250 1 4.961250 351.4982 0.000000 Treat 0.250000 7 0.035714 2.5303 0.042295 Error 0.338750 24 0.014115

Table A4.3 ANOVA for the percentage of total leaf area of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of nitrogen treatments. (Table 4.1).

Univariate Tests of Significance for TaffLAd40 (Spreadsheet1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 759.2756 1 759.2756 209.7374 0.000000 Treat 17.0431 7 2.4347 0.6726 0.693211 Error 86.8830 24 3.6201

Table A4.4 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 20 days of nitrogen treatments. (Table 4.1).

Univariate Tests of Significance for d20 (Spreadsheet41) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 2.790703 1 2.790703 308.8271 0.000000 Treat 0.584922 7 0.083560 9.2470 0.000016 Error 0.216875 24 0.009036

Table A4.5 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 40 days of nitrogen treatments. (Table 4.1).

Univariate Tests of Significance for d40 (Spreadsheet41) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 5.200312 1 5.200312 295.4024 0.000000 Treat 0.447188 7 0.063884 3.6289 0.008274 Error 0.422500 24 0.017604

Table A4.6 ANOVA of Total Dry Mass of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.1a). Univariate Tests of Significance for DW tot (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 5493.984 1 5493.984 357.4045 0.000000 N conc 534.317 7 76.331 4.9656 0.000810 Error 461.157 30 15.372

Tukey HSD test; variable DW tot (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 15.372, df = 30.000 N conc DW tot 1 2 1 50 4.82800 **** 2 150 8.07250 **** **** 5 275 11.57000 **** **** 6 300 12.43000 **** **** 4 250 13.07000 **** **** 3 225 13.99600 **** **** 7 325 15.90600 **** 8 400 16.77000 ****

Table A4.7 ANOVA of Leaf Dry Mass of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.1b). Univariate Tests of Significance for DW Leaf (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 635.4158 1 635.4158 261.2175 0.000000 N conc 76.9043 7 10.9863 4.5164 0.001547 Error 72.9755 30 2.4325

Tukey HSD test; variable DW Leaf (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 2.5132, df = 29.000 N conc DW Leaf 1 2 1 50 0.994000 **** 2 150 2.953333 **** **** 5 275 4.142000 **** **** 6 300 4.486000 **** **** 3 225 4.620000 **** **** 4 250 4.867500 **** **** 7 325 5.424000 **** 8 400 5.468000 ****

Table A4.8 ANOVA of petiole Dry Mass of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.1b). Univariate Tests of Significance for DW Pet (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 405.8561 1 405.8561 473.9098 0.000000 N conc 43.1516 7 6.1645 7.1982 0.000045 Error 25.6920 30 0.8564

Tukey HSD test; variable DW Pet (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = .85640, df = 30.000 N conc DW Pet 1 2 3 1 50 1.270000 **** 2 150 2.075000 **** **** 5 275 3.188000 **** **** **** 4 250 3.210000 **** **** **** 6 300 3.698000 **** **** 3 225 3.980000 **** **** 7 325 4.150000 **** **** 8 400 4.696000 ****

Table A4.9 ANOVA of roots and stolons dry mass of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.1b). Univariate Tests of Significance for DW Root (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 827.6030 1 827.6030 245.9144 0.000000 N conc 68.9572 7 9.8510 2.9271 0.018509 Error 100.9623 30 3.3654

Table A4.10 ANOVA of number of leaves of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.2a).

Univariate Tests of Significance for lf no. (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 22218.78 1 22218.78 291.5659 0.000000 N conc 2792.40 7 398.91 5.2348 0.000555 Error 2286.15 30 76.20

Tukey HSD test; variable lf.no. (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 88.245, df = 30.000 N conc lf.no. 1 2 1 50 10.60000 **** 4 250 17.25000 **** **** 2 150 17.50000 **** **** 3 225 22.80000 **** **** 5 275 24.00000 **** **** 8 400 30.00000 **** **** 6 300 32.20000 **** **** 7 325 35.80000 ****

Table A4.11 ANOVA of number of nodes of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.2b).

Univariate Tests of Significance for node no. (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 180408.5 1 180408.5 699.3752 0.000000 N conc 13376.9 7 1911.0 7.4082 0.000035 Error 7738.7 30 258.0

Tukey HSD test; variable node no. (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 257.96, df = 30.000 N conc node no. 1 2 3 1 50 41.20000 **** 4 250 51.25000 **** **** 2 150 53.75000 **** **** 5 275 61.20000 **** **** **** 3 225 80.60000 **** **** **** 6 300 82.00000 **** **** 7 325 86.40000 **** **** 8 400 97.40000 ****

Table A4.12 ANOVA of number of stolons of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.2c).

Univariate Tests of Significance for st.no. (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 10848.02 1 10848.02 374.4141 0.000000 N conc 840.51 7 120.07 4.1443 0.002693 Error 869.20 30 28.97

Tukey HSD test; variable st.no. (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 28.973, df = 30.000 N conc st.no. 1 2 1 50 10.40000 **** 4 250 13.00000 **** **** 2 150 13.00000 **** **** 3 225 15.80000 **** **** 5 275 16.40000 **** **** 6 300 20.40000 **** **** 7 325 22.00000 **** **** 8 400 24.80000 ****

Table A4.13 ANOVA of total leaf area of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.3a).

Univariate Tests of Significance for L.A). (cm2) (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 5731.785 1 5731.785 540.4045 0.000000 N conc 513.094 7 73.299 6.9108 0.000063 Error 318.194 30 10.606

Tukey HSD test; variable L.A). (m2) (N_general_b_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 10.606, df = 30.000 N conc L.A). (cm2) 1 2 1 50 3.54750 **** 2 150 10.50000 **** **** 7 325 13.27750 **** 3 225 13.31750 **** 6 300 13.71000 **** 4 250 14.03438 **** 5 275 14.58750 **** 8 400 15.73750 ****

Table A4.14 ANOVA of total stolon length of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.3b).

Univariate Tests of Significance for st lgth (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F P Intercept 139869378 1 139869378 343.7443 0.000000 N conc 3867928 7 552561 1.3580 0.258889 Error 12206984 30 406899

Table A4.15 ANOVA of internode length of lotus (Nelumbo nucifera) as a function of N supply. (Figure 4.3c).

Univariate Tests of Significance for av.int.nodal lgth (N_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F P Intercept 551820.1 1 551820.1 546.3853 0.000000 N conc 16218.7 7 2317.0 2.2941 0.053531 Error 30298.4 30 1009.9

Table A4.16 ANOVA of N concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure 4.4).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of N (%) N (%) N (%) N (%)

Fr.eedom SS MS F P Intercept 1 560.2640 560.2640 3170.973 0.000000 N Conc (ppm) 7 9.6568 1.3795 7.808 0.000019 Error 31 5.4772 0.1767 Total 38 15.1340

Tukey HSD test; variable N (%) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = .17669, df = 31.000 N Conc (ppm) N (%) 1 2 3 1 50 2.918997 **** 2 150 3.495496 **** **** 3 225 3.659687 **** **** 4 250 3.687819 **** **** 5 275 3.719496 **** **** **** 6 300 4.039870 **** **** 7 325 4.156970 **** **** 8 400 4.726197 ****

Table A4.17 ANOVA of N concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure 4.4a).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of N (%) N (%) N (%) N (%)

freedom SS MS F P Intercept 1 269.8475 269.8475 2028.784 0.000000 N Conc (ppm) 7 18.7853 2.6836 20.176 0.000000 Error 30 3.9903 0.1330 Total 37 22.7756

Tukey HSD test; variable N (%) (N_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = .13301, df = 30.000 N Conc (ppm) N (%) 1 2 3 4 1 50 1.505907 **** 2 150 2.238113 **** **** 3 225 2.425613 **** **** 5 275 2.511387 **** **** 4 250 2.574410 **** **** 6 300 2.883402 **** **** 7 325 3.294826 **** **** 8 400 3.984575 ****

Table A4.18 ANOVA of N concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure 4.4a).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of N (%) N (%) N (%) N (%)

freedom SS MS F P Intercept 1 225.5814 225.5814 2325.773 0.000000 N Conc (ppm) 7 11.3459 1.6208 16.711 0.000000 Error 30 2.9098 0.0970 Total 37 14.2556

Tukey HSD test; variable N (%) (N_root) Homogenous Groups, alpha = .01000 Error: Between MS = .09699, df = 30.000 N Conc (ppm) N (%) 1 2 3 4 1 50 1.429974 **** 2 150 2.073692 **** **** 3 225 2.337643 **** **** 4 250 2.341714 **** **** 5 275 2.359215 **** **** 6 300 2.767771 **** **** **** 7 325 2.990338 **** **** 8 400 3.282515 ****

Table A4.19 ANOVA of P concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure 4.4b).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1)

freedom SS MS F P Intercept 1 1.124519E+09 1.124519E+09 1321.884 0.000000 N Conc (ppm) 7 7.764397E+06 1.109200E+06 1.304 0.281345 Error 31 2.637150E+07 8.506935E+05 Total 38 3.413590E+07

Table A4.20 ANOVA of P concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure 4.4b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1)

freedom SS MS F P Intercept 1 1.957388E+09 1.957388E+09 1187.699 0.000000 N Conc (ppm) 7 3.439245E+07 4.913207E+06 2.981 0.016930 Error 30 4.944150E+07 1.648050E+06 Total 37 8.383395E+07

Table A4.21 ANOVA of P concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure 4.4b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) freedom SS MS F P

Intercept 1 3.048141E+09 3.048141E+09 2345.356 0.000000 N Conc (ppm) 7 3.685892E+07 5.265560E+06 4.052 0.003100 Error 30 3.898950E+07 1.299650E+06 Total 37 7.584842E+07

Tukey HSD test; variable P (mg kg-1) (N_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1300E3, df = 30.000 N Conc (ppm) P (mg kg-1) 1 2 1 50 7420.00 **** 2 150 8175.00 **** **** 4 250 8350.00 **** **** 5 275 8860.00 **** **** 3 225 8900.00 **** **** 7 325 9660.00 **** **** 8 400 10080.00 **** **** 6 300 10540.00 ****

Table A4.22 ANOVA of K concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure 4.5a).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1)

freedom SS MS F P Intercept 1 3.566955E+10 3.566955E+10 2111.834 0.000000 N Conc (ppm) 7 7.829744E+07 1.118535E+07 0.662 0.701779 Error 31 5.236000E+08 1.689032E+07 Total 38 6.018974E+08

Table A4.23 ANOVA of K concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure 4.5a).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1)

freedom SS MS F P Intercept 1 1.257184E+11 1.257184E+11 6056.772 0.000000 N Conc (ppm) 7 4.491158E+08 6.415940E+07 3.091 0.004140 Error 30 6.227000E+08 2.075667E+07 Total 37 1.071816E+09

Tukey HSD test; variable K (mg kg-1) (N_petiole) Homogenous Groups, alpha = .00100 Error: Between MS = 2076E4, df = 30.000 N Conc (ppm) K (mg kg-1) 1 2 8 400 50400.00 **** 7 325 55800.00 **** **** 1 50 55800.00 **** **** 4 250 59250.00 **** **** 2 150 59250.00 **** **** 6 300 60400.00 **** 3 225 60400.00 **** 5 275 61000.00 ****

Table A4.24 ANOVA of K concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure 4.5a).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1)

freedom SS MS F P Intercept 1 6.906413E+10 6.906413E+10 2889.914 0.000000 N Conc (ppm) 7 8.493658E+08 1.213380E+08 5.077 0.000692 Error 30 7.169500E+08 2.389833E+07 Total 37 1.566316E+09

Tukey HSD test; variable K (mg kg-1) (N_root) Homogenous Groups, alpha = .01000 Error: Between MS = 2390E4, df = 30.000 N Conc (ppm) K (mg kg-1) 1 2 8 400 32200.00 **** 7 325 39800.00 **** **** 4 250 42500.00 **** **** 1 50 44200.00 **** **** 2 150 44750.00 **** **** 6 300 44800.00 **** 5 275 46600.00 **** 3 225 47800.00 ****

Table A4.25 ANOVA of Ca concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure 4.5b).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1)

freedom SS MS F P Intercept 1 1.797455E+10 1.797455E+10 4123.228 0.000000 N Conc (ppm) 7 2.103328E+08 3.004754E+07 6.893 0.000057 Error 31 1.351395E+08 4.359339E+06 Total 38 3.454723E+08

Tukey HSD test; variable Ca (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 4359E3, df = 31.000 N Conc (ppm) Ca (mg kg-1) 1 2 3 8 400 17440.00 **** 1 50 18680.00 **** **** 2 150 21075.00 **** **** **** 4 250 21560.00 **** **** **** 3 225 22340.00 **** **** **** 5 275 22720.00 **** **** 7 325 23600.00 **** **** 6 300 24800.00 ****

Table A4.26 ANOVA of Ca concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure 4.5b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1)

freedom SS MS F P Intercept 1 6.919748E+09 6.919748E+09 4251.156 0.000000 N Conc (ppm) 7 3.171116E+07 4.530165E+06 2.783 0.023502 Error 30 4.883200E+07 1.627733E+06 Total 37 8.054316E+07

Table A4.27 ANOVA of Ca concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure 4.5b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1)

freedom SS MS F P Intercept 1 5.207051E+09 5.207051E+09 1661.940 0.000000 N Conc (ppm) 7 2.280466E+07 3.257808E+06 1.040 0.425004 Error 30 9.399350E+07 3.133117E+06 Total 37 1.167982E+08

Table A4.28 ANOVA of Mg concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.1a).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1)

freedom SS MS F P Intercept 1 1.976352E+09 1.976352E+09 3619.372 0.000000 N Conc (ppm) 7 6.535577E+06 9.336538E+05 1.710 0.143180 Error 31 1.692750E+07 5.460484E+05 Total 38 2.346308E+07

Table A4.29 ANOVA of Mg concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.1a).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1)

freedom SS MS F P Intercept 1 1.732809E+09 1.732809E+09 1550.774 0.000000 N Conc (ppm) 7 2.424718E+07 3.463883E+06 3.100 0.013934 Error 30 3.352150E+07 1.117383E+06 Total 37 5.776868E+07

Table A4.30 ANOVA of Mg concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.1a).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.006994E+09 1.006994E+09 1675.950 0.000000 N Conc (ppm) 7 9.176605E+06 1.310944E+06 2.182 0.064795 Error 30 1.802550E+07 6.008500E+05 Total 37 2.720211E+07

Table A4.31 ANOVA of S concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.1b).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1)

freedom SS MS F P Intercept 1 1.178405E+09 1.178405E+09 1722.856 0.000000 N Conc (ppm) 7 3.064009E+07 4.377156E+06 6.400 0.000106 Error 31 2.120350E+07 6.839839E+05 Total 38 5.184359E+07

Tukey HSD test; variable S (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 6840E2, df = 31.000 N Conc (ppm) S (mg kg-1) 1 2 3 5 275 4220.000 **** 6 300 4580.000 **** **** 8 400 5100.000 **** **** **** 4 250 5120.000 **** **** **** 7 325 5620.000 **** **** **** 3 225 5940.000 **** **** **** 2 150 6475.000 **** **** 1 50 7040.000 ****

Table A4.32 ANOVA of S concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.1b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1)

freedom SS MS F P Intercept 1 1.181139E+09 1.181139E+09 1786.537 0.000000 N Conc (ppm) 7 7.903105E+06 1.129015E+06 1.708 0.144986 Error 30 1.983400E+07 6.611333E+05 Total 37 2.773711E+07

Table A4.33 ANOVA of S concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.1b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 2.221598E+09 2.221598E+09 1552.570 0.000000 N Conc (ppm) 7 1.082618E+07 1.546598E+06 1.081 0.399750 Error 30 4.292750E+07 1.430917E+06 Total 37 5.375368E+07

8000 A

7000 ) -1 6000

5000

4000

3000

Organ Mg Conc. (mg kg (mg Conc. Mg Organ 2000

1000 A

0 B B 8000 ) -1

6000

4000 r k (mg O gan S Conc. g

2000 Leaf Petiole Roo ts & Stolons

0 0 100 200 300 400 500 N Supply (ppm)

Figure A4.1 Effect of nitrogen supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Magnesium; b) Sulphur. Values are means and bars represent S.E. (n=5). (Tables A4.28-33).

Table A4.34 ANOVA of Fe c once nt ration in lotus leaves (Nelum bo nucifera) as a function of N supply. (Figure A4.2a ).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1)

freedom SS MS F P Intercept 1 1028485 1028485 924.3726 0.000000 N Conc (ppm) 7 75769 10824 9.7284 0.000002 Error 31 34492 1113 Total 38 110261

Tukey HSD tes t; variable Fe (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 1112.6, df = 31.000 N Conc (ppm) Fe (mg kg-1) 1 2 3 4 250 119.1667 **** 1 50 123.5589 **** 5 275 127.1223 **** 2 150 137.7039 **** *** * 3 225 151.5018 **** **** 6 300 181.3709 **** **** **** 8 400 223.2038 **** **** 7 325 239.0615 * ***

Table A4.35 ANOVA of Fe concentration in lotus p etio les (Nelumbo nucifera) as a function of N supply. (Figure A4.2a) .

Univariate Results for Each DV (N_petiole) Sigma-restricted paramet erization Effect ive hyp othesi s decom position Degr. Of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1)

freedom SS MS F P Intercept 1 2689561 268956 1 9 66.242 5 0. 000000 N Conc (ppm) 7 48891 6984 2. 5092 0. 037194 Error 30 83506 2784 Total 37 132397

Table A4.36 ANOVA of Fe concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.2a).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Fe (mg kg-1) F e (mg kg-1) Fe ( mg kg-1) Fe ( mg kg-1) Intercept 1 24818541 24818541 5 4 9.9446 0.0000 00 N Conc (ppm) 7 354357 50 622 1.12 17 0.37 5742 Error 30 1353875 4 5129 Total 37 1708232

Table A4.37 ANOVA of Mn concentration in lotus leaves (Nelumbo nucifera) as a function of leaf N concentration. (Figure A4.2b).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterizat ion Effecti ve hypothesis decom pos it ion Degr. Of Mn (mg kg-1)Mn (mg kg-1) Mn (mg k g-1) Mn (mg kg-1)

freedom SS MS F P Intercept 1 56372.34 56372.34 1111.2 10 0 .000000 N Conc (ppm) 7 3396.99 485.28 9.566 0. 000003 Error 31 1572.65 50.73 Total 38 4969.64

Tukey HSD test; variable Mn (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 50.731, df = 31.000 N Conc (ppm) Mn (mg kg-1) 1 2 3 5 275 27.20326 **** 4 250 27.82939 **** **** 3 225 32.00621 **** **** 2 150 32.29556 **** **** 1 50 40.91836 **** **** **** 6 300 44.20539 ** *** *** **** 8 400 45.24919 **** **** 7 325 55.27521 ****

Table A4.38 ANOVA of Mn concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.2b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1)

freedom SS MS F P Intercept 1 10900.32 10900.32 1068.459 0.000000 N Conc (ppm) 7 258.10 36.87 3.614 0.006105 Error 30 306.06 10.20 Total 37 564.16

Tukey HSD test; variable Mn (mg kg-1) (N_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 10.202, df = 30.000 N Conc (ppm) Mn (mg kg-1 ) 1 2 5 275 12.89737 **** 8 400 15.520 13 **** **** 3 225 15.55049 **** *** * 4 250 15.97871 **** *** * 6 300 17.38349 **** **** 2 150 18.01589 **** **** 7 325 18.70184 **** **** 1 50 22.07901 ****

Table A4.39 ANOVA of Mn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.2b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 7089.984 7089.984 88.24139 0.000000 N Conc (ppm) 7 728.165 104.024 1.29467 0.286655 Error 30 2410.428 80.348 Total 37 3138.593

Table A4.40 ANOVA of Zn concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.3a).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1)

freedom SS MS F P Intercept 1 230521.3 230521.3 1725.125 0.000000 N Conc (ppm) 7 7143.8 1020.5 7.637 0.000023 Error 31 4142.4 133.6 Total 38 11286.2

Tukey HSD test; variable Zn (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 133.63, df = 31.000 N Conc (ppm) Zn (mg kg-1) 1 2 3 5 275 50.48216 **** 1 50 65.18822 **** **** 8 400 76.03864 **** **** **** 2 150 76.70671 **** **** **** 6 300 81.99273 **** **** 3 225 83.24147 **** **** 4 250 84.52998 **** **** 7 325 98.55355 ****

A 1000 ) -1 800

600 e Conc.e kg (mg

400 Organ F

200

0 60 B Leaf Petiole Roots & Stolons 50 ) -1

Organ Mn Conc. (mg kg (mg Conc. Mn Organ 20

0 100 200 300 400 500 N Supply (ppm)

Figure A4.2 Effe ct of nitrogen s upp ly o n organ nut ri ent concentrati on in lotus (Nelumbo nucifera) for: a) Iron; b) Manganese. Values are means and bars represent S.E. ( n=5). (Tables A4.34-39).

Table A4.41 ANOVA of Zn concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.3a).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hyp othesis decomp ositio n Degr. Of Zn (mg kg-1)Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1)

freedom SS MS F P Intercept 1 443926.0 443926.0 599.3952 0.000000 N Conc (ppm) 7 18697.1 2671.0 3.6064 0.006180 Error 30 22218.7 740.6 Total 37 40915.8

Tukey HSD test; variable Zn (mg kg-1) (N_petiole) Homogenous Groups, alpha = .01000 Error : Between MS = 740 .62, df = 30 .000 N Conc (ppm) Z n ( mg kg-1) 1 2 5 275 62.6834 **** 1 50 95.7589 **** *** * 3 225 103. 3785 ** ** *** * 8 400 106.5693 **** **** 4 250 116.3806 **** **** 2 150 119.4450 **** ** ** 6 300 122.8888 **** **** 7 325 141.6155 ****

Table A4.42 ANOVA of Zn concent ration in lotus roots a nd stolons (Nelumbo nucifera) as a function of N s upply. (Figure A4.3a).

Univariate Results for Each D V (N_root) Sigma-restricted parameterizat ion Effecti ve hypothesis decom pos it ion Degr. of Zn (mg kg-1) Z n (mg kg-1) Z n (mg kg- 1 ) Zn (mg kg-1) Intercept 1 2029651 2029651 449.5274 0.000000 N Conc (ppm) 7 97717 13960 3.0918 0.014123 Error 30 135452 4515 Total 37 233170

Table A4.43 ANOVA of Cu concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.3b).

Univariate Results for Ea ch DV ( N_lea f) Sigma-restricted parame terization Effec tive hy pothesi s dec omposition Degr. Of Cu (mg kg-1)Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1)

freedom SS MS F P Intercept 1 42781.39 42781.39 814.4080 0.000000 N Conc (ppm) 7 550.58 78.65 1.4973 0.204827 Erro r 31 1628.45 52.53 Total 38 2179.03

Table A4.44 ANOVA of Cu concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.3b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1)

freedom SS MS F P Intercept 1 49681.70 49681.70 1949.789 0.000000 N Conc (ppm) 7 1164.74 166.39 6.530 0.000101 Error 30 764.42 25.48 Total 37 1929.15

Tukey HSD test; variable Cu (mg kg-1) (N_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 25.481, df = 30.000 N Conc (ppm) Cu (mg kg-1) 1 2 5 275 25.07487 **** 8 400 29.44789 **** **** 6 300 36.68753 **** **** 1 50 39.13001 **** 7 325 39.3 214 5 **** 3 225 39.38404 **** 4 250 39.87824 **** 2 150 41.69409 ****

Table A 4.45 ANOVA of Cu concentrati on in lotus roo ts and stolons (Nelumbo nucifera) as a function of N s upply. (Figure A4. 3b).

Univariat e Results for Each DV (N _root) Sigma-re stricted parameterization Effective h ypothesis dec omposi tion Degr. of Cu (mg kg-1) Cu (m g kg-1) Cu (m g kg- 1) Cu (mg kg-1) Intercept 1 164642.0 1646 42.0 1396 .031 0.000000 N Conc (ppm) 7 2092.2 298.9 2.534 0.035653 Error 30 3538.1 117.9 Total 37 5630.3

350 A A

300 ) -1 250

200

150

100 Organ Zn Conc. (mg kg (mg Zn Conc. Organ

0 BB 80 ) -1 60

40 Organ Cu Conc. (mg kg (mg Conc. Cu Organ 20 Leaf Petiole Roots & Stolons

0 0 100 200 300 400 500 N Supply (ppm)

Figure A4.3 Effect of nitrogen supply on tissue nutrient concentration in lotus (Nelumbo nucifera) for: a) Zinc; b) Copper. Value s are means and bars represen t S.E. (n=5). ( Tables A4.40-45).

Table A4.46 ANOVA of B concentration in lotu s leav es (Nelumb o nucifera) as a function of N supply. (Figure A4.4a) .

Univariate Results for Each DV (N_leaf) Sigma-restricted paramet erization Effect ive hyp othesi s decom position Degr. Of B (mg kg-1) B (mg kg-1) B ( mg kg -1 ) B (mg kg-1)

freedom SS MS F P Intercept 1 343592.3 343592.3 9 34 . 8467 0.000000 N Conc (ppm) 7 8495.0 1213.6 3. 3019 0.009658 Error 31 11393.7 367.5 Total 38 19888.7

Tukey HSD test; variable B (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 367.54, df = 31.000 N Conc (ppm) B (mg kg-1) 1 5 275 50.48216 8 50 65.18822 **** 2 400 76.03864 **** 7 150 76.70671 *** * 6 300 81.99273 **** 3 225 83.2414 7 **** 1 250 84.52998 **** 4 325 98.55355

Table A4.47 ANOVA of B concentr ation in lotus pe tioles (Nelumbo nucifera) as a function of N supply. (Figure A4.4a).

Univariate Results for Each DV (N_petio le) Sigma-restricted parameterization Effecti ve hypothesis decom pos it ion Degr. Of B (mg kg-1) B (mg kg-1) B (mg kg -1) B (mg kg-1)

freedom SS MS F P Intercept 1 37208.49 3720 8.49 568 1.037 0 .000000 N Conc (ppm) 7 94.61 13 .52 2.0 64 0 .079234 Error 30 196.49 6.55 Total 37 291.10

Table A4.48 ANOVA of B concentration in l otus ro ots and st olo ns (Nelumbo nucifera) as a function of N supply. (Fi gure A4.4a).

Univariate Results for Each D V (N_roo t) Sigma-restricted parameteriz ation Effec tive hypothesi s deco mposition Degr. of B (mg kg-1) B (mg kg-1) B (mg k g-1 ) B (mg kg-1) Intercept 1 28789.54 2 8789.54 4 663.15 5 0.000000 N Conc (ppm) 7 180.46 2 5.78 4. 176 0.002569 Error 30 185.21 6 .17 Total 37 365.67

Tukey HSD test; variable B (mg kg-1) (N_root) Homogenous Groups, alpha = .01000 Error: Between MS = 6.1738, df = 30.000 N Conc (ppm) B (mg kg-1) 1 2 5 275 25.02010 **** 7 325 25.87500 **** **** 6 300 25.99990 **** **** 8 400 26.20351 **** **** 4 250 27.87319 **** **** 3 225 28.26348 **** **** 2 150 30.65034 **** **** 1 50 31.34339 ****

Table A4.49 ANOVA of Mo concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.4b).

Univariate Results for Each DV (N_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1)

freedom SS MS F P Intercept 1 998.3216 998.3216 1581.274 0.000000 N Conc (ppm) 7 64.4709 9.2101 14.588 0.000000 Error 31 19.5715 0.6313 Total 38 84.0425

Tukey HSD test; variable Mo (mg kg-1) (N_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = .63134, df = 31.000 N Conc (ppm) Mo (mg kg-1) 1 2 3 8 400 2.996790 **** 5 275 3.220837 **** **** 7 325 4.978742 **** **** 6 300 5.135329 **** **** 4 250 5.315236 **** 3 225 5.537829 **** 2 150 6.576824 **** 1 50 6.824503 ****

Table A4.50 ANOVA of Mo concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.4b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1)

freedom SS MS F P Intercept 1 1200.422 1200.422 1190.556 0.000000 N Conc (ppm) 7 44.951 6.422 6.369 0.000124 Error 30 30.249 1.008 Total 37 75.200

Tukey HSD test; variable Mo (mg kg-1) (N_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 1.0083, df = 30.000 N Conc (ppm) Mo (mg kg-1) 1 2 5 275 3.249046 **** 8 400 4.877860 **** **** 7 325 5.377918 **** **** 4 250 6.040159 **** 6 300 6.088900 **** 3 225 6.099823 **** 1 50 6.497467 **** 2 150 6.943131 ****

Table A4.51 ANOVA of Mo concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.4b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effective hypothesis decomposition Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Degr. of SS MS F P Intercept 1 15835.71 15835.71 1439.294 0.000000 N Conc (ppm) 7 712.26 101.75 9.248 0.000005 Error 30 330.07 11.00 Total 37 1042.34

Tukey HSD test; variable Mo (mg kg-1) (N_root) Homogenous Groups, alpha = .05000 Error: Between MS = 11.002, df = 30.000 N Conc (ppm) Mo (mg kg-1) 1 2 5 275 10.00690 **** 8 400 19.57766 **** 3 225 19.88567 **** 7 325 21.27197 **** 4 250 22.33042 **** 6 300 23.21426 **** 1 50 23.22369 **** 2 150 24.56473 ****

120 AA

010 ) -1 g 80

40 Organ k B Conc. (mg

0 25 BB

) 20 -1

15 c. (mc. kg Leaf Petiole 10 Roots & Stolons Organ Mo Con g

0 0 100 200 300 400 500 N Supply (ppm)

Figure A4.4 Effect of nitrogen supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Boron; b) Molybdenum. Values are means and bars represent S.E. (n=5). (Tables A4.46-51).

Table A4.52 ANOVA of Na concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.5a).

Univariate Results for Each DV (N_leaf) Sigma-restricte d parameterization Effec tive hypothesi s decomposition Degr. Of Na (mg kg-1)Na (mg kg -1)Na (mg kg -1) Na (mg k g-1)

freedom SS MS F P Intercept 1 658720621 658720 621 577.3076 0.000000 N Conc (ppm) 7 12238494 17483 56 1 .5323 0.193211 Error 31 35371680 1141022 Total 38 47610174

Table A4.53 ANOVA o f Na concentra tion i n lo tus p etio les (Nelumbo nucifera) as a function of N supply. (Figure A4.5a) .

Univariate Results for Each DV (N_ petiole) Sigma-restricted parameterization Effect ive hy pothe sis d ecomposition Degr. Of Na (mg kg-1) Na (mg kg-1 ) Na (mg k g-1) Na (mg kg-1)

freedom SS MS F P Intercept 1 633619059 63361 9059 1220.0 6 2 0.000000 N Conc (ppm) 7 5560000 79428 6 1.529 0.195400 Error 30 15580000 519333 Total 37 21140000

Table A4.54 ANOVA of Na concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.5a).

Univariate Results for Each DV (N_root) Sigma-restricted parameteriza tion Effec tive h ypothesi s d ecompositi on Degr. of Na (mg kg-1 ) Na (mg k g-1 ) Na (mg kg- 1) Na (mg kg-1) Intercept 1 1.135203E+09 1.135203E+09 1215.2 91 0.000000 N Conc (ppm) 7 1.405700E+ 07 2.008 143E+0 6 2.150 0.068422 Error 30 2.802300E+07 9.341000E+05 Total 37 4.208000E+07

Table A4.55 ANOVA of Al concentration in lotus leaves (Nelumbo nucifera) as a function of N supply. (Figure A4.5b).

Univariate Res ults for Each DV (N_leaf) Sigma-restricted paramet erization Effect ive hypothesi s decompositi on Degr. Of Al (mg kg-1)Al (mg kg -1)Al (mg kg -1) Al (mg kg-1)

freedom SS MS F P Intercept 1 66687.68 66687.6 8 783.8256 0.000000 N Conc (ppm) 7 6002.27 85 7.47 10 .0784 0. 000002 Error 31 2637.47 85.08 Total 38 8639.74

Tukey HSD test; variabl e Al (m g kg-1) (N_leaf) Hom ogen ous G roups, alpha = .01000 Error: Between M S = 85.080, df = 31 .000 N Conc (ppm) Al (mg kg- 1) 1 2 3 1 50 29.13734 **** 4 250 29.34524 **** 5 275 33.69238 **** 3 225 35.77311 **** 2 150 36.20471 **** **** 6 300 45.51554 **** **** **** 7 325 59.39029 **** **** 8 400 62.65613 ****

Table A4.56 ANOVA of Al concentration in lotus petioles (Nelumbo nucifera) as a function of N supply. (Figure A4.5b).

Univariate Results for Each DV (N_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1)

freedom SS MS F P Intercept 1 65844.85 65844.85 1387.400 0.000000 N Conc (ppm) 7 3374.83 482.12 10.159 0.000002 Error 30 1423.78 47.46 Total 37 4798.61

Tukey HSD test; variable Al (mg kg-1) (N_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 47.459, df = 30.000 N Conc (ppm) Al (mg kg-1) 1 2 3 4 250 28.25685 **** 5 275 32.14320 **** 6 300 38.41296 **** **** 2 150 38.52574 **** **** 3 225 38.69297 **** **** 8 400 49.74125 **** **** 1 50 50.76187 **** **** 7 325 58.03392 ****

Table A4.57 ANOVA of Al concentration in lotus roots and stolons (Nelumbo nucifera) as a function of N supply. (Figure A4.5b).

Univariate Results for Each DV (N_root) Sigma-restricted parameterization Effe ctive hypothes is dec ompositi on Deg r. of Al (mg kg-1 ) Al (mg kg-1) Al (m g kg-1) Al (mg kg-1) Intercept 1 887080.8 887080.8 671.2055 0.000000 N Conc (ppm) 7 54405.3 77 72.2 5.8808 0.00023 2 Error 30 39648.7 1 3 21.6 Total 37 94054.0

Tukey HSD test; variable Al (mg kg-1) (N_root) Homogenous Groups, alpha = .01000 Error: Betwe en MS = 1321.6, df = 30.000 N Conc (ppm) A l (mg k g- 1) 1 2 3 225 107.7 566 **** 4 250 112.8677 **** 5 275 122.6772 **** **** 2 150 130.2060 **** **** 6 300 165.3175 **** **** 1 50 182.1942 **** **** 7 325 195.0756 ** ** **** 8 400 211.9270 ****

7000 AA

6000 )

-1 5000 Leaf Pe oleti 4000 Roots & Stolons

3000

2000 Organ Na Conc. (mg kg (mg Na Conc. Organ Leaf 1000 Petiole Roots & Stolons

0 BB

200 ) -1

150

100 Organ Al Conc. (mg kg Conc. (mg Organ Al 50

0 0 100 200 300 400 500

N Supply (ppm)

Figure A4.5 Eff ect of nitrogen su pp ly on organ nutrie nt concentration i n lotus (Nelumbo nucifera) for: a) Sodium; b) Alumin ium. Values are m e ans and bars repre se nt S.E. (n=5). (Tabl es A4.52-57).

Table A4.58 ANOVA for the relationship between N concentration in lotus leaves (Nelumbo nucifera) and N supply. (Tables A4.172-174 & 188-190). Rank 2 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7183532774 0.7017858231 0.3427035647 89.269154205

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.730831528 0.125313434 21.79200944 2.476431733 2.985231323 0.00000 b 0.000244406 2.58679e-05 9.448235507 0.000191891 0.000296920 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 10.484281 1 10.484281 89.2692 0.00000 Error 4.1106007 35 0.11744573 Total 14.594882 36

Table A4.59 ANOVA for the relationship between N concentration in lotus petioles (Nelumbo nucifera) and N supply. (Tables A4.172-173, 175, 188-189 & 192). Rank 5 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8094447418 0.7982356090 0.3483032081 148.67375600

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.421634543 0.120200297 11.82721324 1.177614967 1.665654118 0.00000 b 0.000306977 2.51761e-05 12.19318482 0.000255866 0.000358087 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 18.036375 1 18.036375 148.674 0.00000 Error 4.2460294 35 0.12131512 Total 22.282405 36

Table A4.60 ANOVA for the relationship between N concentration in lotus roots and stolons (Nelumbo nucifera) and N supply. (Tables A4.172, 174-175 & 188, 190-191). Rank 2 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8239766138 0.8133085298 0.2522544309 159.15615236

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.322130850 0.098037290 13.48599950 1.122895105 1.521366595 0.00000 b 0.000807127 6.39779e-05 12.61571054 0.000677108 0.000937145 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 10.127472 1 10.127472 159.156 0.00000 Error 2.1634981 34 0.063632298 Total 12.29097 35

Table A4.61 ANOVA for the relationship between P concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. (Figure 4.7, Tables A4.176-178 & 192-194). Rank 6 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6588079459 0.6387378251 533.96194769 67.581521406

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3819.773835 201.2041435 18.98456846 3411.307709 4228.239962 0.00000 b 24.84002958 3.021608033 8.220798100 18.70583916 30.97422000 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 19268530 1 19268530 67.5815 0.00000 Error 9979037.7 35 285115.36 Total 29247568 36

Table A4.62 ANOVA for the relationship between P concentration in lotus petioles (Nelumbo nucifera) and peti ole N concentration. (Figure 4.7, Tables A4.176-177, 179, 192-193 & 195). Rank 30 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4888820231 0.4579051760 1010.6024331 32.52084 5546

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4861.809633 4 27.9896228 1 1.35964372 3 992.030072 5731.589193 0 .00000 b 491.3507669 86.16099862 5.702705108 316.2505506 666.4509832 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 33214101 1 33214101 32.5208 0.00000 Error 34724787 34 1021317.3 Total 67938889 35

Table A4.63 ANOVA for the relationship between P concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. (Figure 4.7, Tables A4.176, 178-179, 192, & 194-195). Rank 36 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5228100696 0.4938894678 951.30261639 37.250455712

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6841.712863 382.5654445 17.88377116 6064.246340 7619.179387 0.00000 b 346.7721218 56.81701071 6.103315141 231.3060637 462.2381798 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 33710793 1 33710793 37.2505 0.00000 Error 30769207 34 904976.67 Total 64480000 35

Table A4.64 ANOVA for the relationship between K concentration in lotus leaves (Nelumbo nucifera) as a function of leaf N concentration. (Figure 4.8a, Tables A4.180-182 & 196-198). Rank 4 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2223412198 0.1765965857 3104.1525043 10.006885912

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 26482.03354 1169.503888 22.64381831 24107.81443 28856.25266 0.00000 b 55.56434349 17.56494172 3.163366231 19.90561606 91.22307092 0.00322

Soln Vector Cova r Matrix Direct LUDecomp

Source Sum of Squares D F Mean Square F Statistic P>F Regr 96423979 1 96423979 10.0069 0.00322 Error 3.372517e+08 35 9635762.8 Total 4.3367568e+08 36

Table A4.65 ANOVA for the relations hip between K concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. (Figure 4.8a, Tables A4.180-181, 183, 196-197 & 199).

Rank 35 Eqn 1075 y=a+bx2lnx+cx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4926870938 0.4465677387 3790.7917153 16.50989 0624

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37513.33861 5 146.323963 7 .289346509 2 7054.75 47971.92723 0.00 000 b -16150.9684 3540.657402 -4.56157334 -23346.45 -8955.48685 0.00006 c 11640.83835 2601.241059 4.475109413 6354.480491 16927.19621 0.0 0008

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.7449762e+08 2 2.3724881e+08 16.5099 0 .00001 Error 4.8858346e+08 34 14370102 Total 9.6308108e+08 36

Table A4.66 ANOVA for the relationship between K concentration in lotus roots and stolons (Nelumbo nucifer a) and roots and stolon N concentration. (Figure 4.8a, Tables A4.180, 182-183, 196 & 198-199). Rank 9 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1798752229 0.1330109499 5973.4932728 7.8957595303

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 48539.05256 2264.017945 21.43934091 43947.41135 53130.69377 0.00000 b -894.292209 318.2603169 -2.80993942 -1539.75405 -248.830370 0.00796

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.817414e+08 1 2.817414e+08 7.89576 0.00796 Error 1.2845744e+09 36 35682622 Total 1.5663158e+09 37

Table A4.67 ANOVA for the relationship between Ca concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. (Figure 4.8a, Tables A4.184-186 & 200-202). Rank 33 Eqn 1059 y=a+bx2+cx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3707857994 0.3117969681 2215.3284393 9.7231843836

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6560.242110 4324.073479 1.517143994 -2237.15153 15357.63575 0.13875 b 5775.259885 1448.228774 3.987809101 2828.816291 8721.703479 0.00035 c -2383.36186 584.0585135 -4.08069022 -3571.63784 -1195.08588 0.00027

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 95436557 2 47718278 9.72318 0.00048 Error 1.6195344e+08 33 4907680.1 Total 2.5739e+08 35

Table A4.68 ANOVA for the relationship between Ca concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. (Figure 4.8a, Tables A4.184-185, 187, 200-201 & 203). Rank 127 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0572298674 0.0033572884 1452.3322589 2.1853420619

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 13954.07132 346.2640883 40.2989273 13251.8152 14656.32744 0.00000 b -18.4860945 12.50505068 -1.47829025 -43.8475127 6.875323765 0.14803

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4609474.2 1 4609474.2 2.18534 0.14803 Error 75933684 36 2109269 Total 80543158 37

Table A4.69 ANOVA for the relationship between Ca concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. (Figure 4.8a, Tables A4.184, 186-187, 200 & 202-203). Rank 1 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0866437097 0.0295589415 1404.2606925 3.1304787081

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12213.32619 513.0500454 23.80533108 11169.51802 13257.13436 0.00000 b -63.547158 35.91623096 -1.76931589 -136.619279 9.524963248 0.08608

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6173141.5 1 6173141.5 3.13048 0.08608 Error 65074287 33 1971948.1 Total 71247429 34

Table A4.70 ANOVA for the relationship between Mg concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 276 Eqn 6722 y=a+bx2+cx4+dx6 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0142141973 0.0000000000 565.71246311 0.1489979247

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6394.622600 1708.455259 3.742926580 2910.205128 9879.040072 0.00074 b 182.6284858 359.0448533 0.508650894 -549.648320 914.9052916 0.61460 c -13.1982889 23.73049528 -0.55617418 -61.5969531 35.20037534 0.58208 d 0.29100428 5 0.488920240 0.5951 97870 -0.70615512 1.288163688 0.55603

Soln Vector Covar Matrix GaussElim LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 143051.68 3 47683.894 0.148998 0.92955 Error 9920948.3 31 320030.59 Total 10064 000 34

Table A4.71 ANOVA for the relationship between Mg concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. Rank 2643 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0881959025 0.0345 603673 109 9.7259842 3 .3854383804

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 7078.788952 279.5463724 25.32241392 6511.279645 7646.298259 0.00000 b -15.836033 5 8.606745376 -1.839 95608 -33.3086555 1.636588525 0.07427

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 4094339.8 1 4094339.8 3.38544 0.07427 Error 42328903 35 1209397.2 Total 46423 243 36

Table A4.72 ANOVA for the relationship between Mg concentration in lotus roots and stolons (Nelumbo nucifera) and ro o ts and stolon N concentration. (Figure A4.6a). Rank 1 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3336126201 0.2944 133624 495 .61268345 1 7.522003049

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 5588.511539 148.7508177 37.56961895 5286.531325 5890.491753 0.00000 b -31.175311 5 7.447644295 -4.185 92917 -46.2948333 -16.0557898 0.00018

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 4303963.5 1 4303963.5 17.522 0.00018 Error 8597117.6 35 245631.93 Total 12901081 36

35 A

30 ) -1 25

Root Mg Conc. (mg kg Mg Conc. (mg Root 10

0 500 B Leaf Petiole 400 Leaf )

-1 Nrtc vs RBpred g kg 300

200 Organ Fe Conc. (m 100

0 0123456 N Conc. (%)

Figure A4.6 Nutrient concentratio n in org an s of lotus (Nelumbo nuci fera) as a function of o rgan nitrogen co ncentration a) Magnesiu m in ro ots and stolons, the re gression equation is y = 5 588.51 + (-31.18x3) (r2 = 0.29); b) Iron in leaves, the regression equation is y = 76.50 + 5.41x2 (r2 = 0.30). Lines represent leaves (____) and roots and stolons (----) respectively. (Tables A4.72 & 76-77).

Table A4.73 ANOVA for the relationship between S concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 393 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0432615529 0.0000000000 1157.8259630 1.6730564779

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8372.448197 2238.339131 3.740473497 3837.142322 12907.75407 0.00062 b -1483.57854 1146.978409 -1.29346684 -3807.57755 840.4204633 0.20387

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 2242834.2 1 2242834.2 1.67306 0.20387 Error 49600756 37 1340561 Total 51843590 38

Table A4.74 ANOVA for the relationship between S concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. Rank 1330 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0176706762 0.0000000000 716.43780109 0.6116105626

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5571.813066 185.1890891 30.08715629 5195.463557 5948.162576 0.00000 b -4.40681480 5.634914236 -0.78205534 -15.8583383 7.044708715 0.43959

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 313929.38 1 313929.38 0.611611 0.43959 Error 17451626 34 513283.12 Total 17765556 35

Table A4.75 ANOVA for the relationship between S concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. Rank 9 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0806720419 0.0281390158 1171.6235737 3.1590396920

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6742.572761 557.2829288 12.09901185 5612.350597 7872.794926 0.00000 b 235.7044628 132.6142716 1.777368755 -33.2497457 504.6586714 0.08396

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 4336419.5 1 4336419.5 3.15904 0.08396 Error 49417265 36 1372701.8 Total 53753684 37

Table A4.76 ANOVA for the relationship between Fe concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. (Figure A4.6b). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3350288637 0.2959129145 37.676792896 17.633863473

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 76.50410753 20.06375114 3.813051058 35.77252728 117.2356878 0.00053 b 5.411147900 1.288592702 4.199269398 2.795165640 8.027130160 0.00017

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 25031.987 1 25031.987 17.6339 0.00017 Error 49683.925 35 1419.5407 Total 74715.913 36

Table A4.77 ANOVA for the relationship between Fe concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. (Figure A4.6b). Rank 5 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2357368840 0.1907802302 43.479435596 10.795746608

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 235.0002717 11.13791921 21.09911800 212.3890936 257.6114497 0.00000 b 1.124677026 0.342295731 3.285688148 0.429779749 1.819574303 0.00232

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 20408.941 1 20408.941 10.7957 0.00232 Error 66166.146 35 1890.4613 Total 86575.088 36

Table A4.78 ANOVA for the relationship between Fe concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. Rank 10 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1052080143 0.0525731917 197.46793087 4.1152363466

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 616.1508981 94.63850200 6.510573234 424.0245249 808.2772712 0.00000 b 45.45731738 22.40817107 2.028604532 -0.03368835 90.94832311 0.05016

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 160467.81 1 160467.81 4.11524 0.05016 Error 1364775.4 35 38993.584 Total 1525243.2 36

Table A4.79 ANOVA for the relationship between Mn concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 2774 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0215813893 0.0000000000 10.405810132 0.7940670863

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 34.32378227 3.900073742 8.800803405 26.41406611 42.23349843 0.00000 b 0.053206729 0.059708747 0.891104419 -0.06788822 0.174301681 0.37879

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 85.982286 1 85.982286 0.794067 0.37879 Error 3898.1118 36 108.28088 Total 3984.0941 37

Table A4.80 ANOVA for the relationship between Mn concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. Rank 3006 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0006670250 0.0000000000 3.5278749335 0.0233614583

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.60888001 0.903718860 18.37837047 14.77423319 18.44352683 0.00000 b 0.004245030 0.027773510 0.152844556 -0.05213819 0.060628252 0.87940

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.29075441 1 0.29075441 0.0233615 0.87940 Error 435.60655 35 12.445902 Total 435.89731 36

Table A4.81 ANOVA for the relationship between Mn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. Rank 26 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1274641877 0.0761385517 2.2716003427 5.1129667212

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10.59328677 0.878865897 12.05335969 8.809094149 12.37747940 0.00000 b 0.286377883 0.126649358 2.261187016 0.029266018 0.543489749 0.03007

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 26.383768 1 26.383768 5.11297 0.03007 Error 180.60588 35 5.1601681 Total 206.98965 36

Table A4.82 ANOVA for the relationship between Zn concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 37 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0981472717 0.0450971112 14.013685129 3.8089971906

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 62.63490404 7.472110455 8.382491722 47.46571337 77.80409471 0.00000 b 0.947012956 0.485233296 1.951665235 -0.03806301 1.932088918 0.05902

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 748.02371 1 748.02371 3.809 0.05902 Error 6873.418 35 196.38337 Total 7621.4417 36

Table A4.83 ANOVA for the relationship between Zn concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. Rank 401 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0428492862 0.0000000000 26.487275925 1.5668640233

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 98.53444699 6.637293277 14.84557679 85.06002529 112.0088687 0.00000 b 0.261563092 0.208958868 1.251744392 -0.16264596 0.685772147 0.21896

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 1099.2739 1 1099.2739 1.56686 0.21896 Error 24555.153 35 701.57579 Total 25654.426 36

Table A4.84 ANOVA for the relationship between Zn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. Rank 34 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0694378209 0.0162628393 77.634999880 2.6862918021

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 195.9760239 24.99623263 7.840222437 145.2813145 246.6707333 0.00000 b 3.340275815 2.038007302 1.638991093 -0.79299457 7.473546197 0.10993

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 16190.8 1 16190.8 2.68629 0.10993 Error 216978.96 36 6027.1932 Total 233169.76 37

Table A4.85 ANOVA for the relationship between Cu concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 78 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0405538996 0.0000000000 5.6879914952 1.4793811622

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 27.33600846 3.876642749 7.051464431 19.46600528 35.20601164 0.00000 b 0.609188292 0.500854414 1.216298139 -0.40760023 1.625976809 0.23201

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 47.862785 1 47.862785 1.47938 0.23201 Error 1132.3637 35 32.353247 Total 1180.2264 36

Table A4.86 ANOVA for the relationship between Cu concentration in lotus petioles (Nelumbo nucifera) and petiole N concentration. Rank 24 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0327051909 0.0000000000 7.1996552769 1.2171954821

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37.60954047 1.804054831 20.84722694 33.95074769 41.26833325 0.00000 b -0.06194826 0.056149894 -1.10326583 -0.17582552 0.051929004 0.27723

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 63.093372 1 63.093372 1.2172 0.27723 Error 1866.0613 36 51.835036 Total 1929.1547 37

Table A4.87 ANOVA for the relationship between Cu concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon N concentration. Rank 263 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0354530383 0.0000000000 12.282193364 1.3232216057

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 59.61545444 5.842027118 10.20458366 47.76727429 71.46363459 0.00000 b 1.599169083 1.390202590 1.150313699 -1.22029245 4.418630615 0.25760

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 199.61099 1 199.61099 1.32322 0.25760 Error 5430.6819 36 150.85227 Total 5630.2928 37

Table A4.88 ANOVA for the relationship between B concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 40 Eqn 67 y0.5=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1356477051 0.0862561453 19.378051900 5.6496840586

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 11.02514079 1.038454772 10.61687142 8.919056898 13.13122468 0.00000 b -0.08540123 0.068007845 -1.25575562 -0.22332754 0.052525069 0.21729

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 2121.5066 1 2121.5066 5.64968 0.02290 Error 13518.32 36 375.5089 Total 15639.827 37

Table A4.89 ANOVA for the relationship between B concentration in lotus petioles (Nelumbo nucifera) and peti ole N concentration. Rank 4 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0927937010 0.0394286246 2.3116867011 3.579979 0405

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 31.97284084 0 .587622408 5 4.41052006 3 0.77990393 33.16577775 0 .00000 b -0.03423132 0.018091869 -1.89208325 -0.07095977 0.002497124 0.06678

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 19.131034 1 19.131034 3.57998 0.06678 Error 187.03634 35 5.3438954 Total 206.16737 36

Table A4.90 ANOVA for the relationship between B concentration in lotus roots and stolons (Nelumbo nucifer a) and roots and stolon N concentration. Rank 1017 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0642382703 0.0057531622 2.3685155449 2.265387 4955

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 29.70881254 1 .647779038 1 8.02960947 2 6.35638089 33.06124420 0 .00000 b -0.97441838 0.647402267 -1.50512043 -2.29156819 0.342731440 0.14181

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 12.70852 1 12.70852 2.26539 0.14181 Error 185.12557 33 5.6098659 Total 197.83409 34

Table A4.91 ANOVA for the relationship between Mo concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. (Figure A4.7a). Rank 15 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4673890990 0.4360590460 1.0649945510 30.714013620

Parm Value Std Error t-value 9 5% Confidence Limits P>|t| a 8.0544057 25 0.571775462 14.08665860 6.893639827 9.215171623 0.00000 b -0.20412349 0.036831948 -5.54202252 -0.27889632 -0.12935066 0.00000

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares D F Mean Square F Statistic P>F Regr 34.836246 1 34.836246 30.714 0.00000 Error 39.697469 35 1.134213 4 Total 74.533714 36

Table A4.92 ANOVA for the relationship between Mo concentration in lotus petioles (Nelumbo nucifera) and petio le N concentratio n. Rank 2865 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.00785847 00 0.0000000 000 1.4396067494 0.2851 457276

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 5.749132 652 0.360729703 15.93750834 5.017538906 6.480726399 0.00000 b -0.00599535 0.011227450 -0.53399038 -0.02876567 0.016774973 0.59663

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares D F Mean Square F Statistic P>F Regr 0.59095528 1 0.59095528 0.285146 0.59663 Error 74.608833 36 2.072467 6 Total 75.199789 37

Table A4.93 ANOVA for the relationship between Mo concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stol o n N conc entration. Rank 2931 Eqn 4 y=a+bx2

r2 Coef Det DF Adj r 2 Fit S td Err F-va lu e 0.00642401 32 0.0000000 000 4.5885256719 0.2198 286314

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 21.79838 919 1.792089581 12.16367163 18.15642499 25.44035340 0.00000 b -0.11618918 0.247812694 -0.46885886 -0.61980516 0.387426809 0.64216

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.6283968 1 4.6283968 0.2198 29 0.64216 Error 715.85531 34 21.054568 Total 720.4837 35

Table A4.94 ANOVA for the relationship b etween Na concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. Rank 59 E qn 1059 y=a+bx2+cx2.5 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.0680190033 0.0000000 000 1 110.2024059 1.3136985234

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2630.460237 2136.557364 1.231167616 -1702.67894 6963.599409 0.22624 b 273.2951189 714.3111966 0.382599517 -1175.39513 1721.985371 0.70427 c -86.4217098 288.2654785 -0.29979903 -671.051197 498.2077777 0.76605

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 3238396.6 2 1619198. 3 1.3137 0 .28140 Error 44371778 36 1232549.4 Total 47610174 38

Table A4.95 ANOVA for the relationship b etween Na concentration in lotus petioles (Nelumbo nucifera) ande petio le N concentratio n . Rank 2770 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit S td Err F-v alu e 0.00816080 18 0.000000 0000 763 .17 102803 0.2 9620614 61

Parm V alue Std Erro r t-value 95% Confidence Limits P>|t| a 4172.5718 18 181.9547274 22.93192312 3803.550527 4541.593109 0.00000 b -3.57633654 6.571149489 -0.54424824 -16.9032454 9.750572313 0.58963

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares D F Mean Square F Statistic P>F Regr 172519.35 1 172519.35 0.296206 0.58963 Error 20967481 36 582430.0 2 Total 21140000 37

Table A4.96 ANOVA for the relationship between Na concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stol o n N conc entration. Rank 2851 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r 2 Fit Std Err F-val ue 0.00164432 63 0.0000000 000 790 .14 630423 0.0 559991749

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5538.238463 287.4372663 19.26764241 4954.095657 6122.381269 0.00000 b -27.0216400 114.1881115 -0.23664145 -259.079803 205.0365226 0.81435

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 34962.031 1 34962.03 1 0.0559992 0 .81435 Error 21227260 34 624331.18 Total 21262222 35

Leaf Petiole 25 A Roots & Stolons ) -1 20

10 Organ Mo Conc. (mg kg Organ Mo Conc. (mg

B 250 ) -1 200

150

100 Organ Al Conc. (mg kg Conc. (mg Organ Al

0123456 N Conc. (%)

Figure A4.7 Nutrient concen trati on in organs of lotu s (Nelumbo nucifera) as a function of organ N concentration a) Molybdenum, reg re ssion equation is y = 8.05 + (-0.20x2) (r2 = 0.44) for leaves; b) Aluminium, regressi on equations a re y = 24.56 + 0.2 8x3 (r2 = 0.25), y = 36.73 + 0.23x3 (r2 = 0.13), & y = 118.99 + 2.05x3 (r2 = 0.21) for leave s (____), petioles (…..) and roots and stolons (----) respectively. (Tables A4 .91 & 97-99).

