Lydia Rubiang-Y Alambing Doctor of Philosophy

Aibika (a green leafy vegetable in PNG): Biodiversity and its effect on micronutrient composition

Lydia Rubiang-Y alambing

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

Doctor of Philosophy

Food Science and Technology School of Chemical Engineering Faculty of Engineering

March 2014 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Rubiang-Yalambing

First name: Lydia Other name/s:

Abbreviation for degree as given in the University calendar: PhD

School: Chemical Sciences and Engineering Faculty: Engineering

Title: Aibika (a green leafy vegetable in PNG): Biodiversity and effect on micronutrient composition

Abstract 350 words maximum: (PLEASE TYPE)

Over twenty different varieties of aibika or Abe/moschus manihot (L.) which is a commonly consumed green leafy vegetable in Papua New Guinea were studied with two main objectives. Firstly to determine the extent of genetic diversity between the accessions currently held at the National Agricultural Research Institute (NARI) in PNG which would aid effective management of the aibika germplasm and secondly to analyse micronutrients (total folate and minerals) in all accessions and identify any relationships between the nutrient contents and genotypes. Total folate contents ranged from 34 - 132 f..Lg/1 00 g on a fresh weight basis over two years indicating a wide range and a significant difference (p<0.05) between the two years. The mineral contents (mg/lOOg fresh weight) were in the following ranges for the 3 year period; iron, 0.8 -8.7; zinc, 0.32- 2.31; calcium, 197- 635; potassium, 265- 630; sodium, 1.0- 41; magnesium, 79-264; manganese, 0.42 - 2.09 and copper, 0.13 - 1.7. A significant (p<0.05) variation in the mineral contents was observed reflecting on variations in growing conditions between the collections. There was no significant effect of genotype on micronutrient content in all accessions. UPGMA analysis was performed to determine the clusters of accessions of aibika according to concentrations of all minerals and folate in all 3 years. Generally, the clusters of accessions were different in each of the 3 years. Environmental and other factors seem to have a greater impact on the micronutrient data compared to the genotype. The 23 accessions studied were grouped into five main groups according to the techniques of random amplification of polymorphic DNA (RAPD) and directed amplification of minisatellite region DNA (DAMD). Sequencing results from two chloroplast DNA regions studied, the psbM-trnD and the trnL-trnF intergenic spacer regions did not show any variation in the accessions. The nuclear encoded ITS region was also studied which showed that sequences from all accessions were identical with the exception of LAL Am 22 1 where the sequence data from the reverse primer suggested that there were 11 differences from the rest of the accessions. Data from this sequence has been submitted to the Genbank (accession number KC48173).

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I wish to thank the following individuals and organisations, without whose support I would never have done or completed this PhD study:

Assoc. Professor Jayashree Arcot, my supervisor – I am grateful and fortunate to have a supervisor like you. You have assisted me in so many ways not just academically. Thank you for your patience, understanding and for the exposure you have given me in the area of food composition.

The Australian Government (Australian Development Scholarship) – for the full scholarship to study in Australia

The Papua New Guinea University of Technology, Lae, PNG – for allowing me to take up the study scholarship.

The PNG National Agricultural Research Institute (NARI), for the MOA to use the aibika germplasm at Laloki. Rosa Kambuou, Janet Paofa and their staff at NARI Laloki, for the assistance with sample collection, sample exportation and information when needed. The assistance of other staff at Bubia is also acknowledged.

Assoc. Professor Paul Holford, Hawkesbury Campus, University of Western Sydney, Richmond. I would never have done the DNA work without the assistance of someone so helpful, and understanding. I started the DNA work with no background knowledge on molecular biology and have learnt a lot in this study. Thank you.

Professor Heather Greenfield, my co-supervisor, for her professional advice and guidance.

Mr. Camillo Taraborrelli, for his assistance in the importation and quarantine procedures for the aibika samples, and the technical help in the running of my experiments.

Karrie, Nisha, Veronica and Yang, thank you for the friendship and assistance during my study.

My husband and son for their support, understanding and sacrifices made so I could complete my studies.

ABSTRACT

Aibika or Abelmoschus manihot as it is scientifically known is the most popular and commonly-consumed indigenous green leafy vegetable in Papua New Guinea (PNG). Many different varieties of aibika can be found in the country and the PNG National Agricultural Research Institute (NARI) is overseeing the collection and maintenance of these varieties in a field gene bank at Laloki, PNG. At this stage the accessions have only been morphologically characterised and there is no data on genetic differences between the accessions. Over twenty different varieties of aibika were imported into Sydney over a three year period. The two (2) main objectives for this study were: Firstly to determine the extent of genetic diversity between the accessions with the aim of assisting PNGNARI in identifying core genotypes in the current collection which would aid its effective management. Second aim was to analyse micronutrients (total folate and minerals) in all accessions and identify any relationships between the nutrient contents and genotypes. It is known that micronutrients do vary within varieties of same species so that the identification of a nutrient rich variety or varieties would lead to its promotion and consumption by the local communities. Genetic variation was determined using the techniques of random amplified polymorphic DNA (RAPD) and directed amplification of minisatellite region DNA (DAMD). Two chloroplast DNA regions, the psbM-trnD and the trnL-trnF intergenic spacer regions, as well as the nuclear encoded ITS region were also studied to determine if genetic variation could be found among the accessions of aibika. Mineral analysis was performed using ICPOES whilst for the folate, the extract was tri-enzyme treated and analysed using the Vitafast® folic acid kit. Total folate contents ranged from 34 – 132 µg/100 g on a fresh weight basis over two years indicating a wide range and a significant difference (p<0.05) between the two years. The mineral contents (mg/100g fresh weight) were in the following ranges for the 3 year period; iron, 0.8 –8.7; zinc, 0.32 – 2.31; calcium, 197 – 635; potassium, 265 – 630; sodium, 1.0 – 41; magnesium, 79-264; manganese, 0.42 – 2.09 and copper, 0.13 – 1.7. A significant (p<0.05) variation in the mineral contents was observed reflecting on variations in growing conditions between the collections. UPGMA analysis of the bands generated by RAPD and DAMD techniques classified the 23 morphologically different accessions of aibika into five main groups. The sequencing results showed no difference between the accessions at the psbM-trnD and the trnL-trnF intergenic spacer regions. In the ITS region, sequences from all accessions were identical with the exception of LAL AM 221 where the sequence data from the reverse primer suggested that there were 11 differences from the rest of the accessions, data from this sequence was submitted to Genbank (accession number KC48173). UPGMA clustering of accessions based on micronutrient data showed variations from year to year. Aibika is a good source of folate and the minerals studied. There was no significant effect of genotype on micronutrient content in all accessions. Environmental and other factors seem to have a greater impact on the micronutrient data compared to the genotype.