Table A4.97 ANOVA for the relationship between Al concentration in lotus leaves (Nelumbo nucifera) and leaf N concentration. (Figure A4.7b). Rank 2 Eqn 7 y=a +bx3

r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.28560554 50 0.2459169 642 12.9 15 718592 14.792 115324

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 24.84047902 4.823290141 5.150110878 15.06756490 34.61339315 0.00001 b 0.280885537 0.073032175 3.846051914 0.132908294 0.428862779 0.00046

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares D F Mean Square F Statistic P>F Regr 2467.5584 1 2467.5584 14.7921 0.00046 Error 6172.1841 37 166.8157 9 Total 8639.7425 38

Table A4.98 ANOVA for the relationship between Al concentration in lotus petioles (Nelumbo nucifera) and petio le N concentratio n. (Figure A4.7b ). Rank 72 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-valu e 0.17512893 10 0.127993 4414 10.485748822 7. 6431841938

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 36.72849975 2.627468273 13.97866536 31.39974711 42.05725239 0.00000 b 0.226086096 0.0 81778039 2.764630933 0.060232546 0.391939646 0.00893

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 840.3752 1 840.3752 7.64318 0 .00893 Error 3958.2334 36 109.95093 Total 4798.6086 37

Table A4.99 ANOVA for the re lat ionship bet ween Al concentration in lotus roots and stolons (Nelumbo nucifera) and roots and sto lo n N conc entration. (Figure A4.7b). Rank 2 Eq n 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.2544300114 0.2118260 120 4 4.134841257 12.285205344

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 118.9854252 12 .56688186 9.468174085 93.49860745 144.4722429 0.00000 b 2.049906706 0.584847834 3.505025727 0.863780322 3.236033090 0.00124

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 23930.158 1 23930.15 8 12.2852 0 .00124 Error 70123.832 36 1947.8842 Total 94053.989 37

Table A4.100 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 4 .9a). Rank 25 E qn 64 y0.5=a+bx r2 Coef Det DF Adj r2 F it Std Err F-value 0.5250920109 0.4963097085 3.2355456694 37.592815407

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.95021266 1.031898267 1.889927257 -0.14685693 4.047282246 0.06732 b 0.435090285 0.261867738 1.66148869 -0.09708899 0.967269558 0.10581

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err 0.5250920109 0.4963097085 3.2355456694 Source Sum of Squares DF Mean Square F Statistic P>F Regr 393.55 1 393.55 37.5928 0 .00000 Error 355.9377 34 10.468756 Total 749.4877 35

Table A4.101 ANOVA for the rel a tionship bet ween total dry mass of lotus (Nelumbo nucifera) and petiole N conce ntration. (Figure 4 .9a). Rank 12 E qn 1 y=a+bx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.2708332731 0.2252603 527 3 .7995730329 12.257139122

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.74625214 2.247312251 1.666992265 -0.82593901 8.318443292 0.10498 b 2.802640957 0.800521327 3.501019726 1.173968072 4.431313842 0.00135

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 176.95332 1 176.9533 2 12.2571 0 .00135 Error 476.41292 33 14.436755 Total 653.36624 34

Table A4.102 A NOVA for the relationship b etween total dry mass of lotus (Nelumbo nucifera) and roots and stolo ns N concentration. (Figure 4. 9a). Rank 4 Eq n 1 y=a+bx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.3058248491 0.2649910 167 4 .2089036434 15.419551827

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.125147355 2.827374664 0.397947739 -4.61472836 6.865023075 0.69309 b 4.377900201 1.114884767 3.926773717 2.114563797 6.641236605 0.00039

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P >F Regr 273.15535 1 273.15535 15.4196 0.00039 Error 620.02045 35 17.71487 Total 893.1758 36

Table A4.1 03 ANOVA for the relationship between leaf d ry mass of lotu s (Nelumbo nucifera) and leaf N concentration. (Figur e 4. 9b). Rank 3 Eq n 83 y0.5=a+b/x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5712815045 0.5460627694 1.2385363632 46.638651851

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.544463626 0.352898678 7.210181808 1.828041223 3.260886029 0.00000 b -6.5165431 4.679064301 -1.39270219 -16.0155486 2.982462429 0.17249

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err 0.5712815045 0.5460627694 1.2385363632 Source Sum of Squares DF Mean Square F Statistic P>F Regr 71.542401 1 71.54240 1 46.6387 0 .00000 Error 53.689031 35 1.5339723 Total 125.23143 36

Table A4.104 ANOVA f o r the relat ionship between petiole dry mass of lotus (Nelumbo nucifera) and petio le N concentration . (Figure 4 .9b). Rank 2096 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 F it Std Err F-value 0.0206016924 0 0.787159836 0.7572618029

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.7608435 2.381363814 1.999208802 -0.06878616 9.590473164 0.05318 b -0.01778344 0.02043585 -0.87020791 -0.05922926 0.023662386 0.38995

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.46921502 1 0.469215 02 0.757262 0 .38995 Error 22.306342 36 0.61962061 Total 22.775557 37

Table A4.105 ANOVA for the rel a tionship bet ween roots and stolons dry mass of l otus (Nelumb o nucifera) and roots and stolons N concentratio n. (Figure 4.9b). Rank 2 Eq n 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1768874081 0.1298524028 1.9710606592 7.7364223957

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.843642992 0.747053106 3.806480382 1.32854907 4.358736915 0.00053 b 0.292095044 0.1 050 15669 2.781442503 0.079113397 0.505076692 0.00856

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P >F Regr 30.056621 1 30.056621 7.73642 0.00856 Error 139.86288 36 3.8850801 Total 169.91951 37

Table A4.1 06 ANOVA for the re lationshi p between number of leav es of lotus (Nelumbo n ucifer a) and leaf N concentration. (Figure 4 .10a). Rank 9 Eq n 3 y=a+bx1.5

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2023190183 0.1553966076 10.035552087 8.8771900093

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.627416979 7.025080803 0.51635235 -10.6342553 17.88908921 0.60886 b 2.748398203 0.92244801 2.979461362 0.875729186 4.62106722 0.00522

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 894.04227 1 894.04227 8.87 719 0.00522 Error 3524.9307 35 100.71231 Total 4418.973 36

Table A4.107 ANOVA for the relation s hip between number of leaves of lotus (Nelumbo nu cifera) and petiole N concentration. (Figure 4.10a). Rank 12 Eqn 3 y= a+bx1.5

r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.40581854 63 0.3708666 961 9.1166281481 23.904 564899

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 6.962453586 3.849283306 1.808766213 -0.85200697 14.77691414 0.07908 b 3.769022325 0.77088268 4.889229479 2.204047285 5.333997365 0.00002

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1986.77 79 1 1986.7779 23.9 046 0.00002 Error 2908.9518 35 83.112909 Total 4895.7297 36

Table A4.108 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and roo ts and stolons N concentration. (Figure 2.10a). Rank 8 Eqn 3 y=a +bx1.5

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3982329721 0.3617622432 8.6390037462 22.500270747

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 4.8 44074272 4.20 47636 78 1 .15 2044358 -3.701 03362 13.389182 17 0.25734 b 4.7 47614157 1.00 08789 24 4 .7434 45029 2. 71358346 6.781644854 0.00004

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 1679.2489 1 1679.2489 22.5003 0.00004 Error 2537.50 11 34 74.6323 86 Total 4216.75 35

Table A4.109 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 4.10 b). Rank 11 Eqn 3 y= a+bx1.5

r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.50534174 65 0.4762442 021 16.1 50 24558 35.755 920373

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 5.023008238 7.316014377 0.686577141 -9.82929055 19.87530702 0.49687 b 8.348230491 0.99039931 8.429156208 6.337613001 10.35884798 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9326.23 22 1 9326.2322 35. 7559 0.00000 Error 9129.0651 35 260.83043 Total 18455.297 36

Table A4.110 ANOV A for the relati o nship between n u mber of nodes of lotus (Nelumbo nucifera) and petiole N concentration. (Figure 4.10b). Rank 2 Eqn 2 y=a +bxlnx r2 Coef Det DF Adj r 2 Fit S td Err F-va lu e 0.60797295 68 0.5834712 666 13.5 09 556067 51.17 78662 2

Parm V alue Std Erro r t-value 95% Confidence Limits P>|t| a 40.07992232 4.556275845 8.796640871 30.81010941 49.34973522 0.00000 b 10.18599644 1.423844077 7.153870716 7.28916389 13.082829 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9340.37 54 1 9340.3754 51.1 779 0.00000 Error 6022.76 75 33 182.50811 Total 15363.143 34

Table A4.111 ANOVA for the relationship between number of nodes of l otus (Nelumbo nucifera) and root s and stolons N concentration. (Figure 4.10b). Rank 4 Eqn 4 y=a +bx2 r2 Coef Det DF Adj r2 Fit S td Err F-valu e 0.30582484 91 0.2649910 167 4.2 089 036434 15.41 95518 27

Parm V alue Std Erro r t-value 95% Confidence Limits P>|t| a 1.125147355 2.827374664 0.397947739 -4.61472836 6.865023075 0.69309 b 4.377900201 1.114884767 3.926773717 2.114563797 6.641236605 0.00039

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 273.155 35 1 273.155 35 15.4196 0.00039 Error 620.02045 35 17.71487 Total 893.1758 36

Table A4.1 12 ANOVA for the relation sh ip between number of st olons of lotus (Nelumb o nucifera) and leaf N concentration. (Figur e 4. 11a). Rank 3 Eq n 3 y=a+bx1.5

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1612951196 0.1088760645 4.862158508 6.3463788869

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8.048978528 3.503440199 2.297449955 0.921175852 15.1767812 0.02807 b 1.173740651 0.465917634 2.519202034 0.225824098 2.121657204 0.01679

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 150.032 11 1 150.03211 6.34 638 0.01679 Error 780.13932 33 23.640585 Total 930.17143 34

Table A4.113 ANOVA for the relationship between number of stolons of lotus (Nelumbo nucifera) and petiole N co ncentration . (Fi gure 4 .11a). Rank 1 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit Std Err F-va lue 0.32469412 73 0.2849702 524 5.1670406361 16 .828366099

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12.67124369 1.298986361 9.754716498 10.03416118 15.3083262 0.00000 b 0.16540184 0.040319892 4.102239157 0.083548107 0.247255572 0.00023

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares D F Mean Square F Statistic P>F Regr 449.28892 1 449.28892 16.8 284 0.00023 Error 934.44081 35 26.69830 9 Total 1383.7297 36

Table A4.114 ANOVA for the relation ship between number of stolons of lotus (Nelumbo nucifera) and roots and stolons N co nc entration. (Fi gure 4.11a). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-val ue 0.25871399 75 0.2151089 386 5.4135794334 12 .215244701

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10.23004047 2.054710858 4.978822414 6.058755672 14.40132527 0.00002 b 1.008248867 0.288480629 3.495031431 0.422602054 1.593895679 0.00131

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares D F Mean Square F Statistic P>F Regr 357.99025 1 357.99025 12.2152 0.00131 Error 1025.7395 35 29.30684 2 Total 1383.7297 36

Table A4.115 ANOVA for the r elationshi p between total leaf area o f lotus (Nelumbo nuci fera) and leaf N conc entration. (Figure 4 .11 b). Rank 80 E qn 3 y=a+bx1.5

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5008065352 0.4705523859 2.9372432611 34.109866015

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.098520833 1.350749822 1.553596972 -0.64653307 4.843574741 0.12954 b 1.37167061 0.183303131 7.483072436 0.999153828 1.744187392 0.00000

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 294.27939 1 294.27939 34 .1099 0.00000 Error 293.33153 34 8.627398 Total 587.61092 35

Table A4.116 ANOVA for the relatio nship between to tal leaf area of l o tus (Nelumbo nuc ifera) and petiole N concen tration. (Figure 4. 11b). Rank 217 Eqn 803 0 [Gaussian_] y=aexp(-0.5(( x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-val ue 0.35035444 73 0.2894501 767 3.4011531957 8.8 984652566

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.69827418 0.89193885 16.47901556 12.88361095 16.51293741 0.00000 b 3.455697345 0.270710904 12.76526841 2.90493187 4.006462819 0.00000 c 1.723896515 0.362202203 4.759486561 0.986990594 2.460802437 0.00004

Procedure Minimization Iterations LevMarqdt Least Squares 12

Source Sum of Squares DF Mean Square F Statistic P >F Regr 205.8721 2 102.93605 8.89847 0.00081 Error 381.73882 33 11.567843 Total 587.61092 35

Table A4.117 ANOVA for the relationship between total leaf area o f lotus (Nelumbo nucifera) and roots and stolons N concentrat ion. (Fig ur e 4.11b). Rank 1258 Eqn 1 y=a+bx

r2 Coef Det DF Adj r2 F it Std Err F-value 0.2281803993 0.1799416742 3.3890016226 9.7561051417

Parm Value S td Error t-value 95% Confidence Limits P>|t| a 4.968756893 2.34146013 2.122076234 0.205020443 9.732493344 0.04143 b 2.877532 0.921259387 3.123476451 1.003215685 4.751848315 0.00371

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 112.05211 1 112.05211 9.75611 0.00371 Error 379.01596 33 11.485332 Total 491.068 06 3 4

Table A4.1 18 ANOVA for the relations h ip between total stol on le ngth of lotus (Nelumbo nucifera) and leaf N concentration. Rank 16 E qn 7 y=a+bx3

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0477119488 0 652.08951587 1.803687607

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1646.198581 249.0817465 6.60906953 1141.037386 2151.359777 0.00000 b 5.1975438 3.870058209 1.343014373 -2.65129803 13.04638563 0.18767

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 766965.37 1 766965.37 1.8036 9 0.18767 Error 15307947 36 425220.74 Total 16074912 37

Table A4.119 ANOVA for the relatio nship between t o tal stolon length of lotus (Nelumbo nucifera) and petiole N co ncentration . Rank 274 Eqn 8 y =a+bex r2 Coef Det DF Adj r2 Fit Std Err F-val ue 0.05356454 57 0 449 .91 117162 1.8 110748662

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1670.499359 114.3417143 14.60971064 1437.592909 1903.405809 0.00000 b 5.862105172 4.355975256 1.345761816 -3.01072607 14.73493641 0.18784

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 366597.89 1 366597.89 1.8110 7 0.18784 Error 6477442 32 202420.06 Total 6844039.9 33

Table A4.120 ANOV A for the relati on ship between to t al stolon length of lotus (Nelumbo nucifera) and roots an d stolons N co nce ntration . Rank 30 Eqn 5 y= a+bx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-va lue 0.05201998 87 0 650 .61 285551 1.9 754842627

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1737.225897 183.9921233 9.441849278 1364.072575 2110.379218 0.00000 b 33.38506689 23.75283564 1.405519215 -14.7879166 81.55805035 0.16844

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 836216 .74 1 836216 .74 1.97548 0.16844 Error 152386 95 36 423297.09 Total 160749 12 37

Table A4.121 A NOVA for the rel ati onship between internode length of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 4.12 ). Rank 21 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r 2 Fit Std Err F-valu e 0.18528136 9 0.137356 7437 2 5.783983496 7.9596165709

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 160.0246226 15.64696207 10.22720077 128.2596009 191.7896444 0.00000 b -8.36789248 2.965992289 -2.82127924 -14.3891769 -2.34660802 0.00783

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5291.663 1 5291.663 7.95962 0.00783 Error 23268.483 35 664.8138 Total 28560.146 36

Table A4.122 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and petiole N concentration. (Figure 4.12). Rank 1 Eqn 8098 y=aexp(-bx) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2808296753 0.2372435951 22.324121035 13.276700434

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 173.4259736 19.34987585 8.962640119 134.1022947 212.7496525 0.00000 b 0.152459889 0.042307 3.60365631 0.06648172 0.238438058 0.00099

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 6616.6611 1 6616.6611 13.2767 0.00089 Error 16944.457 34 498.36638 Total 23561.118 35

Table A4.123 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and roots and stolons N concentration. (Figure 4.12). Rank 10 Eqn 8102 y=a/(1+abx) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3067103987 0.2646928471 21.918752475 15.041554835

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 220.7732871 45.42426088 4.860250511 128.4600824 313.0864919 0.00003 b 0.001722751 0.000415722 4.14399734 0.000877902 0.002567599 0.00021

Procedure Minimization Iterations LevMarqdt Least Squares 10

Source Sum of Squares DF Mean Square F Statistic P>F Regr 7226.4399 1 7226.4399 15.0416 0.00046 Error 16334.678 34 480.43171 Total 23561.118 35

Table A4.124 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and total leaf area). (Figure 4.13, Table 4.4). Rank 2 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8369057077 0.8260327549 1.8600432082 159.074095

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.679748986 0.865134412 1.941604637 -0.08470428 3.444202251 0.06132 b 0.828839327 0.065715924 12.61245793 0.694810817 0.962867838 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 550.35831 1 550.35831 159.074 0.00000 Error 107.25258 31 3.4597607 Total 657.61089 32

Table A4.125 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the number of leaves. (Figure A4.8a, Table 4.4). Rank 12 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4474454207 0.4149422102 3.9366733514 28.342158969

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.090076134 1.805008229 1.711945733 -0.57428538 6.754437649 0.09576 b 0.570112738 0.107088856 5.323735434 0.352710802 0.787514673 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 439.22969 1 439.22969 28.3422 0.00001 Error 542.4089 35 15.497397 Total 981.63859 36

Table A4.126 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the number of stolons. (Figure A4.9a, Table 4.4). Rank 3 Eqn 8116 y=a0.5bx-0.25b2x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6496940033 0.6290877681 2.9275661922 64.912648727

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 23.71473754 7.112385485 3.334287432 9.275827379 38.15364769 0.00203 b 0.173382071 0.042073361 4.120946551 0.087968608 0.258795535 0.00022

Procedure Minimization Iterations LevMarqdt Least Squares 7 Source Sum of Squares DF Mean Square F Statistic P>F Regr 556.34319 1 556.34319 64.9126 0.00000 Error 299.97253 35 8.5706438 Total 856.31572 36

Table A4.127 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the number of nodes. (Figure A4.8b, Table 4.4). Rank 25 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4761447101 0.4462101221 3.8060042387 32.721268441

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.65625086 1.93721645 0.854964276 -2.2726062 5.58510792 0.39823 b 0.1498245 0.026191946 5.720250732 0.096704771 0.202944229 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 473.98944 1 473.98944 32.7213 0.00000 Error 521.48406 36 14.485668 Total 995.4735 37

Table A4.128 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the internode length. (Figure A4.10, Table 4.4). Rank 1 Eqn 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2217893336 0.1773201526 4.638869875 10.259967323

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 15.27861627 1.230603925 12.41554326 12.78283583 17.77439671 0.00000 b -3.9872e-05 1.2448e-05 -3.20311837 -6.5118e-05 -1.4627e-05 0.00284

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 220.7854 1 220.7854 10.26 0.00284 Error 774.68809 36 21.519114 Total 995.4735 37

Table A4.129 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the total stolon length. (Figure A4.9b, Table 4.4).

Rank 15 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4702205662 0.4399474557 3.8274642961 31.952807727

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.039208399 2.232295547 0.017564161 -4.48809681 4.566513604 0.98608 b 0.047357798 0.008377935 5.652681463 0.030366558 0.064349038 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 468.09211 1 468.09211 31.9528 0.00000 Error 527.38139 36 14.649483 Total 995.4735 37

20 ) -1

10 Total Dry Mass (g plant 5

0 0 102030405060

Number of Leaves

20 ) -1 t

plan 15 g Mass (

y 10 Total Dr 5

0 20 40 60 80 100 120 140

Number of Nodes

Figure A4.8 Total dry mass of lotus (Nelumbo nucifera) as a function of: a) Number of leaves, regression equation is y = 3.09 + 0.57x0.5lnx (r2=0.41); b) Number of nodes, regression equation is y = 1.66 + 0.15x (r2=0.45). (Tables A4.125 & 127).

l Dry Mass (g) Mass l Dry 10 Tota

0 0 5 10 15 20 25 30 35 40

Number of Stolons

20 ) -1

10 Total Dry Mass (g plant 5

0 0 1000 2000 3000 4000

Stolon Length (mm) Figure A4.9 Total dry mass of lotus (Nelumbo nucifera) as a function of: b) Number of stolons, regression equation is y = 0.83 – 0.0073x2 (r2=0.63); b) Total stolon length, regression equation is y = 1.48 + 0.15x/lnx (r2=0.44). (Tables A4.126 & 129).

20 ) -1

10 Total Dry Mass (g plant 5

0 0 50 100 150 200 250 300

Internode Length (mm)

Figure A4.10 Total dry mass of lotus (Nelumbo nucifera) as a function of the internode length, regression equation is y = 15.28-0.00004x2lnx (r2=0.18). (Table A4.128).

Table A4.130 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf P concentration. Rank 91 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0301592248 0 5.1786173305 1.1194951989

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.650780106 9.967733562 0.165612383 -18.5647205 21.86628074 0.86939 b 0.144153059 0.136242544 1.058062001 -0.13215963 0.420465745 0.29708

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 30.022709 1 30.022709 1.1195 0.29708 Error 965.45079 36 26.818077 Total 995.4735 37

Table A4.131 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole P concentration. Rank 2346 Eqn 7902 y=(a+cx)/(1+bx+dx2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0445849023 0 5.288974127 0.5288754185

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.634012142 6.83651e-07 2.39013e+06 1.634010753 1.634013531 0.00000 b -0.00021845 4.94863e-05 -4.41444898 -0.00031902 -0.00011789 0.00010 c 0.000450191 0.000692725 0.649883472 -0.0009576 0.001857977 0.52013 d 1.81287e-08 3.50862e-09 5.166918351 1.09984e-08 2.52591e-08 0.00001

Soln Vector Covar Matrix SVD Cond LvMrq/SVD SVDecomp 1.136514e+21 Source Sum of Squares DF Mean Square F Statistic P>F Regr 44.383089 3 14.794363 0.528875 0.66549 Error 951.09041 34 27.973247 Total 995.4735 37

Table A4.132 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 2145 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.004861634 0 5.2457227803 0.1758738584

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.569509609 10.97847795 0.689486251 -14.6958757 29.83489488 0.49494 b 0.048432226 0.115487183 0.419373173 -0.18578664 0.282651089 0.67744

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.8396278 1 4.8396278 0.175874 0.67744 Error 990.63387 36 27.517607 Total 995.4735 37

Table A4.133 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf P concentration. Rank 439 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0262705602 0 4.7418046498 0.9712555973

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.927456543 4.545722147 1.74393777 -1.29169527 17.14660836 0.08970 b 0.000824885 0.000837002 0.985523007 -0.00087263 0.002522405 0.33094

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 21.838402 1 21.838402 0.971256 0.33094 Error 809.44961 36 22.484711 Total 831.28801 37

Table A4.134 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and petiole P concentration. Rank 2432 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0112877287 0 5.2287582512 0.4109974619

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 13.0356306 1.608143329 8.106012923 9.774164767 16.29709644 0.00000 b -2.039e-12 3.1805e-12 -0.64109084 -8.4893e-12 4.41136e-12 0.52552

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 11.236635 1 11.236635 0.410997 0.52552 Error 984.23686 36 27.339913 Total 995.4735 37

Table A4.135 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 2321 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.143985317 0.0921056392 3.8463258845 5.7189448671

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.46695331 4.59031598 0.319575671 -7.86169113 10.79559775 0.75125 b 0.010924369 0.004568129 2.391431552 0.001640813 0.020207924 0.02246

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 84.607345 1 84.607345 5.71894 0.02246 Error 503.00358 34 14.794223 Total 587.61092 35

Table A4.136 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and leaf P concentration. Rank 2285 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0029104692 0 11.903186096 0.1050827318

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 25.23821618 3.992937014 6.320714825 17.14016458 33.33626778 0.00000 b -6.7661e-12 2.08725e-11 -0.32416467 -4.9098e-11 3.55653e-11 0.74769

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 14.888735 1 14.888735 0.105083 0.74769 Error 5100.6902 36 141.68584 Total 5115.5789 37

Table A4.137 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 4.14). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1809368061 0.134133195 10.788345604 7.9526525768

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.15568368 3.318035598 4.869050738 9.426395588 22.88497177 0.00002 b 1.85058e-11 6.56222e-12 2.820044783 5.19696e-12 3.18146e-11 0.00776

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 925.59652 1 925.59652 7.95265 0.00776 Error 4189.9824 36 116.3884 Total 5115.5789 37

Table A4.138 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 20 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.136002516 0.0866312312 11.080322072 5.6667880026

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5.969850138 7.827491121 0.762677344 -9.90503764 21.84473792 0.45062 b 2.09204e-05 8.78822e-06 2.380501628 3.09704e-06 3.87437e-05 0.02270

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 695.73161 1 695.73161 5.66679 0.02270 Error 4419.8473 36 122.77354 Total 5115.5789 37

Table A4.139 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and leaf P concentration. Rank 102 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0110026251 0 24.085064614 0.4005010666

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 40.87152718 46.35861111 0.881638302 -53.1480939 134.8911482 0.38382 b 0.401003884 0.633646062 0.632851536 -0.88408989 1.68609766 0.53083

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 232.3268 1 232.3268 0.400501 0.53083 Error 20883.252 36 580.09034 Total 21115.579 37

Table A4.140 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and petiole P concentration. Rank 1 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1028174433 0.0515498686 22.939854394 4.1256129327

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 28.53428734 20.80217754 1.371697135 -13.6544841 70.72305881 0.17865 b 0.051092513 0.025154346 2.031160489 7.71355e-05 0.102107891 0.04967

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2171.0498 1 2171.0498 4.12561 0.04967 Error 18944.529 36 526.23692 Total 21115.579 37

Table A4.141 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 18 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1268043888 0.0769074967 22.631118488 5.227875562

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.41295659 23.76802209 0.690547852 -31.7908264 64.61673959 0.49428 b 0.00594149 0.00259856 2.286454802 0.000671366 0.011211614 0.02821

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2677.5481 1 2677.5481 5.22788 0.02821 Error 18438.031 36 512.16752 Total 21115.579 37

Table A4.142 ANOVA for the relationship between number of stolons of lotus (Nelumbo nucifera) and leaf P concentration. Rank 2160 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0035253786 0 6.8792828061 0.1273626328

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6.980775896 28.61250962 0.243976358 -51.0480832 65.00963499 0.80863 b 0.138834958 0.389025275 0.356879017 -0.65014487 0.927814783 0.72327

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.027377 1 6.027377 0.127363 0.72327 Error 1703.6831 36 47.324532 Total 1709.7105 37

Table A4.143 ANOVA for the relationship between number of stolons of lotus (Nelumbo nucifera) and petiole P concentration. Rank 15 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0313089431 0 6.7827012335 1.1635515181

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5.553568416 10.8382826 0.512402991 -16.4274875 27.53462432 0.61150 b 0.137354209 0.127335402 1.078680452 -0.12089396 0.395602373 0.28790

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 53.52923 1 53.52923 1.16355 0.28790 Error 1656.1813 36 46.005036 Total 1709.7105 37

Table A4.144 ANOVA for the relationship between number of stolons of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 49 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0198313356 0 6.8227655746 0.7283726845

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5.03451265 14.27898205 0.352582042 -23.9246052 33.99363048 0.72646 b 0.128193418 0.15020656 0.853447529 -0.17643961 0.432826441 0.39905

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 33.905843 1 33.905843 0.728373 0.39905 Error 1675.8047 36 46.55013 Total 1709.7105 37

Table A4.145 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and leaf P concentration. Rank 1691 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.004746788 0 35.860962336 0.1716993872

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 116.7416297 12.0295997 9.704531538 92.34447069 141.1387886 0.00000 b 2.60566e-11 6.28831e-11 0.414366248 -1.0148e-10 1.53589e-10 0.68106

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 220.80689 1 220.80689 0.171699 0.68106 Error 46296.31 36 1286.0086 Total 46517.117 37

Table A4.146 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and petiole P concentration. Rank 38 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0389777091 0 35.238862124 1.4601092411

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 188.7943955 56.30923919 3.352813823 74.59396533 302.9948256 0.00189 b -0.79939426 0.66155865 -1.2083498 -2.14109739 0.542308866 0.23479

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1813.1307 1 1813.1307 1.46011 0.23479 Error 44703.987 36 1241.7774 Total 46517.117 37

Table A4.147 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and roots and stolons P concentration. Rank 19 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0994962322 0.0465254224 27.107468247 3.867133323

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 172.9878511 28.55073154 6.058963878 115.0267846 230.9489175 0.00000 b -0.00612875 0.003116574 -1.96650282 -0.01245574 0.00019823 0.05721

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2841.6269 1 2841.6269 3.86713 0.05721 Error 25718.519 35 734.81483 Total 28560.146 36

Table A4.148 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1177 Eqn 7902 y=(a+cx)/(1+bx+dx2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.148608987 0.0454100763 4.9927511847 1.9782158378

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.018679173 3.79928e-09 2.68124e+08 1.018679165 1.018679181 0.00000 b -6.0433e-05 2.29857e-06 -26.2914012 -6.5104e-05 -5.5761e-05 0.00000 c 1.56306e-07 1.71007e-05 0.009140356 -3.4596e-05 3.4909e-05 0.99276 d 9.83649e-1 0 6.42222e-1 1 15.316 32781 8.53133e-10 1.11416e-09 0.00000

Soln Vector Covar Matr ix SVD Cond LvMrq/SV D SVDecom p 3.531336e+23 Source Sum of Squares DF Mean Square F Statistic P>F Regr 147.93631 3 49.312103 1.97822 0.13577 Error 847.53719 34 24.927564 Total 995.4735 37

Table A4.149 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole K concentration. (Figure 4.15a). Rank 2 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.263783518 0.2162856805 3.7953395354 11.465476235

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 23.89054391 3.571931651 6.68841015 16.61475723 31.16633059 0.00000 b -3.5113e-09 1.03698e-09 -3.38607091 -5.6235e-09 -1.399e-09 0.00189

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 165.15562 1 165.15562 11.4655 0.00189 Error 460.94727 32 14.404602 Total 626.10289 33

Table A4.150 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolons K concentration. Rank 20 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1614450546 0.1121182931 4.5294836838 6.7384694841

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20.70978266 3.4951663 5.925263887 13.61421784 27.80534747 0.00000 b -9.9475e-07 3.83207e-07 -2.59585621 -1.7727e-06 -2.168e-07 0.01370

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 138.24794 1 138.24794 6.73847 0.01370 Error 718.06779 35 20.516222 Total 856.31572 36

Table A4.151 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1888 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0354570705 0 3.9104760444 1.2130961614

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 13.70465212 1.671916832 8.196970002 10.30311175 17.10619249 0.00000 b -5.8253e-14 5.28897e-14 -1.10140645 -1.6586e-13 4.93518e-14 0.27869

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 18.550452 1 18.550452 1.2131 0.27869 Error 504.63016 33 15.291823 Total 523.18061 34

Table A4.152 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and petiole K concentration. Rank 55 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0229999951 0 4.7497613675 0.8474921378

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.23625749 4.298945653 3.776799895 7.517591606 24.95492338 0.00058 b -1.1592e-09 1.25921e-09 -0.92059336 -3.713e-09 1.39458e-09 0.36339

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 19.11962 1 19.11962 0.847492 0.36339 Error 812.16839 36 22.560233 Total 831.28801 37

Table A4.153 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolons K concentration. Rank 17 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0340213307 0 4.7228948442 1.2679036765

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18.63533982 5.640647632 3.303758901 7.195576203 30.07510344 0.00216 b -0.00156969 0.001394026 -1.12601229 -0.00439691 0.001257525 0.26761

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 28.281524 1 28.281524 1.2679 0.26761 Error 803.00649 36 22.305736 Total 831.28801 37

Table A4.154 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0645734491 0.0111205034 11.48744843 2.4851167278

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 31.78361433 4.889239216 6.500728012 21.86777761 41.69945104 0.00000 b -2.4351e-13 1.54471e-13 -1.5764253 -5.5679e-13 6.97697e-14 0.12368

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 327.93966 1 327.93966 2.48512 0.12368 Error 4750.613 36 131.96147 Total 5078.5526 37

Table A4.155 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and petiole K concentration. Rank 25 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0958969351 0.0442339028 11.293477714 3.8184691532

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37.86236995 7.001298655 5.407906707 23.66307816 52.06166175 0.00000 b -6.7002e-14 3.42878e-14 -1.95409036 -1.3654e-13 2.53742e-15 0.05849

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 487.01763 1 487.01763 3.81847 0.05849 Error 4591.535 36 127.54264 Total 5078.5526 37

Table A4.156 ANOVA for the relationship between number of leaves of lotus (Nelumbo nucifera) and roots and stolons K concentration. (Figure 4.16a). Rank 15 Eqn 5 y=a+bx2lnx

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1937379549 0.1476658381 10.664901196 8.6504957288

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 42.43164576 6.285858653 6.750334059 29.68333354 55.17995798 0.00000 b -8.876e-10 3.01786e-10 -2.94117251 -1.4997e-09 -2.7555e-10 0.00569

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 983.9084 1 983.9084 8.6505 0.00569 Error 4094.6442 36 113.74012 Total 5078.5526 37

Table A4.157 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1448206611 0.0693636606 22.714128293 2.9635439661

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 79.41185635 5 .645646115 1 4.06603509 6 7.95058542 90.87312729 0 .00000 b 31199.48794 1055.180522 29.56791496 29057.3576 33341.61828 0.00000 c 10290.77436 2825.324954 3.642333014 4555.059768 16026.48894 0.00087

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 3057.9721 2 1528.9861 2.96354 0.06471 Error 18057.607 35 515.93162 Total 21115.579 37

Table A4.158 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and petiole K concentration. Rank 210 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1610840038 0.1117360041 21.032250146 6.7205061777

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 117.9670691 19.30517111 6.110646128 78.77548819 157.15865 0.00000 b -1.4747e-08 5.6886e-09 -2.59239391 -2.6296e-08 -3.1986e-09 0.01381

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2972.8532 1 2972.8532 6.72051 0.01381 Error 15482.444 35 442.35555 Total 18455.297 36

Table A4.159 ANOVA for the relationship between number of nodes of lotus (Nelumbo nucifera) and roots and stolons K concentration. (Figure 4.16b). Rank 1023 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1906832533 0.1444365821 21.787605841 8.4819659891

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 117.9676633 16.8098809 7.017757233 83.87564469 152.0596819 0.00000 b -5.3609e-06 1.84071e-06 -2.9123815 -9.094e-06 -1.6277e-06 0.00612

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4026.3873 1 4026.3873 8.48197 0.00612 Error 17089.192 36 474.69977 Total 21115.579 37

Table A4.160 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf K concentration. Rank 185 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0731245965 0.0201602877 6.6346913056 2.8401718987

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 21.58392802 2.823829253 7.643496149 15.85693685 27.31091918 0.00000 b -1.5035e-13 8.92163e-14 -1.68528096 -3.3129e-13 3.05845e-14 0.10059

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 125.02189 1 125.02189 2.84017 0.10059 Error 1584.6886 36 44.019129 Total 1709.7105 37

Table A4.161 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and petiole K concentration. (Figure 4.15b). Rank 30 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2366943291 0.1917939956 5.4933953842 10.85319006

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 29.93748433 4.117594896 7.270624012 21.57832229 38.29664637 0.00000 b -1.6178e-11 4.91073e-12 -3.29441802 -2.6147e-11 -6.2087e-12 0.00226

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 327.52098 1 327.52098 10.8532 0.00226 Error 1056.2087 35 30.177393 Total 1383.7297 36

Table A4.162 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and roots and stolons K concentration. (Figure 4.17a). Rank 23 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3103206076 0.2697512316 5.2217399378 15.748217775

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.61111187 4.09965417 7.954600687 24.28837144 40.9338523 0.00000 b -1.7721e-06 4.46556e-07 -3.96840242 -2.6787e-06 -8.6556e-07 0.00034

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 429.39985 1 429.39985 15.7482 0.00034 Error 954.32988 35 27.266568 Total 1383.7297 36

Table A4.163 ANOVA for the relationship between the internode length of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1894 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0957996908 0.0441311018 34.181213063 3.8141867854

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 94.8370822 14.54806334 6.518880211 65.33224223 124.3419222 0.00000 b 8.9766e-13 4.59633e-13 1.952994313 -3.4518e-14 1.82984e-12 0.05863

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4456.3254 1 4456.3254 3.81419 0.05863 Error 42060.792 36 1168.3553 Total 46517.117 37

Table A4.164 ANOVA for the relationship between the internode length of lotus (Nelumbo nucifera) and petiole K concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1681173172 0.1177001849 23.555647917 6.8711477029

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 77.13221682 15.12839304 5.098506933 46.38762313 107.8768105 0.00001 b 1.95976e-13 7.47632e-14 2.621287413 4.40387e-14 3.47913e-13 0.01301

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3812.5838 1 3812.5838 6.87115 0.01301 Error 18865.531 34 554.86855 Total 22678.114 35

Table A4.165 ANOVA for the relationship between the internode length of lotus (Nelumbo nucifera) and roots and stolons K concentration. (Figure 4.17b). Rank 2 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2815115778 0.2379668249 21.891418305 13.321569768

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 81.36101865 10.02190525 8.118318482 60.99405673 101.7279806 0.00000 b 4.10534e-13 1.12479e-13 3.649872569 1.81949e-13 6.39118e-13 0.00087

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6384.1518 1 6384.1518 13.3216 0.00087 Error 16293.963 34 479.2342 Total 22678.114 35

Table A4.166 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 19 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0526807334 0 5.1181355747 2.0019717437

Parm Value Std Error t-value 95% Confidence Lim its P>|t| a 3.378797765 6.261295833 0.539632347 -9.31969875 16.07729428 0.59277 b 0.000405192 0.000286373 1.414910507 -0.0001756 0.000985983 0.16569

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 52.442274 1 52.442274 2.00197 0.16569 Error 943.03122 36 26.195312 Total 995.4735 37

Table A4.167 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 1 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0895101053 0.0374821114 4.585240005 3.5391538239

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8.031942511 2.409152098 3.333929194 3.145955595 12.91792943 0.00199 b 6.03344e-11 3.20712e-11 1.88126389 -4.709e-12 1.25378e-10 0.06804

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 74.408677 1 74.408677 3.53915 0.06804 Error 756.87933 36 21.024426 Total 831.28801 37

Table A4.168 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 1852 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.0515971453 0 11.608940134 1.958552 9731

Parm Value Std Error t-value 95% Confiden ce Limits P>|t| a 17.2821621 5 .226515462 3 .306631774 6 .682297445 27.88202675 0 .00215 b 6.36378e-13 4.54723e-13 1.399483109 -2.8584e-13 1.5586e-12 0.17023

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 263.94927 1 263. 94927 1.95855 0.17023 Error 4851.6297 36 134.76749 Total 5115.5789 37

Table A4.1 69 ANOVA for the r elations hip between the num ber of nodes of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 985 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0642461526 0.0107745042 23.427775681 2.4716558735

Parm Value Std Erro r t-value 95% Co nfidence Limits P>|t| a 51.6986781 4 12.30929567 4.199970456 26.73426945 76.66308683 0.00017 b 2.57619e-10 1.63864e-10 1.57215008 -7.4713e-11 5.89951e-10 0.12466

Soln Vector Cova r Matrix Direct LU D ecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1356.5947 1 1356.5947 2.47166 0.12466 Error 19758.9 84 3 6 548 .86067 Total 21115.579 37

Table A4.170 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 1625 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.032878356 0 6.777204551 1.2238592989

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.10174064 9.179907173 0.773617914 -11.515974 25.7194553 0.44421 b 0.004648316 0.004201747 1.106281745 -0.00387322 0.013169855 0.27594

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 56.212471 1 56.212471 1.22386 0.27594 Error 1653.4981 36 45.930502 Total 1709.7105 37

Table A4.1 71 ANOVA for the r elation ship between the internode length of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 2139 Eqn 12 y=a+bx0.5

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.000912549 0 28.55274999 0.0319683875

Parm Value Std E rror t-value 95% Confiden ce Limits P>|t| a 104.6927524 71.95630259 1.454949026 -41.3863079 250.7718127 0.15459 b 0.087125869 0 .487289167 0 .178797057 - 0.90212373 1.07637547 0 .85913

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 26.062533 1 26.062533 0.0319684 0.85913 Error 28534.084 35 815.25953 Total 28560.146 36

Table A4. 172 ANOVA for the relationship between combined leaf, petiole and roots and stolon N concentration as a function of N supply. (Figure 4.6, Tables 58-60 & 188-191). Rank 1 Eqn 8157 [Exponential_] y=aexp(-x/b) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4 560461251 0.4461560547 0.6612216849 93.061419773

Parm Value Std Error t-value 95% Confiden ce Limits P>|t| a 1.708279942 0.120896927 14.13005265 1.468714611 1.947845274 0.00000 b -472.331275 5 2.26657266 - 9.03696668 - 575.900978 -368.761572 0 .00000

Procedure Minimization Iterations LevMarqdt Least Squares 10

Source Sum of Squares DF Mean Square F Statistic P>F Regr 40.687766 1 40.687766 93.0614 0.00000 Error 48.530767 111 0.43721412 Total 89.218533 112

Table A4.173 ANOVA for a single line equation combining leaf and petiole N concentration as a function of N supply. (Figure 4.6, Tables 58-59 & 189). Rank 1 Eqn 8157 y=aexp(-x/b) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4921125506 0.4780045659 0.6456929723 70.732632277

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.884496282 0.147330081 12.79098114 1.590867855 2.178124709 0.00000 b -486.220545 61.27817284 -7.93464496 -608.347768 -364.093323 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9

Source Sum of Squares DF Mean Square F Statistic P>F Regr 29.489808 1 29.489808 70.7326 0.00000 Error 30.435117 73 0.41691941 Total 59.924925 74

Table A4.174 ANOVA for a single line equation combining leaf and roots and stolon N concentration as a function of N supply. (Figure 4.6, Tables 58, 60 & 190). Rank 1 Eqn 8157 y=aexp(-x/b) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3693495981 0.3518315314 0.7313154295 42.75351 3808

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.921192314 0.172919464 11.11033004 1.57656432 2.265820309 0.00000 b -540.374701 87.91721527 -6.14640374 -715.593458 -365.155943 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 11

Source Sum of Squares DF Mean Square F Statistic P>F Regr 22.865531 1 22.865531 42.7535 0.00000 Error 39.042025 73 0.53482226 Total 61.907556 74

Table A4.175 ANOVA for a single line equation combining petiole and roots and stolon N concentration as a function of N supply. (Figure 4.6, Tables 59-60 & 191). Rank 1 Eqn 8157 y=aexp( -x/b) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7445304788 0.7375 313138 0.3 624140421 2 15.66273411

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 1.346944961 0.074975039 17.96524519 1.197553934 1.496335987 0.00000 b -403.67334 3 29.6333046 -13.62 22858 -462.718992 -344.627695 0.00000

Procedure Minimizati on Iterations LevMarqdt Least Squares 8

Source Sum of Squares DF Mean Square F Statistic P>F Regr 28.325993 1 28.325993 215.663 0.00000 Error 9.7194514 74 0.13134394 Total 38.045444 75

100

Table A4.176 ANOVA for a single line equation combining leaf, petiole and roots and stolon P concentration as a function of combined N concentration. (Figure 4.7, Tables A4.61-63 & 192). Rank 164 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0697323331 0.0445899638 1933.1002433 4.1977280242

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7697.558045 246.5914688 31.21583274 7208.968659 8186.147431 0.00000 b 2.604495814 0.208045563 12.51887221 2.192280199 3.016711428 0.00000 c 2.449160236 0.466729411 5.247494972 1.524395736 3.373924736 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 11

Source Sum of Squares DF Mean Square F Statistic P>F Regr 31372783 2 15686391 4.19773 0.01746 Error 4.1853017e+08 112 3736876.6 Total 4.4990296e+08 114

Table A4.177 ANOVA for a single line equation combining leaf and petiole P concentration as a function of combined N concentration. (Figure 4.7, Tables A4.61-62 & 193). Rank 2316 Eqn 21 y=a+be-x r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0067731301 0 156 1.8379156 0 .5114488672

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 6430.801273 250.0546715 25.71758102 5932.666823 6928.935723 0.00000 b -2178.3792 2 3046.017372 -0.715 15653 -8246.35699 3889.598544 0.47673

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 1247596.5 1 1247596.5 0.511449 0.47673 Error 1.8295033e+08 75 2439337.7 Total 1.8419792e+08 76

Table A4.178 ANOVA for a single line equation combining leaf and roots and stolon P concentration as a function of combined N concentration. (Figure 4.7, Tables A4.61, 63 & 194). Rank 3 Eqn 2 y=a +bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1408814934 0.1176620743 2047.5358611 12.298782909

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 8770.457499 507.5863861 17.27874848 7759.293566 9781.621433 0.00000 b -422.94434 5 120.6013458 -3.506 96206 -663.194545 -182.694144 0.00077

Soln Vector Covar Matr ix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 51561456 1 51561456 12.2988 0.00077 Error 3.1443023e+08 75 4192403.1 Total 3.6599169e+08 76

101

Table A4.179 ANOVA for a single line equation combining petiole and roots and stolon P concentration as a function of combined N concentration. (Figure 4.7, Tables A4.62-63 & 195). Rank 11 Eqn 84 y0.5=a+be-x r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2335163363 0.2125167838 1511.9598326 22.544784319

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 98.32792598 3.32686644 29.55571789 91.69899989 104.9568521 0.00000 b -74.3275757 30.48844301 -2.43789346 -135.077125 -13.5780269 0.01717

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 51537885 1 51537885 22.5448 0.00001 Error 1.6916567e+08 74 2286022.5 Total 2.2070355e+08 75

Table A4.180 ANOVA for a single line equation combining leaf, petiole and roots and stolon K concentration as a function of combined N concentration. (Figure 4.8a, Tables A4.64-66 & 196). Rank 5 Eqn 3 y=a +bx1.5 r2 Coef Det DF Ad j r2 Fit S td Err F -value 0.2474646497 0.2340 265185 1 0 8 71.33758 3 7.159058917

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 57617.8183 2531.404661 22.761 20416 52602.64911 62632.9875 0.00000 b -2640.1673 1 433.1108829 -6.095 82307 -3498.23809 -1782.09654 0.00000

Soln Vector Covar Matr ix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.3916798e+09 1 4.3916798e+09 37.1591 0.00000 Error 1.3355016e+10 113 1.1818598e+08 Total 1.7746696e+10 114

Table A4.181 ANOVA for a single line equation combining leaf and petiole K concentration as a function of combined N concentration. (Figure 4.8a, Tables A4.64-65 & 197). Rank 6 Eqn 2 y=a +bxlnx r2 Coef Det DF Ad j r2 Fit S td Err F -value 0.3509878257 0.3334 469561 1 1 8 23.021981 4 0.560235958

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 61667.01427 3109.643977 19.830 89213 55472.2858 67861.74273 0.00000 b -4488.9802 704.8512159 -6.368 69186 -5893.11582 -3084.84457 0.00000

Soln Vector Covar Matr ix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.6696659e+09 1 5.6696659e+09 40.5602 0.00000 Error 1.0483789e+10 75 1.3978385e+08 Total 1.6153455e+10 76

102

Table A4.182 ANOVA for a single line equation combining leaf and roots and stolon K concentration as a function of combined N concentration. (Figure 4.8a, Tables A4.64, 66 & 198). Rank 16 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Er r F-valu e 0.361715398 0.34446 44628 66 39.0099 461 42.502442 892

Parm Value St d Error t- value 95% Confidence Limit s P>|t| a 53412.85433 2709.007298 1 9.71676281 480 1 6.23505 58809.4736 0.00000 b -5395.24449 827.5689424 -6 .51938976 -70 43.846 36 -3746.6 4262 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.873356 9e+ 09 1 1.8733569e+09 42.5024 0.00000 Error 3.305734 e+09 75 44076453 Total 5.179090 9e+09 76

Table A4.183 ANOVA fo r a single line equation combinin g petiol e and roots an d stolo n K concentration as a fu n ction of combined N con centration. (Fig u re 4.8a, Tables A4. 65-66 & 199 ). Rank 1332 Eqn 8 y = a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0095168565 0 9588.0597553 0.7110139983

Parm Value St d Error t-v alue 95% Confidence Limits P>|t| a 51305.41144 166 6.206285 30.7 9175244 47985.422 95 54625.39994 0.00000 b -61.3906668 72 .80534686 -0.8 4321646 -206.458487 83.677 153 47 0.40182

Soln Vector Covar M atrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 65364150 1 65364150 0.711014 0.40182 Error 6.8028859e+09 74 91930890 Total 6.86825e+09 75

Table A4.184 ANOVA for a single line equat ion combining lea f, petiole and ro ots and stolon Ca concentration as a function of combined N co ncentration. (Figure 4.8 b, Tables A4.67- 9 & 200). Rank 3 Eqn 2 y=a+ bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3168208035 0 .3 04621175 3996.8578242 52.403163011

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10740.00475 775.9797299 13.84057384 9202.648945 12277.36055 0.00000 b 1440.48314 198.9891646 7.239002902 1046.249715 1834.716565 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F St atistic P>F Regr 8.3713385e+08 1 8.3713385e+08 52.403 2 0.00000 Error 1.8051606e+09 113 15974872 Total 2.6422944e+09 114

103

Table A4.185 ANOVA for a single line equation combining leaf and petiole Ca concentration as a function of combined N concentration. (Figure 4.8b, Tables A4.67-68 & 201). Rank 9 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2503045174 0.2300424773 4055.4945805 25.040618809

Parm Value Std Error t- value 95% Confidence Limit s P>|t| a 1680.144425 3216.837015 0 .522297032 -4728.12352 8088.412373 0.60300 b 8919.246175 1782.401842 5 .004060232 5368.519626 12469.97272 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.118439 7e+ 08 1 4.1184397e+08 25.0406 0.00000 Error 1.2335277e+09 75 16447036 Total 1.6453717e+09 76

Table A4.186 ANOVA for a singl e line equation combinin g leaf and root s and s tolon C a concentration as a fu n ction of combined N concentration. (Fig u re 4.8b, Tables A4. 67, 69 & 202). Rank 11 Eqn 1 y=a + bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4104319334 0.3944976613 4265.2844559 52.211774591

Parm Value Std Error t-v alue 95% Confidence Limits P>|t| a 4621.919822 1740.4231 67 2.6556 29912 1154.819081 8089.0205 63 0.00966 b 3841.785311 531.67821 33 7.2257 71557 2782.627997 4900.9426 25 0.00000

Soln Vector C ovar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9.4987062e+08 1 9.4987062e+08 52.2118 0.00000 Error 1.3644489e+09 75 18192651 Total 2.3143195e+09 76

Table A4.187 ANOV A for a single lin e equ ation combining pe tiole and roots an d s tolon Ca concentration as a function of combined N con centration. (Figu re 4.8b, Tables A4.68- 69 & 203). Rank 97 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0014505725 0 1881.5901512 0.107498302

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12524.59753 449.6967635 27.85120674 11628.55717 13420.63789 0.00000 b 51.01173503 155.585562 0.327869337 -258.999265 361.0227346 0.74394

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Stati stic P>F Regr 380585 1 380585 0.107498 0.74394 Error 2.6198823e+08 74 3540381.5 Total 2.6236882e+08 75

104

Table A4.188 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves, petioles and roots and stolons as a function of N supply (Tables A4.58, 59, 60 & 172). ANOVA SS df ms F Single line RSS 48.53 113 Total Individual 10.52 109 0.097 lines RSS Difference 38.01 4 9.50 97.94 F dist. 19.61 P < 0.0002

Table A4.189 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and petioles as a function of N supply (Tables A4.58, 59 & 173). ANOVA SS df ms F Single line RSS 30.44 75 Total Individual 8.36 73 0.1145 lines RSS Difference 22.08 2 11.04 96.42 F dist. 199.5 P < 0.0103

Table A4.190 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and roots and stolons as a function of N supply (Tables A4.58, 60 & 174). ANOVA SS df ms F Single line RSS 39.04 75 Total Individual 6.27 73 0.086 lines RSS Difference 32.77 2 16.39 190.52 F dist. 199.5 P < 0.0052

Table A4.191 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in petioles and roots and stolons as a function of N supply (Tables A4.59, 60 & 175). ANOVA SS df ms F Single line RSS 9.71 74 Total Individual 6.41 72 0.089 lines RSS Difference 3.30 2 1.65 18.54 F dist. 199.5 P < 0.0525

Table A4.192 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, petioles and roots and stolons as a function of N concentration (Tables A4.61, 62, 63 & 176). ANOVA SS df ms F Single line RSS 4.1853 x 108 110 Total Individual 75473031.7 100 754730.32 lines RSS Difference 343056968.3 10 85764242.08 45.45 F dist. 4.86 P < 0.0000

105

Table A4.193 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, and petioles as a function of N concentration (Tables A4.61, 62 & 177). ANOVA SS df ms F Single line RSS 1.8295 x 108 74 Total Individual 44703824.7 67 667221.26 lines RSS Difference 138246175.3 7 19749453.61 29.6 F dist. 7.31 P < 0.0001

Table A4.194 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves and roots and stolons as a function of N concentration (Tables A4.61, 63 & 178). ANOVA SS df ms F Single line RSS 3.1443 x 108 74 Total Individual 40748244.7 67 608182.76 lines RSS Difference 273681755.3 7 39097393.61 64.29 F dist. 7.31 P < 0.0000

Table A4.195 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in petioles and roots and stolons as a function of N concent ration (Tables A4.62, 63 & 179). ANOVA SS df ms F Single line RSS 1.6692 x 108 73 Total Individual 65493994 66 992333.24 lines RSS Difference 101426006 6 1690 433 4.33 17.03 F dist. 9.12 P < 0.0009

Table A4.196 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves, petioles and roots and stolons as a function of N concentration (Tables A4.64, 65, 66 & 180). ANOVA SS df ms F Single line RSS 1.335501 x 1010 112 Total Individual 2156136690 101 21347888.02 lines RSS Difference 1.119887 x 1010 11 1018079937 47.69 F dist. 4.44 P < 0.0000

Table A4.197 ANOVA of the comparison of regression equations between a single fitted line and th e sum of individual fitted lines for K concentration in leaves and petioles as a function of N concentration (Tables A4.64, 65 & 181). ANOVA SS df ms F Single line RSS 1.0483789 1010 74 Total Individual 871562290 66 13205489.24 lines RSS Difference 9612226710 8 1201528339 90.99 F dist. 6.18 P < 0.0000

106

Table A4.198 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and roots and stolons as a function of N concentration (Tables A4.64, 66 & 182). ANOVA SS df ms F 9 Single line RSS 3.305734 x 10P P 74 Total Individual 1621826100 69 23504726.09 lines RSS Difference 1683907900 5 3366781580 143.24 F dist. 12.4 P < 0.0000

Table A4.199 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in petioles and roots and stolons as a function of N concentration (Tables A4.65, 66 & 183). ANOVA SS df ms F 9 Single line RSS 6.8028859 x 10P P 74 Total Individual 1818884990 67 27147537.16 lines RSS Difference 4984000910 7 712000130 26.23 F dist. 7.31 P < 0.0000

Table A4.200 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves, petioles and roots and stolons as a function of N concentration (Tables A4.67, 68, 69 & 184). ANOVA SS df ms F 9 Single line RSS 1.8051606 x 10P P 112 Total Individual 326857931 100 3268579.31 lines RSS Difference 1478302669 12 123191889.1 37.69 F dist. 4.12 P < 0.0000

Table A4.201 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and petioles as a function of N concentration (Tables A4.67, 68, 185). ANOVA SS df ms F 9 Single line RSS 1.2335277 x 10P P 74 Total Individual 210470001 65 3238000.015 lines RSS Difference 1023057699 9 113673077.7 35.11 F dist. 5.41 P < 0.0000

Table A4.202 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and roots and stolons as a function of N concentration (Tables A4.67, 69, & 186). ANOVA SS df ms F 9 Single line RSS 1.3644489 x 10P P 74 Total Individual 278341370 68 4093255.44 lines RSS Difference 1086107530 6 18107921.7 44.22 F dist. 9.12 P < 0.0000

107

Table A4.203 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in petioles and roots and stolons as a function of N concentration (Tables A4.68, 69 & 187). ANOVA SS df ms F 8 Single line RSS 2.6198823 x 10P P 74 Total Individual 164904491 67 246126.06 lines RSS Difference 97083739 7 138691055.57 56..35 F dist. 7.31 P < 0.0000

Table A4.204 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf S concentration.

Rank 151 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2002272282 0.1531817711 4.4235021689 8.7624300749

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.076930165 0.430642402 9.467089513 3.202679611 4.951180719 0.00000 b -2.573e-12 2.32775e-12 -1.10537393 -7.2986e-12 2.15255e-12 0.27654

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 171.45772 1 171.45772 8.76243 0.00549 Error 684.858 35 19.567371 Total 856.31572 36

Table A4.205 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf S concentration.

Rank 136 Eqn 1041 y=a+bx1.5+cx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5410941407 0.4966838962 2.7710131014 18.865538705

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.573331406 5.438366578 0.840938422 -6.50425881 15.65092162 0.40662 b 0.000102816 4.20976e-05 2.442327282 1.70661e-05 0.000188566 0.02030 c -1.2799e-07 4.4302e-08 -2.88894444 -2.1823e-07 -3.7746e-08 0.00688

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 289.71859 2 144.8593 18.8655 0.00000 Error 245.71244 32 7.6785136 Total 535.43103 34

108

Appendix 5 Phosphorous ANOVA Tables and Miscellaneous Graphs

Table A5.1 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 20 days of phosphorous treatments. (Table 5.1).

Univariate Tests of Significance for No.Lf.d20 (Spreadsheet11) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 2.860804 1 2.860804 85.29104 0.000000 Treat 0.677321 6 0.112887 3.36557 0.017484 Error 0.704375 21 0.033542

Table A5.2 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of phosphorous treatments. (Table 5.1).

Univariate Tests of Significance for No.Lf.d40 (Spreadsheet11) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 7.875804 1 7.875804 316.9186 0.000000 Treat 0.414821 6 0.069137 2.7820 0.037624 Error 0.521875 21 0.024851

Table A5.3 ANOVA for the percentage of total leaf area of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of phosphorous treatments. (Table 5.1).

Univariate Tests of Significance for TaffLA (Spreadsheet11) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 675.2478 1 675.2478 87.05513 0.000000 Treat 73.7769 6 12.2961 1.58526 0.200671 Error 162.8876 21 7.7566

Table A5.4 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 20 days of phosphorous treatments. (Table 5.1).

Univariate Tests of Significance for d20 (Spreadsheet46) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 3.055804 1 3.055804 92.41674 0.000000 Treat 0.247321 6 0.041220 1.24662 0.323232 Error 0.694375 21 0.033065

109

Table A5.5 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 40 days of phosphorous treatments. (Table 5.1).

Univariate Tests of Significance for d40 (Spreadsheet46) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 7.000000 1 7.000000 341.8605 0.000000 Treat 0.590000 6 0.098333 4.8023 0.003140 Error 0.430000 21 0.020476

Table A5.6 ANOVA of Total Dry Mass of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.1a).

Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of DW tot DW tot DW tot DW tot Intercept 1 7262.621 7262.621 286.7764 0.000000 P_conc 6 891.541 148.590 5.8673 0.000566 Error 26 658.451 25.325 Total 32 1549.992

Tukey HSD test; variable DW tot (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 25.325, df = 26.000 P_conc DW tot 1 2 1 5 6.39800 **** 7 100 9.65600 **** 2 15 12.86250 **** **** 5 45 16.47800 **** **** 3 25 17.42000 **** **** 6 50 18.44200 **** **** 4 40 23.11750 ****

110

Table A5.7 ANOVA of Leaf Dry Mass of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.1b).

Univariate Tests of Significance for DW Leaf (P_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 877.8551 1 877.8551 224.3784 0.000000 P_conc 136.6705 6 22.7784 5.8221 0.000596 Error 101.7221 26 3.9124

Tukey HSD test; variable DW Leaf (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 3.9124, df = 26.000 P_conc DW Leaf 1 2 1 5 1.680000 **** 7 100 3.324000 **** **** 2 15 4.490000 **** **** 3 25 5.892000 **** **** 5 45 6.026000 **** **** 6 50 6.438000 **** **** 4 40 8.437500 ****

Table A5.8 ANOVA of Petiole Dry Mass of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.1b).

Univariate Tests of Significance for DW Pet (P_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 493.8797 1 493.8797 308.5449 0.000000 P_conc 53.8515 6 8.9752 5.6072 0.000765 Error 41.6175 26 1.6007

Tukey HSD test; variable DW Pet (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 1.6007, df = 26.000 P_conc DW Pet 1 2 1 5 1.684000 **** 7 100 2.804000 **** **** 2 15 3.200000 **** **** 5 45 4.362000 **** **** 3 25 4.466000 **** **** 6 50 5.172000 **** 4 40 5.530000 ****

111

Table A5.9 ANOVA of Roots and Stolon Dry Mass of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.1b).

Univariate Tests of Significance for DW Root (P_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1113.490 1 1113.490 272.6780 0.000000 P_conc 124.180 6 20.697 5.0683 0.001460 Error 106.172 26 4.084

Tukey HSD test; variable DW Root (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 4.0835, df = 26.000 P_conc DW Root 1 2 1 5 3.034000 **** 7 100 3.528000 **** 2 15 5.172500 **** **** 5 45 6.090000 **** **** 6 50 6.832000 **** **** 3 25 7.062000 **** **** 4 40 9.150000 ****

Table A5.10 ANOVA of the number of leaves of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.2a).

Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of lf no. lf no. lf no. lf no. Intercept 1 9393.127 9393.127 303.7956 0.000000 P_conc 6 580.342 96.724 3.1283 0.019186 Error 26 803.900 30.919 Total 32 1384.242

112

Table A5.11 ANOVA of the number of nodes of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.2b). Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of node no. node no. node no. node no. Intercept 1 115038.1 115038.1 1042.339 0.000000 P_conc 6 7226.0 1204.3 10.912 0.000004 Error 26 2869.5 110.4 Total 32 10095.5

Tukey HSD test; variable node no. (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 110.37, df = 26.000 P_conc node no. 1 2 3 1 5 35.80000 **** 7 100 47.80000 **** 6 50 56.00000 **** **** 2 15 58.25000 **** **** **** 5 45 59.40000 **** **** **** 4 40 75.75000 **** **** 3 25 82.40000 ****

Table A5.12 ANOVA of the number of stolons of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.2c). Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st.no. st.no. st.no. st.no. Intercept 1 7031.527 7031.527 598.4278 0.000000 P_conc 6 366.561 61.093 5.1994 0.001244 Error 26 305.500 11.750 Total 32 672.061

Tukey HSD test; variable st.no. (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 11.750, df = 26.000 P_conc st.no. 1 2 1 5 8.00000 **** 7 100 12.60000 **** **** 2 15 14.75000 **** **** 6 50 15.20000 **** **** 5 45 15.80000 **** **** 4 40 17.75000 **** 3 25 18.60000 ****

113

Table A5.13 ANOVA of total leaf area of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.3a).

Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of L.A). (cm2) L.A). (cm2) L.A). (cm2) L.A). (cm2) Intercept 1 3180.098 3180.098 155.2234 0.000000 P_conc 6 468.645 78.107 3.8125 0.007382 Error 26 532.668 20.487 Total 32 1001.313

Tukey HSD test; variable L.A). (cm2) (P_general_b) Homogenous Groups, alpha = .01000 Error: Between MS = 20.487, df = 26.000 P_conc L.A). (cm2) 1 1 5 2.87000 **** 7 100 7.19500 **** 2 15 8.38750 **** 5 45 10.93750 **** 6 50 11.40250 **** 3 25 13.78000 **** 4 40 14.49375 ****

Table A5.14 ANOVA of total stolon length of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.3b).

Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st lgth st lgth st lgth st lgth Intercept 1 100593676 100593676 285.3549 0.000000 P_conc 6 7562914 1260486 3.5756 0.010216 Error 26 9165554 352521 Total 32 16728468

Table A5.15 ANOVA of internode length of lotus (Nelumbo nucifera) as a function of P supply. (Figure 5.3c).

Univariate Results for Each DV (P_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Int. lgth int. lgth int. lgth int. lgth Intercept 1 28427.29 28427.29 318.0229 0.000000 P_conc 6 322.06 53.68 0.6005 0.727296 Error 26 2324.08 89.39 Total 32 2646.14

114

Table A5.16 ANOVA of N concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure 5.4a).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 438.2053 438.2053 6568.882 0.000000 P Conc (ppm) 6 1.3108 0.2185 3.275 0.015567 Error 26 1.7344 0.0667 Total 32 3.0453

Table A5.17 ANOVA of N concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure 5.4a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 195.9225 195.9225 1421.430 0.000000 P Conc (ppm) 6 1.8295 0.3049 2.212 0.074082 Error 26 3.5837 0.1378 Total 32 5.4132

Table A5.18 ANOVA of N concentration in lotus roots and stolons (Nelumbo nucifera) as a function of roots and stolon P concentration. (Figure 5.4a).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 161.8234 161.8234 2617.315 0.000000 P Conc (ppm) 6 0.8168 0.1361 2.202 0.075268 Error 26 1.6075 0.0618 Total 32 2.4243

115

Table A5.19 ANOVA of P concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure 5.4b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 812332433 812332433 1814.990 0.000000 P Conc (ppm) 6 117453984 19575664 43.738 0.000000 Error 26 11636780 447568 Total 32 129090764

Tukey HSD test; variable P (mg kg-1) (P_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 4476E2, df = 26.000 P Conc (ppm) P (mg kg-1) 1 2 3 4 1 5 2242.000 **** 2 15 3325.000 **** **** 3 25 4280.000 **** **** 4 40 5100.000 **** **** 6 50 5640.000 **** 5 45 5860.000 **** 7 100 8460.000 ****

Table A5.20 ANOVA of P concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure 5.4b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 949362288 949362288 2364.268 0.00 P Conc (ppm) 6 296337211 49389535 122.998 0.00 Error 26 10440195 401546 Total 32 306777406

Tukey HSD test; variable P (mg kg-1) (P_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 4015E2, df = 26.000 P Conc (ppm) P (mg kg-1) 1 2 3 4 1 5 1524.00 **** 2 15 2052.50 **** **** 3 25 3480.00 **** 4 40 6200.00 **** 6 50 6540.00 **** 5 45 7500.00 **** 7 100 10440.00 ****

116

Table A5.21 ANOVA of P concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure 5.4b).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 1.312139E+09 1.312139E+09 1561.516 0.000000 P Conc (ppm) 6 4.926231E+08 8.210384E+07 97.708 0.000000 Error 26 2.184776E+07 8.402983E+05 Total 32 5.144708E+08

Tukey HSD test; variable P (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = 8403E2, df = 26.000 P Conc (ppm) P (mg kg-1) 1 2 3 4 5 1 5 1392.00 **** 2 15 2092.50 **** **** 3 25 4460.00 **** **** 4 40 6700.00 **** **** 6 50 8120.00 **** 5 45 8240.00 **** 7 100 13360.00 ****

Table A5.22 ANOVA of K concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure 5.5a).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 2.362538E+10 2.362538E+10 6709.555 0.000000 P Conc (ppm) 6 5.632879E+07 9.388131E+06 2.666 0.037590 Error 26 9.155000E+07 3.521154E+06 Total 32 1.478788E+08

Table A5.23 ANOVA of K concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure 5.5a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 9.792038E+10 9.792038E+10 6593.111 0.000000 P Conc (ppm) 6 1.099106E+08 1.831843E+07 1.233 0.321696 Error 26 3.861500E+08 1.485192E+07 Total 32 4.960606E+08

117

Table A5.24 ANOVA of K concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure 5.5a).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 6.072216E+10 6.072216E+10 3456.922 0.000000 P Conc (ppm) 6 2.311788E+08 3.852980E+07 2.194 0.076205 Error 26 4.567000E+08 1.756538E+07 Total 32 6.878788E+08

Table A5.25 ANOVA of Ca concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure 5.5b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 1.589497E+10 1.589497E+10 1991.255 0.000000 P Conc (ppm) 6 1.381453E+08 2.302421E+07 2.884 0.027293 Error 26 2.075420E+08 7.982385E+06 Total 32 3.456873E+08

Table A5.26 ANOVA of Ca concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure 5.5b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 4.441760E+09 4.441760E+09 2696.407 0.000000 P Conc (ppm) 6 1.375595E+07 2.292659E+06 1.392 0.255249 Error 26 4.282950E+07 1.647288E+06 Total 32 5.658545E+07

118

Table A5.27 ANOVA of Ca concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure 5.5b).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 3.338457E+09 3.338457E+09 3286.443 0.000000 P Conc (ppm) 6 2.864911E+07 4.774851E+06 4.700 0.002306 Error 26 2.641150E+07 1.015827E+06 Total 32 5.506061E+07

Tukey HSD test; variable Ca (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1016E3, df = 26.000 P Conc (ppm) Ca (mg kg-1) 1 2 5 45 9360.00 **** 4 40 9425.00 **** 2 15 9700.00 **** **** 6 50 9700.00 **** **** 3 25 9840.00 **** **** 1 5 10580.00 **** **** 7 100 12160.00 ****

Table A5.28 ANOVA of Mg concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.1a).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.733320E+09 1.733320E+09 3086.946 0.000000 P Conc (ppm) 6 5.063424E+06 8.439040E+05 1.503 0.216380 Error 26 1.459900E+07 5.615000E+05 Total 32 1.966242E+07

119

Table A5.29 ANOVA of Mg concentration in lotus petiole (Nelumbo nucifera) as a function of P supply. (Figure A5.1a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.110032E+09 1.110032E+09 989.6896 0.000000 P Conc (ppm) 6 5.857288E+06 9.762146E+05 0.8704 0.529698 Error 26 2.916150E+07 1.121596E+06 Total 32 3.501879E+07

Table A5.30 ANOVA of Mg concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.1a).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 645221400 645221400 3450.382 0.000000 P Conc (ppm) 6 2299818 383303 2.050 0.094712 Error 26 4862000 187000 Total 32 7161818

Table A5.31 ANOVA of S concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.1b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 592026667 592026667 1814.534 0.000000 P Conc (ppm) 6 3377606 562934 1.725 0.154842 Error 26 8483000 326269 Total 32 11860606

Table A5.32 ANOVA of S concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.1b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 737263350 737263350 2226.994 0.000000 P Conc (ppm) 6 1353106 225518 0.681 0.666176 Error 26 8607500 331058 Total 32 9960606

120

8000 A ) -1 6000

4000

Organ Mg Conc. (mg kg Conc. (mg Mg Organ 2000

0 B 7000

6 000 ) -1

5000

4000 Conc. (m kg

3000

Organ S Organ 2000 g Leaf 1000 Petiole Roots & Stolons

0 20 40 60 80 100 P Supply (ppm)

Figure A5.1 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Magnesium; b) Sulphur. Values are means and bars represent S.E. (n=5). (Tables A5.28-33).

121

Table A5.33 ANOVA of S concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P su pply. (Figure A5.1b).

Univariate Resul ts for Each DV (P_root) Sigma-restricted pa rameteriz ation Effecti ve hy pothesis dec om position Degr. of S (mg kg-1) S (mg kg-1) S (mg kg -1) S (mg kg-1) Intercept 1 1.491527E+0 9 1.491527E+09 1792.783 0.000000 P Conc (ppm) 6 2.434455E+06 4.057424E+05 0.488 0.811451 Error 26 2.163100E+07 8.319615E+05 Total 32 2.406545E+07

Table A5.34 ANOVA of Fe concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.2a).

Univariate Results for Each DV (P_leaf) Sigma-rest rict ed parameterization Effective hy pothesis decom position Degr. of Fe (mg k g-1) Fe (mg k g-1) F e (mg kg-1) Fe (mg kg-1) Intercept 1 890938.6 8 90938.6 1006.052 0.0 0 0000 P Conc (ppm) 6 1406.1 234.3 0. 26 5 0.9 4 8444 Error 26 23025.1 885.6 Total 32 24431.1

Table A5.35 ANOVA of Fe concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.a).

Univariate Results for Each DV (P_petiole) Sigma-rest rict ed parameterization E ffective hy pothesis decom pos ition Degr. of Fe (mg kg-1) Fe (mg k g-1) F e (mg kg-1) Fe (mg kg-1) Intercept 1 2232108 2 232108 21 2 .3946 0.0 0 0000 P Conc (ppm) 6 73967 1 2 328 1. 17 31 0.3 5 0764 Error 26 273241 10509 Total 32 347208

Table A5.36 ANOVA of Fe concentratio n in lotus root s and s tolo n s (Nelumbo nucifera) as a function of P supply. (Figure A 5.2a).

Univariate Results for E ach DV (P_root ) Sigma-restricted parameter ization Effe ctive hypothesis decom pos ition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (m g kg-1) Fe (mg k g-1) Intercept 1 23439313 234 39313 727.72 47 0.0 00000 P Conc (ppm) 6 486789 811 32 2.5189 0.0 46770 Error 26 837435 32209 Total 32 1324224

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Table A5.37 ANOVA of Mn concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.2b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 51083.04 51083.04 583.4965 0.000000 P Conc (ppm) 6 1436.50 239.42 2.7347 0.033978 Error 26 2276.21 87.55 Total 32 3712.71

Table A5.38 ANOVA of Mn concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.2b).

Univariate Results for Each DV (P_petiole) Sigma-re stri cted p arameteriza tion Effective hy p othesis dec omp osition Degr. of Mn (mg k g-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 12607.01 12607. 01 9 10.2680 0.000000 P Conc (ppm) 6 654.70 109.12 7.8786 0.000067 Error 26 360.09 13.85 Total 32 1014.80

Tukey HSD test; variable Mn (mg kg -1) (P_petiole ) Homogenous Groups, alpha = .01000 E rror: Betwee n MS = 1 3.8 50, df = 26.000 P Conc (ppm) M n (mg kg-1) 1 2 4 40 14.61958 **** 5 45 15.56848 **** 6 50 15.96692 **** 3 25 18.783 65 *** ** *** 7 100 22.12011 **** **** 2 15 22.65791 **** **** 1 5 27.79884 ****

123

Table A5.39 ANOVA of Mn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Fi gure A5 .2b ).

Univariate Re sult s for Eac h DV (P_root) Sigma-re strict ed p arameterizat io n Effec tive hy po thesis decom posi tion Degr. of Mn (mg k g-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 8637.225 8637.225 2105.410 0.000000 P Conc (ppm) 6 405.695 67.616 16.482 0.000000 Error 26 106.662 4.102 Total 32 512.357

Tukey HSD test; variable Mn (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = 4.1024, df = 26.000 P Conc (ppm) Mn (mg kg-1) 1 2 3 4 40 12.90086 **** 6 50 12.97253 **** 5 45 13.44438 **** 3 25 15.06002 **** **** 2 15 17.26438 **** **** 1 5 19.59227 **** **** 7 100 22.58928 ****

Table A5.40 ANOVA of Zn concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.3a).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 66144.02 66144.02 1694.349 0.000000 P Conc (ppm) 6 819.67 136.61 3.499 0.011356 Error 26 1014.99 39.04 Total 32 1834.66

Table A5.41 ANOVA of Zn concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.3a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 74638.65 74638.65 908.6622 0.000000 P Conc (ppm) 6 1472.73 245.46 2.9882 0.023473 Error 26 2135.67 82.14 Total 32 3608.41

124

A 1000 ) -1 800

600

400 Organ Fe Conc. (mg kg (mg Conc. Organ Fe

200

B 50 ) -1 40

20 Organ Mn Conc. (mg kg (mg Conc. Organ Mn

10 Leaf Petiole Roots & Stolons

0 0 20406080100120 P Supply (ppm)

Figure A5.2 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Iron; b) Manganese. Values are means and bars represent S.E. (n=5). (Tables 34- 39).

125

Table A5.42 ANOVA of Zn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.3a).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 277693.4 277693.4 576.1851 0.000000 P Conc (ppm) 6 17457.8 2909.6 6.0372 0.000467 Error 26 12530.7 482.0 Total 32 29988.5

Tukey HSD test; variable Zn (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = 481.95, df = 26.000 P Conc (ppm) Zn (mg kg-1) 1 2 4 40 70.8338 **** 3 25 73.7922 **** 6 50 80.4865 **** 1 5 81.1929 **** 2 15 89.2140 **** **** 5 45 111.1234 **** **** 7 100 138.7564 ****

Table A5.43 ANOVA of Cu concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.3b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 19061.21 19061.21 1766.862 0.000000 P Conc (ppm) 6 63.76 10.63 0.985 0.455440 Error 26 280.49 10.79 Total 32 344.25

Table A5.44 ANOVA of Cu concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.3b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 24266.30 24266.30 67.91899 0.000000 P Conc (ppm) 6 1851.54 308.59 0.86371 0.534239 Error 26 9289.36 357.28 Total 32 11140.90

126

160 A 140 )

-1 120

100

Organ Zn Conc. (mg kg Conc. (mg Organ Zn 40

0 80 B 70

) 60 -1

g kg 50

Organ Cu Conc. (m 20 Leaf 10 Petiole Roots & Stolons

0 0 20 40 60 80 100 120 P Suppl y (ppm)

Figure A5.3 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Zinc; b) Copper. Values are means and bars represent S.E. (n=5). (Tables A5.40- 45).

127

Table A5.45 ANOVA of Cu concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P su pply. (Fig ure A5.3b ).

Univariate R esult s for E ach D V (P_ro ot) Sigma-res tric ted pa rameteri zatio n Effe ctive hypothesis de c omposition Degr. Of Cu (m g kg-1) Cu (mg kg-1) Cu (mg k g-1) Cu (mg kg-1) Intercept 1 67305.69 67305.69 186.4864 0.000000 P Conc (ppm) 6 2747.37 457.90 1.2687 0.305678 Error 26 9383.78 360.91 Total 32 12131.16

Table A5.46 ANOVA of B concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.4a).

Univari ate Results for Each DV (P_leaf) Sigma-restricted parameterization Effect ive hyp othesi s decomposi t ion Degr. of B (mg k g-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 115756.9 1 15756.9 1 25 5 .500 0.000 0 00 P Conc (ppm) 6 1378.9 229. 8 2.4 93 0. 048 6 44 Error 26 2397.2 92.2 Total 32 3776.1

Table A5.47 ANOVA of B concentrat ion in lotus petioles (Nelum b o nucifera) as a function of P supply. ( Figure A5.4a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effec tive hypothesis decomp osition Degr. of B (mg kg-1) B (mg kg-1) B (mg k g-1) B (mg k g-1) Intercept 1 24960.13 2496 0.13 5045.77 8 0. 000 000 P Conc (ppm) 6 64.91 10.8 2 2.187 0.076 953 Error 26 128.62 4.95 Total 32 193.53

Table A5.48 ANOVA of B concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.4a).

Univariate Results for Each DV ( P_root) Sigma-restricted parameterization Effective hyp othesis decomposition Degr. of B (mg k g-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 19104.01 1 9104.01 7 80 5 .319 0.000 0 00 P Conc (ppm) 6 17.94 2 .9 9 1.2 21 0. 327 2 66 Error 26 63.64 2.45 Total 32 81.57

128

Table A5.49 ANOVA of Mo concentr ation in lotus lea ves (Nelum b o nucifera) as a function of P supply. ( Figure A5.4b).

Univariate Results fo r Each DV (P_le af) Sigma-restricted paramet erization E ffective hypothe sis deco mposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (m g kg-1) Mo (mg kg-1) Intercept 1 160.5810 160.5810 1497.208 0.000000 P Conc (ppm) 6 8.3643 1.3941 12.998 0.000001 Error 26 2.7886 0.1073 Total 32 11.1529

Tukey HSD test; variable Mo (mg kg-1) (P_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = .10725, df = 26.000 P Conc (ppm) Mo (mg kg-1) 1 2 1 5 1.506602 **** 7 100 2.055538 **** 6 50 2.061036 **** 3 25 2.123547 **** 2 15 2.202271 **** 4 40 2.303856 **** 5 45 3.267184 ****

Table A5.50 ANOVA of Mo concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.4b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 138.1149 138.1149 3082.258 0.000000 P Conc (ppm) 6 3.8366 0.6394 14.270 0.000000 Error 26 1.1651 0.0448 Total 32 5.0016

Tukey HSD test; variable Mo (mg kg-1) (P_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = .04481, df = 26.000 P Conc (ppm) Mo (mg kg-1) 1 2 6 50 1.751811 **** 4 40 1.801713 **** 1 5 1.856564 **** 7 100 1.897352 **** 3 25 2.070138 **** 2 15 2.229174 **** 5 45 2.786727 ****

129

80 A 70

) 60 -1

Organ B Conc. (mg kg (mg Conc. B Organ 20 Leaf Petiole 10 Roots & Stolons

0 9 B

8 ) -1 7

Organ Mo Conc. (mg kg (mg Conc. Mo Organ 3

1 0 20406080100120 P Supply (ppm)

Figure A5.4 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Boron; b) Molybdenum. Values are means and bars represent S.E. (n=5). (Tables A5.46-51).

130

Table A5.51 ANOVA of Mo concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.4b).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 1588.138 1588.138 1651.157 0.000000 P Conc (ppm) 6 34.633 5.772 6.001 0.000486 Error 26 25.008 0.962 Total 32 59.641

Tukey HSD test; variable Mo (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = .96183, df = 26.000 P Conc (ppm) Mo (mg kg-1) 1 2 3 25 5.789101 **** 6 50 5.988472 **** 4 40 6.095681 **** **** 7 100 7.018533 **** **** 2 15 7.257095 **** **** 5 45 8.017089 **** **** 1 5 8.641892 ****

Table A5.52 ANOVA of Na concentration in lotus leaf (Nelumbo nucifera) as a function of P supply. (Figure A5.5a).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 322036308 322036308 324.0186 0.000000 P Conc (ppm) 6 1987556 331259 0.3333 0.913115 Error 26 25840935 993882 Total 32 27828491

Table A5.53 ANOVA of Na concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.5a).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 263105304 263105304 937.8891 0.000000 P Conc (ppm) 6 6014428 1002405 3.5733 0.010250 Error 26 7293760 280529 Total 32 13308188

131

Table A5.54 ANOVA of Na concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.5a).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 507656017 507656017 893.3069 0.000000 P Conc (ppm) 6 13814197 2302366 4.0514 0.005353 Error 26 14775500 568288 Total 32 28589697

Tukey HSD test; variable Na (mg kg-1) (P_root) Homogenous Groups, alpha = .01000 Error: Between MS = 5683E2, df = 26.000 P Conc (ppm) Na (mg kg-1) 1 2 1 5 2680.000 **** 5 45 3540.000 **** **** 2 15 3975.000 **** **** 6 50 4120.000 **** **** 3 25 4120.000 **** **** 4 40 4300.000 **** **** 7 100 4860.000 ****

Table A5.55 ANOVA of Al concentration in lotus leaves (Nelumbo nucifera) as a function of P supply. (Figure A5.5b).

Univariate Results for Each DV (P_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 50858.79 50858.79 586.5662 0.000000 P Conc (ppm) 6 503.25 83.88 0.9674 0.466406 Error 26 2254.36 86.71 Total 32 2757.61

Table A5.56 ANOVA of Al concentration in lotus petioles (Nelumbo nucifera) as a function of P supply. (Figure A5.5b).

Univariate Results for Each DV (P_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 137902.2 137902.2 55.72863 0.000000 P Conc (ppm) 6 11022.8 1837.1 0.74242 0.620552 Error 26 64337.8 2474.5 Total 32 75360.6

132

Table A5.57 ANOVA of Al concentration in lotus roots and stolons (Nelumbo nucifera) as a function of P supply. (Figure A5.5b).

Univariate Results for Each DV (P_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 866355.3 866355.3 254.4403 0.000000 P Conc (ppm) 6 45225.9 7537.7 2.2137 0.073913 Error 26 88528.6 3404.9 Total 32 133754.5

133

A 5000 )

-1 4000

3000 nc. (mg kg nc. (mg a Co a 2000 Organ N Organ

1000 Leaf Petiole Roots & Stolons

0 B 025 ) -1 200 g kg

150

100 Organ Al Conc. (m Conc. Organ Al

20 40 60 80 100 P Supply (ppm)

Figure A5.5 Effect of phosphorous supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Sodium; b) Aluminium. Values are means and bars represent S.E. (n=5). (Tables A5.52-57).

134

Table A5.58 ANOVA for the relationship between P concentration in lotus leaves (Nelumbo nucifera) and P suppl y. (F igure 5.6, Ta bles A5.163-165 & 1 79-181). Rank 4 Eqn 85 y2=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.9237111194 0.9184498172 571.3585 0257 363.24210486

Parm VE alue Std rro r t-v alue 95% Confidence Limits P>|t| a 1.2 2464e+06 5331 61.00 07 2. 29 6945366 1357 81.664 2.3135e+0 6 0.02878 b 672 290.7917 1831 4.398 87 3 6.708 31876 6348 87.7993 709693.784 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.1858058e+08 1 1.1858058e+08 363.242 0.00000 Error 9793516.2 30 326450.54 Total 1.28374 1e+08 31

Table A5. 59 ANOVA for the relationship between P concentration in lotus petioles (Nelumbo nucifera) and P supply. ( Tables A5.163 -16 4, 166, 179- 180 &182). Rank 7 Eqn 9 y=a+bx0.5lnx

r2 Coef Det DF Adj r2 Fit S td Err F-value 0.9183005396 0.9128539089 899.1671 5115 348.43947059

Parm Value Std Erro r t -v alue 95% Confidence Limits P>|t | a 469 .9441594 310.12 991 63 1 .51 5313856 -162.5 6997 5 1102.4582 94 0.13982 b 225 .9235106 12.1 03131 59 1 8.6 6653344 201.23 9011 250.60801 02 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum o f Squares DF Mean Square F Statistic P>F Regr 2.8171386e+08 1 2.8171386e+08 348.439 0.00000 Error 25063549 31 808501.57 Total 3.0677741e+08 32

Table A5.60 A NOVA for the rela tionship betwee n P concentration in lotus roots and stolons (Nelumbo nucifera) and P supp ly. (Tab les A5.163, 165-1 6 6, 179 & 181-18 2). Rank 14 Eqn 75 y0.5=a+bx0.5

r2 Coef Det DF A dj r2 Fi t Std Err F-value 0.9322611 221 0.9 277 451969 1060 .2750089 426.63970362

Parm Value Std Error t-val ue 95% Confidence Limits P>|t| a 19. 61980467 8.4013 181 95 2. 33 5324555 2.48520325 4 36.754406 09 0.026 17 b 9.8 4217812 1.10 32 315 05 8 .92 1226485 7.592 12263 3 12.09223361 0.00000

Soln Vector Covar Ma trix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.7962114e+08 1 4.7962114e+08 426.64 0.00000 Error 34849676 31 1124183.1 Total 5.1447082e+08 32

135

Table A5.61 ANOVA for the relationsh ip between N co ncentration in lotus leaves (Nelum bo nucifer a) and leaf P conc entration. (Figu r e 5.7, Tables A4 . 159-161 & 179- 1 81). Rank 2 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.26907995 34 0.21867167 43 0.25 72 814516 11.0441609 03

Parm V alue Std E rro r t-v alue 95% C onf idence Limits P>|t| a 1.8 81042346 0.0314 110 87 5 9.884 66238 1. 816892348 1.945192344 0.00000 b 1.67 507e-13 9.9737 e-14 1.679488164 -3.6183e-14 3.71197e-13 0.10344

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.73105437 1 0.73105437 11.0442 0.00235 Error 1.98581 24 30 0.0661937 45 Total 2.7168667 31

Table A5.62 ANOVA for the relationship between N concentration in lo tus petioles (Nelu mbo nucifer a) and petiole P concentration. (Ta bles A4.159-160, 162, 175-176 & 178). Rank 1519 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.04841046 81 0 0.40 76 356947 1.5770 7126 94

Parm V alue Std E rro r t-v alue 9 5% Confidence Limits P>|t| a 2.6 92471658 0.2024 461 51 13.29969302 2.279580012 3.105363305 0.00000 b -0.00039127 0.000311566 -1.25581498 -0.00102671 0.000244174 0.21857

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.26205698 1 0.26205698 1.57707 0.21857 Error 5.1511726 31 0.16616686 Total 5.4132296 32

Table A5.63 AN OVA for th e relati onship between N c oncentration in l otus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Tables A4.159, 161-162,175 &177-178). Rank 17 Eqn 1146 y=a+b(lnx)2+cx0.5 r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.2723630113 0.1970902194 0.242487 3049 5.6146749464

Parm Value Std Erro r t -v alue 95% Confidence Limits P>|t | a 5.1 14184489 0.95 06961 8 5 .37 9409947 3.172 60386 7 7.055765112 0.00001 b -0.0 8288626 0.0259 595 29 - 3.1 9290311 -0.135 90269 -0.02986983 0.00330 c 0.0 4200506 0.0127 425 67 3.296436353 0.015981267 0.068028853 0.00252

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.66028682 2 0.33014341 5.61467 0.00849 Error 1.7640028 30 0.058800093 Total 2.4242896 32

136

Table A5.64 ANOVA for the relatio nship between K concentration in lotus leaves (Nelu mbo nucifer a) and leaf P conc entration. (Figu r e 5.8a, Tables A 4 .167-169 & 183 - 185). Rank 2179 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.01867212 46 0 180 1.7 631649 0.55 1 79479 36

Parm V alue Std Erro r t-value 95% Confide nce Limits P>|t| a 2705 7.96842 421 .04795 33 64.26338903 26196.82866 27919.10817 0.00000 b 1.04013e- 09 1.40022e-09 0.742828913 -1.8237e-09 3.90391e-09 0.46356

Soln Vector Covar Matrix Direct LU Decom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 1791319.3 1 1791319.3 0.551795 0.46356 Error 941441 65 29 324635 0.5 Total 959354 84 30

Table A5.65 ANOVA for the relationship between K concentration in lo tus petioles (Nelu mbo nucifer a) and petiole P concentration. (Tables A4.167-168 , 170, 183-184 & 186). Rank 1 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.45125080 8 0.4120544 371 273 3.1 428148 23.84 74582 22

Parm V alue Std Erro r t-value 95% Confide nce Limits P>|t| a 5268 5.7372 638 .20880 23 82.55250791 51380.45364 53991.02076 0.00000 b 6.60126e-09 1.35178e-09 4.883385938 3.83656e-09 9.36597e-09 0.00004

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.7814217e+08 1 1.7814217e+08 23.8475 0.00004 Error 2.1663202e+08 29 7470069.6 Total 3.9477419e+08 30

Table A5.66 AN OVA for the rela ti onship between K c oncentration in l otus roots and stolons (Nelumbo nuci fera) and ro ots and stolo n P concentratio n. (T ables A4.167, 168-170, 183, 1 84-186 ). Rank 2 Eqn 2 y=a+bxln x

r2 Coef Det DF Adj r2 Fit S td Err F-value 0.2889674374 0.2415652666 3972.097 1031 12.598565848

Parm Value Std Error t-value 95% Confide nce Limits P>|t| a 39375.5751 1 1247.383179 31.56654328 36831.52035 41919.62988 0.00000 b 0.06 363773 0.0179 289 2 3 .54 9445851 0.027 07145 7 0.100204002 0.001 25

Soln Vector Covar Ma trix Direct LUDecom p

Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.9877457e+08 1 1.9877457e+08 12.5986 0.00125 Error 4.8910422e+08 31 15777555 Total 6.8787879e+08 32

137

Table A5.67 ANOVA for the relationship between Ca concentration in lotus leaves (Nelumbo nucifera) and leaf P c once ntration. (Tab les A4.171-173 , 187 -189). Rank 2 914 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0175360864 0 3309.932 6123 0.5533217777

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 198 67.96613 2911 .5521 27 6 .82 3840091 1392 9.81642 25806.115 84 0.00000 b 30. 52618504 41.0 37760 32 0 .7438 56019 -5 3.1708789 114.223249 0.46256

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6062001.9 1 6062001.9 0.553322 0.46256 Error 3.3962527e+08 31 10955654 Total 3.45687 27e+08 32

Table A5.68 ANOVA for the relationship between Ca concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. (Tables A4.171-172, 174, 187-188 & 190). Rank 2629 Eqn 15 y=a +b/x0.5

r2 Coef Det DF Adj r2 Fit S td Err F-value 0.0152217121 0 1340.728 3414 0.4791668132

Parm Value Std Erro r t -v alue 95% Confidence Limits P>|t | a 121 24.63957 693. 31 038 1 1 7.4 8803985 1071 0.623 7 3 13538.655 42 0.00000 b -28 499.8471 411 71.734 63 - 0.6 9221876 -112 470.153 55470.459 22 0.49395

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 861327.5 1 861327.5 0.479167 0.49395 Error 55724127 31 1797552.5 Total 56585455 32

Table A5.69 ANOVA for the relationship between Ca concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Tables A4.171, 173-174, 187 & 189-190 & 186). Rank 6 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3234262683 0.2783213528 1096.2187166 14.819100782

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 9623.583589 233.6246212 41.19250591 9147.103033 10100.06415 0.00000 b 8.70732e-10 2.2619e-10 3.849558518 4.09414e-10 1.33205e-09 0.00055

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 17808046 1 17808046 14.8191 0.00055 Error 37252560 31 1201695.5 Total 55060606 32

138

Table A5.70 ANOVA for the relationship between Mg concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 34 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1805436726 0.1259132508 720.94243779 6.8299598949

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 684.4231652 2528.706183 0.270661404 -4472.90709 5841.753425 0.78845 b 781.9241675 299.195846 2.613419196 171.7102166 1392.138118 0.01371

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r2 Attainable 0.1805436726 0.1259132508 720.94243779 0.8873485806 Source Sum of Squares DF Mean Square F Statistic P>F Regr 3549926.3 1 3549926.3 6.82996 0.01371 Error 16112498 31 519758 Total 19662424 32

Table A5.71 ANOVA for the relationship between Mg concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 81 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0357002049 0 1043.7001482 1.1476787162

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6159.464501 349.6745963 17.61484696 5446.29846 6872.630542 0.00000 b -0.00667318 0.006229065 -1.07129768 -0.01937744 0.006031079 0.29231

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1250177.9 1 1250177.9 1.14768 0.29231 Error 33768610 31 1089310 Total 35018788 32

Table A5.72 ANOVA for the relationship between Mg concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Figure A5.6a). Rank 1 Eqn 6721 y=a+bx2+cx4 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2858516001 0.2119741794 412.90035097 6.004037819

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4762.97485 127.0615756 37.48556421 4503.480494 5022.469206 0.00000 b -1.3336e-05 3.86924e-06 -3.44675888 -2.1238e-05 -5.4343e-06 0.00170 c 6.53517e- 14 1.92983e-14 3.386399557 2.59393e-14 1.04764e-13 0.00199

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2047217.2 2 1023608.6 6.00404 0.00641 Error 5114601 30 170486.7 Total 7161818.2 32

139

) 5000 -1

4000

3000

2000

1000 Roots and stolons Mg Conc. (mg kg (mg Conc. Mg stolons and Roots A

0 B

8000 ) -1

6000

4000 Organ S Conc. (mg kg (mg S Conc. Organ

2000 Leaf Roots & Stolons

0 0 2000 4000 60 00 800 0 10000 12000 14000 16 000

Organ P Conc. (mg kg-1)

Figure A5.6 Nutrient concentration in orga ns of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration a) Magnesium, regression equation is y = 4762.97+(-1.33*10-5)x2 + (6*10-14)x4 (r2 = 0.21) for roots and stolons; b ) Sulphur, regress ion eq uations are y = 141 4.5 3 + 39.80(lnx)2 (r2 = 0.16) & y0.5 = 80.2 2 + (2.2 8* 10-12)x3 (r2 = 0.21) for leaves and roots and stolons respectively. (Tables A5.72, 73 & 75).

140

Table A5.73 ANOVA for the relationship between S concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. (Figure A5.6b). Rank 9 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2168185335 0.1646064357 547.39874151 8.5821419742

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1414.529877 975.1456948 1.450583113 -574.292879 3403.352634 0.15694 b 39.80139066 13.58627495 2.929529309 12.09200023 67.51078109 0.00632

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2571599.2 1 2571599.2 8.58214 0.00632 Error 9289006.8 31 299645.38 Total 11860606 32

Table A5.74 ANOVA for the relationship between S concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 270 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0305208659 0 558.12473281 0.9759331683

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4678.891043 125.6322203 37.2427633 4422.662441 4935.119646 0.00000 b 2.4459e-10 2.47588e-10 0.987893298 -2.6037e-10 7.49549e-10 0.33085

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 304006.32 1 304006.32 0.975933 0.33085 Error 9656599.7 31 311503.22 Total 9960606.1 32

Table A5.75 ANOVA for the relationship between S concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Figure A5.6b). Rank 2 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.258612083 0.2056558032 576.03690159 10.115824975

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 80.21740223 1.55865004 51.4659482 77.02960496 83.40519949 0.00000 b 2.28311e-12 1.39948e-12 1.631398241 -5.7915e-13 5.14536e-12 0.11362

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3356618 1 3356618 10.1158 0.00349 Error 9622736.8 29 331818.51 Total 12979355 30

141

Table A5.76 ANOVA for the relationship between Fe concentration in lotus leaves (Nelumbo nucifera) as a function of leaf P concentration. Rank 133 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1320779934 0.0700835644 21.441101681 4.4131405589

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 167.1526436 4.980503776 33.56139281 156.9663697 177.3389176 0.00000 b -3.5326e-11 1.68159e-11 -2.10074762 -6.9718e-11 -9.3359e-13 0.04447

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2028.8127 1 2028.8127 4.41314 0.04447 Error 13331.904 29 459.72084 Total 15360.717 30

Table A5.77 ANOVA for the relationship between Fe concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 2047 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0829430308 0.0196977225 55.566548379 2.7133438881

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 279.1235624 22.31404414 12.50887381 233.5522046 324.6949201 0.00000 b -0.05175612 0.031420227 -1.64722308 -0.11592479 0.012412541 0.10995

Soln Ve ctor Covar Matrix Direct LUDecomp Source Sum of Squares D F Mean Square F Statistic P>F Regr 8377.8326 1 8377.8326 2.71334 0.10995 Error 92629.239 30 3087.6413 Total 101007.07 31

Table A5.78 ANOVA for the relationship between Fe concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. Rank 12 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0629505343 0.0004805699 200.06963456 2.082565 1506

Parm Value Std Error t-value 95% Confiden ce Limits P>|t| a 1403.60842 3 88.754837 3 .610523359 6 10.7377027 2196.479137 0 .00106 b -65.5334112 45.41125208 -1.44310954 -158.15027 27.083448 0.15902

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 83360.6 24 1 8336 0.624 2.08257 0.15902 Error 1240863.6 31 40027.859 Total 1324224.2 32

142

Table A5.79 ANOVA for the relationship between Mn concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 109 Eqn 7 y=a+bx3

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0773351548 0.0158241652 10.512030868 2.598332225

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37.09895011 2.399533733 15.46089959 32.2050688 41.99283143 0.00000 b 1.31199e-11 8.13922e-12 1.611934312 -3.4802e-12 2.972e-11 0.11711

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P >F Regr 287.12297 1 287.12297 2.59833 0.11711 Error 3425.5866 31 110.50279 Total 3712.7096 32

Table A5.80 ANOVA for the rel a tionship bet ween Mn concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. (Figure A5.7, Tables A5.81, 191-192). Rank 2 Eqn 1110 y=a+bx3+cx0.5 r2 Coef Det DF Adj r 2 Fit S td Err F-valu e 0.63865295 84 0.59993720 39 2.87 63 593762 25.627 6289 29

Parm V alue Std Erro r t-v alue 95% Confide nce Limits P>|t| a 36. 90949717 2.60 88798 86 14.14764143 31.57373869 42.24525564 0.00000 b 1.57225e-11 2.46823e-12 6.36995863 1.06744e-11 2.07706e-11 0.00000 c -0.32149842 0.045034876 -7.13887642 -0.41360508 -0.22939175 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 424.05747 2 212.02873 25.6276 0.00000 Error 239.929 85 29 8.27344 33 Total 663.98732 31

Table A5.81 ANOVA fo r the relation ship between M n co ncentration in lotus roots and stolo ns (Nelum bo nucifera) and roots and stolon P concentration. (Figure A5.7, T a bles A5.80, 191- 1 92). Rank 2 Eqn 6841 Fou ri er Series Polyno m ial 1x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6879081422 0.6556227776 2.308697 5324 33.062772627

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 22. 18610571 0.82 50788 84 2 6.8 8967824 20 .50106983 23.87114159 0.00000 b -2.7 1618917 0.63 36159 97 -4.2868065 -4.01020567 -1.42217267 0.00017 c -8.69631343 1.107793351 -7.85012242 -10.9587293 -6.43389758 0.00000

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 352.45473 2 176.22737 33.0628 0.00000 Error 159.902 53 30 5.33008 43 Total 512.35726 32

143

Petioles, Roots & Stol ons

40 ) -1

20 Organ Mn Conc. (mg kg (mg Conc. Mn Organ 10

0 0 2000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg Kg-1)

Figure A5.7 Manganese concentration in combined petioles, roots and stolons of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration, regression equation is y=24.43+2.58cos(x)+9.39sin(x) (r2 = 0.42). (Tables A5.80-81, 191-192).