TABLE OF CONTENTS

ACKNOWLEDGEMENTS i

ABSTRACT ii

TABLE OF CONTENTS iii

LIST OF FIGURES viii

LIST OF TABLES x

CHAPTER 1 1 Introduction 1

Chapter 2 4 Abelmoschus manihot (L.) (aibika) in Papua New Guinea (PNG): biodiversity and micronutrient composition 4

2.1 Nutritional composition of aibika 6 2.1.1 Aibika consumption 8 2.1.2 Other uses of aibika 8

2.2 Biodiversity and conservation of aibika in PNG 8 2.2.1 Biodiversity and its importance to food and micronutrient security 9 2.2.2 Using biodiversity as a food based approach for micronutrient delivery 11 2.2.3 Factors that contribute to varietal differences in micronutrients 13

2.3 Morphological and genetic characterization of aibika 14 2.3.1 Molecular markers and their importance in the characterization of aibika accessions 17 2.3.2 Applications of molecular markers in the analysis of plant genome 18 2.3.3 Classification of molecular markers 19 2.3.4 Molecular techniques used to characterize aibika accessions in this study 20

2.4 Nutritional status and micronutrient problems in PNG 20 2.4.1 Findings of the National Nutrition Survey, 2005 23

2.5 The food micronutrients of choice for analysis in this research study 25

2.6 References 27

Chapter 3 33 Genetic analysis of aibika biodiversity - random amplification of polymorphic DNA (RAPD) and direct amplification of minisatellite region DNA (DAMD) 33

3.1 Random Amplification of Polymorphic DNA (RAPD) 34

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3.1.1 Advantages and limitations of the technique 35 3.1.2 Applications 35

3.2 Direct Amplification of Minisatellite region DNA (DAMD) 36

3.2.1 Advantages and limitations of the technique 37 3.2.2 Applications of DAMD-PCR 37

3.3 Materials and methods for both RAPD & DAMD-PCR 37 3.3.1 Plant materials and DNA extraction 37 3.3.2 DNA Extraction 38 3.3.2.1 CTAB extraction (after Doyle and Doyle, 1994) 40 3.3.2.2 Modified CTAB extraction (after Maguire et al., 1994) 40 3.3.2.3 Sodium sulphite extraction (after Prabhu et al., 1998; Barawal et al., 2003 41 3.3.2.4 Vitis DNA extraction (after Lodhi et al 1994) 41 3.3.2.5 Lithium chloride extraction (after Hong et al., 1995) 41 3.3.2.6 Qiagen DNeasy Plant Kit 42 3.3.2.7 SDS extraction (after Dellaporta et al., 1983) 42 3.3.2.8 Dual Extraction method 42 3.3.2.9 General consideration on extraction of aibika DNA 42 3.3.3.0 Assessment of DNA concentration and quality 45

3.3.4 DNA amplification for RAPD and DAMD primers 46 3.3.4.1 Optimizing PCR composition and thermo cycling parameters for RAPD primers 47 3.3.4.2 Optimising PCR composition and thermo cycling parameters for RAPD long primers 47 3.3.4.3 Optimizing PCR composition and thermo cycling parameters for DAMD Primers 51 3.3.4.4 Optimizing magnesium chloride concentration 51 3.3.4.5 Optimised temperature conditions used for the primers used in this study 54 3.3.5 Agarose gel electrophoresis 55 3.3.6 Data analysis 55

3.4 Results and Discussion 56 3.4.1 Production of band patterns 56

3.5 Conclusion 62

3.6 References 63

Chapter 4 67 DNA Sequencing- Introduction 67

4.1 Materials and methods 68 4.1.1 Plant materials and DNA extraction 68 4.1.2 DNA amplification 69 4.1.3 PCR conditions for trnL-F 70 4.1.4 PCR conditions for psbM-trnDGUC 70 4.1.5 PCR conditions for ITS 71 4.1.6 DNA sequencing and sequence analysis 72

4.2 Results 73 4.2.1 trnL-F spacer 73 4.2.2 psbM-trnDGUC spacer 79 4.2.3 ITS 83

4.3 Discussion 86

4.4 Conclusion 87

4.5 References 88

Chapter 5 91 Total Folate Composition 91

5.1 Folate 92 5.1.1 Food sources and bioavailability of folate 94 5.1.2 Dietary Folate Requirements 94 5.1.3 Health consequences of folate deficiency 96 5.1.3.1 Megaloblastic-anaemia 96 5.1.3.2 Neural Tube Defects (NTDs) 97 5.1.3.3 Folate and homocysteine 97 5.1.3.4 Food based approach to increasing folate intake 99

5.2 Materials and methods 100 5.2.1 Sample collection, preparation at Laloki aibika germplasm in PNG 100 5.2.2 DAFF regulations and quarantine process 101 5.2.3 Moisture determination 101 5.2.4 Preliminary sample preparation for micronutrient analysis 101 5.2.5 Microbiological assay procedure 101 5.2.5.1 Preparation of extraction buffer (0.1 N phosphate, 1.0% ascorbic acid, pH 6.1) 102 5.2.5.2 Preparation of sample 102 5.2.5.3 Tri-enzyme treatment and deconjugation 102 5.2.5.4 Total Folate assay 103 5.2.5.5 Quality control 103

5.3 Results/Discussion 103 5.3.1 Total Folate analysis 104

5.4 Conclusion 108

5.5 Future work 108

5.6 References 110

Chapter 6 117 Mineral composition 117

6.1.1 Iron 119 6.1.1.1 Deficiency diseases 119 6.1.1.2 Sources of iron in the diet 120 6.1.1.3 PNG perspective 121

6.1.2 Zinc 121 6.1.2.1 Deficiency diseases 122 6.1.2.2 Sources of zinc in the diet 123 6.1.2.3 PNG perspective 123

6.1.3 Calcium 124

6.1.4 Magnesium 125

6.1.5 Manganese 126

6.1.6 Copper 127

6.1.7 Sodium 127

6.1.8 Potassium 128

6.2 Materials and methods 129

6.3 Results and discussion 131

6.4 Statistical analysis 140

6.5 Environmental and or other factors which may influence the variability in the mineral content of aibika accessions 144

6.6 Comparing the analysed aibika data with nutrient data from the Pacific Islands Food Composition Tables 145

6.7 Quality control for mineral analysis 147

6.8 Conclusion 147

6.9 Recommendation for future study 148

6.10 References 149

Chapter 7 157 General Discussion and Conclusions 157

7.1 Relationship between the groups found in this study (see results in Chapter 3, Figure 3.5) and their morphology 157

7.1.1 Group 1: Accessions LAL Am 170, LAL Am 180, LAL Am 200, LAL Am 203, LAL Am 204, LAL Am 206 and LAL Am 220 157 7.1.2 Group 2: Accessions LAL Am 009, LAL Am 011, LAL Am 030, LAL Am 041, LAL Am 045 and LAL Am 221 159 7.1.3 Group 3: Accessions LAL Am 016 and LAL Am 035 161 7.1.4 Group 4: Accessions LAL Am 134, LAL Am 141 and LAL Am 166 162 7.1.5 Group 5: accessions LAL Am 082 and LAL Am 123 163