Table A5.82 ANOVA for the relationship between Zn concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. (Figure A5.8, Tables A5.82-84 & 193-200). Rank 34 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3406548604 0.2966985177 6.2467447715 16.016347187

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.756049535 11.12806042 0.067940819 -21.9397793 23.45187839 0.94627 b 0.620486167 0.155042359 4.002042877 0.304275192 0.936697142 0.00036

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r 2 Attainable 0.3406548604 0.2966 985177 6.2 467447715 0 .8281719439

Source Sum of Squares DF Mean Square F Statistic P>F Regr 624.98702 1 624.98702 16.0163 0.00036 Error 1209.67 64 31 39 .02182 Total 1834.66 34 32

144

Table A5.83 ANOVA for the relationship between Zn concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. (Figure A5.8, Tables A5.193-195, 196-198 & 200). Rank 1 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2092669547 0.1547336412 8.5501163686 7.9394792953

Parm Value Std Error t-value 95% Confidence Limits P>|t| a -5.47519093 18.7435378 -0.29211086 -43.7546019 32.80422005 0.77221 b 6.276142891 2.227392805 2.817708164 1.727199917 10.82508586 0.00848

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 580.41158 1 580.41158 7.93948 0.00848 Error 2193.1347 30 73.10449 Total 2773.5463 31

Table A5.84 ANOVA for the relationship between Zn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stol o n P conce ntration. (Figure A5.8, Tables A5.193, 195-197 & 199-200). Rank 1 Eq n 7 y=a+bx3 r2 Coef Det DF Adj r 2 Fit Std Err F-valu e 0.70021060 46 0.6771498 819 1 5.860688239 63.063225765

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 73.96419763 3.516446887 21.0337878 66.7490446 81.17935066 0.00000 b 3.45311e-11 4.34833e-12 7.941235783 2.56091e-11 4.34532e-11 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 15864.275 1 15864.27 5 63.0632 0 .00000 Error 6792.1586 27 251.56143 Total 22656.434 28

145

200

) 150 -1 g

nc. (mg k nc. (mg 100 Co n Zn

Orga 50

Leaves & Petiole s Roots & Stolons 0 02000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg kg-1) Figure A5.8 Zinc con centration in organs of lotus (Nelumbo nucifera) as a function of organ phosphorous concentration, regression equations are y = 32.29 + 0.024x0.5lnx (r2 = 0.22) & y = 73.96 +(3.4*10-11)x3 (r2 = 0.68) for leaves and petioles, and roots and stolons respectively. (Tables A5.82- 84, 193-200).

Table A5.85 ANOVA for the relationsh ip between Cu c oncentration in lotus leaves (Nelumbo nucifer a) and leaf P conc entration. Rank 2499 Eqn 14 y=a +b/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0243708357 0 2.673068 4 0.7493882887

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 31. 6376544 9.14 15664 74 3 .46 0857009 12 .96808499 50.30722382 0.00164 b -66 .5447743 76.8 70641 51 -0.86567216 -223.535568 90.44601951 0.39354

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.354 6001 1 5.3546001 0.749388 0.39354 Error 214.35884 30 7.1452947 Total 219.71344 31

146

Table A5.86 ANOVA for the relationship between Cu concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 672 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0089844244 0 3.5 142289379 0 .2629104076

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 24.59552739 2.224961539 11.0543607 20.0449701 29.14608468 0.00000 b -0.0151138 5 0.029476175 -0.512 7479 -0.07539939 0.045171699 0.61201

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 3.2468923 1 3.2468923 0.26291 0.61201 Error 358.14435 29 12.349805 Total 361.39124 30

Table A5.87 ANOVA for the relationship between Cu concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. Rank 1 Eqn 12 y= a+bx0.5 r2 Coef Det DF Ad j r2 Fit S td Err F -value 0.1417648864 0.0825 762579 1 1 . 394284513 4 .9554562904

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 30.03041022 6.140292292 4.8907 13469 17.4902604 42.57056003 0.00003 b 0.16973265 9 0.076247146 2.2260 85418 0.014015214 0.325450105 0.03367

Soln Vector Covar Matr ix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 643.3655 1 643.3655 4.95546 0.03367 Error 3894.8916 30 129.82972 Total 4538.2571 31

Table A5.88 ANOVA for the relationship between B concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 2399 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0115469875 0 7.6 529796165 0 .3387744611

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 73.9601342 27.73608279 2.666567401 17.23347554 130.6867929 0.01240 b -1.9060061 6 3.274680753 -0.582 04335 -8.6034803 4.791467988 0.56504

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 19.841376 1 19.841376 0.338774 0.56504 Error 1698.4748 29 58.568097 Total 1718.3162 30

147

Table A5.89 ANOVA for the relationship between B concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 2242 Eqn 13 y=a+blnx

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0553180231 0 1.7 693563231 1 .6981616148

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 32.51964147 4.056012589 8.017638199 24.22416429 40.81511864 0.00000 b -0.6266783 6 0.480900456 -1.303 1353 -1.61023023 0.356873506 0.20278

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.3163018 1 5.3163018 1.69816 0.20278 Error 90.788032 29 3.1306218 Total 96.104334 30

Table A5.90 ANOVA for the relationship between B concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Figure A5.9a). Rank 1 Eqn 7 y=a +bx3

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2419982889 0.1878 553095 1.1 4460197 9 .2584888331

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 23.79332312 0.253051537 94.02560211 23.27577462 24.31087162 0.00000 b 7.23586e-1 3 2.37805e-1 3 3.0427 76501 2.37221e-13 1.20995e-12 0.00494

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 12.129673 1 12.129673 9.25849 0.00494 Error 37.993296 29 1.3101137 Total 50.122969 30

148

) 25 1 - g

20 (mg k c.n Co 15 B ns olo 10 & St

Roots 5

10 ) -1 kg 8

2 Roots & Stolons Mo Conc. (mg

0 0 2000 4000 6000 8000 10000 12000 14000 1 6000

Organ P Conc. (mg kg-1)

Figure A5.9 Nutrient concen tration in organs of lotus (Nelumbo nucifera) as a function of orga n phosphorou s concentration a) Boro n, regre ssi on equations is y = 23.79 + (7.23*10-13)x3 (r2 = 0.19) for roots and st olons; b) Molybd enum , regress io n equation is y = 6.47 + (2.72*106)/x2 (r2 = 0.16) for roots and stolons. (Tables A5.90 & 93).

149

Table A5.91 ANOVA for the relationship between Mo concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 1597 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1487160298 0.0856579579 0.3919881412 4.8914921211

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.519643722 0.708702616 0.733232403 -0.93206778 1.971355222 0.46951 b 0.02196366 0.009930795 2.211671793 0.001621348 0.042305971 0.03532

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.75160077 1 0.75160077 4.89149 0.03532 Error 4.3023317 28 0.1536547 Total 5.0539324 29

Table A5.92 ANOVA for the relationship between Mo concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 1296 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0133309447 0 0.3989877391 0.4188428556

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.500805595 0.864804204 1.735428191 -0.26297421 3.264585397 0.09260 b 0.06635657 0.102531751 0.647180698 -0.14275832 0.275471456 0.52228

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.066676103 1 0.066676103 0.418843 0.52228 Error 4.9349277 31 0.15919122 Total 5.0016038 32

Table A5.93 ANOVA for the relationship between Mo concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Figure A5.9b). Rank 1 Eqn 20 y=a+b/x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2162751458 0.1602947991 1.0611817789 8.002782092

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6.47135201 0.224691588 28.80104259 6.011806113 6.930897907 0.00000 b 2.72374e+06 962819.6926 2.828918891 754551.4424 4.69293e+06 0.00839

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9.0119871 1 9.0119871 8.00278 0.00839 Error 32.657096 29 1.1261068 Total 41.669083 30

150

Table A5.94 ANOVA for the relationship between Na concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 2018 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std E rr F-valu e 0.0044988823 0 945.3330835 5 0.1400956 243

Parm Value Std Err or t-valu e 95% Confidence Limits P>|t| a 3210.427004 215.7869066 14.87776555 2770.326707 3650.5273 02 0.0000 0 b -2.7396e -1 0 7.3195e-1 0 -0.374293 5 -1.7668e- 0 9 1.21886e- 0 9 0.71 073

Soln Vector Covar Matrix Direct LUDecomp Source S um of Squares DF Mean Square F Statistic P>F Regr 125197.1 1 125197.1 0.140096 0.71073 Error 27703294 3 1 893654.64 Total 27828491 32

Table A5.95 ANOVA for the relationship between Na concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 2676 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.022439241 0 647.8142 466 7 0.7 115838728

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2898.59133 5 145.8210 63 6 19.877727 3 2601.187316 3195.9 9535 5 0 .00000 b -2.4242e-10 2.87375e- 1 0 -0.843554 3 1 -8.2852e-10 3.43688e- 1 0 0.40 538

Soln Vector Covar Matrix Direct LUDecomp Source S um of Squares DF Mean Square F Statistic P>F Regr 2 98625.63 1 298625.63 0.711584 0.40538 Error 13009562 31 419663.3 Total 13308188 3 2

Table A5.96 ANOVA fo r the relationship between Na concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon P concentration. (Figure A5.10a). Rank 23 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.278264638 0.2284 897854 755.65399527 11.566482092

Parm Value Std Err or t-value 95% Con fidence Limits P>|t| a -1233.54986 1504.360694 -0.81998278 -4305.86427 1838.764545 0.41869 b 599.911391 4 176.3950 78 4 3.4009531 1 5 239.6645815 960.15 8201 3 0 .00192

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6 604611.2 1 6604611.2 11.5665 0.00192 Error 1 7130389 30 571012.96 Total 23735000 31

151

Table A5.97 ANOVA for the relationship between Al concentration in lotus leaves (Nelumbo nucifera) and leaf P concentration. Rank 2468 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std E rr F-valu e 0.0051322889 0 9.407366579 3 0.1599217 211

Parm Value Std Err or t-valu e 95% Confidence Limits P>|t| a 26.31749589 32.99634587 0.797588193 -40.978995 2 93.61398696 0.43118 b 1.561265 5 04 3.904118908 0.399902139 -6.4012375 9.523768509 0.6919 7

Soln Vector Covar Matrix Direct LUDecomp Source S um of Squares DF Mean Square F Statistic P>F Regr 14.15284 1 14.15284 0.159922 0.69197 Error 2743.4549 31 88.498546 Total 2757.6078 32

Table A5.98 ANOVA for the relationship between Al concentration in lotus petioles (Nelumbo nucifera) and petiole P concentration. Rank 2329 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.022609664 7 0 16.47886 151 6 0.6 939806103

Parm Value Std Err or t-value 95% Confide nce Limits P>|t| a 63.7447593 1 8.499591 27 9 7.4997440 7 2 46.38627816 81.103 2404 7 0 .00000 b -0.0107699 2 0.012928227 -0.83305 49 9 -0.0371728 9 0.015633038 0.41140

Soln Vector Covar Matrix Direct LUDecomp Source SM um of Squares DF ean Square F Statistic P>F Regr 1 88.45243 1 188.45243 0.693981 0.41140 Error 8146.5863 30 271.55288 Total 8335.0387 3 1

Table A5.99 ANOVA for the re lationship between Al concentration in lotus roots and stolons (Nelumbo nucifera) and root and stolon P concentration. (Figure A5.10b). Rank 1 Eq n 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3888407737 0.3466 918616 40.563234353 19.087044278

Parm Value Std Err or t-value 95% Con fidence Limits P>|t| a 133.8699328 8.811117054 15.19329865 115.8752312 151.8646345 0.00000 b 3.6715e-11 8.40378e -12 4.36887 219 7 1.95522e-11 5.3877 8e-11 0 .00014

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3 1405.364 1 31405.364 19.087 0.00014 Error 4 9361.279 30 1645.376 Total 80766.644 31

152

6000 A ) -1 5000

4000

3000 stolon Na Conc Na stolon 2000

Roots andRoots 1000 kg . (mg

0 400 B 350 ) -1

300

250

200

150

100 ots and stolon Al Conc. (m Ro g kg 50

0 0 2000 4000 6000 8000 10000 12000 14000 16000

Organ P Conc. (mg kg-1)

Figure A5.10 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ pho sphorous conce nt ration: a) Sodium, regression equations is y = -1233.54 + 599.9 1lnx (r2 = 0.23) for ro ots and stolons; b) Alumini um, regression equations is y = 133.8 7 + (3.67*10-11)x3 (r2 = 0.35) for roots and stolons. (T ables A5.96 & 99).

153

Table A5.100 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.9a). Rank 1 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5758752547 0.528750283 4.0998681736 19.009156279

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18.68179149 1.205203966 15.50093762 16.21304308 21.1505399 0.00000 b 5370.53322 241.0112092 22.28333378 4876.844138 5864.222302 0.00000 c 2655.689408 417.7626637 6.356933347 1799.941385 3511.437432 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 639.04674 2 319.52337 19.0092 0.00001 Error 470.64973 28 16.808919 Total 1109.6965 30

Table A5.101 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 5.9a). Rank 16 Eqn 1022 y=a+bxlnx+cx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5979417703 0.5532686336 3.9917888877 20.820826847

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.998078768 2.245738831 0.444432253 -3.60210869 5.598266225 0.66015 b 0.000744884 0.000115441 6.452526614 0.000508414 0.000981353 0.00000 c -5.8374e-07 9.27824e-08 -6.29146343 -7.7379e-07 -3.9368e-07 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 663.53387 2 331.76694 20.8208 0.00000 Error 446.1626 28 15.934379 Total 1109.6965 30

Table A5.102 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon P concentration. (Figure 5.9a). Rank 3 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5800335134 0.5315758419 4.1328313542 18.645422152

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 19.03168101 1.283608255 14.82670507 16.39793443 21.6654276 0.00000 b 6183.576172 443.7505055 13.93480367 5273.075344 7094.077001 0.00000 c 4361.787236 535.9239858 8.13881698 3262.162047 5461.412424 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 636.93862 2 318.46931 18.6454 0.00001 Error 461.16797 27 17.080295 Total 1098.1066 29

154

Table A5.103 ANOVA for the relationship between dry mass of lotus leaves (Nelumbo nucifera) and leaf P concentration. (Figure 5.9b). Rank 1 Eqn 8034 y=4an/(1+n)2 n=exp(-(x-b)/c) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6332212359 0.5924680398 1.6056434245 24.170148789

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.131842604 0.455173921 15.66839018 6.199461093 8.064224115 0.00000 b 5528.6187 222.4102225 24.85775446 5073.032012 5984.205388 0.00000 c 1359.211394 168.4594144 8.068479867 1014.137926 1704.284861 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 124.62568 2 62.312838 24.1701 0.00000 Error 72.186543 28 2.5780908 Total 196.81222 30

Table A5.104 ANOVA for the relationship between dry mass of lotus petioles (Nelumbo nucifera) and petiole P concentration. (Figure 5.9b). Rank 3 Eqn 8034 y=4an/(1+n)2 n=exp(-(x-b)/c) r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.7691865306 0.7414889142 0.7789945761 43.322536255

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 5.188975515 0.250925301 20.6793635 4.673191172 5.704759859 0.00000 b 6056.352265 225.5282657 26.85407191 5592.772276 6519.932254 0.00000 c 2097.107959 171.9618904 12.19519019 1743.635231 2450.580687 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 52.57905 2 26.289525 43.3225 0.00000 Error 15.777646 26 0.60683255 Total 68.356697 28

Table A5.105 ANOVA for the relationship between dry mass in lotus roots and stolons (Nelumbo nucifera) and root and stolon P concentration. (Figure 5.9b). Rank 1 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r 2 Fit Std Err F-value 0.5651707443 0.5149981379 1.4654383111 17.546669061

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 7.035720034 0.431283289 16.31345386 6.150799821 7.920640247 0.00000 b 6434.537086 452.1017819 14.23249663 5506.900854 7362.173318 0.00000 c 4767.114026 553.1485025 8.618145045 3632.147049 5902.081003 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 75.363275 2 37.681638 17.5467 0.00001 Error 57.982755 27 2.1475094 Total 133.34603 29

155

Table A5.106 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.10a). Rank 1 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4569640446 0.4007879113 5.0056415085 12.622480337

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20.90421824 1.256162029 16.64133907 18.33879313 23.46964335 0.00000 b 5036.100712 300.2538136 16.77281181 4422.900619 5649.300805 0.00000 c 2735.652772 397.6867085 6.878914264 1923.468161 3547.837382 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 632.54902 2 316.27451 12.6225 0.00011 Error 751.69341 30 25.056447 Total 1384.2424 32

Table A5.107 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 5.10a). Rank 128 Eqn 1002 y=a+bx+cx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4684238863 0.4114693027 4.8775324054 12.777373128

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.274077492 3.617725208 0.075759621 -7.12500134 7.673156322 0.94013 b 0.011589622 0.002300239 5.038442838 0.006885105 0.016294139 0.00002 c -0.00010456 2.07055e-05 -5.04992948 -0.00014691 -6.2214e-05 0.00002

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 607.95565 2 303.97783 12.7774 0.00010 Error 689.91935 29 23.790322 Total 1297.875 31

Table A5.108 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and root and stolon P concentration. (Figure 5.10a). Rank 63 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4504024184 0.3915169632 4.9595222281 11.882939965

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 21.88592418 1.505833175 14.53409616 18.80614953 24.96569882 0.00000 b 5680.382405 424.6925101 13.37528275 4811.788695 6548.976115 0.00000 c 4456.731139 599.9716797 7.428235849 3229.651276 5683.811003 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 584.56604 2 292.28302 11.8829 0.00017 Error 713.30896 29 24.596861 Total 1297.875 31

156

Table A5.109 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.10b). Rank 5 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7556009811 0.7262730988 9.1532610479 40.191702888

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 78.35398962 3.25785501 24.0507909 71.65737274 85.0506065 0.00000 b 4659.178967 102.481876 45.4634434 4448.524454 4869.83348 0.00000 c 2326.89207 208.0414976 11.18474966 1899.256647 2754.527492 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 6734.6976 2 3367.3488 40.1917 0.00000 Error 2178.3369 26 83.782188 Total 8913.0345 28

Table A5.110 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 5.10b). Rank 142 Eqn 1611 y-1=a+b/x0.5+c/x r2 Coef Det DF Adj r2 Fit Std Err F-value 0.641107816 0.602655082 11.050460572 25.902105835

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.054629886 0.007745912 7.052737613 0.038787717 0.070472056 0.00000 b -5.10344764 0.97043878 -5.25890736 -7.0882178 -3.11867748 0.00001 c 150.2674155 29.11124609 5.161833851 90.72823211 209.8065989 0.00002

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6325.9511 2 3162.9755 25.9021 0.00000 Error 3541.2677 29 122.11268 Total 9867.2188 31

Table A5.111 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and roots and stolon P concentration. (Figure 5.10b). Rank 27 Eqn 1456 y-1=a+bxlnx+c/x1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8493883041 0.8313149006 7.3023920649 73.314677753

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.000247662 0.00152542 0.162356414 -0.00288788 0.003383207 0.87228 b 1.9328e-07 2.233e-08 8.655607631 1.4738e-07 2.3918e-07 0.00000 c 1138.747722 138.9689524 8.194259956 853.0929493 1424.402495 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 7819.0001 2 3909.5 73.3147 0.00000 Error 1386.4482 26 53.32493 Total 9205.4483 28

157

Table A5.112 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.11a). Rank 4 Eqn 8040 y=4ax^(-c-1)*b^(c+1)*c^2/(c-1+x^-c*b^c*(c+1))^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5302844157 0.4780937952 2.8903680006 15.805270395

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.75635154 0.754783453 22.2002105 15.21024773 18.30245536 0.00000 b 4957.323546 253.1176391 19.58505762 4438.835566 5475.811525 0.00000 c 2.511014028 0.240815415 10.42713161 2.017726012 3.004302045 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 264.08164 2 132.04082 15.8053 0.00003 Error 233.91836 28 8.3542272 Total 498 30

Table A5.113 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 5.11a). Rank 111 Eqn 8040 y=4ax^(-c-1)*b^(c+1)*c^2/(c-1+x^-c*b^c*(c+1))^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5569097204 0.5057839189 2.8319488096 16.967831552

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18.21339303 0.994420676 18.31558159 16.17301035 20.25377572 0.00000 b 4913.737693 274.871561 17.8764863 4349.747836 5477.727549 0.00000 c 1.940072225 0.147295713 13.17127422 1.637846386 2.242298063 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 272.16178 2 136.08089 16.9678 0.00002 Error 216.53822 27 8.0199341 Total 488.7 29

Table A5.114 ANOVA for the relationship between the number of stolons of lotus petioles (Nelumbo nucifera) and roots and stolon P concentration. (Figure 5.11a). Rank 95 Eqn 8040 y=4ax^(-c-1)*b^(c+1)*c^2/(c-1+x^-c*b^c*(c+1))^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5587948038 0.5097720042 3.2149324801 17.731267267

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 19.23720725 1 .046630212 1 8.38013753 1 7.09328245 21.38113205 0 .0000 0 b 5366.728082 347.5372334 15.44216724 4654.830331 6078.625832 0.00000 c 1.817625892 0.128004244 14.19973151 1.555421085 2.079830698 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 12 Source Sum of Squares D F Mean Square F Statistic P>F Regr 366.53334 2 183.26667 17.7313 0.00001 Error 289.40214 28 10.335791 Total 655.93548 30

158

Table A5.115 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.11b). Rank 68 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4588247478 0.3986941642 440.07742132 11.869623461

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2004.617076 118.5148912 16.91447426 1761.850327 2247.383826 0.00000 b 4844.187618 270.2207153 17.92678112 4290.665575 5397.709661 0.00000 c 2697.059432 370.4762725 7.279978861 1938.17319 3455.945675 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 11 Source Sum of Squares DF Mean Square F Statistic P>F Regr 4597535.7 2 2298767.9 11.8696 0.00018 Error 5422707.8 28 193668.14 Total 10020244 30

Table A5.116 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 5.11b). Rank 146 Eqn 1047 y=a+bx1.5+cx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.321317544 0.2459083822 492.82579875 6.6282037726

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 155.8121505 418.7127056 0.372121859 -701.881946 1013.506247 0.71260 b -0.0059867 0.001697299 -3.52719114 -0.00946346 -0.00250994 0.00147 c 6.67390044 6 1.842164546 3.6228 57936 2.900397434 10.44740346 0.00114

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 3219680 2 1609840 6.6282 0.00440 Error 6800563.5 28 242877.27 Total 10020244 30

Table A5.117 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and roots and stolon P concentration. (Figure 5.11b). Rank 128 Eqn 8040 y=4ax^(-c-1) *b^( c+1)*c^2/(c-1 +x^-c *b^c*(c+1) )^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2703291307 0.189 2545896 511 .00320871 5 .1867327978

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 1931.116496 148.4403213 13.00937965 1627.050282 2235.18271 0.00000 b 5941.39809 1 835.1531805 7.1141 41728 4230.664352 7652.131829 0.00000 c 1.59865049 7 0.18407261 8.6848 90706 1.221594849 1.975706145 0.00000

Procedure Minimiza ti on Iterations LevMarqdt Least Squ ares 15 Source Sum of Squares DF Mean Square F Statistic P>F Regr 2708763.7 2 1354381.9 5.18673 0.01213 Error 7311479.8 28 261124.28 Total 10020244 30

159

Table A5.118 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 5.12). Rank 6 Eqn 8030 y=aexp(-0.5((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6166614352 0.5740682613 2.9860858926 22.521240709

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12.98616927 0.810753644 16.01740475 11.32541572 14.64692282 0.00000 b 5637.059579 241.1400382 23.37670518 5143.106603 6131.012555 0.00000 c 2224.902858 254.5054829 8.742062575 1703.572009 2746.233706 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 401.6307 2 200.81535 22.5 212 0.00000 Error 249.66785 28 8.916709 Total 651.29855 30

Table A5.119 ANOV A for the relati o nship between tot al leaf area of lo t us (Nelumbo nucifera) and petiole P concentration. (Figure 5.12). Rank 140 Eqn 612 1 y0.5=a+bx+cx2 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.53682567 07 0.485361 8564 3.2823378445 16.226 200191

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 1.579640275 0.871614152 1.812316002 -0.20578038 3.365060928 0.08067 b 0.000664713 0.000313028 2.123489816 2.3503e-05 0.001305922 0.04268 c -5.2173e-08 2.59118e-08 -2.01348696 -1.0525e-07 9.04843e-10 0.05377

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 349.63378 2 174.81689 16.2262 0.00002 Error 301.66477 28 10.773742 Total 651.29855 30

Table A5.120 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolon P concentration. (Figure 5.12). Rank 3 Eqn 8040 y=4ax^(-c-1)*b^(c+1)*c^2/(c-1+x^-c*b^c*(c+1))^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5053521705 0.4523541888 3.3893956125 14.813784749

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12.94610837 1.025875676 12.6195685 10.84795703 15.04425971 0.00000 b 5947.93965 525.9656037 11.30860955 4872.219207 7023.660093 0.00000 c 2.168908292 0.221923512 9.773224451 1.715023747 2.622792836 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 340.3616 2 170.1808 14.8138 0.00004 Error 333.15208 29 11.488003 Total 673.51367 31

160

Table A5.121 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and leaf P concentration. Rank 121 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1457913059 0.0542689458 7.4027332703 2.4747745488

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 30.99405208 1.787911723 17.3353369 27.33736202 34.65074213 0.00000 b 4477.462578 550.9507119 8.126793343 3350.641851 5604.283305 0.00000 c 4349.635413 1141.741195 3.809650938 2014.512479 6684.758348 0.00067

Procedure Minimization Iterations LevMarqdt Least Squares 11 Source Sum of Squares DF Mean Square F Statistic P>F Regr 271.23757 2 135.61878 2.47477 0.10178 Error 1589.2133 29 54.80046 Total 1860.4509 31

Table A5.122 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and petiole P concentration. Rank 4 Eqn 1075 y=a+bx2lnx+cx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1362839093 0.0437428996 7.4438157178 2.2879238983

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 26.44438522 2.61811666 10.10053739 21.08973542 31.79903502 0.00000 b 9.00099e-08 5.03646e-08 1.787166973 -1.2997e-08 1.93017e-07 0.08437 c -8.4868e-09 4.52155e-09 -1.87696564 -1.7734e-08 7.60814e-10 0.07062

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 253.54952 2 126.77476 2.28792 0.11950 Error 1606.9014 29 55.410392 Total 1860.4509 31

Table A5.123 ANOVA for the relationship between internode length of lotus petioles (Nelumbo nucifera) and roots and stolon P concentration. Rank 4 Eqn 1076 y=a+bx2lnx+cx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0917181973 0 7.6334420764 1.4642084165

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 26.99907749 2.436038203 11.08319133 22.01681995 31.98133503 0.00000 b 1.89954e-08 1.41057e-08 1.346641349 -9.8541e-09 4.78448e-08 0.18853 c -1.4555e-11 9.61451e-12 -1.51384805 -3.4219e-11 5.10897e-12 0.14089

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 170.637 2 2 85.318601 1.46421 0.24786 Error 1689.8137 29 58.269438 Total 1860.4509 31

161

Table A5.124 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and total leaf area). (Figure 5.13, Table 5.5). Rank 1 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.9309948847 0.9260659479 1.7657168489 391.25869936

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.001666732 0.642602101 4.671112538 1.687397867 4.315935597 0.00006 b 1.663065175 0.084077011 19.78026035 1.491108379 1.835021971 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1219.8492 1 1219.8492 391.259 0.00000 Error 90.414924 29 3.117756 Total 1310.2641 30

Table A5.125 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and the number of leaves. (Figure A5.11, Table 5.5). Rank 16 Eqn 1 y= a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5725069584 0.5440074223 4.6232603299 41.515800213

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.234005254 2.243003385 0.550157553 -3.34063031 5.808640816 0.58615 b 0.800661559 0.124263125 6.443275581 0.547225245 1.054097873 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 887.38097 1 887.38097 41.5158 0.00000 Error 662.61062 31 21.374536 Total 1549.9916 32

Table A5.126 A NOVA for the relationship between t ot al dry mass of lo tus (Nelumbo nucifera) and the number of nodes. (Figure A5.12a, Table 5.5). Rank 1 Eqn 15 y=a+b/x0.5 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.478750053 0.4440000565 5.105130 3515 28.472428105

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 44.0 1636736 5.56 10 980 94 7 .9 15049621 32.67 4 4330 3 55.358301 7 0.00000 b -21 6.720675 40.6 15152 84 - 5.3 3595616 -299 .555825 -133.8855 25 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 742.05855 1 742.05855 28.4724 0.00001 Error 807.93303 31 26.062356 Total 1549.9916 32

162

25 ) -1

15 Dry Mass (g plant Mass Dry 10

0 0 5 10 15 20 25 30

Number of Leaves Figure A5.11 Total dry mass of lotus (Nelumbo nucifera) as a function of the number of leaves, the regression equation is y=1.23+0.8007x (r2 = 0.54). (Tables 5.5 & A5.125).

Table A5.127 A NOVA for the relationship between t ot al dry mass of lo tus (Nelumbo nucifera) and the number of stolons. (Figure A5.12b, Table 5.5). Rank 1 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5725842238 0.5440898387 4.622842 5053 41.528909142

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a -17 .5047569 5.06 54536 27 - 3.4 5571357 -27.8 35817 6 -7.173696 07 0.00161 b 8.55 0234725 1.32 67917 9 6 .4 44292757 5.8 44225029 11.25624442 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 887.50073 1 887.50073 41.5289 0.00000 Error 662.49086 31 21.370673 Total 1549.9916 32

163

35 A 30 )

-1 25

15 tal Dry Mass (g plant 10 To

0 0 2040 60 80100 Number of Nodes

35 B 30 )

-1 25

10 Total Dry Mass (g plant

0 0 5 10 15 20 25 30

Number of Stolons Figure A5.12 Total dry mass of l otus (Nelumbo nucif era) as a function of the number of organs: a) Number of node s, the regression eq u ation is y=44.02-2 1 6.72/x0.5 (r2 = 0.44); b) Number of stolons the regression equa tion is y=-17.50+8 .5 5x0.5 (r2 = 0.54). (T ables 5.5 & A5 .126-127).

164

Table A5.128 ANOVA for the relationship between tot al dry mass of l o tus (Nelumbo nuc ifera) and total stolon length. (Figure A5.13, Table 5.5) Rank 10 Eqn 1 y= a+bx r2 Coef Det DF Adj r 2 Fit S td Err F-valu e 0.70930553 15 0.689257 63 71 3.8 0 19 255381 73.2 01 1381 25

Parm Va lue Std Erro r t-value 9 5% Confidence Limits P>|t| a 0.59 7322916 1.75 72737 68 0.339914547 -2.9915089 4.186154729 0.73629 b 0.007982325 0.000932976 8.555766367 0.006076934 0.009887716 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1058.09 59 1 1058.0959 73.2011 0.00000 Error 433.639 13 30 14.454638 Total 1491.73 51 31

30 )

-1 25 t lan

10 Total Dry Mass (g p

0 01000 20 00 300 0 4000 5000

Total Stolon Lengt h (mm) Figure A5.1 3 Total dry mass of lotus (Nelumbo nucifera) as a function of total stolon length, the regression equation is y=0.60+0.008x (r2 = 0.69). (Tables 5.5 & A5.128).

165

Table A5.129 ANOVA for the relationship between tot al dry mass of lotus (Nelumbo nuc ifera) and leaf N concentration. (Figure 5.14a). Rank 15 Eqn 7 y= a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.54392043 08 0.511343 3187 4.1775668899 34.585 395962

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 31.25157811 3.060711066 10.21056135 24.99172112 37.51143511 0.00000 b -0.34253594 0.05824515 -5.88093496 -0.46166064 -0.22341123 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 603.58658 1 603.58658 34.5 854 0.00000 Error 506.10989 29 17.452065 Total 1109.6965 30

Table A5.130 ANOVA for the relationship between tot al leaf area of lo t us (Nelumbo nuc ifera) and leaf N concentration. (Figure 5.14b). Rank 1 Eqn 8 y=a +bex r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.43680079 53 0.397959 4708 3.5558513485 23.267 120672

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 18.78516304 2.081410527 9.025208045 14.53435565 23.03597043 0.00000 b -0.23043904 0.047773244 -4.82360038 -0.32800502 -0.13287306 0.00004

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 294.19131 1 294.19131 23.2671 0.00004 Error 379.32236 30 12.644079 Total 673.51367 31

Table A5.131 A NOVA for the rela tionship between th e number of leav es of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 5.15a). Rank 1 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit S td Err F-value 0.2137297415 0.1613117242 5.925311 0678 8.4266470899

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 26.2 0555123 3.38 43 958 77 7 .7 43051398 19.30 3 0303 3 33.108072 13 0.00000 b -0.2 275177 0.07 83768 47 - 2.9 0286877 -0.387 36834 -0.067667 07 0.00675

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 295.85378 1 295.85378 8.42665 0.00675 Error 1088.3886 31 35.109311 Total 1384.2424 32

166

Table A5.132 ANOV A for the relationship between th e number of nodes of lotus (Nelum bo nucifera) and leaf N concentration. Rank 2 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.10838935 99 0.048948 6506 17.0 40 055965 3.7685 397701

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 81.70976241 12.1291372 6.73665085 56.97222401 106.4473008 0.00000 b -0.45276463 0.233230819 -1.94127272 -0.92844202 0.022912765 0.06136

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1094.24 64 1 1094.2464 3.7685 4 0.06136 Error 9001.2687 31 290.36351 Total 10095.515 32

Table A5.133 ANOV A for the relati o nship between th e number of sto lo ns of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 5.15b). Rank 1 Eqn 8 y=a +bex r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.22485979 22 0.173183 7783 4.0993358937 8.9927 647753

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 21.26321877 2.341442557 9.081247243 16.48781519 26.03862234 0.00000 b -0.16260607 0.054223824 -2.99879389 -0.27319629 -0.05201585 0.00530

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 151.11941 1 151.11941 8.99276 0.00530 Error 520.9412 31 16.804555 Total 672.06061 32

Table A5.134 A NOVA for the relat ionship between t ot al stolon length of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 5.16). Rank 3 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.2256520893 0.1722487851 559.6699 7889 8.7422753829

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 280 8.545692 399. 67 447 12 7 .0 27083024 1992 .3 0152 8 3624.789856 0.00000 b -22 .666556 7.66 60791 13 - 2.9 567339 -38.32 27782 -7.010333 81 0.00601

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2738347.2 1 2738347.2 8.74228 0.00601 Error 9396914.6 30 313230.49 Total 12135262 31

167

Table A5.135 ANOVA for the relationship between tot al dry mass of lotus (Nelumbo nuc ifera) and roots and stolons N concentration. (Figure 5.17). Rank 1 Eqn 4 y=a +bx2 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.30645063 07 0.260214 0061 5.8887418235 13.697 611119

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 30.44287349 4.369137837 6.967707275 21.53195813 39.35378885 0.00000 b -3.10710031 0.839523502 -3.70102839 -4.81931978 -1.39488084 0.00083

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 474.9959 1 474.9959 13.6 976 0.00083 Error 1074.9957 31 34.67728 Total 1549.9916 32

Table A5.136 ANOVA for the relationship between tot al leaf area of l ot us (Nelumbo nuc ifera) and roots and stolon N concentration. Rank 29 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.19363897 93 0.138027 8744 4.2547822972 7.2041 793073

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 4.171630654 0.796845179 5.235183404 2.544255695 5.799005614 0.00001 b -0.07883928 0.070929033 -1.11152339 -0.22369569 0.066017132 0.27517

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 130.4185 1 130.4185 7.20418 0.01173 Error 543.09517 30 18.103172 Total 673.513 67 31

Table A5.137 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and roots and st olon N concen trat ion. Rank 3 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.164180896 0.1084596224 6.109158 2831 6.0893652125

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t| a 24.0 9695824 3.12 39688 58 7 .7 13571849 17.725 58175 30.46833473 0.00000 b -0.6 2347837 0.25 26593 55 - 2.467 66392 -1 .13878052 -0.10817622 0.01932

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 227.26616 1 227.26616 6.08937 0.01932 Error 1156.9763 31 37.321815 Total 1384.24 24 32

168

Table A5.138 ANOV A for the rela tio nship between t h e number of no de s of lotus (Nelum bo nucifera) and roots and stolon N concentration. Rank 1 Eqn 8 y=a +bex r2 Coef Det DF Adj r2 Fit S td Err F-va lu e 0.15396702 57 0.097564 8274 16.5 98 813318 5.6415 978357

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 83.53219341 10.77417486 7.753001461 61.55811892 105.5062679 0.00000 b -2.54742565 1.07250779 -2.3752048 -4.73481971 -0.36003159 0.02391

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1554.37 64 1 1554.3764 5.64 16 0.02391 Error 8541.1387 31 275.5206 Total 10095.515 32

Table A5.139 ANOV A for the relati o nship between t he number of sto lo ns of lotus (Nelumbo nucifera) and roots and stolon N concentration. Rank 2 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.11958410 43 0.060889 7113 4.3688517737 4.2106 318747

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 18.88618272 2.234048661 8.453792009 14.32981044 23.442555 0.00000 b -0.37076177 0.180684674 -2.05198243 -0.7392706 -0.00225295 0.04870

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 80.367766 1 80.367766 4.21063 0.04870 Error 591.69284 31 19.086866 Total 672.06061 32

Table A5.140 A NOVA for the rela tionship between t ot al stolons length of lotus (Nelumbo nucifera) and roots and stolon N concentration. Rank 2 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.1301282949 0.0701371428 593.1868 9587 4.4878443853

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 226 8.277001 304. 08 844 29 7 .4 59267374 1647 .2 4555 2889.30845 2 0.00000 b -51 .974662 24.5 34249 6 - 2.1 184533 -102 .080284 -1.86903986 0.04253

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1579140.9 1 1579140.9 4.48784 0.04253 Error 10556121 30 351870.69 Total 12135262 31

169

Table A5.141 ANOVA for the relationship between tot al dry mass of lo tus (Nelumbo nuc ifera) and petiole K concentration. Rank 1183 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.05236505 55 0 6.8834213932 1.7130 190579

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 22.03950447 5.716417045 3.855475256 10.38079504 33.69821389 0.00054 b -4.3893e-14 3.35365e-14 -1.30882354 -1.1229e-13 2.45048e-14 0.20021

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 81.165395 1 81.165395 1.71 302 0.20021 Error 1468.8262 31 47.38149 Total 1549.9916 32

Table A5.142 ANOVA for the relationship between tot al leaf area of lo t us (Nelumbo nuc ifera) and petiole K concentration . Rank 2095 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-val ue 0.03224655 51 0 4.6611700109 0.9 996313204

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 13.1115718 3.984361253 3.290758787 4.974420563 21.24872304 0.00256 b -2.3204e-14 2.32081e-14 -0.99981564 -7.0601e-14 2.41934e-14 0.32540

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 21.718496 1 21.718496 0.999631 0.32540 Error 651.79518 30 21.726506 Total 673.51367 31

Table A5.143 A NOVA for the rela t ionship between t he number of leaves o f lotus (Nelumbo nucifera) and petiole K concentration. Rank 2086 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0486876874 0 6.517586 2882 1.5865644652

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 23.5 1468078 5.41 26050 44 4 .3 44429456 12.47 56000 2 34.553761 54 0.00014 b -3.9 997e-14 3.17 542e- 14 - 1.2 5958901 -1.0 476e-13 2.47658e-14 0.21722

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 67.395562 1 67.395562 1.58656 0.21722 Error 1316.8469 31 42.478931 Total 1384.2424 32

170

Table A5.144 ANOV A for the relationship between th e number of nodes of lotus (Nelum bo nucifera) and petiole K concentration. Rank 2139 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.00675050 39 0 17.9 85 088211 0.2106 878702

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 65.58218212 14.93592487 4.390901981 35.12016252 96.04420172 0.00012 b -4.022e-14 8.76247e-14 -0.45900748 -2.1893e-13 1.38491e-13 0.64943

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 68.149814 1 68.149814 0.2106 88 0.64943 Error 10027.365 31 323.4634 Total 10095.515 32

Table A5.145 ANOV A for the relati o nship between th e number of sto lo ns of lotus (Nelu mbo nucifera) and petiole K concentration. Rank 2331 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.00762338 35 0 4.6383298939 0.2381 403226

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 16.4137365 3.851954798 4.261144628 8.557622892 24.2698501 0.00018 b -1.1028e-14 2.25983e-14 -0.48799623 -5.7117e-14 3.50616e-14 0.62899

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.1233757 1 5.1233757 0.23814 0.62899 Error 666.93723 31 21.514104 Total 672.06061 32

Table A5.146 A NOVA for the relat ionship between t ot al stolon length of lotus (Nelumbo nucifera) and petiole K concentration. Rank 21 43 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.0082924822 0 731.5416 2578 0.2592164951

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 203 1.980966 607. 51 721 85 3 .3 44729834 792.94 1430 1 3271.0205 01 0.00217 b -1.8 146e-12 3.56 413e- 12 - 0.5 0913308 -9.08 37e-12 5.45447e- 12 0.61426

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 138720.52 1 138720.52 0.259216 0.61426 Error 16589748 31 535153.15 Total 16728468 32

171

Table A5.147 ANOVA for the relationship between tot al dry mass of lotus (Nelumbo nuc ifera) and roots and stolon K concentration. Rank 2133 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-va lu e 0.00276211 88 0 7.0612763328 0.0858 628475

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 15.8150141 3.921153099 4.033255959 7.817769634 23.81225857 0.00033 b -1.3212e-14 4.5089e-14 -0.29302363 -1.0517e-13 7.87474e-14 0.77146

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.281261 1 4.281261 0.0858 628 0.77146 Error 1545.7103 31 49.861623 Total 1549.9916 32

Table A5.148 ANOVA for the relationship between tot al leaf area of l ot us (Nelumbo nuc ifera) and roots and stolon K concentration. Rank 2129 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-va lu e 0.00216971 9 0 5.6771758213 0.0674 075429

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 10.54845228 3.15255692 3.345998992 4.118770052 16.9781345 0.00216 b -9.4118e-15 3.6251e-14 -0.25962963 -8.3346e-14 6.45225e-14 0.79687

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.172567 1 2.172567 0.0674075 0.79687 Error 999.14008 31 32.230325 Total 1001.3127 32

Table A5.149 A NOVA for the rela tionship between t he number of leav es of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 93 4 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.0133711054 0 6.637463 4993 0.4201217608

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 19.1 1708717 3.685 8 082 51 5 .1 86674365 11.59 9 8316 8 26.634342 66 0.00001 b -2.7 471e-14 4.23 828e- 14 - 0.6 48168 -1.13 91e-13 5.89691e- 14 0.52165

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 18.508851 1 18.508851 0.420122 0.52165 Error 1365.7336 31 44.055922 Total 1384.2424 32

172

Table A5.150 ANOV A for the relationship between th e number of nodes of lotus (Nelum bo nucifera) and roots and stolon K concentration. Rank 2141 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-valu e 0.00233342 14 0 18.0 25 034616 0.0725 052491

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 61.43813663 10.00936899 6.138062919 41.023894 81.85237927 0.00000 b -3.0992e-14 1.15097e-13 -0.26926799 -2.6573e-13 2.0375e-13 0.78951

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 23.557091 1 23.557091 0.0725 052 0.78951 Error 10071.958 31 324.90187 Total 10095.515 32

Table A5.151 ANOV A for the relati on ship between th e number of stol on s of lotus (Nelum bo nucifera) and roots and stolon K concentration. Rank 2120 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.01763072 64 0 4.6148836683 0.5563 615757

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 16.39088852 2.562662123 6.396039637 11.16430466 21.61747237 0.00000 b -2.198e-14 2.94678e-14 -0.74589649 -8.208e-14 3.81201e-14 0.46135

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 11.848917 1 11.848917 0.556362 0.46135 Error 660.21169 31 21.297151 Total 672.06061 32

Table A5.152 A NOVA for the relat ionship between t ot al stolon length of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 2150 Eqn 1 y=a+b x r2 Coef Det DF Adj r2 Fi t Std Err F-value 0.0194772776 0 727.4046 4763 0.6157895092

Parm Va lue Std E rror t-v alue 95% Confidence Limits P>|t | a 792 .3797357 1200 .9 578 57 0. 6 59789793 -1656 . 9899 6 3241.749432 0.51426 b 0.02 1763877 0.027 7344 85 0 .7 84722568 -0. 034 8009 8 0.078328733 0.43857

Soln Vector Covar M atrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 325825.02 1 325825.02 0.61579 0.43857 Error 16402643 31 529117.52 Total 16728468 32

173

Table A5.153 ANOVA for the relationship between tot al dry mass of lotus (Nelumbo nuc ifera) and roots and stolon Ca concentration. Rank 1167 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.14614187 99 0.08921800 53 6.533963139 5.3057 974985

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 28.15821855 5.94216391 4.738714545 16.03909536 40.27734174 0.00005 b -1.3074e-05 5.67587e-06 -2.30343168 -2.465e-05 -1.498e-06 0.02813

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 226.51868 1 226.51868 5.30 58 0.02813 Error 1323.4729 31 42.692674 Total 1549.9916 32

Table A5.154 ANOV A for the relationship between tota l leaf area of lotus (Nelumbo nuci fera) and roots and stolon Ca concentration. Rank 2071 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.06821082 55 0.0039495031 4.5737393466 2.1 961 242103

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 13.73080016 3.153289107 4.354437444 7.290924672 20.17067565 0.00014 b -4.2905e-08 2.89521e-08 -1.48193259 -1.0203e-07 1.6223e-08 0.14879

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 45.940924 1 45.940924 2.19612 0.14879 Error 627.57275 30 20.919092 Total 673.51367 31

Table A5.155 A NOVA for the rel a tionship between t he number of leav es of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 21 22 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.0196990122 0 6.616144 0282 0.6229406944

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 21.5 0960883 6.0169 014 47 3 .5 74864741 9.2380574 2 9 33.781160 24 0.00117 b -4.5 361e-06 5.7472 6e- 06 - 0.7 8926592 -1.6258e -05 7.1855e-0 6 0.43595

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 27.268208 1 27.268208 0.622941 0.43595 Error 1356.9742 31 43.773362 Total 1384.2424 32

174

Table A5.156 ANOV A for the relationship between t he number of nodes of lotus (Nelumbo nucifera) and roots and stolons Ca concentration. Rank 1893 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.03146534 99 0 17.7 59 918842 1.0 071 150736

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 70.54004757 12.02423768 5.866488128 46.01645316 95.06364198 0.00000 b -1.1155e-07 1.11156e-07 -1.00355123 -3.3826e-07 1.15154e-07 0.32336

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 317.658 92 1 317.65892 1.00 712 0.32336 Error 9777.8562 31 315.41472 Total 10095.515 32

Table A5.157 ANOV A for the relati o nship between th e number of stol o ns of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 2101 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.01782745 49 0 4.6144215586 0.5626822943

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 16.84047403 3.124164139 5.390393487 10.46869926 23.21224879 0.00001 b -2.1664e-08 2.88809e-08 -0.75012152 -8.0567e-08 3.72388e-08 0.45884

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 11.98113 1 11.98113 0.562682 0.45884 Error 660.07948 31 21.292886 Total 672.06061 32

Table A5.158 A NOVA for the relationship between t ot al stolon length of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 20 58 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.0660729948 0.0038111944 709.9106 7568 2.1931723006

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 241 7.413326 480.64 041 11 5 .0 29567366 1437.1407 4 5 3397.6859 07 0.00002 b -6.5 801e-06 4.4432 2e- 06 - 1.4 8093629 -1.5642e -05 2.48188e- 06 0.14872

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1105300 1 1105300 2.19317 0.14872 Error 15623168 31 503973.17 Total 16728468 32

175

Table A5.159 ANOVA for the relation ship between combined N concentration in leaves , petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.61-63 & 175). Rank 871 Eqn 5 y =a+bx2lnx r2 Coef Det DF Adj r2 Fit S td Err F-value 0.01778669 96 0 0.7140619568 1.7565531468

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 2.871745281 0.096881986 29.64168464 2.679461357 3.064029205 0.00000 b -2.285e-10 1.72409e-10 -1.3253502 -5.7069e-10 1.13682e-10 0.18817

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.89563 918 1 0.8956391 8 1.7565 5 0.18817 Error 49.458794 97 0.50988448 Total 50.354434 98

Table A5.160 ANOVA for the relationship between com bined leaf and p etiole N concentration as a function of P concentration. (Tables A5.61-63 & 176). Rank 993 Eqn 7 y =a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-val ue 0.01466209 92 0 0.7107519098 0.9523376148

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.128820033 0.1112155 28.13294948 2.906641531 3.350998535 0.00000 b -2.6155e-13 2.68011e-13 -0.97587787 -7.9696e-13 2.73868e-13 0.33280

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.48109075 1 0.48109075 0.952338 0.33280 Error 32.33077 64 0.50516828 Total 32.81186 65

Table A5.161 A NOVA for the rela t ionship between c om bined N concen tration in leaves and roots and stolons of lotus (Nelumbo nucifera) and P concentr ation. (Tables A5.61, 63 & 177). Rank 1113 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0312331359 0.0004786323 0.773383 4068 2.0633660894

Parm Va lue Std E rro r t-v alue 95% Confidence Limits P>|t | a 3.03 3816498 0.11 12767 86 2 7. 26369631 2.811 51556 3 3.2561174 33 0.00000 b -2.1 045e-13 1.4651 e-1 3 - 1.4 3644216 -5.0 314e-13 8.22342e-14 0.15575

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.2341444 1 1.2341444 2.06337 0.15575 Error 38.279801 64 0.59812189 Total 39.513946 65

176

Table A5.162 ANOVA for the relationship between com bined N conce n tration in petiole s and roots and stol ons of lotus (Nelumbo nucifera) a nd P concentrati o n. (Figure 5.7, Tables A5.62-63 & 178). Rank 2619 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.00730755 96 0 0.3662 318416 0.47112660 13

Parm Va lue Std E rro r t-value 95% Confide nce Limits P>|t| a 2.4374 35835 0.1439 466 73 16.93290847 2.149869298 2.725002372 0.00000 b -0.00127965 0.001864332 -0.68638663 -0.00500408 0.002444779 0.49495

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.06319 0214 1 0.0631902 14 0.471127 0.49495 Error 8.58404 88 64 0.1341257 6 Total 8.647239 65

Table A5.163 ANOVA for the relationship between combined P concentration in leaves, petioles and root s and stolons of lotus (Nelumbo nucifera) and P Su pply. (Tables A 5.58-60 & 179). Rank 1 Eqn 9 y=a +bx0.5lnx r2 Coef Det DF Adj r2 Fit S td Err F-value 0.83222253 78 0.82872717 4 130 5.5 19516 481.14678 2 71

Parm Va lue Std E rro r t-value 95% Confide nce Limits P>|t| a 729 .3148117 259.97 163 79 2.805362991 213.3430741 1245.286549 0.00607 b 222.5455204 10.14565438 21.9350583 202.4092049 242.6818359 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 8.2005753e+08 1 8.2005753e+08 481.147 0.00000 Error 1.6532498e+08 97 1704381.2 Total 9.8538251e+08 98

Table A5.164 A NOVA for the rela t ionship between c om bined P conc entration in leaves and petioles of lotus (Nelumbo nucifera) and P supply. (Tables A5.58-59 & 180). Rank 3 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8663362338 0.8620929397 957.49571839 414.81338251

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1144.706174 233.5205324 4.901950857 678.1952814 1611.217066 0.00001 b 185.611784 9.113373412 20.36696793 167.4057277 203.8178403 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3.803001e+08 1 3.803001e+08 414.813 0.00000 Error 58675075 64 916798.05 Total 4.3897518e+08 65

177

Table A5.165 ANOVA for the relationship between combined P concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and P supply. (Tables A5.58, 60 & 181). Rank 1 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7954266171 0.7889322239 1470.9652971 248.84617323

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 859.0001378 358.7489664 2.39443237 142.3166891 1575.683587 0.01959 b 220.8565252 14.00053887 15.7748589 192.8872335 248.8258169 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.3843815e+08 1 5.3843815e+08 248.846 0.00000 Error 1.3847929e+08 64 2163738.9 Total 6.7691744e+08 65

Table A5.166 ANOVA for the relationship between combined P concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and P supply. (Figure 5.7, Tables A5.59-60 & 182). Rank 1 Eqn 8116 [Form.5_] y=a0.5bx-0.25b2x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.9063805619 0.9034085162 1106.7428083 619.61871532

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12812.3125 837.9911014 15.28931809 11138.23283 14486.39218 0.00000 b 1.670524077 0.114258076 14.6206215 1.442267331 1.898780823 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 7.5895835e+08 1 7.5895835e+08 619.619 0.00000 Error 78392297 64 1224879.6 Total 8.3735065e+08 65

Table A5.167 ANOVA for the relationship between combined K concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.64-66 & 183). Rank 76 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.06362346 0.0441156154 11711.328905 6.5908054671

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 39262.18505 1484.805512 26.442645 36315.25712 42209.11298 0.00000 b 6.01184e-07 2.34174e-07 2.567256409 1.36414e-07 1.06595e-06 0.01178

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9.039634e+08 1 9.039634e+08 6.59081 0.01178 Error 1.3304057e+10 97 1.3715522e+08 Total 1.420802e+10 98

178

Table A5.168 ANOVA for the relationship between combined K concentration in leaves and petioles of lotus (Nelumbo nucifera) and P concentration. (Tables A5.64-65 & 184). Rank 2331 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0495514835 0.0193785147 14113.311717 3.3366299033

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37301.08234 2605.657811 14.31541861 32095.68246 42506.48221 0.00000 b 0.000103665 5.67514e-05 1.826644438 -9.7093e-06 0.000217038 0.07242

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.6460852e+08 1 6.6460852e+08 3.33663 0.07242 Error 1.2747876e+10 64 1.9918557e+08 Total 1.3412485e+10 65

Table A5.169 ANOVA for the relationship between combined K concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.64, 66 & 185). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.238074801 0.2138866994 7810.3544251 19.997746869

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32397.8037 1123.777844 28.82936683 30152.79937 34642.80802 0.00000 b 6.61658e-09 1.4796e-09 4.47188404 3.66075e-09 9.57241e-09 0.00003

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.2198953e+09 1 1.2198953e+09 19.9977 0.00003 Error 3.9041047e+09 64 61001636 Total 5.124e+09 65

Table A5.170 ANOVA for the relationship between combined K concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Figure 5.8a, Tables A5.65-66 & 186). Rank 378 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0226034308 0 7249.6399327 1.4800743272

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 47245.79053 1632.645504 28.93818064 43984.20619 50507.37487 0.00000 b 0.031421535 0.025827694 1.216583054 -0.02017522 0.083018285 0.22823

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 77788680 1 77788680 1.48007 0.22823 Error 3.3636659e+09 64 52557279 Total 3.4414545e+09 65

179

Table A5.171 ANOVA for the relationship between combined Ca concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.67-69 & 187). Rank 2380 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0287877005 0.0085541109 5659.0255428 2.8751766727

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 15218.54679 675.0428352 22.54456458 13878.77363 16558.31996 0.00000 b -1.6689e-09 9.84228e-10 -1.69563459 -3.6223e-09 2.84529e-10 0.09316

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 92076297 1 92076297 2.87518 0.09316 Error 3.1063833e+09 97 32024570 Total 3.1984596e+09 98

Table A5.172 ANOVA for the relationship between combined Ca concentration in leaves and petioles of lotus (Nelumbo nucifera) and P concentration. (Figure 5.8b, Tables A5.67-68 & 188). Rank 94 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2412677052 0.2045548523 5099.1127685 10.016619521

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20053.53074 974.176496 20.58511042 18106.79435 22000.26713 0.00000 b 4778.023556 291.8150452 16.37346543 4194.87772 5361.169391 0.00000 c 3912.237755 495.4886927 7.895715508 2922.082612 4902.392898 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 5.2088327e+08 2 2.6044163e+08 10.0166 0.00017 Error 1.6380599e+09 63 26000951 Total 2.1589432e+09 65

Table A5.173 ANOVA for the relationship between combined Ca concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.67, 69 & 189). Rank 2303 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0505125348 0.0203700756 6349.0620756 3.4047866296

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 17119.73344 967.7136073 17.69090908 15186.50327 19052.96361 0.00000 b -2.6043e-07 1.41138e-07 -1.84520639 -5.4239e-07 2.15269e-08 0.06963

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.3724896e+08 1 1.3724896e+08 3.40479 0.06963 Error 2.5798777e+09 64 40310589 Total 2.7171267e+09 65

180

Table A5.174 ANOVA for the relationship between combined Ca concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Figure 5.8b, Tables A5.68-69 & 190). Rank 15 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0385734791 0.0080520022 1502.5454967 2.5677497

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10705.25939 223.936339 47.80492276 10257.89512 11152.62365 0.00000 b 4.40984e-10 2.75199e-10 1.602419951 -1.0879e-10 9.90757e-10 0.11399

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 5797062.1 1 5797062.1 2.56775 0.11399 Error 1.4448915e+08 64 2257643 Total 1.5028621e+08 65

Table A5.175 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves, petioles and roots and stolons as a function of P concentration (Tables A5.61-63 & 159). ANOVA SS df ms F Single line RSS 49.46 97 Total Individual lines 8.37 90 0.093 RSS Difference 41.09 7 5.87 63.12 F dist. 7.31 P< 0.0000

Table A5.176 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and petioles as a function of P concentration (Tables A5.61-62 & 160). ANOVA SS df ms F Single line RSS 32.33 64 Total Individual lines 6.61 60 0.11 RSS Difference 25.72 4 6.43 58.45 F dist. 19.61 P< 0.0006

Table A5.177 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and roots and stolons as a function of P concentration (Tables A5.61, 63 & 161). ANOVA SS df ms F Single line RSS 38.30 64 Total Individual lines 3.75 60 0.0625 RSS Difference 34.55 4 30.55 488.8 F dist. 19.61 P< 0.0000

181

Table A5.178 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in petioles and roots and stolons as a function of P concentration (Tables A5.62-63 & 162). ANOVA SS df ms F Single line RSS 8.58 64 Total Individual lines 6.38 60 0.106 RSS Difference 2.2 4 0.55 5.19 F dist. 19.61 P< 0.0587

Table A5.179 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, petioles and roots and stolons as a function of P supply (Tables A5.58-60 & 163). ANOVA SS df ms F Single line RSS 1.65 x 108 97 Total Individual 44643217.84 92 485252.37 lines RSS Difference 120356782.2 5 24071356.44 49.61 F dist. 12.4 P< 0.0002

Table A5.180 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, and petioles as a function of P supply (Tables A5.58-59 & 164). ANOVA SS df ms F Single line RSS 58675075 64 Total Individual 9793541.84 61 160549.87 lines RSS Difference 48881533.16 3 16293844.39 101.49 F dist. 42.15 P< 0.0014

Table A5.181 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves and roots and stolons as a function of P supply (Tables A5.58, 60 & 165). ANOVA SS df ms F Single line RSS 1.38 x 108 64 Total Individual 19579668.84 61 320978.18 lines RSS Difference 118420331.2 3 39473443.73 122.98 F dist. 42.15 P< 0.001

Table A5.182 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in petioles and roots and stolons as a function of P supply (Tables A5.59-60 & 166). ANOVA SS df ms F Single line RSS 78392297 64 Total Individual 59913225 62 966342.34 lines RSS Difference 18479072 2 9239536 9.56 F dist. 199.5 P< 0.0992

182

Table A5.183 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves, petioles and roots and stolons as a function of P concentration (Tables A5.64-66 & 167). ANOVA SS df ms F Single line RSS 1.33 x 1010 97 Total Individual 2211144165 89 24844316.46 lines RSS Difference 1.11 x 1010 8 1387500000 55.85 F dist. 6.11 P< 0.0000

Table A5.184 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and petioles as a function of P concentration (Tables A5.64-65 & 168). ANOVA SS Df ms F Single line RSS 1.27 x 1010 64 Total Individual 311144165 58 5364554.57 lines RSS Difference 1.2 x 1010 6 2.0 x 108 372.82 F dist. 9.13 P< 0.0000

Table A5.185 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and roots and stolons as a function of P concentration (Tables A5.64, 66 & 169). ANOVA SS df ms F Single line RSS 3.9 x 109 64 Total Individual 1994144165 60 33235736.08 lines RSS Difference 1905855835 4 476463958.8 14.34 F dist. 19.61 P< 0.0091

Table A5.186 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in petioles and roots and stolons as a function of P concentration (Tables A5.65-66 & 170). ANOVA SS df ms F Single line RSS 3.63 x 109 64 Total Individual 2117000000 60 35283333.33 lines RSS Difference 1513000000 4 378250000 10.72 F dist. 19.61 P< 0.0158

Table A5.187 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves, petioles and roots and stolons as a function of P concentration (Tables A5.67-70 & 171). ANOVA SS df ms F Single line RSS 3.11 x 109 97 Total Individual lines 431976687 93 4644910.61 RSS Difference 2678023313 4 669505828.3 144.14 F dist. 19.56 P< 0.0001

183

Table A5.188 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and petioles as a function of P concentration (Tables A5.67-68 & 172). ANOVA SS df ms F 9 Single line RSS 1.64 x 10P P 63 Total Individual lines 394724127 62 6366518.18 RSS Difference 1245275873 1 1245275873 195.60 F dist. 25465 P< 0.0568

Table A5.189 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and roots and stolons as a function of P concentration (Tables A5.67, 69 & 173). ANOVA SS df ms F 9 Single line RSS 2.58 x 10P P 64 Total Individual lines 376252560 62 6068589.68 RSS Difference 2203747440 2 1101873720 181.57 F dist. 199.5 P< 0.0055

Table A5.190 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in petioles and roots and stolons as a function of P concentration (Tables A5.68-69 & 174). ANOVA SS df ms F 8 Single line RSS 1.44 x 10P P 64 Total Individual lines 92976687 62 1499623.98 RSS Difference 51023313 2 25511656.5 17.01 F dist. 199.5 P< 0.057

Table A5.191 ANOVA for the relationship between combined Mn concentration in petioles, roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.80-81 & 192). Rank 1 Eqn 6841 y=a+bcos(x)+csin(x) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4617038522 0.4352302712 3.364125404 26.589117305

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24.42775865 1.037754954 23.53904317 22.35331606 26.50220125 0.00000 b -2.58193561 0.775391754 -3.32984663 -4.13192164 -1.03194958 0.00147 c -9.39108785 1.287802016 -7.29233821 -11.9653674 -6.8168083 0.00000

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 601.83615 2 300.91807 26.5891 0.00000 Error 701.67506 62 11.31734 Total 1303.5112 64

184

Table A5.192 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Mn concentration in petioles and roots and stolons as a function of P concentration (Tables A5.80, 81 & 191). ANOVA SS df ms F Single line RSS 701.67 62 Total Individual lines 399.83 59 6.77 RSS Difference 301.84 3 100.61 14.86 F dist. 42.31 P<

185

Table A5.193 ANOVA for the relationship between combined Zn concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.82-84 & 197). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3471582369 0.3335573668 23.618537968 51.581180744

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 51.12508278 2.817362232 18.14643577 45.53339863 56.71676693 0.00000 b 2.95021e-11 4.10778e-12 7.18200395 2.13493e-11 3.76549e-11 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 28773.805 1 28773.805 51.5812 0.00000 Error 54110.028 97 557.83534 Total 82883.833 98

Table A5.194 ANOVA for the relationship between combined Zn concentration in leaves and petioles of lotus (Nelumbo nucifera) and P concentration. (Tables A5.82-83 & 198). Rank 4 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2454878665 0.2215351004 8.1175559037 20.823022932

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.28579816 3.285232732 9.827552806 25.7227913 38.84880501 0.00000 b 0.023773256 0.005209749 4.563225058 0.013365586 0.034180925 0.00002

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1372.1271 1 1372.1271 20.823 0.00002 Error 4217.2617 64 65.894714 Total 5589.3888 65

Table A5.195 ANOVA for the relationship between combined Zn concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.82, 84 & 199). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4079608306 0.3891659364 25.377273393 44.100955667

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 56.45195538 3.651360236 15.46052751 49.15752476 63.746386 0.00000 b 3.19258e-11 4.80748e-12 6.64085504 2.23217e-11 4.15298e-11 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 28401.28 1 28401.28 44.101 0.00000 Error 41216.384 64 644.006 Total 69617.665 65

186

Table A5.196 ANOVA for the relationship between combined Zn concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and P concentration. (Tables A5.83-84 & 200). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3285446327 0.3072285893 26.480058263 31.315345016 Parm Value Std Error t-value 95% Confidence Limits P>|t| a 58.04521812 3.946534276 14.70789662 50.16110957 65.92932668 0.00000 b 2.71404e-11 4.84996e-12 5.596011528 1.74515e-11 3.68293e-11 0.00000 Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 21958.116 1 21958.116 31.3153 0.00000 Error 44876.383 64 701.19349 Total 66834.499 65

Table A5.197 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Zn concentration in leaves, petioles and roots and stolons as a function of P concentration (Tables A5.82-84 & 193). ANOVA SS df ms F Single line RSS 54110.03 97 Total Individual lines 10194.97 88 115.85 RSS Difference 43915.06 9 4879.45 42.12 F dist. 5.30 P<

Table A5.198 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Zn concentration in leaves and petioles as a function of P concentration (Tables A5.82, 83 & 194). ANOVA SS df ms F Single line RSS 4217.26 64 Total Individual lines 3402.81 61 55.78 RSS Difference 814.45 3 271.48 4.87 F dist. 42.15 P<

Table A5.199 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Zn concentration in leaves and roots and stolons as a function of P concentration (Tables A5.82, 84 & 195). ANOVA SS df ms F Single line RSS 41216.38 64 Total Individual lines 8001.84 58 140.38 RSS Difference 33214.54 6 5535.76 39.43 F dist. 9.24 P< Table A5.200 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Zn concentration in petioles and roots and stolons as a function of P concentration (Tables A5.83, 84 & 196). ANOVA SS df ms F Single line RSS 44876.38 64 Total Individual lines 8985.29 57 157.64 RSS Difference 35891.09 7 5127.30 32.52 F dist. 7.42 P<

187

Appendix 6 Potassium ANOVA Tables and Miscellaneous Graphs

Figure A6.1 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 20 days of potassium treatments. (Table 6.1).

Univariate Tests of Significance for Nolfd20 (Spreadsheet6) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 7.507812 1 7.507812 703.1707 0.000000 Treatment 0.255938 7 0.036563 3.4244 0.011083 Error 0.256250 24 0.010677

Figure A6.2 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of potassium treatments. (Table 6.1).

Univariate Tests of Significance for Nolfd40 (Spreadsheet6) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 6.037813 1 6.037813 465.5663 0.000000 Treatment 0.175937 7 0.025134 1.9380 0.107334 Error 0.311250 24 0.012969

Table A6.3 ANOVA for the percentage of total leaf area of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of potassium treatments. (Table 6.1). Univariate Tests of Significance for TLAaff (Spreadsheet6) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 93.93643 1 93.93643 217.9389 0.000000 Treatment 15.46391 7 2.20913 5.1253 0.001144 Error 10.34453 24 0.43102

Table A6.4 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 20 days of potassium treatments. (Table 6.1). Univariate Tests of Significance for d20 (Spreadsheet14) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 3.187813 1 3.187813 174.3761 0.000000 Treatment 0.693438 7 0.099063 5.4188 0.000800 Error 0.438750 24 0.018281

Table A6.5 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 40 days of potassium treatments. (Table 6.1). Univariate Tests of Significance for d40 (Spreadsheet14) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 7.125313 1 7.125313 677.2574 0.000000 Treatment 0.172187 7 0.024598 2.3380 0.057066 Error 0.252500 24 0.010521 188

Table A6.6 ANOVA of Total Dry Mass of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.1a).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of DW tot DW tot DW tot DW tot Intercept 1 6590.519 6590.519 517.3872 0.000000 K_conc 7 532.597 76.085 5.9731 0.000367 Error 25 318.452 12.738 Total 32 851.049

Tukey HSD test; variable DW tot (K_general) Homogenous Groups, alpha = .01000 Error: Between MS = 12.738, df = 25.000 K_conc DW tot 1 2 6 375 9.58333 **** 7 400 9.99250 **** 8 500 11.56250 **** 4 325 12.09000 **** 3 300 14.55250 **** **** 5 350 15.54600 **** **** 1 50 18.84500 **** **** 2 225 22.15750 ****

Table A6.7 ANOVA of Leaf Dry Mass of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.1b).

Univariate Tests of Significance for DW Leaf (K_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 943.0535 1 943.0535 495.5032 0.000000 K_conc 57.3458 7 8.1923 4.3044 0.003018 Error 47.5806 25 1.9032

Tukey HSD test; variable DW Leaf (K_general) Homogenous Groups, alpha = .01000 Error: Between MS = 1.9032, df = 25.000 K_conc DW Leaf 1 2 8 500 4.080000 **** 6 375 4.200000 **** **** 7 400 4.330000 **** **** 4 325 4.872000 **** **** 3 300 5.070000 **** **** 5 350 5.726000 **** **** 1 50 6.745000 **** **** 2 225 8.225000 ****

189

Table A6.8 ANOVA of Petiole Dry Mass of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.1b).

Univariate Tests of Significance for DW Pet (K_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 389.4243 1 389.4243 440.7124 0.000000 K_conc 34.1678 7 4.8811 5.5240 0.000628 Error 22.0906 25 0.8836

Tukey HSD test; variable DW Pet (K_general) Homogenous Groups, alpha = .01000 Error: Between MS = .88362, df = 25.000 K_conc DW Pet 1 2 6 375 2.283333 **** 7 400 2.375000 **** 8 500 2.810000 **** **** 4 325 2.862000 **** 3 300 3.527500 **** **** 5 350 3.886000 **** **** 1 50 4.605000 **** **** 2 225 5.442500 ****

Table A6.9 ANOVA of Roots and Stolon Dry Mass of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.1b).

Univariate Tests of Significance for DW Root (K_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 944.8861 1 944.8861 309.2278 0.000000 K_conc 99.5536 7 14.2219 4.6543 0.001890 Error 76.3908 25 3.0556

Tukey HSD test; variable DW Root (K_general) Homogenous Groups, alpha = .01000 Error: Between MS = 3.0556, df = 25.000 K_conc DW Root 1 2 6 375 3.100000 **** 7 400 3.287500 **** 4 325 4.356000 **** **** 8 500 4.672500 **** **** 5 350 5.934000 **** **** 3 300 5.955000 **** **** 1 50 7.495000 **** **** 2 225 8.490000 ****

190

Table A6.10 ANOVA of the number of leaves of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.2a).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of lf no. lf no. lf no. lf no. Intercept 1 29333.16 29333.16 442.2174 0.000000 K_conc 7 627.03 89.58 1.3504 0.269107 Error 25 1658.30 66.33 Total 32 2285.33

Table A6.11 ANOVA of the number of nodes of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.2b).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of node no. node no. node no. node no. Intercept 1 215347.5 215347.5 455.1582 0.000000 K_conc 7 6025.7 860.8 1.8194 0.127697 Error 25 11828.2 473.1 Total 32 17853.9

Table A6.12 ANOVA of the number of stolons of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.2c).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st.no. st.no. st.no. st.no. Intercept 1 9804.858 9804.858 272.9486 0.000000 K_conc 7 261.283 37.326 1.0391 0.429737 Error 25 898.050 35.922 Total 32 1159.333

191

Table A6.13 ANOVA of total leaf area of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.3a).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of L.A). (cm2) L.A). (cm2) L.A). (cm2) L.A). (cm2) Intercept 1 5016.021 5016.021 826.3003 0.000000 K_conc 7 249.892 35.699 5.8808 0.000409 Error 25 151.761 6.070 Total 32 401.654

Tukey HSD test; variable L.A). (cm2) (K_general) Homogenous Groups, alpha = .01000 Error: Between MS = 6.0705, df = 25.000 K_conc L.A). (cm2) 1 2 3 8 500 9.02813 **** 6 375 9.15000 **** **** 7 400 10.36250 **** **** **** 4 325 11.99250 **** **** **** 3 300 12.24375 **** **** **** 5 350 13.56500 **** **** **** 1 50 16.24688 **** **** 2 225 17.15313 ****

Table A6.14 ANOVA of total stolon length of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.3b).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st lgth st lgth st lgth st lgth Intercept 1 133668379 133668379 384.4778 0.000000 K_conc 7 5398984 771283 2.2185 0.067264 Error 25 8691554 347662 Total 32 14090538

Table A6.15 ANOVA of internode length of lotus (Nelumbo nucifera) as a function of K supply. (Figure 6.3c).

Univariate Results for Each DV (K_general) Sigma-restricted parameterization Effective hypothesis decomposition internode internode internode internode Degr. of length length length length SS MS F P Intercept 1 20796.18 20796.18 423.9149 0.000000 K_conc 7 144.71 20.67 0.4214 0.879673 Error 25 1226.44 49.06 Total 32 1371.15

192

Table A6.16 ANOVA of K concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure 6.4a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 3.380059E+10 3.380059E+10 2614.877 0.000000 K conc (ppm) 7 1.435578E+09 2.050826E+08 15.866 0.000000 Error 25 3.231567E+08 1.292627E+07 Total 32 1.758735E+09

Tukey HSD test; variable K (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 1293E4, df = 25.000 K conc (ppm) K (mg kg-1) 1 2 3 1 50 18800.00 **** 2 225 26500.00 **** **** 5 350 30200.00 **** **** 3 300 30750.00 **** **** 4 325 36000.00 **** **** 8 500 38000.00 **** 7 400 39000.00 **** 6 375 39666.67 ****

Table A6.17 ANOVA of K concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure 6.4a).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 1.018363E+11 1.018363E+11 4525.924 0.000000 K conc (ppm) 7 3.826998E+09 5.467141E+08 24.298 0.000000 Error 25 5.625167E+08 2.250067E+07 Total 32 4.389515E+09

Tukey HSD test; variable K (mg kg-1) (K_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 2250E4, df = 25.000 K conc (ppm) K (mg kg-1) 1 2 3 1 50 30250.00 **** 2 225 49000.00 **** 5 350 57200.00 **** **** 3 300 59000.00 **** **** 4 325 60800.00 **** **** 8 500 62750.00 **** 6 375 63666.67 **** 7 400 66750.00 ****

193

Table A6.18 ANOVA of K concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure 6.4a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 5.052032E+10 5.052032E+10 2526.955 0.000000 K conc (ppm) 7 2.052145E+09 2.931635E+08 14.664 0.000000 Error 25 4.998142E+08 1.999257E+07 Total 32 2.551959E+09

Tukey HSD test; variable K (mg kg-1) (K_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1999E4, df = 25.000 K conc (ppm) K (mg kg-1) 1 2 1 50 19775.00 **** 2 225 36750.00 **** 6 375 39666.67 **** 5 350 42400.00 **** 4 325 43200.00 **** 8 500 44000.00 **** 7 400 45250.00 **** 3 300 45500.00 ****

Table A6.19 ANOVA of N concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure 6.4b).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 459.6208 459.6208 5670.424 0.000000 K conc (ppm) 7 0.8902 0.1272 1.569 0.190730 Error 25 2.0264 0.0811 Total 32 2.9166

Table A6.20 ANOVA of N concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure 6.4b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 286.5195 286.5195 2251.037 0.000000 K conc (ppm) 7 1.2393 0.1770 1.391 0.252631 Error 25 3.1821 0.1273 Total 32 4.4214

194

Table A6.21 ANOVA of N concentration in lotus roots and stolons (Nelumbo nucifera) as a function of roots and stolon K concentration. (Figure 6.4b).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 278.6557 278.6557 2586.876 0.000000 K conc (ppm) 7 0.8832 0.1262 1.171 0.353871 Error 25 2.6930 0.1077 Total 32 3.5761

Table A6.22 ANOVA of P concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure 6.5a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 1.063569E+09 1.063569E+09 2013.852 0.000000 K conc (ppm) 7 4.255621E+06 6.079459E+05 1.151 0.364673 Error 25 1.320317E+07 5.281267E+05 Total 32 1.745879E+07

Table A6.23 ANOVA of P concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure 6.5a).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 1.886092E+09 1.886092E+09 1945.294 0.000000 K conc (ppm) 7 3.161439E+06 4.516342E+05 0.466 0.849838 Error 25 2.423917E+07 9.695667E+05 Total 32 2.740061E+07

Table A6.24 ANOVA of P concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure 6.5a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 3.386670E+09 3.386670E+09 2877.701 0.000000 K conc (ppm) 7 1.303167E+07 1.861667E+06 1.582 0.186850 Error 25 2.942167E+07 1.176867E+06 Total 32 4.245333E+07

195

Table A6.25 ANOVA of Ca concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure 6.5b).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 1.922966E+10 1.922966E+10 2013.458 0.000000 K conc (ppm) 7 3.413783E+08 4.876832E+07 5.106 0.001054 Error 25 2.387642E+08 9.550567E+06 Total 32 5.801424E+08

Tukey HSD test; variable Ca (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 9551E3, df = 25.000 K conc (ppm) Ca (mg kg-1) 1 2 8 500 19775.00 **** 1 50 19900.00 **** 7 400 23650.00 **** **** 3 300 24500.00 **** **** 6 375 25666.67 **** **** 4 325 26000.00 **** **** 2 225 26000.00 **** **** 5 350 29800.00 ****

Table A6.26 ANOVA of Ca concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure 6.5b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 7.230686E+09 7.230686E+09 1416.563 0.000000 K conc (ppm) 7 7.237276E+07 1.033897E+07 2.026 0.091663 Error 25 1.276097E+08 5.104387E+06 Total 32 1.999824E+08

196

Table A6.27 ANOVA of Ca concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure 6.5b).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 5.138440E+09 5.138440E+09 1602.454 0.000000 K conc (ppm) 7 1.054645E+08 1.506636E+07 4.699 0.001783 Error 25 8.016517E+07 3.206607E+06 Total 32 1.856297E+08

Tukey HSD test; variable Ca (mg kg-1) (K_root) Homogenous Groups, alpha = .01000 Error: Between MS = 3207E3, df = 25.000 K conc (ppm) Ca (mg kg-1) 1 2 1 50 8650.00 **** 3 300 11275.00 **** **** 2 225 12275.00 **** **** 8 500 12975.00 **** **** 5 350 12980.00 **** **** 7 400 13550.00 **** **** 4 325 14080.00 **** 6 375 15166.67 ****

Table A6.28 ANOVA of Mg concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.1a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.625244E+09 1.625244E+09 2325.298 0.000000 K conc (ppm) 7 5.641559E+07 8.059370E+06 11.531 0.000002 Error 25 1.747350E+07 6.989400E+05 Total 32 7.388909E+07

Tukey HSD test; variable Mg (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 6989E2, df = 25.000 K conc (ppm) Mg (mg kg-1) 1 2 1 50 4050.000 **** 3 300 6700.000 **** 8 500 6700.000 **** 2 225 6825.000 **** 7 400 7900.000 **** 4 325 8080.000 **** 5 350 8120.000 **** 6 375 8400.000 **** 197

Table A6.29 ANOVA of Mg concentration in lotus petiole (Nelumbo nucifera) as a function of K supply. (Figure A6.1a).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 2.019855E+09 2.019855E+09 760.4685 0.000000 K conc (ppm) 7 2.062015E+07 2.945736E+06 1.1091 0.388128 Error 25 6.640167E+07 2.656067E+06 Total 32 8.702182E+07

Table A6.30 ANOVA of Mg concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.1a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.030636E+09 1.030636E+09 2674.985 0.000000 K conc (ppm) 7 5.268439E+06 7.526342E+05 1.953 0.102928 Error 25 9.632167E+06 3.852867E+05 Total 32 1.490061E+07

Table A6.31 ANOVA of S concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.1b).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 896342863 896342863 2386.260 0.000000 K conc (ppm) 7 8431758 1204537 3.207 0.014487 Error 25 9390667 375627 Total 32 17822424

Table A6.32 ANOVA of S concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.1b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 1.189353E+09 1.189353E+09 2001.042 0.000000 K conc (ppm) 7 8.963258E+06 1.280465E+06 2.154 0.074538 Error 25 1.485917E+07 5.943667E+05 Total 32 2.382242E+07

198

A 10000

) 8000 -1 (mg (mg kg 6000

4000 Organ Mg Conc. Mg Organ

2000

0 B

8000 ) -1 g

6000

4000 rga k onc. (mg O n S C

2000 Leaf Petiole Roots & Stolons

0 0 100 200300 400 500 600 K Supply (ppm)

Figure A6.1 Effect of potassium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Magnesium; b) Sulphur. Values are means and bars represent S.E. (n=5). (Tables A6.28-33).

199

Table A6.33 ANOVA of S concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.1b).

Univariate Results for Each DV (K_ roo t) Sigma-restricted parame terization Effectiv e hypothesis decomposition Degr. of S (mg kg-1) S (m g kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 2.088942E +09 2.0889 42 E+09 2509.822 0.000000 K conc ( ppm ) 7 9.794152E +06 1.399165 E +06 1.681 0.159463 Error 25 2.080767E+07 8.323067E +05 Total 32 3.060182E+07

Table A6.34 ANOVA of Fe concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.2a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Intercept 1 1413592 1413592 1185.473 0.000000 K conc (ppm) 7 52934 7562 6.342 0.000240 Error 25 29811 1192 Total 32 82745

Tukey HSD test; variable Fe (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 1192.4, df = 25.000 K conc (ppm) Fe (mg kg-1) 1 2 3 7 400 161.5906 **** 6 375 180.5321 **** **** **** 4 325 184.793 7 *** * **** 3 300 188.1528 **** ** ** **** 8 500 191.14 89 *** * **** **** 5 350 219.58 84 *** * **** **** 2 225 263.5961 **** **** 1 50 285.0000 ****

Table A6.35 ANOVA of Fe concentration in lotus petioles (Nelumbo n ucifera) as a function of K supply. (Figure A6.2a).

Univariate Results for Each D V (K_petiole) Sigma-restricted parameterizat ion Effectiv e hypothesis decomp osition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) F e (mg kg-1) Intercept 1 3348801 334880 1 535.3912 0 .000000 K conc (p pm) 7 35992 5142 0.8220 0. 57833 7 Error 25 156372 6255 Total 32 192364

200

Table A6.36 ANOVA of Fe concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.2a).

Univariate Results for Each DV (K_root) Sigma-restricted param eterization E ffective hyp oth esis decom posi tion Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Intercept 1 25030471 2503047 1 77 4.5231 0.000000 K conc (pp m) 7 360274 51468 1. 5926 0.1 8 3693 Error 25 807932 32317 Total 32 1168206

Table A6.37 ANOVA of Mn concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.2b).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 62226.33 62226.33 786.0587 0.000000 K conc (ppm) 7 2326.73 332.39 4.1988 0.003487 Error 25 1979.06 79.16 Total 32 4305.79

Tukey HSD test; variable Mn (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 79.162, df = 25.000 K conc (ppm) Mn (mg kg-1) 1 7 400 34.43490 **** 6 375 36.68018 **** 8 500 39.27048 **** 5 350 40.24522 **** 4 325 40.56837 **** 3 300 44.06135 **** 2 225 57.00217 **** 1 50 59.04284 ****

Table A6.38 ANOVA of Mn concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.2b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 10802.37 10802.37 559.0887 0.000000 K conc (ppm) 7 308.23 44.03 2.2790 0.061072 Error 25 483.03 19.32 Total 32 791.26

201

1200 A

1000 ) -1

800

600

Organ Fe Conc. (mg kg (mg Organ Fe Conc. 400

200

B 60 Leaf Petiole Roots & Stolons

) 50 -1

Organ Mn Conc. (mg kg (mg Conc. Mn Organ 20

0 100 200 300 400 500 600 K Supply (ppm)

Figure A6.2 Effect of potassium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Iron; b) Manganese. Values are means and bars represent S.E. (n=5). (Tables A6.36- 39).

202

Table A6.39 ANOVA of Mn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.2b).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 6249.470 6249.470 1591.891 0.000000 K conc (ppm) 7 209.105 29.872 7.609 0.000061 Error 25 98.145 3.926 Total 32 307.251

Tukey HSD test; variable Mn (mg kg-1) (K_root) Homogenous Groups, alpha = .01000 Error: Between MS = 3.9258, df = 25.000 K conc (ppm) Mn (mg kg-1) 1 2 2 225 10.57284 **** 5 350 11.70050 **** 8 500 12.18298 **** **** 3 300 12.32205 **** **** 7 400 13.66144 **** **** 6 375 16.37151 **** **** 4 325 16.86049 **** 1 50 17.66004 ****

Table A6.40 ANOVA of Zn concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.3a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. Zn (mg kg- Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) of 1) Intercept 1 216587.7 216587.7 3684.224 0.000000 K conc (ppm) 7 5467.7 781.1 13.287 0.000001 Error 25 1469.7 58.8 Total 32 6937.4

Tukey HSD test; variable Zn (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 58.788, df = 25.000 K conc (ppm) Zn (mg kg-1) 1 2 3 5 350 57.35924 **** 1 50 67.07536 **** **** 8 500 83.50304 **** **** 7 400 83.72343 **** **** 3 300 84.88669 **** **** 4 325 87.42286 **** **** 6 375 94.23229 **** 2 225 97.20959 ****

203

Table A6.41 ANOVA of Zn concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.3a).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 436433.6 436433.6 1438.937 0.000000 K conc (ppm) 7 17019.4 2431.3 8.016 0.000041 Error 25 7582.6 303.3 Total 32 24601.9

Tukey HSD test; variable Zn (mg kg-1) (K_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 303.30, df = 25.000 K conc (ppm) Zn (mg kg-1) 1 2 5 350 69.7490 **** 3 300 102.1515 **** **** 1 50 105.0401 **** **** 2 225 117.4503 **** 7 400 130.3962 **** 8 500 132.9712 **** 4 325 133.6596 **** 6 375 138.9549 ****

Table A6.42 ANOVA of Zn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.3a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 1664379 1664379 333.3769 0.000000 K conc (ppm) 7 87624 12518 2.5073 0.042515 Error 25 124812 4992 Total 32 212436

204

Table A6.43 ANOVA of Cu concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.3b).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 34765.35 34765.35 2560.739 0.000000 K conc (ppm) 7 1057.67 151.10 11.129 0.000003 Error 25 339.41 13.58 Total 32 1397.08

Tukey HSD test; variable Cu (mg kg-1) (K_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 13.576, df = 25.000 K conc (ppm) Cu (mg kg-1) 1 2 1 50 24.32768 **** 5 350 26.97604 **** 2 225 30.73490 **** **** 8 500 30.85312 **** **** 3 300 31.14052 **** **** 6 375 38.99641 **** 7 400 39.49262 **** 4 325 40.06446 ****

Table A6.44 ANOVA of Cu concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.3b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 55155.81 55155.81 775.5154 0.000000 K conc (ppm) 7 831.36 118.77 1.6699 0.162344 Error 25 1778.04 71.12 Total 32 2609.39

205

A 350

300 ) -1 kg 250

200

150 Organ Zn Conc. (mg

100

50 B 100 )

-1 80

40 Organ Cu Conc. (mg kg Organ Conc. (mg Cu

20 Leaf Petiole Roots & Stolons

0 0 100 200 300 400 500 K Supply (ppm)

Fig ure A6 .3 Effect of potassium su pply on organ nutrient concentratio n in lotus (Nelumbo nucifera) for: a) Zinc; b) Copper. Values ar e means and bars repre sent S.E. (n=5). (Tables A6.40- 45).

206

Table A6.45 ANOVA of Cu concentrati on in lotus root s and stolo ns (Nelumbo nucifera) as a function of K s upply. (Figure A6 .3b).

Univariat e Results for Each DV ( K_root) Sigma-restricted param eteri zation Effectiv e hypothesis decomposition Degr. of Cu (m g kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 152169.1 1521 69.1 72 5.2219 0.000000 K conc (ppm) 7 5951.2 850. 2 4.05 18 0.004273 Error 25 5245.6 209.8 Total 32 11196.8

Tukey HSD test; variable Cu (mg kg-1) (K_root) Homogenous Groups, alpha = .01000 Error: Between MS = 209.82, df = 25.000 K conc (ppm) Cu (mg kg-1) 1 2 5 350 49.3 9 653 ** * * 1 50 56.45 394 ** * * **** 8 500 66.80701 **** **** 6 375 67.10 509 **** **** 3 300 67.80 612 *** * **** 7 400 73.21971 **** **** 2 225 74.36438 **** **** 4 325 94.21239 ****

Table A6.46 ANOVA of B concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Fi gure A6.4a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterizati on E ffectiv e hyp othesis dec o mposition Degr. of B (mg k g-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 399751.7 3 99751.7 1 313.699 0 .000000 K conc (ppm) 7 12157.5 1736.8 5.708 0.000503 Error 25 7607.4 304.3 Total 32 19764.8

Tukey HSD test; variable B (mg kg-1) (K_leaf) Homoge nous Groups, alpha = .01000 Error: Betw een MS = 304. 29, df = 25 .000 K conc (ppm) B (m g kg-1) 1 2 5 350 80.4395 **** 2 225 99.9504 **** 3 300 101.3320 **** **** 7 400 105.1650 **** **** 8 500 115.7860 **** **** 4 325 116.6065 **** **** 6 375 121.6673 **** **** 1 50 149.4693 ****

207

Table A6.47 ANOVA of B concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.4a).

Univariat e Results fo r Each DV (K_pe tiole) Sigma-restricted param eterization E f fective h ypoth esis decom posi tion Degr. of B (mg kg-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 32424.34 3 242 4.34 333 0 .376 0.000 0 00 K conc (ppm) 7 212.80 30.40 3.122 0.016446 Error 25 243.40 9.74 Total 32 456.19

Table A6.48 ANOVA of B concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.4a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Ef fective hyp othesis decomposi tion Degr. of B (mg k g-1) B (mg kg-1) B ( mg kg-1) B (mg kg-1) Intercept 1 27429.84 2 7429.84 385 0 .049 0.000 0 00 K conc (pp m) 7 232.92 33.2 7 4.6 70 0. 001 8 50 Error 25 178.11 7.12 Total 32 411.03

Tukey HSD test; variable B (mg kg-1) (K_r oot ) Homogen ous Groups, alpha = .01000 Error: Betw een MS = 7.1245, df = 25.0 00 K conc (ppm) B (m g kg-1) 1 2 1 50 23.91651 **** 5 350 26.52461 ***** *** 8 500 29.32997 ***** *** 2 225 29.62406 **** **** 7 400 29.85136 **** **** 3 300 30.39957 **** **** 6 375 30.62240 **** **** 4 325 32.97502 ****

Table A6.49 ANOVA of Mo concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.4b).

Univ ariate Resu lts for Each DV (K_leaf) Sigma-re str icted parameteriza tion Effective hy p othesis dec omp osition Degr. of Mo (mg k g-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg -1) Intercept 1 604.9429 604.94 29 1 066.334 0.000000 K conc (pp m) 7 12.7000 1.8143 3 .198 0 .014677 Error 25 14.1828 0.5673 Total 32 26.8827

208

Table A6.50 ANOVA of Mo conc entration in lo tu s petiol es (Nelum b o nucifera) as a function of K supply. (Figure A6.4b).

Univariate Results for Each DV (K_peti ol e) Sigma-restricted para meterization Effective h ypothe sis decom po sition Degr. of Mo (mg kg-1) Mo (mg kg -1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 1075.453 1075.453 924 .48 9 3 0 .0 00000 K conc (ppm) 7 46.646 6.664 5.72 83 0 .00049 1 Error 25 29.082 1.163 Total 32 75.728

Tukey HSD test; variable Mo (mg kg-1) (K_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 1.1633, df = 25.000 K conc (ppm) Mo (mg kg-1) 1 2 5 350 3.780849 **** 1 50 4.492195 **** **** 2 225 5.167449 **** **** 3 300 5.864357 **** **** 7 400 5.940976 **** **** 8 500 6.718088 **** 6 375 6.978651 **** 4 325 7.241660 ****

Table A6.51 ANOVA of Mo concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.4b).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 12325.85 12325.85 826.0253 0.000000 K conc (ppm) 7 1010.39 144.34 9.6732 0.000009 Error 25 373.05 14.92 Total 32 1383.44

Tukey HSD test; variable Mo (mg kg-1) (K_root) Homogenous Groups, alpha = .01000 Error: Between MS = 14.922, df = 25.000 K conc (ppm) Mo (mg kg-1) 1 2 3 5 350 9.77643 **** 8 500 17.33580 **** **** 7 400 18.30563 **** **** 6 375 18.78684 **** **** **** 3 300 18.95187 **** **** 4 325 19.64252 **** 2 225 23.45224 **** **** 1 50 30.10173 ****

209

160 A

140

) 120 -1

100

60 Organ kg B Conc. (mg 40

0 B Leaf 30 Petiole Roots & Stolons ) -1 25

Organ Mo Conc. (mg kg (mg Conc. Mo Organ 10

0 100 200 300 400 500 K Supply (ppm)

Figure A6.4 Effect of potassium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Boron; b) Molybdenum. Values are means and bars represent S.E. (n=5). (Tables A6.46-51).

210

Table A6.52 ANOVA of Na concentration in lotus leaf (Nelumbo nucifera) as a function of K supply. (Figure A6.5a).

Univariate Results for Each DV (K_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 1.126138E+09 1.126138E+09 545.2820 0.000000 K conc (ppm) 7 3.427627E+07 4.896610E+06 2.3710 0.052752 Error 25 5.163100E+07 2.065240E+06 Total 32 8.590727E+07

Table A6.53 ANOVA of Na concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.5a).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 610842375 610842375 2576.235 0.000000 K conc (ppm) 7 31614152 4516307 19.048 0.000000 Error 25 5927667 237107 Total 32 37541818

Tukey HSD test; variable Na (mg kg-1) (K_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 2371E2, df = 25.000 K conc (ppm) Na (mg kg-1) 1 2 3 7 400 3000.000 **** 6 375 3666.667 **** **** 5 350 3720.000 **** **** 8 500 4350.000 **** **** 4 325 4420.000 **** 3 300 4500.000 **** 2 225 4525.000 **** 1 50 6625.000 ****

Table A6.54 ANOVA of Na concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.5a).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Na (mg kg-1) Intercept 1 994634735 994634735 1332.612 0.000000 K conc (ppm) 7 7861106 1123015 1.505 0.211252 Error 25 18659500 746380 Total 32 26520606

211

8000 ) 1 -

6000 nc. (mg kg nc. (mg o 4000 Organ Na C Na Organ 2000

0 B Leaf Petiole Roots & Stolons 020

150

100 Organ Al Conc. (ppm) Conc. Organ Al

0 100 200 300 400 500 K Supply (ppm )

Figure A6.5 Effect of potassium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Sodium; b) Aluminium. Values are means and bars represent S.E. (n=5). (Tables A6.52-57).

212

Table A6.55 ANOVA of Al concentration in lotus leaves (Nelumbo nucifera) as a function of K supply. (Figure A6.5b).

Univariate Results for Each DV (K_leaf) Sigma-rest rict ed parameterization Effective h yp othesis dec om position Degr. of Al (mg k g-1)Al (mg kg -1) Al (mg kg-1) Al (mg kg -1) Intercept 1 195784.8 195784.8 1 027.519 0.000000 K conc (pp m) 7 9812.9 1401.8 7.357 0 .000079 Error 25 4763.5 190.5 Total 32 14576.4

Tukey HSD test; variable Al (mg kg-1) (K_leaf) Homogenous Groups, alpha = .05000 Error: Between MS = 190.54, df = 25.000 K conc (ppm) Al (mg kg-1) 1 2 7 400 60.1403 **** 6 375 64.0670 **** 4 325 66.3554 **** 5 350 73.2516 **** 3 300 73.3853 **** 2 225 77.5474 **** 8 500 90.1070 **** **** 1 50 118.2885 ****

Table A6.56 ANOVA of Al concentration in lotus petioles (Nelumbo nucifera) as a function of K supply. (Figure A6.5b).

Univariate Results for Each DV (K_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 98461.66 98461.66 250.6798 0.000000 K conc (ppm) 7 4194.08 599.15 1.5254 0.204399 Error 25 9819.47 392.78 Total 32 14013.54

Table A6.57 ANOVA of Al concentration in lotus roots and stolons (Nelumbo nucifera) as a function of K supply. (Figure A6.5b).

Univariate Results for Each DV (K_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 666094.2 666094.2 390.0717 0.000000 K conc (ppm) 7 37878.0 5411.1 3.1688 0.015336 Error 25 42690.5 1707.6 Total 32 80568.5

213

Table A6.58 ANOVA for the relationship between K concentration in lotus leaves (Nelumbo nucifera) and K supply. (Figure 6.6, Tables A6.135-138 & 151-154). Rank 1 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6720949446 0.6502346076 4313.1387689 63.539561047

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12838.75775 2540.854789 5.052928568 7656.650245 18020.86526 0.00002 b 194.6958045 24.42499524 7.97117062 144.8806983 244.5109107 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.182037e+09 1 1.182037e+09 63.5396 0.00000 Error 5.7669815e+08 31 18603166 Total 1.7587352e+09 32

Table A6.59 ANOVA for the relationship between K concentration in lotus petioles (Nelumbo nucifera) and K supply. (Figure 6.6, Tables A6.135-136, 138, 151-152 & 154). Rank 1 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8103235913 0.7976784973 5182.4376816 132.43624495

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6183.03783 4432.180227 1.395033034 -2856.45334 15222.529 0.17292 b 1568.012677 136.253021 11.50809476 1290.122809 1845.902545 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3.5569277e+09 1 3.5569277e+09 132.436 0.00000 Error 8.3258747e+08 31 26857660 Total 4.3895152e+09 32

Table A6.60 ANOVA for the relationship between K concentration in lotus roots and stolons (Nelumbo nucifera) and K supply. (Figure 6.6, Tables A6.135, 137-138, 151 & 153-154). Rank 1 Eqn 8100 y=a(1-exp(-bx)) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8117302404 0.7982824005 3814.8022617 125.03429667

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 43350.17134 921.7639978 47.02957747 41464.95229 45235.39039 0.00000 b 0.012118875 0.001680465 7.211620164 0.008681938 0.015555811 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 13 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.8195886e+09 1 1.8195886e+09 125.034 0.00000 Error 4.2202877e+08 29 14552716 Total 2.2416174e+09 30

214

Table A6.61 ANOVA for the relationship between N concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Tables A6.139-141 & 155-158). Rank 1 Eqn 6721 y=a+bx2+cx4 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2040036789 0.1187183587 0.2620934648 3.7161645914

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.351870506 0.24169372 18.00572439 3.857551346 4.846189666 0.00000 b -1.2696e-09 4.69308e-10 -2.70515765 -2.2294e-09 -3.0971e-10 0.01131 c 5.61273e-19 2.06786e-19 2.714272653 1.38349e-19 9.84198e-19 0.01107

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.51054887 2 0.25527444 3.71616 0.03658 Error 1.9920965 29 0.068692984 Total 2.5026454 31

Table A6.62 ANOVA for the relationship between N concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. (Tables A6.139-140, 142, 155-156 & 158). Rank 21 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1054098601 0.0457705174 0.3571998368 3.6527405303

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.025134068 0.551125588 7.303478831 2.90110602 5.149162115 0.00000 b -0.00444628 0.002326414 -1.91121441 -0.00919103 0.000298477 0.06526

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.46605946 1 0.46605946 3.65274 0.06526 Error 3.9553434 31 0.12759172 Total 4.4214029 32

Table A6.63 ANOVA for the relationship between N concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. (Tables A6.139, 141-142, 155, 157-158). Rank 1 Eqn 8114 y=a+0.25b2x2-a0.5bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1982651484 0.1448161583 0.3041178339 7.6661499582

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.628138415 0.262186817 13.83798946 3.093404876 4.162871954 0.00000 b 9.58035e-06 3.41133e-06 2.808393846 2.6229e-06 1.65378e-05 0.00854

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.70902425 1 0.70902425 7.66615 0.00941 Error 2.8671174 31 0.092487657 Total 3.5761416 32

215

Table A6.64 ANOVA for the relationship between P concentration in lotus leaves (Nelumbo nucifera) and K supply. (Tables A6.143-146 & 159-161). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0588165424 0 728.05357703 1.937255483

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5438.808244 250.4027509 21.72024159 4928.108467 5949.508022 0.00000 b 7.83521e-12 5.62934e-12 1.391853255 -3.6459e-12 1.93163e-11 0.17387

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1026865.5 1 1026865.5 1.93726 0.17387 Error 16431922 31 530062.01 Total 17458788 32

Table A6.65 ANOVA for the relationship between P concentration in lotus petioles (Nelumbo nucifera) and K supply. (Tables A6.143-144, 146 & 159-162). Rank 1 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.511655755 0.4754821072 550.27493132 29.336602785

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 79.45518127 2.9608126 26.83559955 73.3902316 85.52013095 0.00000 b 3.53284e-14 1.30288e-14 2.711555321 8.64006e-15 6.20168e-14 0.01131

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 8883196.7 1 8883196.7 29.3366 0.00001 Error 8478470 28 302802.5 Total 17361667 29

Table A6.66 ANOVA for the relationship between P concentration in lotus roots and stolons (Nelumbo nucifera) and K supply. (Tables A6.143, 145-146, 159, 161-162). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2962310693 0.2493131406 981.72555468 13.048548673

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8998.564354 390.4409059 23.04718644 8202.254877 9794.873832 0.00000 b 1.77968e-11 4.92676e-12 3.612277491 7.74863e-12 2.7845e-11 0.00106

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 12575996 1 12575996 13.0485 0.00106 Error 29877337 31 963785.06 Total 42453333 32

216

Table A6.67 ANOVA for the relationship between Ca concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure 6.8, Tables A6.147-149 & 163-165). Rank 2256 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0424508551 0 4233.1825984 1.3743174593

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6462.288499 15476.36204 0.417558628 -25101.96 38026.53697 0.67915 b 169.0668472 144.2164902 1.172312868 -125.064624 463.1983181 0.25000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 24627542 1 24627542 1.37432 0.25000 Error 5.5551488e+08 31 17919835 Total 5.8014242e+08 32

Table A6.68 ANOVA for the relationship between Ca concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. (Figure 6.8, Tables A6.147-148, 150, 163-164 & 166). Rank 2 Eqn 6721 y=a+bx2+cx4 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1694046413 0.0834809835 2353.0439392 3.0593352025

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10097.89857 2095.434657 4.818999506 5818.450093 14377.34706 0.00004 b 3.64366e-06 1.48743e-06 2.449632607 6.05921e-07 6.68141e-06 0.02035 c -5.808e-16 2.53222e-16 -2.29364129 -1.098e-15 -6.3652e-17 0.02899

Soln Vector Covar Matrix GaussElim LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 33877951 2 16938975 3.05934 0.06178 Error 1.6610447e+08 30 5536815.8 Total 1.9998242e+08 32

Table A6.69 ANOVA for the relationship between Ca concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. (Figure 6.8, Tables A6.147, 149-150, 163 & 165-166). Rank 142 Eqn 34 lny=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5815309665 0.5480534438 1198.1251964 36.131240116

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5.742154987 0.861315638 6.666725569 3.971695337 7.512614636 0.00000 b 0.346712674 0.081154741 4.27224178 0.179896715 0.513528632 0.00023

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 51866539 1 51866539 36.1312 0.00000 Error 37323104 26 1435504 Total 89189643 27

217

Table A6.70 ANOVA for the relationship between Mg concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure A6.6a).