7.2 Relationship between the genotypes and micronutrient data over the 3 year period 165

7.3 General conclusions 168

7.4 Future work 169

Appendix A 170 Appendix B 171 Appendix C 172 Appendix D 173

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LIST OF FIGURES

Figure 2.0 Aibika plants 5 Figure 2.1 Bundles of aibika leaves on sale at a typical PNG market 6 Figure 2.2 Map of Papua New Guinea 22 Figure 3.0 Six DAMD-PCR primers with variable MgCl2 concentrations 52 Figure 3.1 OPB primers OPB1, OPB2, OPB3, OPB4, OPB5, OPB6 with variable MgCl2 concentrations using DNA extracted from accession LAL AM 167 as the target. 53 Figure 3.2 Band patterns produced with primer long RAPD primer BOXA1R with 1-5 mM MgCl2 53 Figure 3.3 Band patterns produced using primer BOXA1R with samples: LAL Am 009, LAL Am 011, LAL Am 030, LAL Am 035, LAL Am 041, LAL Am 082, LAL Am 123, LAL Am 141, LAL Am 204 all in triplicate. 56 Figure 3.4 Band patters produced using DAMD primer URP9F with duplicates of 14 samples. 57 Figure 3.5 Clustering determined by UPGMA analysis of accessions of accessions of aibika in the NARI collection from data based on the presence or absence of bands generated from RAPD and DAMD. 58

Figure 3.6 Relationships among 23 of the aibika accessions in the NARI collection determined by multidimensional scaling using genetic distances calculated according to the method of Nei and Li (1979) from RAPD and DAMD profiles (D-star: = 16.53148; D-hat: = 11.78294). The colours relate to the groups highlighted in Fig 3.5 62

Figure 4.0 Positions and directions of universal primers for trnL-F region (Taberlet et al. 1991). 70 Figure 4.1. Positions and directions of primers for psbM-trnDGUC and trnCGCA-ycf6 regions (Shaw et al. 2005) 71 Figure 4.2 Positions and directions of primers for ITS regions (http://www.fao.org/ DOCREP/005/ X4946E/x4946e06.gif) 71 Figure 4.3 The trnL-F regions from A. manihot (LAL Am 141), H. rosa-sinensis(AY328142) and H. syriacus(AY328143) 78 Figure 4.4 Sequence data from LAL Am 167, H. mechowii (AY727113), H. cannabinus (AY727114) and H. macrophyllus (AY727112) for the psbM-trnDGUC spacer region 82 Figure 4.5 Comparison of sequences of the internal transcribed spacer regions from accessions LAL Am 122 and 221 from the collection at National Agricultural Research Institute with sequence JF421456 from A. manihot obtained from GenBank 86 Figure 5.1 Chemical formula of folic acid and the important natural folates 93 Figure 5.2 The role that folate and its co-factors play in the DNA and methylation cycles 98

viii

Figure 7.0 LAL Am 170 158 Figure 7.1 LAL Am 200 158 Figure 7.2 LAL Am 204 158 Figure 7.3LAL Am 206 159 Figure 7.4 LAL Am 009 159 Figure 7.5 LAL Am 041 160 Figure 7.6 LAL Am 045 160 Figure 7.7 LAL Am 030 160 Figure 7.8 LAL Am 221 161 Figure 7.9 LAL Am 016 161 Figure 7.10 LAL Am 035 162 Figure 7.11 LAL Am 134 162 Figure 7.12 LAL Am 141 162 Figure 7.13 LAL Am 166 163 Figure 7.14 LAL Am 082 163 Figure 7.15 LAL Am 123 163 Figure 7.16 Clustering determined by UPGMA analysis of accessions from first sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers. 166 Figure 7.17 Clustering determined by UPGMA analysis of accessions from second sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers. 167 Figure 7.18 Clustering determined by UPGMA analysis of accessions from third sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers. 167

LIST OF TABLES

Table 2.0 Comparison of nutrient values of aibika with two other popular green leafy vegetables consumed in PNG (raw values per 100g). 7 Table 2.1 Morphological differences in the features of some of the aibika accessions collected from NARI collection and used in this study 15 Table 3.0 Aibika accessions used for genetic analysis. 37 Table 3.1 Mean DNA concentrations and ratios for all the extraction methods used in the study 45 Table 3.2 Sequences of RAPD primers used to amplify DNA fragments from accessions of aibika 46 Table 3.3 Long RAPD primer sequences used to amplify DNA profiles from aibika 48 Table 3.4 DAMD PCR primers and their sources used to amplify DNA profiles from aibika 50 Table 3.5 Genetic distances among 23 of aibika accessions in the NARI collection calculated according to the method of Nei and Li (1979) using data from RAPD and DAMD profiles. 59 Table 4.0 Accession used for sequencing 68 Table 4.1 List of primer sequences and references used for sequence analysis 79 Table 5.0 The total folate content of accessions of aibika (µg/100g) on a fresh weight basis. 104 Table 5.1 Summary of statistics 105 Table 5.2 Folate content of green leafy vegetables from Fiji (µg/100 g ± SD on a fresh weight basis 107 Table 6.0 Calcium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 131 Table 6.1 Iron values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 132 Table 6.2 Manganese values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 133 Table 6.3 Sodium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 134 Table 6.4 Magnesium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 135 Table 6.5 Potassium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 136 Table 6.6 Zinc values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis 137 Table 6.7 Copper values for aibika accessions collected and analysed over 2 year period, values in fresh weight basis 138 Table 6.8 Statistics of the mineral data (tables 6.1 – 6.7) 139 Table 6.9 Statistics of the moisture content over the 3 year period 140 Table 6.10 Mineral composition of several green leafy vegetables consumed in the Pacific 146 Table 6.11 Mineral values of SRM 157a Tomato leaves 147

CHAPTER 1

Introduction

Biodiversity encompasses species diversity, genetic diversity and ecosystem diversity all of which are vital for food, fuel, medicine and for the survival of humanity (Bioversity International, 2011). Biodiversity has greater implication in the areas of agriculture and human nutrition. Identification, conservation and sustainable use of plant genetic resources are an important consideration with regards to food and micronutrient security. Having a big genetic pool of plant species to choose from is crucial to crop selection and breeding. Maintaining a greater biodiversity level is essential for a healthy diet that contains a variety of nutrients. A number of studies have shown that varietal differences do exist in the nutrient composition of crops, which means that consuming one or the other of the variety is the difference between having an adequate amount of a certain nutrient or being deficient (Burlingame et al. 2009). The variety of food crops grown and consumed varies from one locality to the other; climate, geography and agricultural practices may also influence the nutritional composition of different varieties.

Aibika is a commonly consumed green leafy vegetable, especially in the coastal regions of Papua New Guinea (PNG), although the plant originates in the tropical Asian region, it is important in the diets of the Melanesian people in the Pacific Region. The plant is from the tribe of Hibisceae of the Malvaceae family (Preston, 1998). PNG has the greatest diversity of aibika with over 140 accessions (Kambuou, 1995).The PNG National Agricultural Research Institute (NARI) is currently involved in identifying and preserving important agricultural food crops in the country with the intention of preserving the genetic pool of these crops for conservation and breeding purposes and aibika is one of those crops. The initial collection of the aibika germplasm was 114 accessions, however, over the years the number has reduced due to problems with effective management and funding for their maintenance. The accessions are maintained in a field gene bank, so they are grown in open fields and have to be replanted every year which leads to management problems. Morphological characterization of the aibika accessions has been done. But such data is unreliable as it is influenced by the

environment and physiological age of the plant. Genetic diversity data is needed for effective conservation and management of this genetic resource.

Like any other developing country, PNG has problems with food security as well as micronutrient deficiencies. The PNG National Nutrition Survey 2005 (PNG NNS, 2005), showed iron deficiency and iron deficiency anaemia as well as vitamin A deficiency diseases as being prevalent in the country. PNG does not have a national food composition database for the foods grown and consumed in the country. However, the Pacific Islands Food Composition Tables are normally used given some similarities to the foods consumed in the region. Knowledge of the nutrient composition of commonly consumed foods and the varieties included is essential to healthy eating, nutrition, food security and trade.

Food based approaches to addressing micronutrient problems are being promoted as the long term strategy by the Food and Agriculture Organisation (FAO) and World Health Organisation (WHO) especially in the developing countries where food fortification is not practised. Green leafy vegetables like aibika are very good sources of micronutrients like iron, folate, beta-carotene and others. Though many varieties of aibika are commonly consumed in the country, micronutrient content of the different varieties are unknown.

The information gap in the knowledge of the genetic diversity of the aibika germplasm and the potential for its contribution to addressing the food and micronutrient security in the country and its potential in the wider sense of food based approaches to addressing micronutrient deficiencies were explored in this study. The specific objectives of this study were to:

1. To determine the extent of the genetic diversity between the different accessions or varieties of aibika currently being held at Laloki, PNG.

Chapter3 and Chapter4 describe the techniques or the methods used to generate data on the genetic diversity of the aibika accessions.

2. To analyse all accessions available for the micronutrients (total folate and minerals) and to identify any relationships between the nutrient contents and the genotypes.

Chapter 5 discusses the total folate contents and relationship with the genotypes, whilst Chapter 6 discusses the eight (8) minerals that were analysed. The relationship between the accessions and the micronutrient data are discussed in Chapter 7.

Chapter 2

Abelmoschus manihot (L.) (aibika) in Papua New Guinea (PNG): biodiversity and micronutrient composition

Green leafy vegetables (GLV) are an integral part of a main meal in both rural and urban areas in PNG. A typical meal especially in the rural setting usually lacks animal sources and is characteristically based on starchy roots and tubers complemented by an assortment of various indigenous green leafy vegetables. In such a meal, the GLV contributes towards the protein and the micronutrients that are lacking in the staple roots and tubers. A household survey in 1996 showed 75% of households as consuming various green leafy vegetables (Gibson & Rozelle 1998). There are about forty (40) different species of GLV consumed in the country and the GLV of choice according to popularity and common consumption include; aibika (Abelmoschus manihot), Amaranthus spp, Gnetum gnemon, Rungia Klossii, Ficus spp, choko tips, pumpkin tips, water dropwort, and blackberried nightshade (Kambuou, 1995).

Aibika is important in the lowland or coastal areas where it is most commonly consumed. It grows at sea level to about 1800 metres and is not suited to the highland areas. It is grown mostly from cuttings rather than through propagation of seeds and is easy to grow and manage, and ready to be harvested in about 80 days after planting (http://www.papuaweb.org/dlib/bk/french/03.pdf). The shrub is well suited to the tropical climate and is found in countries like China, Malaysia, Japan, Indonesia and the Pacific Islands.

Figure 2.0 below shows the aibika plant in the field and Figure 2.1 shows bundles of aibika being sold at the market.

Figure 2.0 Aibika plants

Taxonomically, Aibika belongs to the tribe Hibisceae of the family Malvaceae, which consists of five genera. According to Waalkes, (1966) as cited in Preston (1998), the following is a description of Abelmoschus manihot subsp. Manihot: the stems of the plant do not normally have prickly hairs; the pedicel however, may sometimes have prickly hairs and the plant is either cultivated or established in the wild. It is said to be one of the most polymorphic of the species. Preston (1998), whilst giving a description of the taxonomy of the plant quotes several researchers as having difficulty comparing the similarities in the features of Abelmoschus manihot in various countries where it is found: e.g. in Indonesia, Sri Lanka and Thailand. Preston concludes the taxonomy description of aibika with an understanding that the plant is a form of the genus Abelmoschus manihot which includes Abelmoschus esculentus and A. caillei which are both species of okra and includes seven other species.

Though the plant originates from the tropical Asian region, it is not an important food item there as it is in the Pacific Island countries. Of the Pacific Island countries it is most commonly known and consumed by the Melanesian people compared to Polynesians and Micronesians (Preston, 1998). In PNG, it is known as aibika, in the Solomon Islands it is known as slippery cabbage, Aelan cabis in Vanuatu, and bele in Fiji.

Figure 2.1 Bundles of aibika leaves on sale at a typical PNG market

2.1 Nutritional composition of aibika Green leafy vegetables are rich sources of micronutrients like carotenes, ascorbic acid, riboflavin and folic acid and minerals like iron, calcium and phosphorus. Like other green leafy vegetables, aibika contributes to the micronutrient status of the PNG food supply. The table below (Table 2.0) shows micronutrient data for aibika, choko leaves and amaranth from the Pacific Islands Food Tables, the vegetables shown here are not from PNG.

Table 2.0 Comparison of nutrient values of aibika with two other popular green leafy vegetables consumed in PNG (raw values per 100g).

Nutrient Aibika Amaranth Choko leaves

Water (g) 89 89 91 Energy (kcal) 31 32 21 Protein (g) 3.6 3.7 4.4

Minerals Sodium (mg) 18 34 3 Potassium (mg) 484 646 359 Calcium (mg) 268 310 71 Zinc (mg) 1.4 0.7 0.4 Iron (mg) 1.9 4.9 7.3 Magnesium (mg) 118 130 41

Vitamins Beta carotene equivalents (µg) 9669 9510 68 Vitamin C (mg) 26.0 45 40 Riboflavin (mg) 0.37 0.22 0.10 Niacin (mg) 1.6 1.2 0.5 Thiamin (mg) 0.13 trace 0.1 Source: Pacific Islands Food Composition Tables (2nd ed.)2004

Aibika seems to compare well with amaranth except for vitamin C, sodium, calcium and iron and choko leaves have higher iron content compared to the other two. Amaranth and aibika seem to be good sources of a number of micronutrients.

Devi et al. (2008) reported the folate content of some Fijian foods which included aibika and the folic acid content was 131±14µg/100g whilst the total folate was 177± 5µg/100g on a fresh weight basis. Like other green leafy vegetables, aibika is a good source of folate and because it is commonly consumed, it contributes to the folate status of the population. In communities where food from animal sources is less consumed and less variety of foods is consumed, green leafy vegetables are major potential sources of micronutrients.