Rank 49 Eqn 75 y0.5=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4662692736 0.4281456503 1013.9290203 25.334514706

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 38.73732779 21.58841351 1.794357319 -5.41593543 82.890591 0.08319 b 0.258684278 0.117497324 2.201618468 0.018375269 0.498993286 0.03580

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 26045200 1 26045200 25.3345 0.00002 Error 29813510 29 1028052.1 Total 55858710 30

Table A6.71 ANOVA for the relationship between Mg concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 2181 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0244688917 0 1404.6393368 0.7524790816

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3115.483807 5391.606458 0.577839616 -7895.64555 14126.61317 0.56768 b 39.26060402 45.25950098 0.867455521 -53.1716282 131.6928362 0.39258

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1484650 1 1484650 0.752479 0.39258 Error 59190350 30 1973011.7 Total 60675000 31

Table A6.72 ANOVA for the relationship between Mg concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. Rank 9 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2606679409 0.1841853141 605.98393161 5.2885832078

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5971.023765 179.5703727 33.25172006 5604.292139 6337.755391 0.00000 b 35885.45545 2225.283264 16.12624156 31340.82073 40430.09016 0.00000 c 28746.62289 5343.331346 5.379906472 17834.08446 39659.16132 0.00001

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 3884110.3 2 1942055.1 5.28858 0.01078 Error 11016496 30 367216.53 Total 14900606 32

218

8000 ) -1

6000

4000 Leaf Mg Conc. (mg kg Conc. (mg Leaf Mg 2000

0 10000 B ) -1 8000

6000

4000

2000 Roots & Stolons S Conc. (mg kg (mg Stolons S Conc. & Roots

0 0 10000 20000 30000 40000 50000 60000

Organ K Conc. (mg kg-1)

Figure A6.6 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentration a) Magnesium, regression equation is y0.5 = 38.74 + 0.26x0.5 (r2 = 0.43), for leaves; b) Sulphur, regression equation is y = 6275.75 + 0.00022x1.5 (r2 = 0.26), for roots and stolons. (Tables A6.70 & 75).

219

Table A6.73 ANOVA for the relationship between S concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. Rank 1634 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1354391428 0.0778017523 705.01819652 4.8563538268

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4790.657284 242.4800886 19.75690998 4296.115883 5285.198685 0.00000 b 1.20129e-11 5.45123e-12 2.203713644 8.95092e-13 2.31308e-11 0.03510

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2413853.9 1 2413853.9 4.85635 0.03510 Error 15408570 31 497050.66 Total 17822424 32

Table A6.74 ANOVA for the relationship between S concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 370 Eqn 7 y=a+bx3

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0509821795 0 853.98317455 1.6653507753

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5628.122459 358.0588106 15.71843031 4897.856701 6358.388218 0.00000 b 2.13145e-12 1.65166e-12 1.290484706 -1.2371e-12 5.50003e-12 0.20643

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1214519.1 1 1214519.1 1.66535 0.20643 Error 22607905 31 729287.26 Total 23822424 32

Table A6.75 ANOVA for the relationship between S concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. (Figure A6.6b). Rank 2 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3063650583 0.2601227288 827.48141721 13.692096859

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 6275.754543 499.4822602 12.56451939 5257.053758 7294.455329 0.00000 b 0.000218952 5.91717e-05 3.700283348 9.82706e-05 0.000339634 0.00083

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9375327.8 1 9375327.8 13.6921 0.00083 Error 21226490 31 684725.5 Total 30601818 32

220

Table A6.76 ANOVA for the relationship between Fe concentration in lotus leaves (Nelumbo nucifera) as a function of leaf K concentration. (Figure A6.7a). Rank 1 Eqn 17 y=a+b/x r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3517498986 0.3085332252 41.59687117 16.821049213

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 102.0424162 27.23945988 3.746124798 46.48717147 157.5976608 0.00074 b 3.25798e+06 794369.3883 4.101347244 1.63786e+06 4.87811e+06 0.00028

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 29105.456 1 29105.456 16.821 0.00028 Error 53639.29 31 1730.2997 Total 82744.747 32

Table A6.77 ANOVA for the relationship between Fe concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1537250903 0.0932768825 54.261947188 5.2678244022

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 358.3602142 23.08760765 15.52175607 311.1407547 405.5796737 0.00000 b -2.4198e-13 1.05432e-13 -2.29517416 -4.5762e-13 -2.6352e-14 0.02915

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 15510.366 1 15510.366 5.26782 0.02915 Error 85386.408 29 2944.3589 Total 100896.77 30

Table A6.78 ANOVA for the relationship between Fe concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1161994297 0.0572793917 182.49712172 4.0757863744

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1014.172482 72.58071382 13.97302986 866.1431398 1162.201823 0.00000 b -1.849e-12 9.15857e-13 -2.01885769 -3.7169e-12 1.89177e-14 0.05222

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 135744.88 1 135744.88 4.07579 0.05222 Error 1032461.2 31 33305.199 Total 1168206.1 32

221

350 A

300 ) -1 250

200

150

Leaf Fe Conc. (mg kg Fe Conc. (mg Leaf 100

0 B 60

) 50 -1

20 Leaf Mn Conc. (mg kg (mg Conc. Mn Leaf

0 0 10000 20000 30000 40000 50000

Organ K Conc. (mg kg-1)

Figure A6.7 Nutrie nt concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassi um concentration : a) Iron, regression equation is y = 102.04 + 3.26 * 10-6 (r2 = 0.31); b) Manga nese, regression e quation is y = 1 0 2.51 – 0.33x0.5 (r2 = 0.37). (Table s A6.76 & 79).

222

Table A6.79 ANOVA for the relationsh i p between Mn conce ntra tion in lotus leav es (Nelumbo nucifera) and leaf K concentration. (Figur e A 6.7b). Rank 11 E qn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.419228012 0.3791747714 8.6730157859 21.655383901

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 102.508499 12.81771865 7.997405922 76.33122526 128.6857727 0.00000 b -0.33227465 0.07140264 -4.65353456 -0.4780983 -0.18645101 0.00006

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1628.94 4 1 1628.944 21.6 554 0.00006 Error 2256.6361 30 75.221203 Total 3885.5801 31

Table A6.80 ANOVA for the relationship between Mn concentration i n lotus petioles (Nelumbo nucifera) and roots and stolon K concentration. Rank 1002 Eqn 9 y=a+bx0.5lnx

r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.13224661 02 0.0724015 489 3.481047473 4.5720 343523

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 27.55728609 4.625374786 5.957849334 18.11101057 37.00356161 0.00000 b -0.00381091 0.001782271 -2.13823159 -0.00745079 -0.00017103 0.04076

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 55.402502 1 55.4025 02 4.57203 0.04076 Error 363.53075 30 12.117692 Total 418.93325 31

Table A6.81 ANOVA for the relationship between Mn concentration i n lotus roots and stolons (Nelum bo nucifera) and roots and stolon K concentration. Rank 8 Eqn 13 y=a+blnx r2 Coef Det DF Adj r 2 Fit S td Err F-valu e 0.11832232 29 0.059543 81 11 2.9 5 61 099737 4.16 02 4144 18

Parm V alue Std Erro r t-value 9 5% Confidence Limits P>|t| a 53. 87687639 19.6 24032 71 2.745453862 13.85339783 93.90035496 0.00997 b -3.78985443 1.85807509 -2.03966699 -7.57942356 -0.0002853 0.04998

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 36.354628 1 36.3546 28 4.16024 0.04998 Error 270.89617 31 8.7385862 Total 307.2508 32

223

Table A6.82 ANOVA for the relationship b etween Zn concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure A 6.8a). Rank 1 Eq n 7 y=a+bx3

r2 Coef Det DF Adj r2 F it Std Err F-value 0.1972004882 0.1436805207 13.403580174 7.6148715128

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 70.00431316 4.609953792 15.1854696 60.60225042 79.4063759 0.00000 b 2.85987e-13 1.03637e-13 2.759505665 7.46178e-14 4.97356e-13 0.00963

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1368.0571 1 1368.0571 7.61487 0.00963 Error 5569.3348 31 179.65596 Total 6937.3919 32

Table A6.83 ANOVA for the relationship between Zn concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0809082507 0.0175226128 25.536947416 2.6409197141

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 100.5994979 10.77421383 9.337061569 78.59561779 122.6033781 0.00000 b 8.03359e-14 4.94347e-14 1.625090679 -2.0623e-14 1.81295e-13 0.11460

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1722.238 1 1722.238 2.64092 0.11460 Error 19564.071 30 652.13568 Total 21286.308 31

Table A6.84 ANOVA for the relationship between Zn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. Rank 2112 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0080021276 0 70.65830455 0.2420003468

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 204.9400813 29.83024423 6.870211309 144.0185951 265.8615674 0.00000 b 1.82427e-13 3.70836e-13 0.491935308 -5.7492e-13 9.39774e-13 0.62635

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1208.21 1 1208.21 0.242 0.62635 Error 149777.88 30 4992.596 Total 150986.09 31

224

A 100

80 ) -1

40 Leaf Zn Conc. (mg kg Leaf Zn Conc. (mg

0 B

40 ) -1 30

20 Leaf Cu Conc. (mg kg Leaf Cu Conc. (mg 10

0 0 10000 20000 30000 40000 50000

Organ K Conc. (mg kg-1)

Figure A6.8 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentration: a) Zinc, regression equations is y = 70.00 + 2.86*10-13x3 (r 2 = 0.14) for leaves; b) Copper, regression equation is y = 22.01 + 9.79*10-9x2 (r2 = 0.43) for leaves. (Tables A6.82 & 85).

225

Table A6.85 ANOVA for the relationship between Cu concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure A6.8b). Rank 2 Eqn 4 y=a +bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4700945486 0.4347 675185 4.8 868523413 2 7.50100224

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 22.0143839 2.204277772 9.987118764 17.51872974 26.51003805 0.00000 b 9.78929e-0 9 1.86671e-0 9 5.2441 398 5.98211e-09 1.35965e-08 0.00001

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 656.76039 1 656.76039 27.501 0.00001 Error 740.3211 31 23.881326 Total 1397.0815 32

Table A6.86 ANOVA for the relationship between Cu concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 1 Eqn 7 y=a +bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1667147953 0.1071 944235 6.8 540716566 5 .8020099675

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 33.30148718 2.920153482 11.40401948 27.32910272 39.27387164 0.00000 b 3.20765e-1 4 1.33167e-1 4 2.4087 36176 4.84073e-15 5.93123e-14 0.02259

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 272.56855 1 272.56855 5.80201 0.02259 Error 1362.3706 29 46.978298 Total 1634.9392 30

Table A6.87 ANOVA for the relationship between Cu concentration in lotus roots and stolons (Nelumbo nucifera) and roots and st olon K concentration. Rank 2175 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0297185084 0 14. 660819805 0 .9188624731

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 49.81631918 17.93927107 2.776942218 13.17944001 86.45319835 0.00937 b 0.00813157 9 0.008483003 0.9585 73144 -0.00919302 0.025456183 0.34544

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 197.49997 1 197.49997 0.918862 0.34544 Error 6448.1891 30 214.93964 Total 6645.6891 31

226

Table A6.88 ANOVA for the relationship between B concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. Rank 2481 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0269215935 0 24. 908041392 0 .8576589444

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 276.9914443 180.1388337 1.537655366 -90.4041291 644.3870178 0.13428 b -16.113285 8 17.39910066 -0.926 09878 -51.5989856 19.3724139 0.36155

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 532.10064 1 532.10064 0.857659 0.36155 Error 19232.726 31 620.41053 Total 19764.827 32

Table A6.89 ANOVA for the relationship between B concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 2 Eqn 12 y= a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0806189807 0.0193 269128 3.6 782531148 2 .7183380442

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 22.3867606 5.675196915 3.944666756 10.81212019 33.96140102 0.00043 b 0.03949745 8 0.023956172 1.6487 38319 -0.00936148 0.088356392 0.10930

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 36.77788 1 36.77788 2.71834 0.10930 Error 419.41593 31 13.529546 Total 456.1938 32

Table A6.90 ANOVA for the relationship between B concentration in lotus roots and stolons (Nelumbo nucifera) and roots and st olon K concentration. (Figure A6.9a). Rank 120 Eqn 73 y0.5=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2915094778 0.2409 03012 2.7 960226961 1 1.932093081

Parm Value Std Error t-value 95% Confidenc e Limits P>|t| a 2.350666581 1.91521329 1.227365429 -1.56638441 6.267717571 0.22956 b 0.02742016 2 0.017102057 1.6033 25396 -0.00755747 0.062397796 0.11970

Soln Vector Covar Matr ix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 93.282036 1 93.282036 11.9321 0.00172 Error 226.71454 29 7.8177429 Total 319.99658 30

227

20 A ) -1

15 (mg onc. B C kg 10 ons ol s & sSt & 5 oot R

1400

B )

1 120 -

100 (mg kg onc. 80 Mo C

ons 60 ol

& St & 40 s Root 20

010000 200 00 30000 40000 50000

Organ K Conc. (mg kg-1)

Figure A6.9 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentrat ion a) Boron, regr ession equatio n is y = (2.35 + 0.027(lnx)2)0.5 (r2 = 0.24) for roots and stolons; b ) Molybdenum , r eg ression equatio n is y = 41.69 exp(-1 .98*10-5x) (r2 = 0.28), for roots and stolons. ( Tables A6.90 & 93).

228

Table A6.91 A NOVA for the relationship bet ween Mo concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. Rank 18 E qn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.1766496352 0.1217596 109 0 .8449836988 6.6510430132

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.103729923 1.247878493 0.884485091 -1.44133504 3.648794888 0.38324 b 0.017937875 0.006955464 2.578961615 0.003752112 0.032123638 0.01488

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.7488278 1 4.7488278 6.65104 0.01488 Error 22.1339 21 31 0.71399745 Total 26.882749 32

Table A6.92 ANOVA for the relationship between Mo concentration i n lotus petioles (Nelumbo nucifera) and petiole K concentration. Rank 13 Eqn 9 y= a+bx0.5lnx

r2 Coef Det DF Adj r2 Fit S td Err F-val u e 0.17777127 48 0.1190406 516 1.2570850192 6.2699 913197

Parm Value Std E rror t-value 95% Confidence Limits P>|t| a 1.564855107 1.67054423 0.936733718 -1.85179147 4.981501683 0.35663 b 0.001611667 0.000643638 2.503995072 0.000295279 0.002928056 0.01816

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 9.9082337 1 9.9082337 6.2699 9 0.01816 Error 45.82762 29 1.5802627 Total 55.735853 30

Table A6.93 ANOVA for the relationship between Mo concentration i n lotus roots an d stolons (Nelumbo nucifera) and roots and stolon K concentration. (Figure A6.9b). Rank 9 Eqn 8098 y=aexp(-bx) r2 Coef Det DF Adj r 2 Fit S td Err F-va lu e 0.32197883 61 0.2767774 252 5.5007373637 14 .72 12866 65

Parm V alue Std Erro r t-value 95% Confidence Limits P>|t| a 41.69009699 7.243523592 5.75549958 26.91683323 56.46336075 0.00000 b 1.98323e-05 4.62995e-06 4.283493312 1.03895e-05 2.92752e-05 0.00017

Procedure Minimization Iterations LevMarqdt Least Squares 7 Source Sum of Squares DF Mean Square F Statistic P>F Regr 445.43833 1 445.43833 14.7 213 0.00057 Error 938.00146 31 30.258112 Total 1383.4398 32

229

Table A6.94 ANOVA for the relationship b etween Na concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure A 6.10a). Rank 1 Eq n 6 y=a+bx2.5

r2 Coef Det DF Adj r2 F it Std Err F-value 0.3011413052 0.2545507255 1391.6460953 13.358037226

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4155.347415 537.5238234 7.730536274 3059.06035 5251.634481 0.00000 b 8.61661e-09 2.35757e-09 3.654864871 3.80831e-09 1.34249e-08 0.00094

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 25870228 1 25870228 13.358 0.00094 Error 60037044 31 1936678.9 Total 85907273 32

Table A6.95 ANOVA for the relationship between Na concentration in lotus petioles (Nelumbo nucifera) and petiole K concentration. (Figure A6.10a). Rank 9 Eqn 66 y0.5=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7603556759 0.7432382242 542.75094378 92.012672039

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 89.30029391 4.630424071 19.28555409 79.83001334 98.77057447 0.00000 b -1.7208e-06 3.47146e-07 -4.95686358 -2.4307e-06 -1.0108e-06 0.00003

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 27104963 1 27104963 92.0127 0.00000 Error 8542779 29 294578.59 Total 35647742 30

Table A6.96 ANOVA for the relationship between Na concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon K concentration. (Figure A6.10a). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2544285199 0.2047237545 798.64820295 10.578843648

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4333.068519 401.3301264 10.79676863 3514.55033 5151.586708 0.00000 b 7.38439e-07 2.27036e-07 3.252513435 2.75395e-07 1.20148e-06 0.00276

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6747598.5 1 6747598.5 10.5788 0.00276 Error 19773008 31 637838.95 Total 26520606 32

230

10000 A

8000 ) -1

6000

4000 Organ Na Conc. (mg kg (mg Organ Na Conc.

2000

3000 B Leaf Petiole 250 Roots & Stolons ) -1 200

150

100 Organ Al Conc. (mg kg Organ Al Conc. (mg

0 02000 0 40000 600008 0000

Organ K Conc. (mg kg-1)

Figure A6.10 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ potassium concentration: a) Sodium, regression equations are y = 4155.35 + 8.62*10-9x2.5 (r2 = 0.25), y = (89.30 – 1.72*10-6x1.5)0.5(r2 = 0.74), y = 4333.07 + 7.38*10-7x2 (r2=0.20) for leaves, petioles and roots and stolons respectivel y; b) Aluminium, regression equations are y = (15.70 – 0.0038x0.5)0.5 (r2 = 0.59), y = 76.03 – 7.87*10-9 (r2 = 0.5 8), y = 204.53 – 8.8 7*10-6 (r2 = 0.36) for leaves (____), petioles (…..) and roots and s tolons (-----). (Ta b les A6.94-99).

231

Table A6.97 A NOVA for the relationship b etween Al concentration in lotus leaves (Nelumbo nucifera) and leaf K concentration. (F i gure A6.1 0b). Rank 440 Eqn 72 y0.5=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.6189509971 0.5907251 451 1 3.054512572 45.481362734

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 15.69694004 1.871964534 8.385276406 11.86239452 19.53148556 0.00000 b -0.00376443 0.001026826 -3.6660872 -0.00586779 -0.00166108 0.00102

Soln Vector Covar Matrix Direct LUDec omp Source Sum of Squares DF Mean Square F Statistic P>F Regr 7750.9474 1 7750.9474 45.4814 0.00000 Error 4771.76 84 28 170.420 3 Total 12522.7 16 29

Table A6.98 ANOVA for the relati ons hip between Al c oncentration in lotus petioles (Nelumbo nucifer a) and petiole K concentration. (Figure A6.10b). Rank 2 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.61006747 42 0.58118358 34 7.74 38 10125 43.8072952 38

Parm V alue Std Erro r t-v alue 95% Confi dence Limits P>|t| a 76. 03304434 4.15 75116 68 1 8.288 11328 67 .51676775 84.54932093 0.00000 b -7.8 677e-09 1.18 871e-0 9 -6.61870797 -1.0303e-08 -5.4327e-09 0.00000

Soln Vector Covar Matrix Direct LUDec omp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2626.9743 1 2626.9743 43.8073 0.00000 Error 1679.06 47 28 59.9665 95 Total 4306.03 9 29

Table A6.99 ANOVA for the relat ion ship between Al c oncentration in lotus roots an d sto lons (Nelum bo nucifera) and root and stolon K concentration. ( Figure A6.10b). Rank 1 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.40443463 93 0.36031868 67 26.7 06 006007 19.0141513 42

Parm V alue Std Erro r t-v alue 95% Confi dence Limits P>|t| a 204 .5260986 17.2 54699 19 1 1.853 35637 16 9.1814496 239.8707476 0.00000 b -8.8 656e-06 2.03 314e-0 6 -4.36052191 -1.303e-05 -4.7009e-06 0.00016

Soln Vector Covar Matrix Direct LUDeco mp Source Sum of Squares DF Mean Square F Statistic P>F Regr 13561.097 1 13561.097 19.0142 0.00016 Error 19969.9 01 28 713.21076 Total 33530.9 98 29

232

Table A6.100 A NOVA for the relationship be tween total dry mass of lotus (Nelumbo nucifera) and leaf K concentration. (Figure 6.9a). Rank 20 E qn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.6358186548 0.6088422 589 2 .6342573655 48.88477285

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 22.0535817 1.294358084 17.03823847 19.40220936 24.70495404 0.00000 b -7.4328e-09 1.06307e-09 -6.99176464 -9.6104e-09 -5.2552e-09 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 339.22668 1 339.22668 48.8848 0.00000 Error 194.30073 28 6.9393119 Total 533.527 42 29

Table A6.101 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole K concentratio n. (Figure 6.9 a). Rank 4 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6023914334 0.5718061591 2.624183 524 40.905981585

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 22. 50872401 1.42 75417 52 1 5.7 6747159 19.579 65028 25.437797 74 0.00000 b -1.0 108e-11 1.58 042e- 12 -6 .3 9577842 -1 .3351e-11 -6.8652e-12 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Square s DF Mean Square F Statistic P>F Regr 281.69246 1 281.69246 40.906 0.00000 Error 185.93116 27 6.8863392 Total 467.623 62 28

Table A6.102 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon K co ncentration. ( Fig ure 6.9a). Rank 84 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1706402808 0.1114003009 3.909442 1548 5.966733167

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 19. 3997839 2.4678 869 7 7 .86 0888338 14.352 38832 24.447179 48 0.00000 b -7.0 257e-07 2.87 62e-0 7 -2 .4 4268974 -1.2 908e-06 -1.1432e-07 0.02091

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 91.193986 1 91.193986 5.96673 0.02091 Error 443.2284 29 15.283738 Total 534.422 39 30

233

Table A6.103 ANOVA for the relationship between dry mass of lotus leaves (Nelumbo nucifera) and leaf K concentration. (Figure 6.9b ).

Rank 1 Eq n 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.4611830257 0.4240232 344 1 .1617405498 25.677533247

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.682240126 0.518790181 14.80799062 6.62272923 8.741751022 0.00000 b -2.0945e-10 4.13343e-11 -5.06730039 -2.9387e-10 -1.2504e-10 0.00002

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 34.655454 1 34.6554 54 25.6775 0.00002 Error 40.489233 30 1.3496411 Total 75.144688 31

Table A6.104 ANOVA for the relationship between dry mass of lotus petioles (Nelumbo nucifer a) and petiole K concentration. (Figure 6.9b). Rank 1 Eqn 6 y=a +bx2.5 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.60579853 43 0.5765984 257 0.7 350 281876 43.02 96699 4

Parm V alue Std Erro r t-value 95% Confide nce Limits P>|t| a 5.7781 44297 0.3 773490 82 15.31246415 5.005179742 6.551108853 0.00000 b -2.7804e-12 4.23864e-13 -6.55970045 -3.6487e-12 -1.9122e-12 0.00000

Soln Vector Cova r Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 23.247486 1 23.2474 86 43.0297 0.00000 Error 15.12746 28 0.54026644 Total 38.374947 29

Table A6.105 ANOVA for the relati onship between d ry mass in lotus r oots and stolons (Nelum bo nucifera) and root and stolon K concentration. (Figure 6.9b). Rank 39 Eqn 4 y= a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F-value 0.17519244 0.116277 6143 1.8 385 3255 6.1597 1652 96

Parm V alue Std Erro r t-value 95% Confide nce Limits P>|t| a 7.4067 4565 0.9 741138 74 7.603572693 5.414459081 9.399032218 0.00000 b -1.3404e-09 5.40056e-10 -2.48187762 -2.4449e-09 -2.3581e-10 0.01911

Soln Vector Covar M atrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 20.821086 1 20.8210 86 6.15972 0.01911 Error 98.025856 29 3.3802019 Total 118.84694 30

234

Table A6.106 A NOVA for the r ela tionship between total leaf area of lotus (Nelumbo nucifera) and leaf K concentration. (Figure 6.10 ). Rank 1 Eq n 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.5918771585 0.5646689 69 2 .2995380433 44.957522701

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 19.00304114 1.03723629 18.32084098 16.88758378 21.1184985 0.00000 b -5.8897e-09 8.78392e-10 -6.70503711 -7.6811e-09 -4.0982e-09 0.00000

Soln Vector Covar Matrix Direct LUDec omp Source Sum of Squares DF Mean Square F Statistic P>F Regr 237.72977 1 237.72977 44.9575 0.00000 Error 163.924 13 31 5.28787 52 Total 401.6539 32

Table A6.107 ANOV A for the relationship between tot al leaf area of lotus (Nelumbo nuc ifera) and pet iole K concentration. (Figure 6.1 0 ). Rank 3 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.35923713 05 0.31651960 59 2.88 13 354121 17.3798320 36

Parm V alue Std Erro r t-v alue 95% Confi dence Limits P>|t| a 18. 62063333 1.53 17141 5 1 2.156 72867 15 .49668173 21.74458494 0.00000 b -1.8 38e-09 4.40 888e-1 0 -4.16891257 -2.7372e-09 -9.3883e-10 0.00023

Soln Vector Covar Matrix Direct LUDecom p Source Sum of Squares DF Mean Square F Statistic P>F Regr 144.289 1 144.289 17.3798 0.00023 Error 257.364 91 31 8.30209 38 Total 401.6539 32

Table A6.108 ANOV A for the relationship between tot al leaf area of lotus (Nelumbo nuc ifera) and roo ts and stolon K c oncentration. Rank 22 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.18667010 79 0.13244811 51 3.24 62 242304 7.11491536 42

Parm V alue Std Erro r t-v alue 95% Confi dence Limits P>|t| a 17. 5917262 1.95 94777 38 8 .9777 62729 13 .59534501 21.5881074 0.00000 b -6.1 918e-07 2.32 132e-0 7 -2.66737987 -1.0926e-06 -1.4575e-07 0.01204

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 74.976777 1 74.976777 7.11492 0.01204 Error 326.677 12 31 10.5379 72 Total 401.6539 32

235

Table A6.109 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and leaf K concentration. Rank 21 E qn 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.0638987619 0 6 .5545997301 1.9795552245

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.69508474 2.898996701 11.27806897 26.76597075 38.62419872 0.00000 b -3.2474e-10 2.30805e-10 -1.40696667 -7.9679e-10 1.47314e-10 0.17006

Soln Vector Covar Matrix Direct LUDec omp Source Sum of Squares DF Mean Square F Statistic P>F Regr 85.047191 1 85.047191 1.97956 0.17006 Error 1245.92 06 29 42.9627 78 Total 1330.96 77 30

Table A6.110 ANOV A for the rela tio nship between the number of leaves of lotus (Nelum bo nucifer a) and petiole K concentration. Rank 2 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.11525702 88 0.05206110 22 6.37 22 576377 3.77788119 57

Parm V alue Std Erro r t-v alue 95% Conf idence Limits P>|t| a 33. 91104383 2.78 89241 55 1 2.159 18467 28 .20705348 39.61503418 0.00000 b -2.4 497e-14 1.26 035e-1 4 -1.94367724 -5.0274e-14 1.27991e-15 0.06170

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 153.40339 1 153.40339 3.77788 0.06170 Error 1177.56 44 29 40.6056 67 Total 1330.96 77 30

Table A6.111 ANOV A for the rela tio nship between the number of leaves of lotus (Nelum bo nucifer a) and root and st olon K concentr a tion. Rank 9 97 Eqn 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.01257677 43 0 8.53 18 969107 0.39484589 17

Parm V alue Std Erro r t-v alue 95% Conf idence Limits P>|t| a 32. 78099284 4.16 88078 23 7 .8633 97459 24 .27865323 41.28333244 0.00000 b -1.3 853e-10 2.20 454e-1 0 -0.62836764 -5.8815e-10 3.11093e-10 0.53437

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 28.742122 1 28.742122 0.394846 0.53437 Error 2256.59 12 31 72.7932 65 Total 2285.33 33 32

236

Table A6.112 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and leaf K concentration. Rank 75 E qn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit S td Err F- value 0.0573854279 0 2 3.299817467 1.887248848

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 91.88858202 8.013611325 11.46656336 75.54471397 108.2324501 0.00000 b -2.4749e-13 1.80155e-13 -1.37377176 -6.1492e-13 1.19937e-13 0.17937

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1024.5525 1 1024.5525 1.88725 0.17937 Error 16829.326 31 542.88149 Total 17853.879 32

Table A6.113 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and petiole K concentration. Rank 927 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0800874978 0.0187599977 23.017529301 2.6988571494

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 96.81742846 9.650809769 10.03205231 77.13447217 116.5003847 0.00000 b -7.3134e-14 4.45175e-14 -1.64281988 -1.6393e-13 1.76598e-14 0.11053

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1429.8725 1 1429.8725 2.69886 0.11053 Error 16424.006 31 529.80666 Total 17853.879 32

Table A6.114 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 2098 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0039465181 0 23.951172193 0.1228267998

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 85.3955644 9.525592285 8.964856131 65.96799086 104.8231379 0.00000 b -4.2125e-14 1.20198e-13 -0.35046655 -2.8727e-13 2.03021e-13 0.72836

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 70.460656 1 70.460656 0.122827 0.72836 Error 17783.418 31 573.65865 Total 17853.879 32

237

Table A6.115 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf K concentration. Rank 2075 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.027072205 0 6.032031765 0.8625905848

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20.32846185 2.074623895 9.798625139 16.09723852 24.55968518 0.00000 b -4.3317e-14 4.66399e-14 -0.92875755 -1.3844e-13 5.18055e-14 0.36019

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 31.38571 1 31.38571 0.862591 0.36019 Error 1127.9476 31 36.385407 Total 1159.3333 32

Table A6.116 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and petiole K concentration. Rank 1977 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0303878742 0 6.021744624 0.97154736

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20.93066445 2.52480234 8.290021012 15.78129613 26.08003277 0.00000 b -1.148e-14 1.16465e-14 -0.98567102 -3.5233e-14 1.22735e-14 0.33193

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r2 Attainable 0.0303878742 0 6.021744624 0.6641748131

Source Sum of Squares DF Mean Square F Statistic P>F Regr 35.229676 1 35.229676 0.971547 0.33193 Error 1124.1037 31 36.261408 Total 1159.3333 32

Table A6.117 ANOVA for the relationship between the number of stolons of lotus petioles (Nelumbo nucifera) and roots and stolon K concentration. Rank 2160 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0020158884 0 6.1092110432 0.062618774

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8.52158111 40.55578392 0.210119995 -74.1924855 91.23564771 0.83495 b 0.960904181 3.839969745 0.250237435 -6.87076574 8.792574106 0.80405

Soln Vector Covar Matrix Direct LUDecomp

Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.3370867 1 2.3370867 0.0626188 0.80405 Error 1156.9962 31 37.32246 Total 1159.3333 32 238

Table A6.118 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and leaf K concentration. Rank 1 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2508156446 0.1705458922 574.22196855 4.854381728

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2487.601903 166.9244131 14.90256492 2146.203146 2829.000661 0.00000 b 29148.23412 1506.91362 19.34300263 26066.24972 32230.21852 0.00000 c 16907.35651 3504.194481 4.824891026 9740.474084 24074.23893 0.00004

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 3201279 2 1600639.5 4.85438 0.01519 Error 9562195.2 29 329730.87 Total 12763474 31

Table A6.119 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and petiole K concentration. Rank 1712 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0536564806 0 655.85426209 1.7576607917

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2391.05658 274.9871473 8.695157586 1830.216595 2951.896564 0.00000 b -1.6817e-12 1.26847e-12 -1.325768 -4.2688e-12 9.05363e-13 0.19460

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 756048.67 1 756048.67 1.75766 0.19460 Error 13334489 31 430144.81 Total 14090538 32

Table A6.120 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 2130 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0030402665 0 673.16534154 0.0945356751

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 685.8646706 4468.784585 0.153479018 -8428.28158 9800.010916 0.87902 b 130.0955038 423.120846 0.307466543 -732.865151 993.0561583 0.76054

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 42838.99 1 42838.99 0.0945357 0.76054 Error 14047699 31 453151.58 Total 14090538 32

239

Table A6.121 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and leaf K concentration. Rank 2154 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0045883941 0 6.6353383624 0.142895879

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.332244641 47.98780021 0.152793931 -90.5395191 105.2040084 0.87955 b 1.752105077 4.63500595 0.378015713 -7.70105188 11.20526203 0.70800

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.2913791 1 6.2913791 0.142896 0.70800 Error 1364.8592 31 44.027715 Total 1371.1505 32

Table A6.122 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and petiole K concentration. Rank 1007 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0111016064 0 6.613594445 0.3480133063

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 23.97894569 2.77295365 8.647438337 18.32346944 29.63442195 0.00000 b 7.54584e-15 1.27912e-14 0.589926526 -1.8542e-14 3.36336e-14 0.55952

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 15.221974 1 15.221974 0.348013 0.55952 Error 1355.9286 31 43.739631 Total 1371.1505 32

Table A6.123 ANOVA for the relationship between internode length of lotus petioles (Nelumbo nucifera) and roots and stolon K concentration. Rank 742 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.013170172 0 6.6066737059 0.4137241509

Parm Value Std Error t-value 95% Confidence Limits P>|t| a -2.73335497 43.85817241 -0.06232259 -92.1826873 86.71597737 0.95071 b 2.671043551 4.152651949 0.643213923 -5.79834593 11.14043304 0.52482

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 18.058289 1 18.058289 0.413724 0.52482 Error 1353.0923 31 43.648137 Total 1371.1505 32

240

Table A6.124 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and total leaf area). (Figure 6.11). Rank 1 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8459002337 0.8348931075 1.8872994995 159.18977274

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.133345197 0.636939163 11.19941371 5.83065834 8.436032053 0.00000 b 0.010714927 0.000849242 12.61704295 0.008978031 0.012451823 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 567.01796 1 567.01796 159.19 0.00000 Error 103.29508 29 3.5618994 Total 670.31304 30

Table A6.125 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolons N concentration. Rank 2868 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0005332783 0 5.2381829469 0.0165404488

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.97255134 4.505044664 3.323507859 5.784452179 24.16065051 0.00229 b -0.48813827 3.795501923 -0.12860968 -8.22911548 7.252838932 0.89850

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.45384611 1 0.45384611 0.0165404 0.89850 Error 850.59538 31 27.438561 Total 851.04922 32

Table A6.126 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolons N concentration. Rank 2773 Eqn 1 y=a+bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0023779393 0 3.5952423442 0.0738918288

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.1068237 5.625546954 2.507635936 2.633445049 25.58020235 0.01760 b -0.51679586 1.901169402 -0.27183051 -4.39425642 3.360664701 0.78755

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.9551086 1 0.9551086 0.0738918 0.78755 Error 400.69879 31 12.925768 Total 401.6539 32

241

Table A6.127 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and petiole P concentration. Rank 2021 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0571813201 0 3.4950970322 1.8801291919

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 16.04499609 2.594183545 6.184988766 10.75412386 21.33586831 0.00000 b -5.8146e-08 4.24059e-08 -1.37117803 -1.4463e-07 2.83414e-08 0.18016

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 22.9671 1 22.9671 1.88013 0.18016 Error 378.6868 31 12.215703 Total 401.6539 32

Table A6.128 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon P concentration. Rank 26 Eqn 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0418483786 0 5.1287745945 1.3539608013

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18.85744937 3.929098797 4.79943375 10.84399955 26.8708992 0.00004 b -4.5091e-09 3.87512e-09 -1.16359821 -1.2412e-08 3.39428e-09 0.25347

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 35.61503 1 35.61503 1.35396 0.25347 Error 815.43419 31 26.304329 Total 851.04922 32

Table A6.129 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolon P concentration. Rank 795 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0305605509 0 3.5440961221 0.977242137

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.4246893 1.958549543 7.364985664 10.43020118 18.41917743 0.00000 b -1.6376e-12 1.65655e-12 -0.98855558 -5.0162e-12 1.74097e-12 0.33053

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 12.274765 1 12.274765 0.977242 0.33053 Error 389.37914 31 12.560617 Total 401.6539 32

242

Table A6.130 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 2099 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0001230365 0 5.2392578707 0.0038146016

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.52213679 2.10225803 6.907875523 10.23455327 18.80972031 0.00000 b -7.2465e-15 1.17329e-13 -0.06176246 -2.4654e-13 2.32047e-13 0.95115

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.10471014 1 0.10471014 0.0038146 0.95115 Error 850.94451 31 27.449823 Total 851.04922 32

Table A6.131 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 2105 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0025094714 0 3.5950053279 0.0779893248

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 12.95007719 1.442499874 8.977523963 10.0080793 15.89207508 0.00000 b -2.2483e-14 8.05072e-14 -0.27926569 -1.8668e-13 1.41713e-13 0.78190

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.007939 1 1.007939 0.0779893 0.78190 Error 400.64596 31 12.924063 Total 401.6539 32

Table A6.132 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole P concentration. (Figure 6.12. Rank 36 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2661801303 0.2137644253 3.9033749176 10.519235166

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 26.93193835 3.968293102 6.786781533 18.81586767 35.04800902 0.00000 b -1.8627e-05 5.74301e-06 -3.24333704 -3.0372e-05 -6.8807e-06 0.00297

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 160.2746 1 160.2746 10.5192 0.00297 Error 441.85374 29 15.236336 Total 602.12834 30

243

Table A6.133 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 6.13a). Rank 6 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5534025022 0.521502681 2.8688078795 35.935428758

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 21.81738779 1.461209571 14.93104633 18.82887867 24.80589692 0.00000 b -4.97e-08 8.29075e-09 -5.99461665 -6.6656e-08 -3.2743e-08 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 295.75069 1 295.75069 35.9354 0.00000 Error 238.6717 29 8.2300586 Total 534.42239 30

Table A6.134 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 6.13b). Rank 1 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4181571538 0.378030061 2.6572568731 21.560314262

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 17.47034931 1.114835161 15.67079146 15.19355217 19.74714646 0.00000 b -2.4615e-10 5.30107e-11 -4.64330855 -3.5441e-10 -1.3788e-10 0.00006

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 152.23768 1 152.23768 21.5603 0.00006 Error 211.83042 30 7.0610141 Total 364.06811 31

Table A6.135 ANOVA for the relationship between combined K concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and K Supply. (Tables A6.58-60 & 151) Rank 9 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3235677004 0.3094753608 11381.646425 46.399420844

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 17498.83869 3871.068684 4.52041545 9815.838913 25181.83846 0.00002 b 253.4788915 37.21221481 6.811712035 179.6229459 327.334837 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.010668e+09 1 6.010668e+09 46.3994 0.00000 Error 1.2565562e+10 97 1.2954188e+08 Total 1.857623e+10 98

244

Table A6.136 ANOVA for the relationship between combined K concentration in leaves and petioles of lotus (Nelumbo nucifera) and K supply. (Tables 6.58-59 & 152). Rank 3 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2777976975 0.2548706403 13267.683888 24.6178288

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 17957.59756 5526.708162 3.249239336 6916.728769 28998.46634 0.00185 b 263.6003897 53.12771952 4.961635698 157.465569 369.7352105 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.3335117e+09 1 4.3335117e+09 24.6178 0.00001 Error 1.1266012e+10 64 1.7603144e+08 Total 1.5599524e+10 65

Table A6.137 ANOVA for the relationship between combined K concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and K supply. (Tables A6.59-60 & 153). Rank 1 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5599098786 0.5459387636 6012.3733007 81.424759348

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3852.113217 3635.919533 1.059460525 -3411.47105 11115.69749 0.29337 b 1008.605271 111.7745658 9.023566886 785.3099061 1231.900636 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.9433937e+09 1 2.9433937e+09 81.4248 0.00000 Error 2.3135125e+09 64 36148633 Total 5.2569062e+09 65

Table A6.138 ANOVA for the relationship between combined K concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and K supply. (Tables A6.59-60 & 154). Rank 19 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.43935987 0.4215617707 9974.7819167 50.155224675

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 19828.87916 4155.036335 4.772251687 11528.23986 28129.51846 0.00001 b 282.8704349 39.9419688 7.082035348 203.0771794 362.6636905 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.990258e+09 1 4.990258e+09 50.1552 0.00000 Error 6.3677616e+09 64 99496274 Total 1.135802e+10 65

245

Table A6.139 ANOVA for the relationship between combined N concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables 61-63 & 155). Rank 1 Eqn 8106 y=ab/(b+x) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2797266828 0.2647209887 0.4348816088 37.671100107

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.337113471 0.23710156 18.29221817 3.866532507 4.807694435 0.00000 b 121285.508 26246.49171 4.621017898 69193.4873 173377.5286 0.00001

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 7.1244343 1 7.1244343 37.6711 0.00000 Error 18.344835 97 0.18912201 Total 25.46927 98

Table A6.140 ANOVA for the relationship between combined leaf and petiole N concentration as a function of K concentration. (Figure 6.7a, Tables 61-62 & 156). Rank 1 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4689026563 0.4520424232 0.3836197184 56.505215778

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.083780295 0.105403211 38.74436324 3.873213174 4.294347415 0.00000 b -7.3003e-08 9.71174e-09 -7.51699513 -9.2405e-08 -5.3602e-08 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 8.3155386 1 8.3155386 56.5052 0.00000 Error 9.4185017 64 0.14716409 Total 17.73404 65

Table A6.141 ANOVA for the relationship between combined N concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Figure 6.7a, Tables 61, 63 & 157). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2643173867 0.2409623831 0.4536810981 22.994036347

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.793951816 0.106968549 35.46791883 3.580257573 4.007646058 0.00000 b -7.982e-15 1.66459e-15 -4.79520973 -1.1307e-14 -4.6567e-15 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4.7327829 1 4.7327829 22.994 0.00001 Error 13.172898 64 0.20582654 Total 17.905681 65

246

Table A6.142 ANOVA for the relationship between combined N concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.62-63 & 158). Rank 2116 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0040868897 0 0.7155602288 0.3036709075

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.837926711 0.482310162 5.884028438 1.876902734 3.798950688 0.00000 b -5.6499e-05 0.000102528 -0.55106343 -0.00026079 0.000147792 0.58325

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.15548753 1 0.15548753 0.303671 0.58325 Error 37.889957 74 0.51202644 Total 38.045444 75

Table A6.143 ANOVA for the relationship between combined P concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.64-66 & 159). Rank 31 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0824102933 0.063293841 2012.4445572 8.7117350906

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4297.892049 1233.001538 3.485715076 1850.725308 6745.05879 0.00074 b 17.61381315 5.967618541 2.951564855 5.769742264 29.45788404 0.00396

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 35281944 1 35281944 8.71174 0.00396 Error 3.9284351e+08 97 4049933.1 Total 4.2812545e+08 98

Table A6.144 ANOVA for the relationship between combined P concentration in leaves and petioles of lotus (Nelumbo nucifera) and K concentration. (Figure 6.7b, Tables A6.64-65 & 160). Rank 1 Eqn 5 y=a+bx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6299628168 0.6180261334 761.38838285 107.25316065

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5179.964534 171.1721341 30.26172783 4837.904319 5522.024749 0.00000 b 6.18585e-08 5.97302e-09 10.35631018 4.99224e-08 7.37946e-08 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 62175973 1 62175973 107.253 0.00000 Error 36521873 63 579712.27 Total 98697846 64

247

Table A6.145 ANOVA for the relationship between combined P concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.64, 66 & 161). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3670621554 0.3469688905 1984.2039191 37.115773928

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5572.098714 467.833937 11.91042007 4637.492984 6506.704443 0.00000 b 4.43528e-11 7.28018e-12 6.092271656 2.9809e-11 5.88967e-11 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.4612722e+08 1 1.4612722e+08 37.1158 0.00000 Error 2.5197217e+08 64 3937065.2 Total 3.9809939e+08 65

Table A6.146 ANOVA for the relationship between combined P concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.65-66 &162). Rank 9 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1207876362 0.0928761326 1581.9824332 8.7924249396

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 9797.010959 342.3399664 28.61778325 9113.108256 10480.91366 0.00000 b -6.2195e-12 2.0975e-12 -2.96520234 -1.041e-11 -2.0293e-12 0.00425

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 22004524 1 22004524 8.79242 0.00425 Error 1.6017078e+08 64 2502668.4 Total 1.821753e+08 65

Table A6.147 ANOVA for the relationship between combined Ca concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.67-69 & 163). Rank 21 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0954340085 0.0765888836 5804.5698075 10.233746245

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20484.04691 1124.128751 18.22215373 18252.96251 22715.13131 0.00000 b -1.5293e-06 4.78045e-07 -3.1990227 -2.4781e-06 -5.8049e-07 0.00186

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3.4480593e+08 1 3.4480593e+08 10.2337 0.00186 Error 3.268224e+09 97 33693031 Total 3.6130299e+09 98

248

Table A6.148 ANOVA for the relationship between combined Ca concentration in leaves and petioles of lotus (Nelumbo nucifera) and K concentration. (Tables A6.67-68 & 164). Rank 1 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3602174179 0.3399068598 4774.8265802 36.033983096

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24437.60507 968.5145437 25.2320476 22502.77484 26372.43529 0.00000 b -9.1872e-09 1.53047e-09 -6.00283126 -1.2245e-08 -6.1297e-09 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 8.2153766e+08 1 8.2153766e+08 36.034 0.00000 Error 1.459134e+09 64 22798969 Total 2.2806717e+09 65

Table A6.149 ANOVA for the relationship between combined Ca concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.67, 69 & 165). Rank 1 Eqn 8040 [LDR Peak_] y=4ax^(-c-1)*b^(c+1)*c^2/(c-1+x^-c*b^c*(c+1))^2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3565760208 0.3254426024 5660.2269357 17.456832536

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24452.24338 1301.860151 18.78254232 21850.68346 27053.80331 0.00000 b 29498.03317 959.8748774 30.73112326 27579.87629 31416.19006 0.00000 c 3.534676059 0.357854451 9.8774126 2.819561002 4.249791116 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.1185699e+09 2 5.5928495e+08 17.4568 0.00000 Error 2.0184046e+09 63 32038169 Total 3.1369745e+09 65

Table A6.150 ANOVA for the relationship between combined Ca concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and K concentration. (Tables A6.68-69 & 166). Rank 29 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2465220559 0.2226021211 2388.998075 20.939447132

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4630.153764 2030.291302 2.280536669 574.1806216 8686.126906 0.02592 b 42.43144549 9.272678911 4.575964066 23.90713985 60.95575113 0.00002

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.1950795e+08 1 1.1950795e+08 20.9394 0.00002 Error 3.6526796e+08 64 5707311.8 Total 4.8477591e+08 65

249

Table A6.151 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves, petioles and roots and stolons as a function of K supply (Tables A6.58-60 & 135). ANOVA SS df ms F Single line RSS 1.26 x 1010 97 Total Individual 1.83 x 109 91 20109890.11 lines RSS Difference 1.077 x 1010 6 1795000000 89.26 F dist. 7.06 P value 0.0000

Table A6.152 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and petioles as a function of K supply (Tables A6.58-59 & 136). ANOVA SS df ms F Single line RSS 1.13 x 1010 64 Total Individual 1.41 x 109 62 22741935.48 lines RSS Difference 9.89 x 109 2 4945000000 217.44 F dist. 99.48 P value 0.0046

Table A6.153 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and roots and stolons as a function of K supply (Tables A6.58, 60 & 137). ANOVA SS df ms F Single line RSS 2.31 x 109 64 Total Individual 9.99 x 108 60 16650000 lines RSS Difference 1.31 x 109 4 327500000 19.67 F dist. 13.65 P value 0.005

Table A6.154 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in petioles and roots and stolons as a function of K supply (Tables A6.59-60 & 138). ANOVA SS df ms F Single line RSS 6.37 x 109 64 Total Individual 1.26 x 109 60 21000000 lines RSS Difference 5.11 x 109 4 1277500000 60.83 F dist. 13.65 P value 0.0005

Table A6.155 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves, petioles and roots and stolons as a function of K concentration (Tables A6.61-63 & 139). ANOVA SS df ms F Single line RSS 18.34 97 Total Individual 9.73 93 0.105 lines RSS Difference 8.61 4 2.15 20.5 F dist. 13.56 P value 0.0045

250

Table A6.156 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and petioles as a function of K concentration (Tables A6.61-62 & 140). ANOVA SS df ms F Single line RSS 9.42 64 Total Individual 6.86 62 0.11 lines RSS Difference 2.56 2 1.28 11.64 F dist. 99.48 P value 0.0822

Table A6.157 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and roots and stolons as a function of K concentration (Tables A6.61, 63 & 141). ANOVA SS df ms F Single line RSS 13.17 64 Total Individual 5.77 62 0.093 lines RSS Difference 7.4 2 3.7 39.78 F dist. 99.48 P value 0.0248

Table A6.158 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in petioles and roots and stolons as a function of K concentration (Tables A6.62-63 & 142). ANOVA SS df ms F Single line RSS 37.89 74 Total Individual 6.83 62 0.11 lines RSS Difference 31.06 12 2.59 23.53 F dist. 3.54 P value 0.0000

Table A6.159 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, petioles and roots and stolons as a function of K concentration (Tables A6.64-66 & 143). ANOVA SS df ms F Single line RSS 3.93 x 108 97 Total Individual 54787729 90 608752.54 lines RSS Difference 338212271 7 48316038.71 79.37 F dist. 5.82 P value 0.0000

Table A6.160 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for P concentration in leaves, and petioles as a function of K concentration (Tables A6.64-65 & 144). ANOVA SS df ms F Single line RSS 365 21873 63 Total Individual 24910392 59 422210.03 lines RSS Difference 11611481 4 2902870.25 6.88 F dist. 13.75 P value 0.0356

251

Table A6.161 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for P concentration in leaves and roots and stolons as a function of K concentration (Tables A6.64, 66 & 145). ANOVA SS df ms F Single line RSS 2.52 x 108 64 Total Individual 46309259 62 746923.53 lines RSS Difference 205690741 2 102845370.5 137.69 F dist. 99.48 P value 0.0072

Table A6.162 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for P concentration in petioles and roots and stolons as a function of K concentration (Tables A6.65-66 & 146). ANOVA SS df ms F Single line RSS 1.60 x 108 64 Total Individual 38355807 59 650098.42 lines RSS Difference 121644193 5 24328838.6 37.42 F dist. 9.29 P value 0.0004

Table A6.163 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for Ca concentration in leaves, petioles and roots and stolons as a function of K concentration (Tables A6.67-69 & 147). ANOVA SS df ms F Single line RSS 3.27 x 109 97 Total Individual 758323104 87 8716357.52 lines RSS Difference 2511676896 10 251167689.6 28.82 F dist. 4.08 P value 0.0000

Table A6.164 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and petioles as a function of K concentration (Tables A6.67-68 & 148). ANOVA SS df ms F Single line RSS 1.46 x 109 64 Total Individual 7.21 x 108 61 11819672.13 lines RSS Difference 7.39 x 108 3 739000000 62.52 F dist. 26.32 P value 0.0028

Table A6.165 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for Ca concentration in leaves and roots and stolons as a function of K concentration (Tables A6.67, 69 & 149). ANOVA SS df ms F Single line RSS 2.02 x 109 63 Total Individual 592323104 57 10391633.3 lines RSS Difference 1427676896 6 237946149.3 22.89 F dist. 7.14 P value 252

Table A6.166 ANOVA of the comparison of regression equations between a single fitted line and the sum of indi vidual fitted lines for Ca concentration in petioles and roots and stolons as a function of K concentration (Tables A6.68-69 & 150). ANOVA SS df ms F Single line RSS 3.65 x 108 64 Total Individual 203323104 56 3630769.71 lines RSS Difference 161676896 8 20209612 5.57 F dist. 5.12 P value 0.0072

253

Appendix 7 Calcium ANOVA Tables and Miscellaneous Graphs

Table A7.1 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 20 days of calcium treatments. (Table 7.1).