2.1.1 Aibika consumption

The young leaves and shoots are picked and steamed, fried or cooked in water or coconut cream normally in combination with onion, ginger, garlic and some animal protein. The plant is inherently slimy or mucilaginous. In PNG particularly, a dish cooked with aibika which is very much liked all over the country is called aigir. To prepare aigir, aibika leaves and coconut milk are mixed together and placed on large banana leaves and hot stones are placed along with it. The whole package is wrapped up with some more banana leaves to keep all the steam in to cook the aibika. Aibika is also consumed after being cooked in pit ovens, which is called mumu. In this cooking method, a pit is dug in the ground and hot stones are put into the pit and food items like aibika leaves, some form of meat along with root, tubers or cooking bananas are mixed with coconut milk and wrapped in banana leaves and put into the pit. Then more hot stones are placed around the wraps of food and covered with more leaves to keep all the steam in to cook the food (Sowei & Osilis, 1993; Preston, 1998)

2.1.2 Other uses of aibika Preston (1998) cites records by a number of researchers on the medicinal uses of aibika in PNG, Fiji, Vanuatu and New Caledonia. The outstanding similarity across all these countries is in the use of aibika for easing childbirth and aiding lactation. The cooked leaves are also used to treat other ailments like colds, constipation, stomach ailments and skin rashes.

2.2 Biodiversity and conservation of aibika in PNG Papua New Guinea is said to be the centre of diversity for a number of crops like root/tuber crops, banana species; sugar cane and a number of green leafy vegetables (Kambuou, 1995). Greatest diversity of aibika exists in PNG, with over 140 accessions. The different varieties maybe identified by the shape and size of the leaves, stem colour, and branching and flowering patterns (Kambuou, 1995). The National Agricultural Research Institute under the direction of the PNG Department of Agriculture and Livestock has established a national collection of aibika, the collection being made from six provinces. There are altogether 112 accessions which are maintained in a field

genebank with approximately ten plants per accession which are replanted once every year (Kambuou & Kewere, 2004). There is a need to identify and conserve the traditional or indigenous green leafy vegetables because with the change in times and food trade, introduced species and other imported vegetables may displace them especially in the urban markets. Development in the form of mining or logging or infrastructure building and modernized farming techniques may also lead to the loss of traditional vegetables. These traditional vegetables are very important to local communities in times when introduced crops fail or in times of natural disasters.

2.2.1 Biodiversity and its importance to food and micronutrient security

Biodiversity encompasses species diversity, genetic diversity and ecosystem diversity all of which are vital for food, fuel, medicine and for the survival of humanity (Biodiversity International, 2011).

Plant genetic resources are important resources for any country, be it aibika or any other indigenous crop which need to be conserved and managed effectively so that they are not lost. Having a huge variety is fundamental to crop selection and, selective breeding in turn is important for food and micronutrient security and for sustainable agriculture. The concept is important for PNG being a developing country that has more than half of its population dependent on agriculture.

For years, wild plants have sustained lives; however with the advent of agricultural revolution, there came a shift in the human food supply with the resulting reduction in dietary diversity. More focus has been given to domesticated cultivars with resulting effects of the erosion of wild and sometimes indigenous species of plants. Wild and indigenous plant species have sustained life especially during the periods of drought or other natural disasters when other introduced or domesticated cultivars have failed and hence an important consideration for food security (Grivetti & Ogle, 2000).

Edible wild plants make up a regular part of the diet of millions of people worldwide and provide a broad range of micronutrients and in some geographical locations help

sustain lives during the periods leading up to the harvest of domesticated crops. Knowledge and preservation of these plant species is also important in terms of sustaining lives during periods of natural disasters and periods of social unrest or wars when supply or production of domesticated species is affected.

With the advance in agricultural technologies and farming systems as well as domestication of only certain species of plants for consumption, the nutritional quality of diets may decline. Wild species augment such diets with assortments of different nutrients and some of those species or varieties may be more nutritious than the domesticated species.

In addition to their contribution to good health and nutrition, diversity in food crops also helps the farmers deal with pests, diseases and variations in climate and environmental changes, because different varieties and species are able to withstand certain diseases/pests or climatic conditions and hence provide food for the farmer when other varieties fail (Kambuou, Gwabu & Taylor, 2007). Food security is an important issue for Papua New Guinea. PNG is currently one of the 62 countries defined by the FAO as low income food deficit countries. The classification is based on low cash incomes and dependence on basic foodstuff imports. Some of the past natural disasters have seen shortages of basic foodstuffs across the affected areas and this shows that food security is an important issue for the country. Knowledge of the nutrient content of the foods consumed by people in a household would enable the assessment of household food security (Burlingame, 2000) and on a national level, would also be helpful in determining the national food security.

The vital role that biodiversity plays in food security and nutrition is recognised by a new international initiative lead by Food and Agriculture Organisation (FAO) and Bioversity International under the umbrella of the Convention of Biological Diversity (CBD), the general aim of which is to promote the importance and sustainable use of biodiversity in the activities of agriculture and human nutrition (Toledo & Burlingame 2006). The interaction and relationship between nutrition and biodiversity programmes are important in addressing two Millennium Development Goals (MDGs), Goal 1 and 7

(UN, 2005; Toledo & Burlingame, 2006). Potential use and value of indigenous, underutilised or wild foods as well as the biodiversity in the local ecosystem, the species available and diversity within the species are all encompassed in this initiative (Toledo & Burlingame, 2006). Knowledge of the composition of local diversity of food species and the varieties within would enhance their sustainable and increased use to address food security and nutritional deficiencies.

Burlingame et al. (2009) highlighted the importance of obtaining compositional data on the nutrient content as well as the bioactive components in foods below the level of species, meaning at the subspecies, cultivar, variety or breed level (Toledo and Burlingame, 2006) due to its importance in the areas of health, agriculture, trade and environment.

2.2.2 Using biodiversity as a food based approach for micronutrient delivery

The three known approaches to dealing with micronutrient deficiencies in the world include supplementation, food fortification and consuming a diet that includes a wide variety of foods. Foods contain various amounts of certain nutrients depending on the source of the foods being consumed. Although supplementation is essential in addressing particular target groups who maybe at high risk for certain micronutrient problems, it is not a sustainable strategy (Kennedy, Nantel & Shetty, 2003). Although fortification may not be feasible at this stage in a developing country like PNG due to lack of logistics and infrastructure, it is a sustainable approach to addressing micronutrient problems and combined with food based approaches would greatly reduce the problems currently faced. Affordability and accessibility of fortified foods would be another issue to be addressed for fortification programs to be successful. In developing countries like PNG and many others, micronutrient deficiencies exist alongside malnutrition which have many causative factors; including affordability, accessibility, dependence on monotonous diets, availability and lack of proper knowledge of the interactions of the different nutrients and its effects on bioavailability of specific micronutrients. Diet diversification as part of a food based approach to addressing

micronutrient deficiency promoted by a number of researchers can be seen as a holistic approach (Kennedy et al., 2003; Tontisirin et al., 2002).

It is known that apart from nutrients, plants also provide phyto-chemicals, antioxidants and other components like phytates and oxalates which may either promote or interfere with the bioavailability of certain nutrients. Therefore for food based approaches as such to be effective, there has to be a multi-sectorial approach; looking at policy issues, public health issues, nutrition education, improved production, processing, preservation and distribution of a variety of foods which is accessible and affordable for all. Moreover, creating or making marketing opportunities available for lesser known varieties of fruits and vegetables would encourage growing and consumption of these nutrient-rich foods.

Data from a number of studies show that the composition of nutrients and other bioactive compounds can be significantly different from one cultivar or variety to the other, with a huge range between the lowest and the highest values. A study of the varietal differences in nutrient composition of rice showed significant differences between varieties; protein content of 200 varieties ranged from 5.55 – 14.58 g/100 g dry matter basis (Kennedy & Burlingame, 2003). Englberger et al. (2003b), analysed the carotenoid content of different cultivars of edible pandanus fruit of the Federated States of Micronesia and found that the β-carotene content ranged from 19-393 µg/100 g in five cultivars, whilst the α-carotene ranged from <5 to 190 µg/100 g. Englberger et al. (2003a) also did similar studies on cultivars of giant swamp taro, banana and breadfruit and found significant differences between the cultivar with the highest and the lowest value of β-carotene. Work by Andre et al. (2007) on Andean potato cultivars as a source of antioxidants and mineral micronutrients also showed variability in the micronutrient contents amongst the tubers with some cultivars having high values of certain nutrients like iron and zinc. Fungo and Pillay (2011) studied 47 genotypes of banana, including11 accessions from PNG, which were obtained from a Musa germplasm collection in Belgium and grown in Uganda. This study was basically to grow different genotypes under similar conditions and study the relationship between pulp colour and β-carotene contents. This study was done to assess the suitability of banana as a food based

approach to address vitamin A deficiency in Uganda where banana is a staple food crop. The study showed higher β-carotene content in yellow to orange varieties and it also showed that some PNG bananas had very high content. These findings opened the doors for the introduction of the β- carotene rich varieties to the local community and also for the study of the genes for β- carotene in the rich varieties for breeding using biofortification strategies. Shohag et al. (2011) studied 57 spinach accessions which were collected from the United States Department of Agriculture (USDA) along with 11 accessions from Asian Vegetable Research and Development Centre (AVRDC) germplasm collections which were grown under controlled conditions. This study was done to investigate the natural variation in the folate content in different genotypes of spinach grown under-controlled conditions. Spinach is a green leafy vegetable of high nutritional quality and a very good source of folate so the objective of this study was to identify and promote folate rich varieties for direct use as well as for breeding. The results showed significant difference between the highest, 173.2±1.1 µg/100 g of fresh weight and the lowest value of 54.1±2.5µg/100g of fresh weight. There are a number of studies which have shown varietal differences in the nutrient composition of several crops, some of which are highlighted in Burlingame et al. (2009). These varietal differences mean that consuming one or the other of the varieties could be the difference between being deficient or having enough of a particular nutrient (Burlingame et al., 2009).

2.2.3 Factors that contribute to varietal differences in micronutrients

There are a number of factors that contribute to the differences in micronutrients between varieties and cultivars. Rodriguez-Amaya et al. (2008) discussed various factors affecting food carotenoids in the Brazilian food database. Some factors influencing both the quality and quantity of micronutrients included: the cultivar or variety being analysed or consumed, environmental factors like the climate/season and where grown, agricultural practices and conditions of production, and the part of the plant being analysed or consumed. The processes that the plant goes through after harvest, like processing and storage, also contribute to the differences in micronutrient levels. Harvesting at optimum maturity contributed to increased carotenoid content in a

number of vegetables (Rodriguez-Amaya et al.2008.) A study by Nikkarinen and Mertanen (2004), in determining the content of trace elements in edible wild mushrooms grown in two geochemically different provinces in Finland, one with high concentrations of nickel, barium, cobalt, copper, magnesium, manganese, sulphur and zinc and the other with low concentrations of the trace elements mentioned. The study showed that natural geology and geochemistry did have an effect on the trace element content of the edible mushrooms. It was also noted that even for samples within the same mushroom species, the trace element content varied in different geochemical provinces. Mercadante and Rodriguez-Amaya (1991), looked at the effects of some agricultural variables on the carotenoid composition of two kale cultivars in Brazil: cultivar, seasonal change and use of agrochemicals. Their study showed evidence of cultivar differences in the content of carotenoids, with some effect of seasonal differences with higher values in winter compared to summer with one cultivar having higher values in the winter and the other having higher values in the summer. Carotenoid content was higher for the samples grown in an organic farm compared to one that used agrochemicals. A study by Burgos et al. (2009) looked at, amongst other parameters, whether environment and genotype x environment (G x E) interaction had any effect on ascorbic acid concentration in 25 varieties of Andean potato. The varieties were grown in three different environments and the results showed evidence of the effect of genotype, as well as that of environment, and that of G x E on the concentration of ascorbic acid.

In the current study, the knowledge of the genetic variation between the different varieties of aibika and the correlation with micronutrient data would allow for the identification and promotion of nutrient-rich varieties for consumption in the local communities.

2.3 Morphological and genetic characterization of aibika

The aibika accessions have all been morphologically characterized. Table 2 below shows some of the morphological differences in the accessions that are being studied.

Morphological variation can be observed in the varying colours of the petiole which can be green, white or red; variation can also be observed in the colour of the leaves; they can vary from light green to very dark green; and also in the shape of the blade of the leaf. The colour of the stem also varies; it can be light or dark green, pink, red, purple or it can be either light or dark green with a tinge of pink, red or purple. Descriptor list from the International Board of Plant Genetic Resources (IBPGR) was used to compile phenotypic or morphological descriptions (Sowei & Osilis, 1993). A passport data for the characterization has been documented. Sowei & Osilis have detailed descriptions of the documentation of the germplasm at Laloki, PNG.

Table 2.1 Morphological differences in the features of some of the aibika accessions collected from NARI collection and used in this study

Sample ID Morphological feature LAL Am 041

LAL Am 200

LAL Am 035

LAL Am 045

LAL Am 141

LAL Am 203

However, relying on morphological characterization alone for accession or variety identification is misleading since other factors like geography, environment and stage of growth often influence these characteristics. Genetic characterization is needed by PNG NARI to be able to better conserve and maintain the aibika accessions and at this point in time most accessions have been lost due to the cost of maintenance of the plants on the field and of natural disasters. There is no data available on the DNA sequence and genetic characterisation of aibika hence this research is a preliminary study into the genetic variation in the aibika accessions maintained at NARI Laloki, PNG.