Univariate Tests of Significance for Nolfd20 (Spreadsheet19) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 2.178828 1 2.178828 119.0142 0.000000 Treatment 0.949297 7 0.135614 7.4076 0.000089 Error 0.439375 24 0.018307

Table A7.2 ANOVA for the percentage number of leaves of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of calcium treatments. (Table 7.1).

Univariate Tests of Significance for Nolfd40 (Spreadsheet19) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 4.277813 1 4.277813 268.4118 0.000000 Treatment 0.434688 7 0.062098 3.8964 0.005691 Error 0.382500 24 0.015938

Table A7.3 ANOVA for the percentage of total leaf area of lotus (Nelumbo nucifera) estimated to be displaying marginal necrosis after 40 days of calcium treatments. (Table 7.1).

Univariate Tests of Significance for TaffLAd40 (Spreadsheet19) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 152.9110 1 152.9110 132.4122 0.000000 Treatment 45.7660 7 6.5380 5.6615 0.000600 Error 27.7154 24 1.1548

Table A7.4 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 20 days of calcium treatments. (Table 7.1).

Univariate Tests of Significance for NecRTd20 (Spreadsheet26) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 0.675703 1 0.675703 140.2541 0.000000 Treatment 0.336172 7 0.048025 9.9683 0.000008 Error 0.115625 24 0.004818

254

Table A7.5 ANOVA for the percentage of roots of lotus (Nelumbo nucifera) estimated to be displaying blackening symptoms after 40 days of calcium treatments. (Table 7.1).

Univariate Tests of Significance for NecRtd40 (Spreadsheet26) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 7.900313 1 7.900313 1547.816 0.000000 Treatment 0.387187 7 0.055312 10.837 0.000004 Error 0.122500 24 0.005104

Table A7.6 ANOVA of Total Dry Mass of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.1a).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of DW tot DW tot DW tot DW tot Intercept 1 21610.53 21610.53 358.2019 0.000000 Ca conc (ppm) 7 1440.72 205.82 3.4115 0.008422 Error 30 1809.92 60.33 Total 37 3250.63

Tukey HSD test; variable DW tot (Ca_general) Homogenous Groups, alpha = .01000 Error: Between MS = 60.331, df = 30.000 Ca conc (ppm) DW tot 1 1 50 14.85800 **** 8 350 16.92800 **** 6 230 20.28600 **** 7 250 22.57600 **** 3 150 27.37000 **** 4 175 28.66333 **** 5 200 30.02800 **** 2 100 32.83200 ****

255

Table A7.7 ANOVA of Leaf Dry Mass of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.1b).

Univariate Tests of Significance for DW Leaf (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 2314.736 1 2314.736 433.8895 0.000000 Ca conc (ppm) 159.205 7 22.744 4.2632 0.002252 Error 160.046 30 5.335

Tukey HSD test; variable DW Leaf (Ca_general) Homogenous Groups, alpha = .01000 Error: Between MS = 5.3349, df = 30.000 Ca conc (ppm) DW Leaf 1 2 1 50 4.24400 **** 8 350 6.31600 **** **** 6 230 6.47400 **** **** 7 250 7.50800 **** **** 3 150 8.76200 **** **** 4 175 9.52000 **** **** 5 200 9.83200 **** **** 2 100 10.68600 ****

Table A7.8 ANOVA of Petiole Dry Mass of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.1b).

Univariate Tests of Significance for DW Pet (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1645.665 1 1645.665 349.5735 0.000000 Ca conc (ppm) 109.367 7 15.624 3.3188 0.009772 Error 141.229 30 4.708

Tukey HSD test; variable DW Pet (Ca_general) Homogenous Groups, alpha = .01000 Error: Between MS = 4.7076, df = 30.000 Ca conc (ppm) DW Pet 1 1 50 4.308000 **** 8 350 4.612000 **** 6 230 5.640000 **** 7 250 5.894000 **** 3 150 7.544000 **** 5 200 7.986000 **** 4 175 8.196667 **** 2 100 9.228000 ****

256

Table A7.9 ANOVA of Roots and Stolon Dry Mass of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.1b).

Univariate Tests of Significance for DW Root (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 3402.004 1 3402.004 277.2809 0.000000 Ca conc (ppm) 235.221 7 33.603 2.7388 0.025302 Error 368.075 30 12.269

Table A7.10 ANOVA of the number of leaves of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.2a).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of lf no. lf no. lf no. lf no. Intercept 1 22678.66 22678.66 395.9570 0.000000 Ca conc (ppm) 7 869.10 124.16 2.1677 0.066368 Error 30 1718.27 57.28 Total 37 2587.37

Table A7.11 ANOVA of the number of nodes of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.2b).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of node no. node no. node no. node no. Intercept 1 207092.7 207092.7 507.0224 0.000000 Ca conc (ppm) 7 7628.3 1089.8 2.6681 0.028480 Error 30 12253.5 408.4 Total 37 19881.8

Table A7.12 ANOVA of the number of stolons of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.2c).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st.no. st.no. st.no. st.no. Intercept 1 15580.06 15580.06 416.6288 0.000000 Ca conc (ppm) 7 687.21 98.17 2.6253 0.030598 Error 30 1121.87 37.40 Total 37 1809.08

257

Table A7.13 ANOVA of total leaf area of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.3a).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of L.A). (cm2) L.A). (cm2) L.A). (cm2) L.A). (cm2) Intercept 1 13289.07 13289.07 455.8707 0.000000 Ca conc (ppm) 7 787.06 112.44 3.8571 0.004179 Error 30 874.53 29.15 Total 37 1661.59

Tukey HSD test; variable L.A). (cm2) (Ca_general) Homogenous Groups, alpha = .01000 Error: Between MS = 29.151, df = 30.000 Ca conc (ppm) L.A). (cm2) 1 2 1 50 11.30750 **** 8 350 14.60250 **** **** 6 230 16.08500 **** **** 7 250 17.92000 **** **** 3 150 21.63250 **** **** 4 175 21.64583 **** **** 5 200 23.19750 **** **** 2 100 25.38000 ****

Table A7.14 ANOVA of total stolon length of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.3b).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of st lgth st lgth st lgth st lgth Intercept 1 231901385 231901385 459.9901 0.000000 Ca conc (ppm) 7 10786613 1540945 3.0566 0.014961 Error 30 15124330 504144 Total 37 25910943

Table A7.15 ANOVA of internode length of lotus (Nelumbo nucifera) as a function of Ca supply. (Figure 7.3c).

Univariate Results for Each DV (Ca_general) Sigma-restricted parameterization Effective hypothesis decomposition Internode internoder internode internode Degr. of length length length length Intercept 1 42423.60 42423.60 716.9190 0.000000 Ca conc (ppm) 7 953.70 136.24 2.3024 0.052789 Error 30 1775.25 59.17 Total 37 2728.94

258

Table A7.16 ANOVA of Ca concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure 7.4a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 1.136685E+10 1.136685E+10 1857.701 0.000000 Ca (ppm) 7 1.438054E+09 2.054363E+08 33.575 0.000000 Error 31 1.896820E+08 6.118774E+06 Total 38 1.627736E+09

Tukey HSD test; variable Ca (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 6119E3, df = 31.000 Ca (ppm) Ca (mg kg-1) 1 2 3 4 1 50 5380.00 **** 2 100 10460.00 **** **** 4 175 15650.00 **** **** 3 150 17280.00 **** 5 200 20980.00 **** **** 6 230 21120.00 **** **** 7 250 21880.00 **** **** 8 350 24200.00 ****

259

Table A7.17 ANOVA of Ca concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure 7.4a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 3.447837E+09 3.447837E+09 2662.256 0.000000 Ca (ppm) 7 1.776294E+08 2.537563E+07 19.594 0.000000 Error 31 4.014750E+07 1.295081E+06 Total 38 2.177769E+08

Tukey HSD test; variable Ca (mg kg-1) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 1295E3, df = 31.000 Ca (ppm) Ca (mg kg-1) 1 2 3 4 1 50 5840.00 **** 2 100 7220.00 **** **** 4 175 8425.00 **** **** **** 3 150 8740.00 **** **** 5 200 10540.00 **** **** 7 250 10780.00 **** **** 6 230 11300.00 **** **** 8 350 12580.00 ****

Table A7.18 ANOVA of Ca concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure 7.4a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Ca (mg kg-1) Intercept 1 3.001174E+09 3.001174E+09 1672.294 0.000000 Ca (ppm) 7 8.884497E+07 1.269214E+07 7.072 0.000046 Error 31 5.563400E+07 1.794645E+06 Total 38 1.444790E+08

Tukey HSD test; variable Ca (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1795E3, df = 31.000 Ca (ppm) Ca (mg kg-1) 1 2 3 1 50 6280.00 **** 2 100 7060.00 **** **** 4 175 8450.00 **** **** **** 5 200 8580.00 **** **** **** 3 150 8780.00 **** **** **** 7 250 10060.00 **** **** 8 350 10180.00 **** **** 6 230 10980.00 ****

260

Table A7.19 ANOVA of N concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure 7.4b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 632.8630 632.8630 10493.75 0.000000 Ca (ppm) 7 2.8869 0.4124 6.84 0.000061 Error 31 1.8696 0.0603 Total 38 4.7565

Tukey HSD test; variable N (%) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = .06031, df = 31.000 Ca (ppm) N (%) 1 2 7 250 3.734407 **** 5 200 3.790634 **** 8 350 3.915945 **** 4 175 3.962585 **** 2 100 4.041120 **** 6 230 4.060761 **** **** 3 150 4.144222 **** **** 1 50 4.664781 ****

Table A7.20 ANOVA of N concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure 7.4b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 187.2420 187.2420 1753.269 0.000000 Ca (ppm) 7 11.2427 1.6061 15.039 0.000000 Error 31 3.3107 0.1068 Total 38 14.5534

Tukey HSD test; variable N (%) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = .10680, df = 31.000 Ca (ppm) N (%) 1 2 5 200 1.756031 **** 4 175 1.847774 **** 7 250 1.875840 **** 8 350 1.951897 **** 3 150 2.144991 **** 2 100 2.184493 **** 6 230 2.283407 **** 1 50 3.532521 ****

261

Table A7.21 ANOVA of N concentration in lotus roots and stolons (Nelumbo nucifera) as a function of roots and stolon Ca concentration. (Figure 7.4b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of N (%) N (%) N (%) N (%) Intercept 1 188.0516 188.0516 3505.455 0.000000 Ca (ppm) 7 6.6603 0.9515 17.736 0.000000 Error 31 1.6630 0.0536 Total 38 8.3233

Tukey HSD test; variable N (%) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = .05365, df = 31.000 Ca (ppm) N (%) 1 2 5 200 1.785017 **** 7 250 1.951812 **** 4 175 1.977777 **** 8 350 1.980061 **** 3 150 2.215043 **** 6 230 2.244142 **** 2 100 2.258447 **** 1 50 3.202614 ****

Table A7.22 ANOVA of P concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 1.425900E+09 1.425900E+09 2471.161 0.000000 Ca (ppm) 7 1.490686E+07 2.129551E+06 3.691 0.005162 Error 31 1.788750E+07 5.770161E+05 Total 38 3.279436E+07

Tukey HSD test; variable P (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 5770E2, df = 31.000 Ca (ppm) P (mg kg-1) 1 2 7 250 5440.000 **** 5 200 5500.000 **** 8 350 5540.000 **** **** 6 230 5800.000 **** **** 2 100 6220.000 **** **** 4 175 6225.000 **** **** 3 150 6380.000 **** **** 1 50 7400.000 ****

262

Table A7.23 ANOVA of P concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 2.175641E+09 2.175641E+09 983.1684 0.000000 Ca (ppm) 7 5.443794E+07 7.776848E+06 3.5143 0.006843 Error 31 6.859950E+07 2.212887E+06 Total 38 1.230374E+08

Tukey HSD test; variable P (mg kg-1) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 2213E3, df = 31.000 Ca (ppm) P (mg kg-1) 1 2 7 250 6100.00 **** 5 200 6520.00 **** 8 350 7000.00 **** **** 6 230 7340.00 **** **** 2 100 7380.00 **** **** 3 150 7540.00 **** **** 4 175 7775.00 **** **** 1 50 10260.00 ****

Table A7.24 ANOVA of P concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of P (mg kg-1) P (mg kg-1) P (mg kg-1) P (mg kg-1) Intercept 1 2.762182E+09 2.762182E+09 1937.715 0.000000 Ca (ppm) 7 5.868897E+07 8.384139E+06 5.882 0.000210 Error 31 4.419000E+07 1.425484E+06 Total 38 1.028790E+08

Tukey HSD test; variable P (mg kg-1) (Ca_root) Homogenous Groups, alpha = .05000 Error: Between MS = 1425E3, df = 31.000 Ca (ppm) P (mg kg-1) 1 2 5 200 7000.00 **** 7 250 7120.00 **** 8 350 7320.00 **** 2 100 8460.00 **** **** 6 230 8740.00 **** **** 4 175 8850.00 **** **** 3 150 9140.00 **** **** 1 50 10880.00 ****

263

Table A7.25 ANOVA of K concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 2.748346E+10 2.748346E+10 5534.181 0.000000 Ca (ppm) 7 6.102436E+07 8.717766E+06 1.755 0.132483 Error 31 1.539500E+08 4.966129E+06 Total 38 2.149744E+08

Table A7.26 ANOVA of K concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 1.301452E+11 1.301452E+11 5114.732 0.000000 Ca (ppm) 7 2.121744E+08 3.031062E+07 1.191 0.336571 Error 31 7.888000E+08 2.544516E+07 Total 38 1.000974E+09

Table A7.27 ANOVA of K concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure 7.5b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of K (mg kg-1) K (mg kg-1) K (mg kg-1) K (mg kg-1) Intercept 1 6.576022E+10 6.576022E+10 5637.629 0.000000 Ca (ppm) 7 3.467590E+08 4.953700E+07 4.247 0.002172 Error 31 3.616000E+08 1.166452E+07 Total 38 7.083590E+08

Tukey HSD test; variable K (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1166E4, df = 31.000 Ca (ppm) K (mg kg-1) 1 2 1 50 36400.00 **** 5 200 38000.00 **** **** 4 175 40000.00 **** **** 7 250 40400.00 **** **** 2 100 41600.00 **** **** 8 350 43000.00 **** **** 3 150 44000.00 **** **** 6 230 46000.00 ****

264

Table A7.28 ANOVA of Mg concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 1.577600E+09 1.577600E+09 2358.033 0.000000 Ca (ppm) 7 1.956769E+07 2.795385E+06 4.178 0.002411 Error 31 2.074000E+07 6.690323E+05 Total 38 4.030769E+07

Tukey HSD test; variable Mg (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 6690E2, df = 31.000 Ca (ppm) Mg (mg kg-1) 1 2 8 350 4960.000 **** 4 175 5800.000 **** **** 5 200 6240.000 **** **** 7 250 6240.000 **** **** 3 150 6600.000 **** **** 6 230 6880.000 **** **** 2 100 6920.000 **** **** 1 50 7380.000 ****

Table A7.29 ANOVA of Mg concentration in lotus petiole (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 756704379 756704379 1250.451 0.000000 Ca (ppm) 7 10372808 1481830 2.449 0.040327 Error 31 18759500 605145 Total 38 29132308

265

Table A7.30 ANOVA of Mg concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Mg (mg kg-1) Intercept 1 676501879 676501879 4209.466 0.000000 Ca (ppm) 7 8141590 1163084 7.237 0.000037 Error 31 4982000 160710 Total 38 13123590

Tukey HSD test; variable Mg (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1607E2, df = 31.000 Ca (ppm) Mg (mg kg-1) 1 2 1 50 3540.000 **** 4 175 3750.000 **** 2 100 3980.000 **** 5 200 4120.000 **** 8 350 4140.000 **** 7 250 4340.000 **** **** 3 150 4380.000 **** **** 6 230 5160.000 ****

Table A7.31 ANOVA of S concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 639954561 639954561 2254.513 0.000000 Ca (ppm) 7 9949731 1421390 5.007 0.000705 Error 31 8799500 283855 Total 38 18749231

Tukey HSD test; variable S (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 2839E2, df = 31.000 Ca (ppm) S (mg kg-1) 1 2 5 200 3440.000 **** 4 175 3475.000 **** 3 150 3780.000 **** **** 7 250 3800.000 **** **** 2 100 4020.000 **** **** 6 230 4420.000 **** **** 1 50 4680.000 **** **** 8 350 4880.000 ****

266

Table A7.32 ANOVA of S concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 695874682 695874682 1847.640 0.000000 Ca (ppm) 7 12941936 1848848 4.909 0.000812 Error 31 11675500 376629 Total 38 24617436

Tukey HSD test; variable S (mg kg-1) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 3766E2, df = 31.000 Ca (ppm) S (mg kg-1) 1 2 5 200 3460.000 **** 4 175 3725.000 **** **** 2 100 3860.000 **** **** 3 150 3920.000 **** **** 7 250 4140.000 **** **** 1 50 4780.000 **** **** 6 230 4820.000 **** **** 8 350 5180.000 ****

Table A7.33 ANOVA of S concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.1b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of S (mg kg-1) S (mg kg-1) S (mg kg-1) S (mg kg-1) Intercept 1 1.317227E+09 1.317227E+09 2649.496 0.000000 Ca (ppm) 7 1.850544E+07 2.643634E+06 5.317 0.000454 Error 31 1.541200E+07 4.971613E+05 Total 38 3.391744E+07

Tukey HSD test; variable S (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 4972E2, df = 31.000 Ca (ppm) S (mg kg-1) 1 2 3 5 200 4720.000 **** 4 175 5000.000 **** **** 2 100 5700.000 **** **** **** 3 150 5760.000 **** **** **** 7 250 5800.000 **** **** **** 1 50 6100.000 **** **** **** 8 350 6600.000 **** **** 6 230 6940.000 ****

267

8000 A 7000 )

-1 6000

5000

4000

3000

Organ Mg Conc. (mg kg (mg Conc. Mg Organ 2000

1000

7000 B

6000 ) -1 5000

4000

3000

Organ S Conc. (mg kg (mg S Conc. Organ 2000 Leaf 1000 Petiole Roots & Stolons

0 0 50 100 150 200 250 300 350

Ca Supply (mg kg-1)

Figure A7.1 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Magnesium; b) Sulphur. Values are means and bars represent S.E. (n=5). (Tables A7.28-33).

268

Table A7.34 ANOVA of Fe concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Intercept 1 1564617 1564617 1362.464 0.000000 Ca (ppm) 7 147542 21077 18.354 0.000000 Error 31 35600 1148 Total 38 183142

Tukey HSD test; variable Fe (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 1148.4, df = 31.000 Ca (ppm) Fe (mg kg-1) 1 2 3 8 350 134.6439 **** 7 250 143.2796 **** 6 230 159.6212 **** 5 200 171.7567 **** 4 175 187.4301 **** 3 150 214.0097 **** **** 2 100 292.0000 **** **** 1 50 304.0000 ****

Table A7.35 ANOVA of Fe concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Intercept 1 1988678 1988678 610.0109 0.000000 Ca (ppm) 7 30070 4296 1.3177 0.275140 Error 31 101062 3260 Total 38 131133

Table A7.36 ANOVA of Fe concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Fe (mg kg-1) Intercept 1 19843202 19843202 703.4987 0.000000 Ca (ppm) 7 481790 68827 2.4401 0.040924 Error 31 874400 28206 Total 38 1356190

269

Table A7.37 ANOVA of Mn concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 59582.23 59582.23 1101.671 0.000000 Ca (ppm) 7 1581.54 225.93 4.178 0.002414 Error 31 1676.59 54.08 Total 38 3258.13

Tukey HSD test; variable Mn (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 54.083, df = 31.000 Ca (ppm) Mn (mg kg-1) 1 6 230 29.86727 **** 7 250 31.66447 **** 8 350 35.29853 **** 5 200 36.51538 **** 3 150 42.34811 **** 4 175 43.81617 **** 2 100 46.33702 **** 1 50 47.69838 ****

Table A7.38 ANOVA of Mn concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 16616.19 16616.19 1210.657 0.000000 Ca (ppm) 7 771.49 110.21 8.030 0.000015 Error 31 425.47 13.72 Total 38 1196.97

Tukey HSD test; variable Mn (mg kg-1) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 13.725, df = 31.000 Ca (ppm) Mn (mg kg-1) 1 2 7 250 16.03124 **** 6 230 16.89470 **** 8 350 18.22259 **** 3 150 19.11878 **** 5 200 19.17100 **** 4 175 21.48759 **** **** 2 100 24.26771 **** **** 1 50 30.38630 ****

270

Table A7.39 ANOVA of Mn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.2b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Mn (mg kg-1) Intercept 1 11973.78 11973.78 1429.714 0.000000 Ca (ppm) 7 1481.34 211.62 25.268 0.000000 Error 31 259.62 8.37 Total 38 1740.97

Tukey HSD test; variable Mn (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 8.3749, df = 31.000 Ca (ppm) Mn (mg kg-1) 1 2 3 7 250 12.14504 **** 6 230 13.38014 **** 8 350 13.88873 **** **** 5 200 14.96271 **** **** 3 150 16.17182 **** **** 4 175 16.89148 **** **** 2 100 20.85870 **** 1 50 32.26004 ****

271

1000 A

) 800 -1

600

400 Organ Fe Conc. (mg kg (mg Organ Fe Conc.

200

50 B Leaf Petiole 45 Roots & Stolons )

-1 40

Organ Mn Conc. (mg kg (mg Mn Conc. Organ 20

10 0 100 200 300 400 Ca Supply (ppm)

Figure A7.2 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Iron; b) Manganese. Values are means and bars represent S.E. (n=5). (Tables A7.34- 39).

272

Table A7.40 ANOVA of Zn concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.3a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 69798.04 69798.04 2926.977 0.000000 Ca (ppm) 7 632.82 90.40 3.791 0.004403 Error 31 739.24 23.85 Total 38 1372.06

Tukey HSD test; variable Zn (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 23.846, df = 31.000 Ca (ppm) Zn (mg kg-1) 1 2 4 175 38.09245 **** 8 350 39.96366 **** 5 200 40.02441 **** **** 3 150 41.23690 **** **** 7 250 41.39564 **** **** 2 100 42.10456 **** **** 1 50 44.47381 **** **** 6 230 52.07086 ****

Table A7.41 ANOVA of Zn concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.3a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 56086.15 56086.15 973.8288 0.000000 Ca (ppm) 7 1716.88 245.27 4.2586 0.002133 Error 31 1785.40 57.59 Total 38 3502.28

Tukey HSD test; variable Zn (mg kg-1) (Ca_petiole) Homogenous Groups, alpha = .01000 Error: Between MS = 57.593, df = 31.000 Ca (ppm) Zn (mg kg-1) 1 2 5 200 31.05174 **** 7 250 33.02610 **** **** 3 150 34.16031 **** **** 4 175 35.06378 **** **** 2 100 35.38913 **** **** 8 350 37.64224 **** **** 1 50 47.79337 **** **** 6 230 50.08074 ****

273

Table A7.42 ANOVA of Zn concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.3a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Zn (mg kg-1) Intercept 1 258202.4 258202.4 1032.648 0.000000 Ca (ppm) 7 13649.5 1949.9 7.798 0.000019 Error 31 7751.2 250.0 Total 38 21400.7

Tukey HSD test; variable Zn (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 250.04, df = 31.000 Ca (ppm) Zn (mg kg-1) 1 2 3 5 200 56.9430 **** 7 250 61.7634 **** 8 350 68.0775 **** **** 3 150 77.2624 **** **** **** 2 100 82.6974 **** **** **** 4 175 88.9915 **** **** **** 6 230 104.2367 **** **** 1 50 112.7408 ****

Table A7.43 ANOVA of Cu concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.3b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Cu (mg kg-1) Intercept 1 13123.35 13123.35 4724.948 0.000000 Ca (ppm) 7 451.67 64.52 23.231 0.000000 Error 31 86.10 2.78 Total 38 537.77

Tukey HSD test; variable Cu (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 2.7775, df = 31.000 Ca (ppm) Cu (mg kg-1) 1 2 3 4 2 100 14.19543 **** 1 50 15.58905 **** **** 3 150 16.42243 **** **** **** 4 175 17.86075 **** **** **** 5 200 18.26206 **** **** **** 7 250 18.97029 **** **** 8 350 19.81904 **** 6 230 26.03234 ****

274

120 A

100 ) -1

60 Conc. (mg kg Conc. (mg

40 Organ Zn Organ

0 B 100 Leaf Petiole Roots & Stolons )

-1 80

. (mg kg . (mg 60

40 Organ Cu Conc Organ

0 0 50 100 150 200 250 300 350 400 Ca Supply (ppm )

Figure A7.3 Effect of calcium su pp ly on organ nu tr ient concent rat ion in lotus (Nelumbo nucifera) for: a) Zinc; b) C oppe r. Values ar e m eans a nd bars re present S.E . ( n=5). (Tables A7.40-45).

275

Table A7.44 ANOVA of Cu con centration in lotus pe tiol es (Nelumbo nucifera) as a function of Ca suppl y. (Figure A7.3 b).

Univariate Resul ts for Each D V (Ca _pe tio le) Sigma-restricted pa rameteriza tion Effectiv e hypo the sis decomposition Degr. of Cu (mg kg-1) Cu (mg kg -1) Cu (m g kg-1) Cu (mg kg-1) Intercept 1 12289.71 12289.71 247.70 47 0.000000 Ca (ppm) 7 471.92 67.42 1.3588 0.257365 Error 31 1538.05 49.61 Total 38 2009.97

Table A7.45 ANOVA of Cu concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.3b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Cu (mg kg-1) Cu (mg kg-1) Cu (mg k g-1) Cu (m g kg-1) Intercept 1 78846.01 78846.01 135.2635 0.0000 00 Ca (ppm) 7 5993.08 856.15 1.4688 0.214778 Error 31 18070.11 582.91 Total 38 24063.19

Table A7.46 ANOVA of B concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of B (mg kg-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 86888.05 86888.05 1414.076 0.000000 Ca (ppm) 7 2809.31 401.33 6.532 0.000090 Error 31 1904.80 61.45 Total 38 4714.11

Tukey HSD test; variable B (mg kg-1) (Ca_leaf) Homogenous Groups, alpha = .01000 Error: Between MS = 61.445, df = 31.000 Ca (ppm) B (mg kg-1) 1 2 2 100 38.09446 **** 3 15 0 42.14731 *** * 5 200 42.92203 **** 7 250 43.26641 **** 4 175 44.75039 *** * 8 350 47.06996 *** * **** 6 230 53.96761 **** **** 1 50 66.41791 ****

276

Table A7.4 7 ANOVA of B concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4a) .

Univariate Results for Each DV (Ca _petiole) Sigma-restricte d par ameterizat ion Effective hypo th esis decom positi on Degr. of B (mg kg-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 26556.65 26556.65 3515.568 0.000000 Ca (ppm) 7 91.88 13.13 1.738 0.136590 Error 31 234.17 7.55 Total 38 326.05

Table A7.48 ANOVA of B concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4a).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of B (mg kg-1) B (mg kg-1) B (mg kg-1) B (mg kg-1) Intercept 1 21505.75 21505.75 6037.589 0.000000 Ca (ppm) 7 41.62 5.95 1.669 0.153409 Error 31 110.42 3.56 Total 38 152.04

Table A7.49 ANOVA of Mo concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 11579.82 11579.82 10.42743 0.002934 Ca (ppm) 7 19643.82 2806.26 2.52699 0.035283 Error 31 34425.97 1110.52 Total 38 54069.79

Table A7.50 ANOVA of Mo concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Intercept 1 21717.47 21717.47 14.91936 0.000534 Ca (ppm) 7 22711.93 3244.56 2.22893 0.058781 Error 31 45125.38 1455.66 Total 38 67837.31

277

70 A

60 ) -1 50

Organ B Conc. (mg kg (mg Conc. Organ B 20

0 B Leaf 8 Petiole Roots & Stolons ) -1 6

4 Organ Mo Conc. (mg kg (mg Conc. Mo Organ 2

0 0 50 100 150 200 250 300 350 400 Ca Supply (ppm)

Figure A7.4 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Boron; b) Molybdenum. Values are means and bars represent S.E. (n=5). (Tables A7.46-51).

278

Table A7.51 ANOVA of Mo concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.4b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameteri zation Effectiv e hypothesis d ecomposition Degr. of Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg-1) Mo (mg kg -1) Intercept 1 1185.879 1185.879 1580.493 0.000000 C)a (ppm 7 50.983 7.283 9.707 0.000002 Error 31 23.260 0.750 Total 38 74.243

Tukey HSD test; vari abl e Mo (mg kg-1) (Ca_ root) Hom oge nous Grou ps, alpha = .01000 Error: Betw een MS = .75032, df = 3 1.000 Ca (ppm) Mo (m g kg-1) 1 2 2 100 4.433258 **** 5 200 4.487770 **** 4 175 4.540593 **** 3 150 5.122765 **** 7 250 5.437608 **** 8 350 5.810839 **** 1 50 6.397113 **** **** 6 230 8.004659 ****

Table A7.52 ANOVA of Na concentration in lotus leaf (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5a).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameteriza tion Effective h ypothesis d ec omposition Degr. of Na (mg kg-1) Na (mg kg -1) Na (mg kg-1) Na (mg kg -1) Intercept 1 192715287 192715287 326.2722 0.000000 C)a (ppm 7 9302492 1328927 2.2499 0.056701 Error 31 18310400 590658 Total 38 27612892

279

Table A7.53 ANOVA of Na concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5a).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted parameteriza tion Effective hypothesis d ecomposition Degr. of Na (mg kg-1) Na (mg kg -1) Na (mg kg -1) Na (mg kg -1) Intercept 1 571392136 571392136 2628.260 0.000000 C)a (ppm 7 7576397 1082342 4.979 0.000735 Error 31 6739500 217403 Total 38 14315897

Tukey H S D test; vari able Na (mg kg-1) (Ca_pet iole) Homoge nous Grou ps, alpha = .01000 Error: Betw een MS = 2174E2, df = 31.000 Ca (ppm) Na ( mg kg-1) 1 2 1 50 3080.000 **** 8 350 3580.000 **** **** 4 175 3625.000 **** **** 6 230 3760.000 **** **** 5 200 3840.000 **** **** 7 250 3940.000 **** **** 3 150 4220.000 **** **** 2 100 4660.000 ****

Table A7.54 ANOVA of Na concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5a).

Univariate Result s for Each D V (Ca_root) Sigma-restricted p arameteriza ti on Effective hypothesis d ec omposition Degr. of Na (mg kg-1) Na (mg kg-1) Na (mg kg -1) Na (mg kg -1) Intercept 1 689522970 689522970 1325.841 0.000000 C)a (ppm 7 5261077 751582 1.445 0.223339 Error 31 16122000 520065 Total 38 21383077

280

Table A7.55 ANOVA of Al concentration in lotus leaves (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5b).

Univariate Results for Each DV (Ca_leaf) Sigma-restricted parameteriza tion Effective h ypothesis d ec omposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg -1) Intercept 1 91495.09 91495.09 842.5186 0.000000 C)a (ppm 7 3170.37 452.91 4.1705 0.002440 Error 31 3366.51 108.60 Total 38 6536.88

Tukey HSD test; vari abl e Al (mg kg-1) (Ca_ leaf) H omoge nous Grou ps, alpha = .01000 Error: Between MS = 108.60, df = 31.000 Ca (ppm) Al (m g kg-1) 1 2 8 350 41.67245 **** 7 250 42.05279 **** 5 200 43.65229 **** 3 150 44.83667 **** **** 4 175 45.49086 **** **** 6 230 46.12892 * *** **** 2 100 54.86082 **** **** 1 50 69.84978 ****

Table A7.56 ANOVA of Al concentration in lotus petioles (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5b).

Univariate Results for Each DV (Ca_petiole) Sigma-restricted pa rameterizat ion Effective h ypothesis decom position Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg- 1) Intercept 1 111779.6 111779 .6 2 92.7513 0.000000 Ca (ppm) 7 2755.1 3 93.6 1 .0308 0.430008 Error 31 11836.6 381.8 Total 38 14591.6

281

5000 A

4000 ) -1

3000

2000 Organ Na Conc. (mg kg (mg Conc. Na Organ 1000

0 250 B Leaf Petiole Roots & Stolons

) 200 -1

150

100 Organ kgAl Conc. (mg

0 0 50 100 150 200 250 300 350 400 Ca Supply (ppm)

Figure A7.5 Effect of calcium supply on organ nutrient concentration in lotus (Nelumbo nucifera) for: a) Sodium; b) Aluminium. Values are means and bars represent S.E. (n=5). (Tables 52-57).

282

Table A7.57 ANOVA of Al concentration in lotus roots and stolons (Nelumbo nucifera) as a function of Ca supply. (Figure A7.5b).

Univariate Results for Each DV (Ca_root) Sigma-restricted parameterization Effective hypothesis decomposition Degr. of Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Al (mg kg-1) Intercept 1 1061654 1061654 666.9965 0.000000 Ca (ppm) 7 49393 7056 4.4331 0.001638 Error 31 49342 1592 Total 38 98736

Tukey HSD test; variable Al (mg kg-1) (Ca_root) Homogenous Groups, alpha = .01000 Error: Between MS = 1591.7, df = 31.000 Ca (ppm) Al (mg kg-1) 1 2 5 200 119.1984 **** 6 230 129.7697 **** 7 250 151.6994 **** **** 2 100 155.3849 **** **** 4 175 171.6796 **** **** 8 350 173.5006 **** **** 3 150 180.2961 **** **** 1 50 242.0000 ****

Table A7.58 ANOVA for the relationship between Ca concentration in lotus leaves (Nelumbo nucifera) and Ca supply. (Figure 7.6, Tables A7.141-144 & 157-160). Rank 1 Eqn 8116 y=a0.5bx-0.25b2x2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8772288464 0.870213352 2330.4592773 257.22849021

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24385.97353 1044.400546 23.34925391 22267.83105 26504.11601 0.00000 b 0.872486917 0.053947208 16.17297639 0.763076908 0.981896925 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.3970183e+09 1 1.3970183e+09 257.228 0.00000 Error 1.9551746e+08 36 5431040.4 Total 1.5925358e+09 37

283

Table A7.59 ANOVA for the relationship between Ca concentration in lotus petioles (Nelumbo nucifera) and Ca supply. (Figure 7.6, Tables A7.141-142, 144, 157-158 & 160). Rank 2 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8384455515 0.8289423486 983.435823 181.64522593

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1027.867488 649.6501641 1.582186143 -290.992461 2346.727436 0.12260 b 644.6753737 47.83316155 13.47758235 547.5688933 741.7818542 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.7567746e+08 1 1.7567746e+08 181.645 0.00000 Error 33850111 35 967146.02 Total 2.0952757e+08 36

Table A7.60 ANOVA for the relationship between Ca concentration in lotus roots and stolons (Nelumbo nucifera) and Ca supply. (Figure 7.6, Table A7.141, 143-144 & 157, 159-160). Rank 4 Eqn 76 y0.5=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.521566715 0.4942276701 1296.1806317 39.24560085

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 27.52656127 21.77381097 1.264205026 -16.6327741 71.68589666 0.21428 b 12.9853468 4.182017332 3.105043755 4.50382254 21.46687106 0.00370

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 65935915 1 65935915 39.2456 0.00000 Error 60483032 36 1680084.2 Total 1.2641895e+08 37

Table A7.61 ANOVA for the relationship between N concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.7, Tables A7.145-147 & 161-163). Rank 16 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5778223459 0.5522358215 0.2033820648 46.534816737

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8.283815831 0.614900916 13.4717897 7.034186821 9.533444841 0.00000 b -0.43492175 0.063756155 -6.82164326 -0.56448984 -0.30535365 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.9248785 1 1.9248785 46.5348 0.00000 Error 1.406385 34 0.041364264 Total 3.3312634 35

284

Table A7.62 ANOVA for the relationship between N concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Tables A7.145-146, 148 & 161-162 & 164). Rank 2596 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0795131391 0.0283749802 0.4550468286 3.1961196538

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.918235409 1.517955213 3.240039869 1.842565999 7.993904819 0.00253 b -0.03300775 0.01846309 -1.78776946 -0.07041752 0.004402025 0.08201

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.66181288 1 0.66181288 3.19612 0.08201 Error 7.6615018 37 0.20706762 Total 8.3233147 38

Table A7.63 ANOVA for the relationship between N concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Tables A7.145, 147-148, 161 & 163- 164). Rank 2596 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0795131391 0.0283749802 0.4550468286 3.1961196538

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.918235409 1.517955213 3.240039869 1.842565999 7.993904819 0.00253 b -0.03300775 0.01846309 -1.78776946 -0.07041752 0.004402025 0.08201

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.66181288 1 0.66181288 3.19612 0.08201 Error 7.6615018 37 0.20706762 Total 8.3233147 38

Table A7.64 ANOVA for the relationship between P concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Tables A7.149-152 & 165-167). Rank 1 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3674490965 0.3302402198 623.5081123 20.331515307

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7143.030784 285.1456095 25.05046736 6564.154422 7721.907147 0.00000 b -0.00706503 0.001566857 -4.50904816 -0.01024592 -0.00388415 0.00007

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 7904128 1 7904128 20.3315 0.00007 Error 13606683 35 388762.37 Total 21510811 36

285

Table A7.65 ANOVA for the relationship between P concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Tables A7.149-150, 152, 165-166 & 168). Rank 2650 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0240319335 0 1647.3286622 0.9110764699

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18898.83523 10972.88754 1.722321054 -3334.3468 41132.01725 0.09336 b -1155.77029 1210.860495 -0.95450326 -3609.2067 1297.66612 0.34602

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2472380.7 1 2472380.7 0.911076 0.34602 Error 1.0040659e+08 37 2713691.7 Total 1.0287897e+08 38

Table A7.66 ANOVA for the relationship between P concentration in lotus roots and stolons (Nelumbo nucifera) and Ca supply. (Tables A7.149, 151-152,165 & 177-168). Rank 2688 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0052875974 0 1663.0726346 0.1966810746

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8786.343072 850.3258819 10.33291266 7063.419179 10509.26696 0.00000 b -0.0004259 0.000960349 -0.4434874 -0.00237175 0.001519949 0.66000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 543982.6 1 543982.6 0.196681 0.66000 Error 1.0233499e+08 37 2765810.6 Total 1.0287897e+08 38

Table A7.67 ANOVA for the relationship between K concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.8b, Table A7.153-155 & 169-172). Rank 40 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0981197376 0.0480152786 2289.1113069 4.0254016438

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 30000.52758 1714.093946 17.50226564 26527.44334 33473.61181 0.00000 b -26.2558462 13.08643672 -2.00634036 -52.7714856 0.25979327 0.05217

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 21093228 1 21093228 4.0254 0.05217 Error 1.9388113e+08 37 5240030.6 Total 2.1497436e+08 38

286

Table A7.68 ANOVA for the relationship between K concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure 7.8b, Tables A7.153-154, 156, 169-170 & 172). Rank 42 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0250006347 0 5135.8553189 0.9487426517

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 56765.66555 1488.691707 38.13124323 53749.28964 59782.04147 0.00000 b 1.20612e-09 1.23827e-09 0.974034215 -1.3029e-09 3.71509e-09 0.33636

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 25024994 1 25024994 0.948743 0.33636 Error 9.7594936e+08 37 26377010 Total 1.0009744e+09 38

Table A7.69 ANOVA for the relationship between K concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 7.8b, Tables A7.153, 155-156, 169 & 171-172). Rank 18 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3568382163 0.3178587142 3107.7219849 18.863837468

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 25142.37524 3776.322926 6.657898631 17467.96371 32816.78677 0.00000 b 19.22011462 4.425281992 4.343251946 10.2268596 28.21336965 0.00012

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.8218573e+08 1 1.8218573e+08 18.8638 0.00012 Error 3.2836982e+08 34 9657935.9 Total 5.1055556e+08 35

Table A7.70 ANOVA for the relationship between Mg concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. Rank 1 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0428432134 0 825.41108644 1.5666320175

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8010.379815 1315.21581 6.090544041 5340.349773 10680.40986 0.00000 b -17.5423661 14.01537337 -1.25165172 -45.9950867 10.91035446 0.21900

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1067351.8 1 1067351.8 1.56663 0.21900 Error 23845621 35 681303.46 Total 24912973 36

287

Table A7.71 ANOVA for the relationship between Mg concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure A7.6). Rank 1 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4338266807 0.4014739196 643.12091323 27.584769494

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2867.862558 308.8688914 9.285048243 2241.447412 3494.277703 0.00000 b 0.001606641 0.000305903 5.252120476 0.00098624 0.002227042 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 11409185 1 11409185 27.5848 0.00001 Error 14889762 36 413604.51 Total 26298947 37

Table A7.72 ANOVA for the relationship between Mg concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.6). Rank 22 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5822407029 0.5590318531 384.9359942 51.567747644

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 124.5755902 569.0860511 0.218904663 -1028.50228 1277.653457 0.82793 b 43.55110517 6.064710839 7.181068698 31.26283378 55.83937656 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 7641088.1 1 7641088.1 51.5677 0.00000 Error 5482501.6 37 148175.72 Total 13123590 38

288

6000 A

5000 ) -1

4000

3000

2000 Organ Mg Conc. (mg kg (mg Organ Mg Conc.

1000 Roots & Stolons Petiole

7000 B ) -1 6000

5000

4000

3000

2000 Roots & Stolons S conc. (mg kg (mg S conc. Stolons & Roots 1000

0 0 2000 4000 6000 8000 10000 12000 14000

Organ Ca Conc. (mg kg-1)

Figure A7.6 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ calcium concentration a) Magnesium, regression equations are y = 2 867.86 + 0.0016x1.5 (r2 = 0.40) & y = 124.58 + 43.55x0.5 (r2 = 0.56) for petioles and roots and stolons respectively; b) Sulphur, regression equation is y = (5 229.77 + 7.89*10-10x3)0.5 (r2 = 0.16) for roots and stolons. (Tables A7.71-72 & 75).

289

Table A7.73 ANOVA for the relationship between S concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. Rank 2633 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0188111824 0 705.12670068 0.7093576055

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5842.65057 2099.519969 2.782850679 1588.619034 10096.6821 0.00843 b -183.101638 217.4000373 -0.8422337 -623.595955 257.3926791 0.40507

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 352695.2 1 352695.2 0.709358 0.40507 Error 18396536 37 497203.66 Total 18749231 38

Table A7.74 ANOVA for the relationship between S concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1571359114 0.1103101287 748.85773686 6.8979433327

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3773.504966 217.065753 17.38415624 3333.687973 4213.321958 0.00000 b 4.742e-10 1.80552e-10 2.626393598 1.08367e-10 8.40032e-10 0.01248

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3868283.2 1 3868283.2 6.89794 0.01248 Error 20749153 37 560787.91 Total 24617436 38

Table A7.75 ANOVA for the relationship between S concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.6b). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.202175047 0.1578514385 855.1936196 9.3760877157

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 5229.765447 244.1561287 21.41975905 4735.058139 5724.472755 0.00000 b 7.89486e-10 2.5783e-10 3.062039797 2.67073e-10 1.3119e-09 0.00408

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6857259.2 1 6857259.2 9.37609 0.00408 Error 27060177 37 731356.13 Total 33917436 38

290

Table A7.76 ANOVA for the relationship between Fe concentration in lotus leaves (Nelumbo nucifera) as a function of leaf Ca concentration. (Figure A7.7a). Rank 6 Eqn 74 y0.5=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.7167856006 0.6985137039 33.62847193 80.988605334

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 18.94154661 1.088772266 17.39716119 16.72379008 21.15930314 0.00000 b -0.00285173 0.000622752 -4.57923488 -0.00412023 -0.00158322 0.00007

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 91587.918 1 91587.918 80.9886 0.00000 Error 36187.972 32 1130.8741 Total 127775.89 33

Table A7.77 ANOVA for the relationship between Fe concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure A7.7a). Rank 2442 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0051430058 0 59.379243345 0.1912749414

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 220.9807717 17.21181412 12.83890066 186.1063237 255.8552197 0.00000 b 6.26132e-12 1.43165e-11 0.437349907 -2.2747e-11 3.52693e-11 0.66440

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r2 Attainable 0.0051430058 0 59.379243345 0.7891430385 Source Sum of Squares DF Mean Square F Statistic P>F Regr 674.41527 1 674.41527 0.191275 0.66440 Error 130458.1 37 3525.8945 Total 131132.51 38

Table A7.78 ANOVA for the relationship between Fe concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.7a). Rank 4 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2695244185 0.2277829567 145.44450125 13.282961554

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 574.4566202 42.34998275 13.56450659 488.5668743 660.3463661 0.00000 b 1.61184e-10 4.42258e-11 3.64457975 7.14903e-11 2.50878e-10 0.00084

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 280989.14 1 280989.14 13.283 0.00084 Error 761547.71 36 21154.103 Total 1042536.8 37 Pure Err 130416.67 8 16302.083

291

1200 A

) 1000 -1

800

600

400 Organ Fe Conc. (mg kg (mg Conc. Fe Organ

200

0 60 B 50 ) -1 40

20 Organ Mn Conc. (mg kg (mg Conc. Mn Organ

10 Leaf Petiole Roots & Stolons 0 0 5000 10000 15000 20000 25000 30000

Organ CaConc. (mg kg-1)

Figure A7.7 Nutrient concentration in organs of lotus (Nelumbo nucifera) in relation to organ calcium concentration: a) Iron, regression equations are y = (18.94 – 0.0029x/lnx)0.5 (r2 = 0.70) & y = 574.46 + 1.61*10-10x3 (r2=0.23) for leaves and roots ant stolons respectively; b) Manganese, regression equations are y = 49.78 – 6.08*10-5xlnx (r2=0.19), y = 43.95 – 0.24x0.5 (r2=0.26), & y = (9.18 – 0.052x0.5)0.5 (r2=0.30) for leaves (___), petioles (….) & roots and stolons (----) respectively. (Tables A7.76, 78 & 79-81).

292

Table A7.79 ANOVA for the relationship between Mn concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure A7.7b). Rank 4 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2305139432 0.1865433114 7.8717399803 10.784473458

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 49.78336181 3.362881498 14.80378117 42.96312202 56.6036016 0.00000 b -6.0778e-05 1.85075e-05 -3.28397221 -9.8313e-05 -2.3243e-05 0.00228

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 668.25224 1 668.25224 10.7845 0.00228 Error 2230.7145 36 61.96429 Total 2898.9667 37

Table A7.80 ANOVA for the relationship between Mn concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure A7.7b). Rank 33 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2942368702 0.2550278075 4.7782559862 15.425521311

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 43.94672051 5.97390928 7.356442566 31.84243056 56.05101046 0.00000 b -0.24130942 0.061440446 -3.92753374 -0.36579959 -0.11681926 0.00036

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 352.19134 1 352.19134 15.4255 0.00036 Error 844.77402 37 22.83173 Total 1196.9654 38

Table A7.81 ANOVA for the relationship between Mn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.7b). Rank 90 Eqn 75 y0.5=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3385743107 0.301828439 5.578722762 18.939768587

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 9.1829233 1.828586379 5.021870122 5.477855363 12.88799124 0.00001 b -0.05245596 0.019945 -2.63003056 -0.09286837 -0.01204355 0.01237

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r2 Attainable 0.3385743107 0.301828439 5.578722762 0.9302942018 Source Sum of Squares DF Mean Square F Statistic P>F Regr 589.44627 1 589.44627 18.9398 0.00010 Error 1151.5195 37 31.122148 Total 1740.9657 38

293

Table A7.82 ANOVA for the relationship between Zn concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. Rank 2455 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0007893727 0 6.0871516235 0.029229865

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 42.31396305 1.601700801 26.41814441 39.06860896 45.55931714 0.00000 b 3.08826e-14 1.80635e-13 0.170967438 -3.3512e-13 3.96883e-13 0.86518

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.0830663 1 1.0830663 0.0292299 0.86518 Error 1370.9764 37 37.053415 Total 1372.0594 38

Table A7.83 ANOVA for the relationship between Zn concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. Rank 2436 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.011607812 0 9.6725089246 0.434533023

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 36.56131511 2.803697325 13.04039305 30.88048472 42.2421455 0.00000 b 1.53728e-12 2.33207e-12 0.659191189 -3.1879e-12 6.2625e-12 0.51386

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 40.653792 1 40.653792 0.434533 0.51386 Error 3461.6249 37 93.557429 Total 3502.2787 38

Table A7.84 ANOVA for the relationship between Zn concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 2654 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0120780093 0 21.799494138 0.4401241567

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 127.9831458 72.806002 1.757865317 -19.6742701 275.6405616 0.08727 b -0.58773297 0.885915803 -0.66341854 -2.38445349 1.208987558 0.51129

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 209.1549 1 209.1549 0.440124 0.51129 Error 17107.846 36 475.21794 Total 17317.001 37

294

Table A7.85 ANOVA for the relationship between Cu concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure A7.8). Rank 1 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4651668954 0.4317398264 2.0171878351 28.701491022

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 14.02209452 0.732482646 19.14324469 12.53184737 15.51234166 0.00000 b 1.51077e-06 2.81997e-07 5.357377252 9.37038e-07 2.08449e-06 0.00001

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 116.78771 1 116.78771 28.7015 0.00001 Error 134.27854 33 4.0690468 Total 251.06625 34

Table A7.86 ANOVA for the relationship between Cu concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure A7.8). Rank 3 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1915654918 0.1440105208 3.4627557506 8.2935502456

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.161639591 4.347684799 0.957208212 -4.66462978 12.98790897 0.34503 b 0.129011303 0.044797886 2.879852469 0.038066759 0.219955847 0.00675

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 99.445285 1 99.445285 8.29355 0.00675 Error 419.67371 35 11.990677 Total 519.11899 36

Table A7.87 ANOVA for the relationship between Cu concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 164 Eqn 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.095297971 0.0436007122 13.765260192 3.7921070634

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 8.416197044 16.90397231 0.497882799 -25.8666478 42.69904187 0.62159 b 0.038650812 0.019848072 1.947333321 -0.00160294 0.078904568 0.05933

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 718.5375 1 718.5375 3.79211 0.05933 Error 6821.366 36 189.48239 Total 7539.9035 37

295

50 )

-1 40

20 Organ Cu Conc. (mg kg (mg Conc. Cu Organ

10 Leaf Petiole

0 0 5000 10000 15000 20000 25000 30000

Organ Ca Conc. (mg kg-1)

Figure A7.8 Copper concentration in organs of lotus (Nelumbo nucifera) in relation to organ Ca concentration, regression equations are y = 14.02 + 1.5*10-6x1.5 (r2 = 0.433) & y = 4.16 + 0.13x0.5 (r2 = 0.14) for leaves (____) and petioles (…..) respectively. (Tables A7.85-86).