2.3.1 Molecular markers and their importance in the characterization of aibika accessions

Characterization of accessions whether morphologically or genetically is important for its maintenance, conservation and also for selective breeding.

Although morphological characterization based on phenotypic differences is important and useful, there are a number of factors which make it unreliable and difficult to rely on solely. It is influenced by the environment, needs an expert in a particular species of organism to be able to characterize it and needs the plant to grow to a certain age so that some specific characters can be seen and scored (Newbury and Ford-Lloyd, 1993) based on the environment or the physiological age of the plant (De Vicente and Fulton, 2003). Moreover, molecular markers have the advantages of being found in all tissues or parts of the plant or organism and they may or may not match the morphological or phenotypic expression of a trait (Agarwal et al., 2008).

Molecular markers rely on polymorphisms that take place naturally in the sequence of a DNA. The events that contribute to polymorphism includes; the situation where some bases in a DNA sequence are replaced by other bases; or when there has been an insertion or deletion of a number of bases in the sequence; or when the sequence of DNA is altered due to a reshuffle of the chromosomes; all these events contribute to

genotype variations (De Vicente and Fulton, 2003). At a molecular level, polymorphism is evident when varied band patterns are observed using a suitable technique.

Agarwal et al. (2008) defined a molecular marker as a specific fragment of DNA which represents differences at the genomic level. There are many different types of molecular marker techniques, each have their own advantages and disadvantages based on their specific features. The literature lists some of the criteria for an ideal molecular marker technique, some of which are listed here: that the marker should be polymorphic and be found throughout the genome; that the technique should be easy to do, quick and inexpensive, should be reproducible, should not require large amounts of DNA, should be able to distinguish accessions that maybe closely related and must be able to pick out a heterozygous from a homozygous form of the markers or be co-dominant (De Vicente and Fulton, 2003; Agarwal et al., 2008). There is no ideal molecular marker, the type and scope of study determines the choice of marker to use.

2.3.2 Applications of molecular markers in the analysis of plant genome

Molecular markers have several applications in genome analysis of plants and their breeding. Some of these applications include: germplasm characterization, genotyping of cultivars, assessment of genetic variation of germplasms, construction of genetic distances between and within populations. is the last-mentioned is essential for effective management and utilization of genetic resources for crop breeding and other crop enhancement plans including identifying varieties which are highly productive, nutrient dense or resistant to certain diseases (Vashney et al., 2005; Mondini, Moorani & Pagnotta, 2009; Joshi et al.1999). Molecular markers are also used to map and tag desired genes which facilitates marker-assisted crop breeding (Mohan et al., 1997). Some PCR based markers are used for the reconstruction of phylogenies for various species of plants, which unveils the understanding behind the pattern of genetic variation within species (Joshi et al., 1999).

2.3.3 Classification of molecular markers There is a wide range of molecular genetic marker techniques available and that makes it easy to characterize genetic variations. The choice of the appropriate technique for use is a big decision and the choice would depend on a number of factors including the cost and the levels of polymorphisms to be studied (De Vicente and Fulton, 2003).

Molecular markers are usually grouped into two groups based on method of analysis: hybridization-based markers and polymerase chain reaction (PCR) based markers. A common example of the hybridization method is the restriction fragment length polymorphism (RFLP). The method involves the use of a restriction enzyme to digest a DNA template, the fragments are then separated using electrophoresis, and hybridized with DNA labeled probes and finally detected by autoradiography (Semagn et al. 2006; Khanuja 2011). PCR-based markers on the other hand use PCR techniques to amplify micro levels of DNA using the thermostable DNA polymerase. Since its development in 1983 by Kary Mullis, the technique has been used widely in the field of molecular biology for the rapid copying of DNA and many more PCR-based markers have been developed. The basic components of a PCR include the polymerase enzyme, primers, nucleotides, buffer solutions and the template DNA to be amplified. Important to a PCR also is the cycle of heating and cooling which helps facilitate the denaturing of the double stranded DNA, then annealing of the primer to the denatured DNA followed by the extension of the new strands of DNA. The profile of the cycle of heating and cooling is dependent on the type of primers used (http://en.wikipedia.org/wiki/Polymerase_chain_reaction).

Some advantages of the PCR based technique over the hybridization technique are that micro-levels of DNA are required, technically, it is less demanding, prior knowledge of the DNA sequence is not necessary for a number of applications, and a lot of genetic markers can be produced in a short time because of high polymorphism being detected. PCR also allows for screening of a number of genes simultaneously which can be for direct data collection or as an initial study leading to nucleotide sequencing (Semagn et al. 2006).

The PCR-based techniques are grouped into two according to the primers that are used for amplification. Group 1 includes the arbitrary or semi-arbitrary primed PCR techniques. These are techniques that were developed with no prior knowledge of the sequence. Examples of techniques in group 1 include; RAPD, AFLP, ISSR, AP-PCR, DAF. Group 2 are the site-targeted PCR techniques which are developed from known DNA sequences. Examples include EST, CAPS, SSR, SCAR, and STS (Semagn et al. 2006).

2.3.4 Molecular techniques used to characterize aibika accessions in this study

The two techniques chosen for the genetic characterization of aibika are: random amplification of polymorphic DNA or RAPD; and directed amplification of minisatellite region DNA or DAMD. Both techniques are PCR based techniques, RAPD obviously belongs to the first group and DAMD-PCR belongs to the second group of PCR based techniques. Apart from their various advantages and disadvantages, RAPD was chosen mainly because there is no knowledge of the gene sequence of the aibika so the hypothesis is that random or arbitrary primers will have a complementary gene sequence to that of the target DNA and so will be able to amplify it. Similarly, since studies have shown that minisatellite core sequences do exist in various plants and other eukaryotic organisms, it is hoped that the use of core sequences as primers would amplify complementary sequences in the aibika genome. These two techniques will be discussed in Chapter 3.

2.4 Nutritional status and micronutrient problems in PNG

Micronutrient deficiency is a major nutritional problem especially in developing countries. It is well recognized that a diet that contains sufficient amounts of a variety of food from different food groups is able to provide an array of micronutrients and hence prevent micronutrient deficiencies. In some developing countries satisfying hunger and having enough to eat is all that matters. Dependence on staple diets which are comprised mostly of starch and little or nothing of the micronutrients is a problem in the developing countries.

Papua New Guinea is the largest of the Pacific Island countries and lies between the equator and 12 degrees south latitude. PNG shares borders with Australia to the south, Indonesia to the west, and Solomon Islands to the east. Papua New Guinea is a very mountainous country, has several large volcanic islands and 600 small and scattered islands. The geography is similarly diverse mostly mountainous, also consists of tropical rainforests, large wetland areas and rugged terrain which has led to lack of transport infrastructure development. Some areas in the country are very remote and can only be reached by small planes. It is situated on the Pacific Ring of Fire hence there are a number of active volcanoes and earthquakes. It is a tropical country with northwest monsoon from December to March and southwest monsoon from May to October, with slight seasonal variations in the temperature. It is said to be one of the least explored countries with many undiscovered plant and animal species [http://en.wikipedia.org/wiki/Papua_New_Guinea].