Table A7.88 ANOVA for the relationship between B concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. Rank 2488 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1237422274 0.07506124 10.566104074 5.2250177461

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 84.76340157 16.43489081 5.157527514 51.46314968 118.0636535 0.00001 b -0.40066026 0.175280008 -2.28582977 -0.75581129 -0.04550923 0.02809

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 583.33433 1 583.33433 5.22502 0.02809 Error 4130.7745 37 111.64256 Total 4714.1089 38

296

Table A7.89 ANOVA for the relationship between B concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. Rank 1600 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1321370826 0.0810863228 2.3405050969 5.3289497685

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24.5098626 0.68927962 35.55866429 23.11055058 25.90917462 0.00000 b 1.32193e-12 5.72649e-13 2.308451812 1.59393e-13 2.48447e-12 0.02700

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 29.191796 1 29.191796 5.32895 0.02700 Error 191.72874 35 5.4779641 Total 220.92054 36

Table A7.90 ANOVA for the relationship between B concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.9a). Rank 1 Eqn 70 y0.5=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5458253778 0.517439464 1.0566479932 39.65927771

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.712104844 0.063857374 73.79108369 4.582186039 4.842023648 0.00000 b 2.04784e-13 6.4345e-14 3.182598408 7.38734e-14 3.35695e-13 0.00318

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 44.279781 1 44.279781 39.6593 0.00000 Error 36.844664 33 1.116505 Total 81.124446 34

Table A7.91 ANOVA for the relationship between Mo concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure A7.9b). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.5420025785 0.509288477 0.3372711237 34.319133772

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1.100812298 0.133878543 8.22246997 0.826999934 1.374624662 0.00000 b 1.86299e-09 3.18011e-10 5.858253475 1.21258e-09 2.51339e-09 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3.9038636 1 3.9038636 34.3191 0.00000 Error 3.2988025 29 0.11375181 Total 7.2026661 30

297

) 25 -1

10 oots & Stolons B Conc. (mg kg (mg B Conc. oots & Stolons

R 5

0 9 Leaf B Petiole 8 Roots & Stolons )

-1 7

Organ Mo Conc. (mg kg Conc. (mg Mo Organ 3

0 5000 10000 15000 20000 25000 30000

Organ Ca Conc. (mg kg-1)

Figure A7.9 Nutrient concent ratio n in organs of lotus (Nelumbo nucifera) as a function of organ calcium concentrati on: a) Boro n, regres sion equations is y = (4.71 + 2.05*1 0-13x3)0.5 (r2 = 0.52) for roots and stolons; b) Mol ybdenum, reg res sion equation s are y = 1.10 + 1.86*10-9x2 (r2 = 0.51 ), y = 0.15 + 0 .0016x0.5lnx (r2 = 0.39), & y=3.78+ 2.00*10-8x2 (r2 = 0.16) for leave s (___), petioles (….) and roots an d stolons (----) re spectively. (Ta b les A7.90-93).

298

Table A7.92 ANOVA for the rela tio nship bet ween Mo concentration in lotus petioles (Nelumbo nucifera) and petio le Ca concentratio n . (Figure A7.9b). Rank 1 Eq n 9 y=a+bx0.5lnx r2 Coef Det DF Adj r2 Fit S td Err F- value 0.4306396631 0.3850908 362 0 .2462065137 19.665281398

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 0.152538423 0.327287652 0.466068372 -0.52021098 0.825287826 0.64505 b 0.00158383 0.000357156 4.434555378 0.000849684 0.002317975 0.00015

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.1920631 1 1.1920631 19.6653 0.00015 Error 1.5760588 26 0.060617647 Total 2.7681219 27

Table A7.93 ANOVA for the relationship between Mo concentration in lotus roots and stolons (Nelumbo nucifera) and ro ots and stolo n C a concentrat ion. (Figure A7.9b). Rank 4 Eqn 4 y=a+bx2

r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3162479144 0.2760272035 1.088755 9344 16.188143681

Parm V alue Std Erro r t-v alue 95% Confidence Limits P>|t| a 3.7 82372148 0.44 52119 19 8 .49 5666861 2.8785 43902 4.6862003 95 0.00000 b 2.0 0463e-08 4.98 237e- 09 4. 02 3449227 9. 93157e-09 3.01611e-08 0.00029

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 19.189255 1 19.189255 16.1881 0.00029 Error 41.488632 35 1.1853895 Total 60.677887 36

Table A7.94 AN OVA for the rela ti onship between N a concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. Rank 51 Eqn 13 y=a+bln x

r2 Coef Det DF A dj r2 Fi t Std Err F-value 0.0382481654 0 574.1543 0524 1.4316936102

Parm Va lue Std E rror t-v alue 95% Confidence Limits P>|t | a 421 5.921606 173 6.7 852 27 2. 42 7428297 693 .55 7906 9 7738.2853 05 0.02034 b -21 4.870422 179. 57736 47 - 1.1 96534 -579 .07019 8 149.32935 37 0.23931

Soln Vector Covar Ma trix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 471962.33 1 471962.33 1.43169 0.23931 Error 11867514 36 329653.17 Total 12339476 37

299

Table A7.95 ANOVA for the relationship between Na concentration in lotus petioles (Nelumbo nucifera) and petio le Ca concentratio n. Ra nk 2781 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r 2 Fit S td Err F-valu e 0.01922497 81 0 61 6. 01 760728 0.72 52 6743 9

Parm V alue Std Erro r t-value 9 5% Confidence Limits P>|t| a 402 2.746312 232. 34823 23 17.31343627 3551.964075 4493.528549 0.00000 b -1.8867e-06 2.21537e-06 -0.85162635 -6.3754e-06 2.6021e-06 0.39990

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 275222.81 1 275222.81 0.725267 0.39990 Error 14040675 37 379477.69 Total 14315897 38

Table A7.96 ANOVA for the relationship between Na concentration in lotus roots and stolons (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure A7.10a). Rank 11 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2584157511 0.2134712511 544.08439611 11.847791467

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1414.147791 806.4002978 1.753654848 -224.654785 3052.950368 0.08850 b 29.59819148 8.598970808 3.442062095 12.12298027 47.07340268 0.00155

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3507276 1 3507276 11.8478 0.00155 Error 10064946 34 296027.83 Total 13572222 35

Table A7.97 ANOVA for the relationship between Al concentration in lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure A7.10b). Rank 27 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3410754574 0.3034226264 9.4538049758 18.634480388

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 78.21273572 7.257659243 10.77657866 63.49352055 92.93195089 0.00000 b -0.2377071 0.055065997 -4.31676735 -0.34938612 -0.12602808 0.00012

Soln Vector Covar Matrix Direct LUDecomp r2 Coef Det DF Adj r2 Fit Std Err r2 Attainable 0.3410754574 0.3034226264 9.4538049758 0.7709001268 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1665.446 1 1665.446 18.6345 0.00012 Error 3217.4794 36 89.374429 Total 4882.9255 37

300

6000 A ) -1 5000

4000

3000

2000

Roots & Stolons Na Conc. (mg kg (mg & Stolons Na Conc. Roots 1000

0 B 80 ) -1 60

40 Leaf Al Conc. (mg kg (mg Conc. Al Leaf 20

0 0 5000 10000 15000 20000 25000 30000

Organ Ca Conc. (mg kg-1)

Figure A7.10 Nutrient concentration in organs of lotus (Nelumbo nucifera) as a function of organ calcium concentration: a) Sodium, regression equations is y = 1 414.15 + 29.60x0.5 (r2 = 0.21) for roots and stolons; b) Aluminium, regression equations is y = 78.21 -0.24x0.5 (r2 = 0.30) for leaves. (Tables A7.96 & 97).

301

Table A7.98 ANOVA for the relationship between Al concentration in lotus petioles (Nelumbo nucifera) and petiole Ca concentration. Rank 46 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0656753899 0.009049656 10.072432118 2.3899223387

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 45.50345207 3.07028427 14.82059903 39.26388372 51.74302042 0.00000 b 3.83075e-12 2.47794e-12 1.545937366 -1.205e-12 8.86653e-12 0.13138

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 242.46692 1 242.46692 2.38992 0.13138 Error 3449.4322 34 101.45389 Total 3691.8991 35

Table A7.99 ANOVA for the relationship between Al concentration in lotus roots and stolons (Nelumbo nucifera) and root and stolon Ca concentration. Rank 2484 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0244698284 0 51.021866885 0.9280939498

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 329.058632 170.199865 1.933365999 -15.7990516 673.9163156 0.06087 b -1.99434646 2.070163451 -0.96337633 -6.18889605 2.200203116 0.34161

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2416.0428 1 2416.0428 0.928094 0.34161 Error 96319.543 37 2603.2309 Total 98735.586 38

Table A7.100 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.9a). Rank 2 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4316516528 0.3799836212 6.9753807235 12.911233284

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.9737977 2.14702268 15.35791774 28.61052265 37.33707275 0.00000 b 13932.87546 699.9674115 19.90503449 12510.37054 15355.38039 0.00000 c 8735.555975 995.743152 8.772900881 6711.962423 10759.14953 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1256.4163 2 628.20814 12.9112 0.00007 Error 1654.3018 34 48.655936 Total 2910.7181 36

302

Table A7.101 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole Ca concentration. (Figure 7.9a). Rank 2401 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0703876932 0.0187425651 9.0577365642 2.8015384803

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 27.98770165 2.62549789 10.65995968 22.66793762 33.30746569 0.00000 b -3.6553e-12 2.18384e-12 -1.6737797 -8.0802e-12 7.69615e-13 0.10261

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 229.84548 1 229.84548 2.80154 0.10261 Error 3035.5759 37 82.042592 Total 3265.4214 38

Table A7.102 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 7.9a). Rank 19 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3567102376 0.2999493762 7.4238096024 9.703914975

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 30.30811108 1.935632933 15.65798482 26.37856732 34.23765485 0.00000 b 7718.893085 355.819741 21.69326824 6996.540608 8441.245562 0.00000 c 3723.077852 748.6883317 4.97280069 2203.159735 5242.99597 0.00002

Procedure Minimization Iterations LevMarqdt Least Squares 10 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1069.6227 2 534.81137 9.70391 0.00044 Error 1928.9532 35 55.112949 Total 2998.576 37

Table A7.103 ANOVA for the relationship between dry mass of lotus leaves (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.9b). Rank 4 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3871834638 0.3314728696 2.2111552796 10.740765785

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10.16246232 0.669780765 15.17281901 8.801304038 11.5236206 0.00000 b 14152.92988 762.911055 18.55121876 12602.50808 15703.35168 0.00000 c 9172.03974 1123.609725 8.163012066 6888.590047 11455.48943 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 105.02767 2 52.513834 10.7408 0.00024 Error 166.23306 34 4.8892077 Total 271.26073 36

303

Table A7.104 ANOVA for the relationship between dry mass of lotus petioles (Nelumbo nucifera) and petiole Ca concentration. (Figure 7.9b). Rank 2273 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1047361568 0.0549992766 2.4799471018 4.328598582

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.951267387 0.718843592 11.06119256 6.49475192 9.407782854 0.00000 b -1.244e-12 5.97922e-13 -2.08052844 -2.4555e-12 -3.2489e-14 0.04446

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 26.621477 1 26.621477 4.3286 0.04446 Error 227.55509 37 6.1501376 Total 254.17657 38

Table A7.105 ANOVA for the relationship between dry mass of lotus roots and stolons (Nelumbo nucifera) and root and stolon Ca concentration. (Figure 7.9b). Rank 1 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4568389473 0.4042749744 2.9056252446 13.457193072

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 13.71433168 0.939569356 14.59640163 11.80049153 15.62817183 0.00000 b 13958.36264 686.0172179 20.34695672 12560.9913 15355.73399 0.00000 c 8448.292866 961.8622798 8.783266631 6489.043517 10407.54221 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 227.22896 2 113.61448 13.4572 0.00006 Error 270.16506 32 8.4426581 Total 497.39402 34

Table A7.106 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.10a). Rank 15 Eqn 1064 y=a+bx2+cx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2901275312 0.2274917251 5.5937850504 7.1523154076

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.926250173 5.283820357 0.553813335 -7.80047542 13.65297577 0.58323 b -7.4644e-08 1.9742e-08 -3.78099549 -1.1472e-07 -3.4566e-08 0.00059 c 0.02418444 0.006535578 3.700428887 0.010916512 0.037452368 0.00074

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 447.59807 2 223.79903 7.15232 0.00249 Error 1095.1651 35 31.290431 Total 1542.7632 37

304

Table A7.107 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and petiole Ca concentration. (Figure 7.10a). Rank 87 Eqn 1060 y=a+bx2+cx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3591930879 0.3009379141 5.1237396477 9.529052167

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.64054752 4.934041017 0.535169349 -7.38663024 12.66772528 0.59602 b 6.90478e-07 1.66277e-07 4.152568591 3.52562e-07 1.02839e-06 0.00021 c -4.7617e-11 1.11314e-11 -4.27769668 -7.0238e-11 -2.4995e-11 0.00015

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 500.32685 2 250.16342 9.52905 0.00052 Error 892.59207 34 26.252708 Total 1392.9189 36

Table A7.108 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 7.10a). Rank 2081 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0416688582 0 6.8691114624 1.6087839427

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 22.57217668 1.961118072 11.50985094 18.59857403 26.54577934 0.00000 b -2.6267e-12 2.07095e-12 -1.26837847 -6.8229e-12 1.5694e-12 0.21259

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 75.909975 1 75.909975 1.60878 0.21259 Error 1745.8336 37 47.184692 Total 1821.7436 38

Table A7.109 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.10b). Rank 106 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2532405874 0.1853533681 666.64918174 5.7650294233

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2931.435745 187.4918235 15.63500578 2550.406516 3312.464973 0.00000 b 14608.40245 1092.084252 13.37662586 12389.02023 16827.78468 0.00000 c 11527.19451 1923.834444 5.991780921 7617.49253 15436.8965 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 11 Source Sum of Squares DF Mean Square F Statistic P>F Regr 5124201.8 2 2562100.9 5.76503 0.00698 Error 15110318 34 444421.13 Total 20234520 36

305

Table A7.110 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and petiole Ca concentration. (Figure 7.10b). Rank 2658 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0496997924 0 741.21269 1.8304665405

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2734.019677 216.9225097 12.60366977 2293.643571 3174.395784 0.00000 b -2.4191e-10 1.78799e-10 -1.35294735 -6.0489e-10 1.21075e-10 0.18475

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1005651.5 1 1005651.5 1.83047 0.18475 Error 19228869 35 549396.25 Total 20234520 36

Table A7.111 ANOVA for the relationship between total stolon length of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 7.10b). Rank 700 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0690694095 0.0173510433 810.70866829 2.7451758238

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2811.465739 231.4557609 12.14688167 2342.491821 3280.439658 0.00000 b -4.0497e-10 2.44418e-10 -1.65685721 -9.0021e-10 9.02723e-11 0.10601

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1804262.8 1 1804262.8 2.74518 0.10601 Error 24318196 37 657248.54 Total 26122459 38

Table A7.112 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf Ca concentration. (Figure 7.11). Rank 2 Eqn 8033 y=aexp(-exp(-((x-b)/c))-((x-b)/c)+1) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3568748042 0.3001284634 5.3717978221 9.7108760707

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24.31299027 1.589467763 15.29630914 21.08619916 27.53978137 0.00000 b 14240.44114 816.2733235 17.44567748 12583.31819 15897.56408 0.00000 c 9587.32236 1245.680654 7.696452803 7058.456189 12116.18853 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 560.43819 2 280.2191 9.71088 0.00044 Error 1009.9674 35 28.856212 Total 1570.4056 37

306

Table A7.113 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and petiole Ca concentration. Rank 2568 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0421960009 0 6.5510712635 1.6300329012

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 21.10228629 1.898909695 11.11284352 17.25472978 24.9498428 0.00000 b -2.0166e-12 1.57948e-12 -1.27672742 -5.2169e-12 1.18377e-12 0.20965

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 69.955364 1 69.955364 1.63003 0.20965 Error 1587.9118 37 42.916535 Total 1657.8671 38

Table A7.114 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. (Figure 7.11). Rank 9 Eqn 8031 y=a/(1+((x-b)/c)2) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2564775713 0.1927470774 5.8515463483 6.2090881251

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 22.28596748 1.385826426 16.08135555 19.47538122 25.09655374 0.00000 b 8055.085801 401.7770277 20.048647 7240.244222 8869.92738 0.00000 c 4154.863405 908.3284072 4.574186354 2312.688012 5997.038798 0.00005

Procedure Minimization Iterations LevMarqdt Least Squares 12 Source Sum of Squares DF Mean Square F Statistic P>F Regr 425.20574 2 212.60287 6.20909 0.00482 Error 1232.6614 36 34.240595 Total 1657.8671 38

Table A7.115 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 10 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0580067206 0.0009162188 6.6029344136 2.0936757638

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 25.40498274 1.821063038 13.95063334 21.70413738 29.1058281 0.00000 b -2.9587e-13 2.0448e-13 -1.44695396 -7.1143e-13 1.1968e-13 0.15707

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 91.281631 1 91.281631 2.09368 0.15707 Error 1482.3573 34 43.598743 Total 1573.6389 35

307

Table A7.116 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and petiole Ca concentration. Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0743390054 0.0229133945 8.0479393207 2.9714368589

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 28.12117753 2.332795567 12.05471149 23.39448473 32.84787032 0.00000 b -3.3448e-12 1.94038e-12 -1.72378562 -7.2764e-12 5.86784e-13 0.09309

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 192.45797 1 192.45797 2.97144 0.09309 Error 2396.4651 37 64.769327 Total 2588.9231 38

Table A7.117 ANOVA for the relationship between the number of leaves of lotus (Nelumbo nucifera) and root and stolon Ca concentration. Rank 2 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0861822626 0.0324282781 6.9401952238 3.3008542817

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.24584458 4.809771473 6.704236315 22.48148938 42.01019977 0.00000 b -0.000105 5.77938e-05 -1.81682533 -0.00022233 1.23264e-05 0.07782

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 158.98997 1 158.98997 3.30085 0.07782 Error 1685.8208 35 48.16631 Total 1844.8108 36

Table A7.118 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 14 Eqn 8036 y=4an(1-n) n=exp(-(x-b)/c) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1300716691 0.0509872753 19.332106429 2.541839707

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 82.49951155 6.053268623 13.62891963 70.19778963 94.80123347 0.00000 b -1443.05894 2853.632252 -0.50569198 -7242.33741 4356.219536 0.61634 c 19381.22926 4543.342866 4.265852222 10148.04567 28614.41285 0.00015

Procedure Minimization Iterations LevMarqdt Least Squares 11 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1899.9252 2 949.96262 2.54184 0.09359 Error 12706.832 34 373.73034 Total 14606.757 36

308

Table A7.119 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and petiole Ca concentration. Rank 20 Eqn 1041 y=a+bx1.5+cx2lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1992965439 0.1265053206 18.906949023 4.2313308622

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.186901402 31.15144976 0.070202235 -61.1204613 65.4942641 0.94444 b 0.000323526 0.000122634 2.638143762 7.43038e-05 0.000572748 0.01248 c -2.6425e-07 9.71135e-08 -2.72099693 -4.616e-07 -6.6887e-08 0.01018

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3025.1707 2 1512.5854 4.23133 0.02286 Error 12154.073 34 357.47272 Total 15179.243 36

Table A7.120 ANOVA for the relationship between the number of nodes of lotus (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 148 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0341961328 0 22.947198913 1.3100557559

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 81.05422391 6.551381023 12.3720821 67.77986506 94.32858276 0.00000 b -7.9185e-12 6.91829e-12 -1.14457667 -2.1936e-11 6.09927e-12 0.25974

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 689.84122 1 689.84122 1.31006 0.25974 Error 19483.236 37 526.57394 Total 20173.077 38

Table A7.121 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and leaf Ca concentration. Rank 21 Eqn 10 y=a+b(lnx)2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1198078892 0.0695111972 7.4468826488 4.900162089

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 7.704627572 11.58315337 0.665158038 -15.7870963 31.19635142 0.51019 b 0.27349501 0.123550408 2.213630974 0.022923169 0.524066851 0.03328

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 271.74369 1 271.74369 4.90016 0.03328 Error 1996.4182 36 55.456061 Total 2268.1619 37

309

Table A7.122 ANOVA for the relationship between internode length of lotus (Nelumbo nucifera) and petiole Ca concentration. Rank 2550 Eqn 13 y=a+blnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0152731067 0 8.5254259099 0.5738697213

Parm Value Std Error t-value 95% Confidence Limits P>|t| a -1.59027674 46.69029405 -0.03406011 -96.1937986 93.01324512 0.97301 b 3.876512973 5.117225864 0.757541894 -6.4919715 14.24499745 0.45352

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 41.710508 1 41.710508 0.57387 0.45352 Error 2689.2668 37 72.682887 Total 2730.9773 38

Table A7.123 ANOVA for the relationship between internode length of lotus petioles (Nelumbo nucifera) and roots and stolon Ca concentration. Rank 2405 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0286568549 0 8.4672917653 1.0915850255

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 35.85546134 2.417395465 14.83226963 30.95735287 40.75356981 0.00000 b -2.6671e-12 2.55278e-12 -1.04478946 -7.8395e-12 2.50531e-12 0.30290

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 78.261221 1 78.261221 1.09159 0.30290 Error 2652.7161 37 71.69503 Total 2730.9773 38

Table A7.124 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and total leaf area. (Figure 7.12). Rank 17 Eqn 2 y=a+bxlnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.8979374408 0.8922672986 3.0012486673 325.52275357

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 4.817165219 1.183205492 4.071283686 2.419763169 7.214567269 0.00024 b 0.339693472 0.018827668 18.04224913 0.301544993 0.37784195 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2932.1441 1 2932.1441 325.523 0.00000 Error 333.27726 37 9.0074936 Total 3265.4214 38

310

Table A7.125 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 7.13a) Rank 25 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2705634586 0.2300392063 8.0234751348 13.724083453

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 37.00139855 3.655143518 10.12310416 29.5953743 44.4074228 0.00000 b -0.20931264 0.056500693 -3.70460301 -0.32379392 -0.09483136 0.00069

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 883.5037 1 883.5037 13.7241 0.00069 Error 2381.9177 37 64.376153 Total 3265.4214 38

Table A7.126 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and petiole N concentration. (Figure 7.13a). Rank 25 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2591844806 0.2180280628 8.0858147858 12.944957996

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 35.06386092 3.25358088 10.77700608 28.47147986 41.65624197 0.00000 b -3.18942629 0.886466334 -3.59791023 -4.98557769 -1.39327488 0.00093

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 846.34654 1 846.34654 12.945 0.00093 Error 2419.0748 37 65.380401 Total 3265.4214 38

Table A7.127 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolons N concentration. (Figure 7.13a). Rank 25 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2512067678 0.2096071437 8.1292355641 12.412839762

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 38.43831405 4.21213603 9.1256108 29.90371578 46.97291233 0.00000 b -4.23533532 1.202132187 -3.52318602 -6.6710865 -1.79958414 0.00115

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 820.29595 1 820.29595 12.4128 0.00115 Error 2445.1254 37 66.084471 Total 3265.4214 38

311

Table A7.128 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf N concentration. (Figure 7.13b). Rank 24 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3025615621 0.2638149822 5.5901947788 16.051277342

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 28.63324094 2.546647664 11.24350311 23.47324263 33.79323924 0.00000 b -0.157715 0.03936572 -4.00640454 -0.23747753 -0.07795248 0.00029

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 501.60687 1 501.60687 16.0513 0.00029 Error 1156.2603 37 31.250278 Total 1657.8671 38

Table A7.129 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and petiole N concentration. (Figure 7.13b). Rank 18 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2938378418 0.2546066108 5.6250478503 15.395897419

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 27.22898561 2.263414216 12.03004974 22.64287278 31.81509843 0.00000 b -2.41973153 0.616686837 -3.92376062 -3.66925775 -1.17020531 0.00036

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 487.1441 1 487.1441 15.3959 0.00036 Error 1170.723 37 31.641163 Total 1657.8671 38

Table A7.130 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolons N concentration. (Figure 7.13b). Rank 18 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2868055952 0.2471836838 5.6529867098 14.879262865

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 29.82685092 2.929076026 10.18302381 23.89197916 35.76172269 0.00000 b -3.2245654 0.835950345 -3.85736476 -4.91836169 -1.53076911 0.00044

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 475.48557 1 475.48557 14.8793 0.00044 Error 1182.3816 37 31.956259 Total 1657.8671 38

312

Table A7.131 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf N concentration. Rank 16 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0449902331 0 6.8571976804 1.7430592669

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 24.37389004 3.12383864 7.802544513 18.04439173 30.70338835 0.00000 b -0.06375203 0.048287857 -1.3202497 -0.16159252 0.034088463 0.19486

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 81.960669 1 81.960669 1.74306 0.19486 Error 1739.7829 37 47.02116 Total 1821.7436 38

Table A7.132 ANOVA for the relationship between the total stolon length of lotus (Nelumbo nucifera) and leaf N concentration. Rank 1 Eqn 8 y=a+bex r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1353290286 0.0872917524 781.32479277 5.7908432508

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3295.850674 355.9373219 9.259637781 2574.653155 4017.048193 0.00000 b -13.2401765 5.50202893 -2.4064171 -24.388346 -2.09200695 0.02122

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 3535127 1 3535127 5.79084 0.02122 Error 22587332 37 610468.43 Total 26122459 38

Table A7.133 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 7.14a). Rank 7 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2545207392 0.2131052248 8.111226635 12.632500792

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 39.00252698 4.329143395 9.009294316 30.23084927 47.7742047 0.00000 b -3.9087e-07 1.09973e-07 -3.55422295 -6.1369e-07 -1.6804e-07 0.00106

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 831.11746 1 831.11746 12.6325 0.00106 Error 2434.3039 37 65.791998 Total 3265.4214 38

313

Table A7.134 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and leaf P concentration. (Figure 7.14b). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.261321355 0.2202836525 5.7530980092 13.08944045

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 29.67871389 3.070557311 9.665578878 23.45717381 35.90025397 0.00000 b -2.822e-07 7.80012e-08 -3.61793317 -4.4025e-07 -1.2416e-07 0.00088

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 433.23609 1 433.23609 13.0894 0.00088 Error 1224.6311 37 33.098137 Total 1657.8671 38

Table A7.135 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and leaf P concentration. Rank 32 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0431178851 0 6.8639163411 1.667250046

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 23.35536597 2.460564367 9.491873605 18.369789 28.34094294 0.00000 b -1.1929e-11 9.23893e-12 -1.29122037 -3.0649e-11 6.79035e-12 0.20464

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 78.549731 1 78.549731 1.66725 0.20464 Error 1743.1939 37 47.113348 Total 1821.7436 38

Table A7.136 ANOVA for the relationship between the total stolon length of lotus (Nelumbo nucifera) and leaf P concentration. Rank 7 Eqn 3 y=a+bx1.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1658628291 0.1195218751 767.40549249 7.3572128063

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3937.610462 546.2337503 7.208654646 2830.835755 5044.38517 0.00000 b -0.00303524 0.001119015 -2.71241826 -0.00530257 -0.0007679 0.01008

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 4332744.9 1 4332744.9 7.35721 0.01008 Error 21789714 37 588911.19 Total 26122459 38

314

Table A7.137 ANOVA for the relationship between total dry mass of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 9 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0626417183 0.0105662582 9.0953949795 2.4726335922

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 32.05392877 5.126654203 6.252407029 21.66634067 42.44151687 0.00000 b -1.0708e-13 6.80962e-14 -1.572461 -2.4505e-13 3.08974e-14 0.12436

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 204.55161 1 204.55161 2.47263 0.12436 Error 3060.8698 37 82.72621 Total 3265.4214 38

Table A7.138 ANOVA for the relationship between total leaf area of lotus (Nelumbo nucifera) and roots and stolon K concentration. Rank 2031 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0280028965 0 6.5994309037 1.0659570544

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 22.76368179 3.719794495 6.119607364 15.22666222 30.30070136 0.00000 b -5.1013e-14 4.94092e-14 -1.03245196 -1.5113e-13 4.90999e-14 0.30856

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 46.425082 1 46.425082 1.06596 0.30856 Error 1611.4421 37 43.552488 Total 1657.8671 38

Table A7.139 ANOVA for the relationship between the number of stolons of lotus (Nelumbo nucifera) and roots and stolons K concentration. Rank 2066 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 7.116932e-05 0 7.0166095175 0.0026334523

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 20.31822648 3.954938818 5.137431302 12.30475926 28.33169371 0.00001 b 2.69582e-15 5.25326e-14 0.051317174 -1.0375e-13 1.09137e-13 0.95935

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 0.12965226 1 0.12965226 0.00263345 0.95935 Error 1821.6139 37 49.232809 Total 1821.7436 38

315

Table A7.140 ANOVA for the relationship between the total stolon length of lotus (Nelumbo nucifera) and roots and stolons K concentration. Rank 2043 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0013134042 0 839.69347088 0.0486598667

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2594.077039 473.2964397 5.480871651 1635.08736 3553.066717 0.00000 b -1.3868e-12 6.28669e-12 -0.22058982 -1.4125e-11 1.13513e-11 0.82662

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 34309.348 1 34309.348 0.0486599 0.82662 Error 26088150 37 705085.13 Total 26122459 38

Table A7.141 ANOVA for the relationship between combined Ca concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca supply. (Tables A7.58-60 & 157). Rank 1 Eqn 8100 y=a(1-exp(-bx)) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3122448153 0.3001789349 4687.0882168 52.210662393

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 17195.41108 1899.546355 9.052377709 13432.77533 20958.04682 0.00000 b 0.007101041 0.001768264 4.015825313 0.003598449 0.010603632 0.00011

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.1470054e+09 1 1.1470054e+09 52.2107 0.00000 Error 2.5264115e+09 115 21968796 Total 3.6734169e+09 116

Table A7.142 ANOVA for the relationship between combined Ca concentration in leaves and petioles of lotus (Nelumbo nucifera) and Ca supply. (Tables A7.58-59 & 158). Rank 1 Eqn 8100 y=a(1-exp(-bx)) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.4191252036 0.403635209 4790.3968247 54.837145065

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 21525.69787 3246.507623 6.630416549 15059.71756 27991.67818 0.00000 b 0.005759044 0.001711521 3.364868387 0.002350254 0.009167834 0.00120

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.2583974e+09 1 1.2583974e+09 54.8371 0.00000 Error 1.7440405e+09 76 22947902 Total 3.0024379e+09 77

316

Table A7.143 ANOVA for the relationship between combined Ca concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and Ca supply. (Tables A7.58, 60 & 159). Rank 1 Eqn 8100 y=a(1-exp(-bx)) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3364057756 0.3187099296 5229.6269707 38.527820174

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 19495.82005 2834.163928 6.87886112 13851.09338 25140.54672 0.00000 b 0.006683874 0.002102741 3.178648063 0.002495902 0.010871846 0.00214

Procedure Minimization Iterations LevMarqdt Least Squares 9 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.0536973e+09 1 1.0536973e+09 38.5278 0.00000 Error 2.0785239e+09 76 27348998 Total 3.1322212e+09 77

Table A7.144 ANOVA for the relationship between combined Ca concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca supply. (Figure 7.6, Tables A7.59-60 & 160). Rank 1 Eqn 8156 y=axb r2 Coef Det DF Adj r2 Fit Std Err F-value 0.6221755727 0.6121002547 1357.0947141 125.15163158

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 1454.062322 269.9937223 5.385541226 916.3232208 1991.801424 0.00000 b 0.356389 0.034924783 10.20447292 0.286830267 0.425947733 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 24 Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.3049252e+08 1 2.3049252e+08 125.152 0.00000 Error 1.3996966e+08 76 1841706.1 Total 3.7046218e+08 77

Table A7.145 ANOVA for the relationship between combined N concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Tables A7.61-63 & 161). Rank 699 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2607835705 0.2478148612 0.8602507455 40.570135355

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.406149011 0.102530477 23.46764675 2.203055869 2.609242153 0.00000 b 1.87437e-11 2.94274e-12 6.369469001 1.29147e-11 2.45727e-11 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 30.023172 1 30.023172 40.5701 0.00000 Error 85.103605 115 0.74003135 Total 115.12678 116

317

Table A7.146 ANOVA for the relationship between combined leaf and petiole N concentration as a function of Ca concentration. (Table A7.61-62 & 162). Rank 974 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1981333144 0.1767502028 0.9469239617 18.778847111

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.683395841 0.147710154 18.16663081 2.389205573 2.97758611 0.00000 b 1.51734e-11 3.50146e-12 4.333456716 8.19967e-12 2.21472e-11 0.00004

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 16.838335 1 16.838335 18.7788 0.00004 Error 68.146539 76 0.89666499 Total 84.984874 77

Table A7.147 ANOVA for the relationship between combined N concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.61-63 & 163). Rank 762 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2477570647 0.2276972531 0.882283656 25.031191431

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 2.582709715 0.147323202 17.53090949 2.289290129 2.876129301 0.00000 b 2.59628e-09 5.18932e-10 5.003118171 1.56274e-09 3.62982e-09 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 19.484891 1 19.484891 25.0312 0.00000 Error 59.160258 76 0.77842445 Total 78.64515 77

Table A7.148 ANOVA for the relationship between combined N concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Figure 7.7, Table A7.62-63 & 164). Rank 2221 Eqn 12 y=a+bx0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.1304610058 0.1072732993 0.5116050271 11.402635771

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 3.823888761 0.482363101 7.927407286 2.863179385 4.784598137 0.00000 b -0.01704722 0.005048367 -3.3767789 -0.02710191 -0.00699252 0.00116

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 2.9845225 1 2.9845225 11.4026 0.00116 Error 19.892217 76 0.2617397 Total 22.87674 77

318

Table A7.149 ANOVA for the relationship between combined P concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Figure 7.8a, Tables A7.64- 66 & 165). Rank 1 Eqn 8106 y=ab/(b+x) r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2762965541 0.2636000024 1525.1950943 43.90486725

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10270.12871 666.4548182 15.41008997 8950.009978 11590.24744 0.00000 b 27584.79154 6452.947715 4.274758259 14802.74404 40366.83904 0.00004

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.0213238e+08 1 1.0213238e+08 43.9049 0.00000 Error 2.6751531e+08 115 2326220.1 Total 3.6964769e+08 116

Table A7.150 ANOVA for the relationship between combined P concentration in leaves and petioles of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.64-65 & 166). Rank 1 Eqn 8110 y=a/(1+2a2bx)0.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2853700357 0.2663132366 1355.2193557 30.34874522

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 9877.305264 970.6232253 10.17625069 7944.141571 11810.46896 0.00000 b 4.74765e-13 9.54281e-14 4.975105613 2.84703e-13 6.64827e-13 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 13 Source Sum of Squares DF Mean Square F Statistic P>F Regr 55739097 1 55739097 30.3487 0.00000 Error 1.3958308e+08 76 1836619.5 Total 1.9532218e+08 77

Table A7.151 ANOVA for the relationship between combined P concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.64, 66 & 167). Rank 1 Eqn 8114 y=a+0.25b2x2-a0.5bx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3690591026 0.352234012 1426.5512086 44.455022504

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 9640.173214 419.1506 22.99930673 8805.362444 10474.98398 0.00000 b 0.002053053 0.000317655 6.463155015 0.001420389 0.002685718 0.00000

Procedure Minimization Iterations LevMarqdt Least Squares 8 Source Sum of Squares DF Mean Square F Statistic P>F Regr 90468120 1 90468120 44.455 0.00000 Error 1.5466367e+08 76 2035048.4 Total 2.4513179e+08 77

319

Table A7.152 ANOVA for the relationship between combined P concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.65-66 & 168). Rank 152 Eqn 11 y=a+bx/lnx r2 Coef Det DF Adj r2 Fit Std Err F-value 0.0683664974 0.0435229373 1727.2368893 5.5771435722

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 10122.44107 938.338623 10.78762061 8253.577734 11991.3044 0.00000 b -2.17022618 0.918965244 -2.36159767 -4.00050409 -0.33994828 0.02076

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 16638556 1 16638556 5.57714 0.02076 Error 2.2673439e+08 76 2983347.3 Total 2.4337295e+08 77

Table A7.153 ANOVA for the relationship between combined K concentration in leaves, petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.67-69 & 169). Rank 1 Eqn 6 y=a+bx2.5 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.2972738587 0.2849453299 11355.109941 48.648387665

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 47897.8217 1353.378469 35.39129873 45217.03942 50578.60398 0.00000 b -2.7093e-07 3.88434e-08 -6.97483962 -3.4787e-07 -1.9399e-07 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.2726512e+09 1 6.2726512e+09 48.6484 0.00000 Error 1.482793e+10 115 1.2893852e+08 Total 2.1100581e+10 116

Table A7.154 ANOVA for the relationship between combined K concentration in leaves and petioles of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.67-68 & 170). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3989722332 0.3829448261 12689.249074 50.450064697

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 53947.98667 2179.466643 24.75283888 49607.20265 58288.77068 0.00000 b -5.401e-05 7.60409e-06 -7.1028209 -6.9155e-05 -3.8866e-05 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 8.1233202e+09 1 8.1233202e+09 50.4501 0.00000 Error 1.2237295e+10 76 1.6101704e+08 Total 2.0360615e+10 77

320

Table A7.155 ANOVA for the relationship between combined K concentration in leaves and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.67, 69 & 171). Rank 1 Eqn 4 y=a+bx2 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.3732125254 0.3564981927 6459.6473497 45.253220712

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 39256.04825 1078.628084 36.39442439 37107.77424 41404.32226 0.00000 b -2.5559e-05 3.79937e-06 -6.72705141 -3.3126e-05 -1.7991e-05 0.00000

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 1.8882831e+09 1 1.8882831e+09 45.2532 0.00000 Error 3.1712553e+09 76 41727044 Total 5.0595385e+09 77

Table A7.156 ANOVA for the relationship between combined K concentration in petioles and roots and stolons of lotus (Nelumbo nucifera) and Ca concentration. (Table A7.68-69 & 172). Rank 1 Eqn 7 y=a+bx3 r2 Coef Det DF Adj r2 Fit Std Err F-value 0.084578483 0.0601672426 9307.9688623 7.0218632511

Parm Value Std Error t-value 95% Confidence Limits P>|t| a 45508.64845 1866.192081 24.385833 41791.8048 49225.4921 0.00000 b 4.56976e-09 1.72452e-09 2.649879856 1.13509e-09 8.00443e-09 0.00979

Soln Vector Covar Matrix Direct LUDecomp Source Sum of Squares DF Mean Square F Statistic P>F Regr 6.0836218e+08 1 6.0836218e+08 7.02186 0.00979 Error 6.5845096e+09 76 86638284 Total 7.1928718e+09 77

Table A7.157 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves, petioles and roots and stolons as a function of Ca supply (Tables A7.58-60 & 141). ANOVA SS df ms F Single line RSS 2.53 x 109 115 Total Individual lines 290333143 107 2713393.86 RSS Difference 2239666857 8 279958357.1 103.18 F dist. 5.03 P value 0.0000

Table A7.158 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and petioles as a function of Ca supply (Tables A7.58-59 & 142). ANOVA SS df ms F Single line RSS 1.744 x 109 76 Total Individual lines 229850111 71 3237325.51 RSS Difference 1514149889 5 302829977.8 93.54 F dist. 9.20 P value 0.0000

321

Table A7.159 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in leaves and roots and stolons as a function of Ca supply (Tables A7.58, 60 & 143). ANOVA SS Df ms F Single line RSS 2.08 x 109 76 Total Individual lines 256483032 72 3562264.33 RSS Difference 1823516968 4 455879242 127.97 F dist. 13.65 P value 0.0001

Table A7.160 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for Ca concentration in petioles and roots and stolons as a function of Ca supply (Tables A7.59-60 & 144). ANOVA SS Df ms F Single line RSS 1.4 x 108 76 Total Individual lines 94333143 71 1328635.82 RSS Difference 45666857 5 9133371.4 6.87 F dist. 9.20 P value 0.0193

Table A7.161 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves, petioles and roots and stolons as a function of Ca concentration (Tables A7.61-63 & 145). ANOVA SS df ms F Single line RSS 85.1 115 Total Individual lines 16.73 108 0.15 RSS Difference 16.37 7 2.34 15.09 F dist. 5.82 P value 0.0005

Table A7.162 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and petioles as a function of Ca concentration (Tables A7.61-62 & 146). ANOVA SS df ms F Single line RSS 68.15 76 Total Individual lines 9.07 71 0.13 RSS Difference 59.08 5 11.82 92.49 F dist. 9.20 P value 0.0000

Table A7.163 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in leaves and roots and stolons as a function of Ca concentration (Tables A7.61, 63 & 147). ANOVA SS df ms F Single line RSS 59.16 76 Total Individual lines 9.07 71 0.13 RSS Difference 50.09 5 10.02 78.42 F dist. 9.20 P value 0.0001

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Table A7.164 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for N concentration in petioles and roots and stolons as a function of Ca concentration (Tables A7.62-63 & 148). ANOVA SS df ms F Single line RSS 19.89 76 Total Individual lines 15.32 74 0.21 RSS Difference 4.57 2 2.14 10.31 F dist. 99.48 P value 0.0923

Table A7.165 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, petioles and roots and stolons as a function of Ca concentration (Tables A7.64-66 & 149). ANOVA SS df ms F Single line RSS 2.68 x 108 115 Total Individual lines 215606683 109 1978042.96 RSS Difference 52393317 6 8732219.5 4.41 F dist. 7.06 P value 0.0327

Table A7.166 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves, and petioles as a function of Ca concentration (Tables A7.64-65 & 150). ANOVA SS df ms F Single line RSS 1.4 x 108 76 Total Individual lines 113606683 72 1577870.6 RSS Difference 26393317 4 6598329.25 4.18 F dist. 13.65 P value 0.0848

Table A7.167 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in leaves and roots and stolons as a function of Ca concentration (Tables A7.64, 66 & 151). ANOVA SS df ms F Single line RSS 1.55 x 108 76 Total Individual lines 115606683 72 1605648.38 RSS Difference 39393317 4 9848329.25 6.13 F dist. 13.65 P value 0.0437

Table A7.168 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for P concentration in petioles and roots and stolons as a function of Ca concentration (Tables A7.65-66 & 152). ANOVA SS df ms F Single line RSS 2.27 x 108 76 Total Individual lines 202000000 74 2729729.73 RSS Difference 25000000 2 12500000 4.58 F dist. 13.65 P value 0.1956

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Table A7.169 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves, petioles and roots and stolons as a function of Ca concentration (Tables A7.67-69 & 153). ANOVA SS df ms F Single line RSS 1.48 x 1010 115 Total Individual lines 1498000000 108 13870370.37 RSS Difference 1.3302 x 10 7 1900285714 137.00 F dist. 5.82 P value 0.0000

Table A7.170 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and petioles as a function of Ca concentration (Tables A7.67-68 & 154). ANOVA SS df ms F Single line RSS 1.22 x 1010 76 Total Individual lines 1170000000 74 15810810.81 RSS Difference 1.2083 x 1010 2 6041500000 382.11 F dist. 99.48 P value 0.0026

Table A7.171 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in leaves and roots and stolons as a function of Ca concentration (Tables A7.67, 69 & 155). ANOVA SS df ms F Single line RSS 3.17 x 109 76 Total Individual lines 522000000 71 7352112.68 RSS Difference 2648000000 5 529600000 360.17 F dist. 9.20 P value 0.0000

Table A7.172 ANOVA of the comparison of regression equations between a single fitted line and the sum of individual fitted lines for K concentration in petioles and roots and stolons as a function of Ca concentration (Tables A7.68-69 & 156). ANOVA SS df ms F Single line RSS 6.58 x 109 76 Total Individual lines 1304000000 71 18366197.18 RSS Difference 5276000000 5 1055200000 57.45 F dist. 9.20 P value 0.0001

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Appendix 8 ANOVA Tables for Constant Treatments

Table A8.1 Comparison of constant means of nitrogen in leaves for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.58 , 5.58 , 6.58 & 7.58 ). Univariate Tests of Significance for N (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition

SS Degr. of MS F p

Intercept 275.2913 1 275.2913 5641.344 0.000000 "V2" 1.0261 3 0.3420 7.009 0.003184

Error 0.7808 16 0.0488

Tukey HSD test; variable N (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = .04880, df = 16.000 V2 N 1 2 2 P 3.437027 **** 3 K 3.622967 **** **** 1 N 3.719496 **** **** 4 Ca 4.060761 ****

Table A8.2 Comparison of constant means of nitrogen in petioles for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.59 , 5.59 , 6.59 & 7.59 ). Univariate Tests of Significance for Npt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition

SS Degr. of MS F p

Intercept 128.4579 1 128.4579 779.2841 0.000000 "V2" 1.2077 3 0.4026 2.4421 0.101843

Error 2.6375 16 0.1648

Tukey HSD test; variable Npt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = .16484, df = 16.000 V2 Npt 1 4 Ca 2.283407 **** 2 P 2.406215 **** 1 N 2.511387 **** 3 K 2.936363 ****

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Table A8.3 Comparison of constant means of nitrogen in roots and stolons for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.60 , 5.60 , 6.60 & 7.60).

Univariate Tests of Significance for Nrt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition

SS Degr. of MS F p

Intercept 117.3147 1 117.3147 1573.803 0.000000

"V2" 1.5362 3 0.5121 6.869 0.003474

Error 1.1927 16 0.0745

Tukey HSD test; variable Nrt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = .07454, df = 16.000 V2 Nrt 1 2 2 P 2.193770 **** 4 Ca 2.244142 **** 1 N 2.359215 **** **** 3 K 2.890584 ****

Table A8.4 Comparison of constant means of phosphorous in leaves for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.61, 5.61, 6.61 & 7.61).

Univariate Tests of Significance for P (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 606100500 1 606100500 2253.162 0.000000 "V2" 3565500 3 1188500 4.418 0.019133 Error 4304000 16 269000

Tukey HSD test; variable P (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 269E3, df = 16.000 V2 P 1 1 N 4800.000 **** 3 K 5560.000 **** 4 Ca 5800.000 **** 2 P 5860.000 ****

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Table A8.5 Comparison of constant means of phosphorous in petioles for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.62, 5.62, 6.62 & 7.62 ).

Univariate Tests of Significance for Ppt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p

Intercept 1.061424E+09 1 1.061424E+09 994.5416 0.000000 "V2" 1.949500E+06 3 6.498333E+05 0.6089 0.618881

Error 1.707600E+07 16 1.067250E+06

Tukey HSD test; variable Ppt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 1067E3, df = 16.000 V2 Ppt 1 1 N 6760.000 **** 4 Ca 7340.000 **** 2 P 7500.000 **** 3 K 7540.000 ****

Table A8.6 Comparison of constant means of phosphorous in roots and stolons for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.63, 5.63, 6.63 & 7.63).

Univariate Tests of Significance for Prt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1.638050E+09 1 1.638050E+09 1473.398 0.000000 "V2" 1.252200E+07 3 4.174000E+06 3.754 0.032433 Error 1.778800E+07 16 1.111750E+06

Tukey HSD test; variable Prt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 1112E3, df = 16.000 V2 Prt 1 2 P 8240.00 **** 4 Ca 8740.00 **** 1 N 8860.00 **** 3 K 10360.00 ****

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Table A8.7 Comparison of constant means of potassium in leaves for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.64, 5.64, 6.64 & 7.64).

Univariate Tests of Significance for K (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1.529045E+10 1 1.529045E+10 3042.876 0.000000 "V2" 4.615000E+07 3 1.538333E+07 3.061 0.058321 Error 8.040000E+07 16 5.025000E+06

Tukey HSD test; variable K (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 5025E3, df = 16.000 V2 K 1 2 P 26200.00 **** 4 Ca 27000.00 **** 1 N 27200.00 **** 3 K 30200.00 ****

Table A8.8 Comparison of constant means of potassium in petioles for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.65 , 5.65 , 6.65 & 7.65).

Univariate Tests of Significance for Kpt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 6.938420E+10 1 6.938420E+10 4728.055 0.000000 "V2" 1.330000E+08 3 4.433333E+07 3.021 0.060419 Error 2.348000E+08 16 1.467500E+07

Tukey HSD test; variable Kpt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 1468E4, df = 16.000 V2 Kpt 1 2 P 55600.00 **** 3 K 57200.00 **** 1 N 61000.00 **** 4 Ca 61800.00 ****

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Table A8.9 Comparison of constant means of potassium in roots and stolons for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.66 , 5.66 , 6.66 & 7.66 ).

Univariate Tests of Significance for Krt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 3.996180E+10 1 3.996180E+10 7168.036 0.000000 "V2" 5.700000E+07 3 1.900000E+07 3.408 0.043279 Error 8.920000E+07 16 5.575000E+06

Tukey HSD test; variable Krt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 5575E3, df = 16.000 V2 Krt 1 3 K 42400.00 **** 2 P 43800.00 **** 4 Ca 46000.00 **** 1 N 46600.00 ****

Table A8.10 Comparison of constant means of calcium in leaves for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.67 , 5.67 , 6.67 & 7.67 ).

Univariate Tests of Significance for Ca (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 1.221168E+10 1 1.221168E+10 1447.353 0.000000 "V2" 2.149820E+08 3 7.166067E+07 8.493 0.001326 Error 1.349960E+08 16 8.437250E+06

Tukey HSD test; variable Ca (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 8437E3, df = 16.000 V2 Ca 1 2 4 Ca 21120.00 **** 1 N 22720.00 **** 2 P 25200.00 **** **** 3 K 29800.00 ****

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Table A8.11 Comparison of constant means of calcium in petioles for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.68 , 5.68 , 6.68 & 7.68 ).

Univariate Tests of Significance for Capt (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition SS Degr. of MS F p Intercept 3.406050E+09 1 3.406050E+09 1107.208 0.000000 "V2" 6.095000E+07 3 2.031667E+07 6.604 0.004112 Error 4.922000E+07 16 3.076250E+06

Tukey HSD test; variable Capt (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 3076E3, df = 16.000 V2 Capt 1 2 4 Ca 11300.00 **** 2 P 11500.00 **** **** 1 N 13900.00 **** **** 3 K 15500.00 ****

Table A8.12 Comparison of constant means of calcium in roots and stolons for trials evaluating N, P, K, and Ca effects on lotus (Nelumbo nucifera). (Tables A4.69 , 5.69 , 6.69 & 7.69 ).

Univariate Tests of Significance for Cart (Constants_a1) Sigma-restricted parameterization Effective hypothesis decomposition

SS Degr. of MS F p Intercept 2.473088E+09 1 2.473088E+09 1280.563 0.000000 "V2" 3.289200E+07 3 1.096400E+07 5.677 0.007628

3.090000E+07 16 1.931250E+06 Error

Tukey HSD test; variable Cart (Constants_a1) Homogenous Groups, alpha = .01000 Error: Between MS = 1931E3, df = 16.000 V2 Cart 1 2 2 P 9360.00 **** 4 Ca 10980.00 **** **** 1 N 11160.00 **** **** 3 K 12980.00 ****