The country is divided into twenty two provinces which are further divided into a number of districts. The 22 provinces are categorised into four main regions according to the location of provinces; the colour coded map below (Figure 2.2) shows the different regions. The highlands region (the yellow coloured area) encompasses all the provinces located in the inland or highland areas of the main land. The islands region (the green coloured areas) includes all the New Guinea Island provinces; the Southern region (purple area) covers all the area towards the south including the Milne Bay islands, the Western province and the National Capital District, then there is the Momase region, the blue coloured areas. These regional groupings is important in terms of organisation of government services, some food crops grown and consumed maybe similar within the provinces in a region, similarly some cooking and food preparation practises maybe shared within a region. [http://en.wikipedia.org/wiki/Papua_New_Guinea]

Figure 2.2 Map of Papua New Guinea, showing the four regions. [Purple = Southern region, Orange = Highlands region, Blue = Momase region and Green = the Islands region

More than half of the total population of about seven million live in the rural areas, the typical diets are heavily dependent on the starchy roots and tubers and up in the highlands sweet potatoes are an integral part of every meal, while along the coast this maybe taro, yam, or banana along with some sweet potato. Some areas like the Sepik provinces, the New Ireland and the Milne Bay areas also depend on starchy sago as a staple food. Fruits do not feature much in the diet especially that of an adult diet but are enjoyed when in season. Green leafy vegetables are an important part of every main meal, nuts are seasonal, legumes may not be prominent in some diets, but beans and ground nuts are popular all across the country. A typical diet almost always lacks food from an animal source.

Traditional nutritional problems of protein energy malnutrition, stunting and wasting in young children still exist in the country, Muller and Smith (1999) did a further analysis from the 1982/1983 PNG National Nutrition Survey data to study the correlation between the pattern of child growth with environmental, socioeconomic and dietary factors, they found that though growth of a child was influenced by a wide range of ecological factors, the most important ones were diet and physical environment. Local environment dictated what was grown and consumed and income earned which in turn influenced the diet. Small scale studies into the prevalence of vitamin A deficiency showed vitamin A deficiency in some provinces. Iron deficiency anaemia is a widespread problem in PNG affecting mostly the women and the children (FAO nutrition country profile, 2003). According to Mason et al .(2001), PNG is ranked as one of the countries in the low serum retinol range of 10 to less than 15 percent and the same document rates prevalence of iron deficiency anaemia in pregnant women in PNG as over 50 percent. Although a National Nutrition Survey was done in 1982/1983 period, micronutrient deficiencies in the country were not studied on a national level until the recent 2005 National Nutrition Survey.

2.4.1 Findings of the National Nutrition Survey, 2005 (PNGNNS 2005)

The following are some results from the National Nutrition Survey 2005. The survey was done with the intention of determining the status of iron and iron deficiency anaemia, iodine deficiency and vitamin A deficiency in both children and adults. The survey also included anthropometric measurements of children as indicators for malnutrition, the coverage of iodised salts in PNG and survey of consumption of centrally processed foods which was geared towards finding a suitable food vehicle for fortification. Anaemia is defined as low haemoglobin level, in this study the Hb levels were adjusted for altitude and cigarette smoking; Hb<11.0 g/dL for children, Hb <12.0 for non- pregnant women and Hb <13.0 g/dL for men. Almost half of 910 children studied were anaemic with the highest being amongst the 6-11 months old. Regional differences were apparent with Momase and Southern regions classed as regions with severe anaemia

problems. Using the WHO criteria (WHO, 2001) for defining anaemia as a public health problem, greater than 40 per cent of the children studied were anaemic in these two regions. Of the 760 women of child bearing age, a third was anaemic, regional factors were also evident with Momase having the highest whilst the highlands region had the lowest. Out of the 778 men with measured haemoglobin, 26% were anaemic. Nationally the prevalence is moderate but severe in the Momase region. Helminth infection and infection was also studied for children 6-59 months and women as contributing factor to anaemia. Markers of inflammation studied were C-reactive protein (CRP) and α1-acid glycoprotein (AGP).Prevalence of infection was higher in children suffering from an inflammation, hook worm and round worm did not seem to affect prevalence of anaemia. Iron deficiency is defined as transferrin receptor concentration or TfR >8.0µg/l. Children within the age range 6-11 had the highest prevalence and 14.9 percent of the 753 women were iron deficient. Amongst the children aged between 6-59 months, the prevalence of iron deficiency anaemia was highest in the age range 6-11 months old. The prevalence amongst the non-pregnant women of 15-49 years of age was 15% of the 742 women involved in the study. Important point to note is that in all the sectors of population involved in the survey (children, men and women), a high prevalence of anaemia was evident.

WHO criteria for vitamin A deficiency states that if the prevalence is 10-20% then it is considered to be a moderate public health problem and prevalence of more than 20% is considered severe (WHO, 2009). In this survey, measurement of the retinol binding protein on dried blood spots was used to study the status of vitamin A in children between the ages of 6-59 months and women of 15-49 years; the deficiency is moderate to severe for the children, and the results are different for each region with Momase having the highest prevalence of the deficiency compared to other regions. Children in the urban areas had higher prevalence compared to the ones in the rural areas. The prevalence in women was 0.7% which is much less compared to the WHO criteria for moderate prevalence. Therefore nationally, it can be stated that the prevalence of vitamin A is moderate, however, in certain provinces/regions, it may be severe.

In this survey, 690 women of child bearing age were assessed for iodine deficiency disorders using urinary iodine analysis. The median urinary iodine of 170µg/L was well above the WHO cut off of 100µg/L, though adequate, there were differences in the values in the different regions of the country.

The survey showed highest prevalence of underweight and wasting in the children of age 6-23 months old to almost none in the 48-59 month old, it also found that though underweight and wasting is not critical on the national front, there are particular provinces and regions within the country that have a higher prevalence of these problems. There are many factors that contribute to these problems such as socioeconomic status, type or quality of weaning or complementary food given to the children and breast feeding practices. Roots and tubers and sago which are the staple starchy crops obviously lack micronutrients. Currently the following measures are available and used within the country; iron and folic acid supplementation are accessible to women attending antenatal clinics along with chloroquin prophylaxis for malaria. There are also other measures in place to address the malaria problems like the distribution of treated mosquito nets in endemic areas.

As of 1995, it was made mandatory for all salt sold in the country to be iodised with potassium iodate at 30 mg/kg. And as of 2002, high dosage vitamin A capsules were introduced along with the routine immunisation schedule for the 6-12 months old children.

All these measures are currently being utilised, however, there are no regular and updated data on the coverage and accessibility of these supplementation by the target groups. Knowing that most people live in the rural and remote areas, they may not have access to proper antenatal and post natal clinics to access these supplementations. .

2.5 The food micronutrients of choice for analysis in this research study The food micronutrients of choice for study in this research are: the vitamin folate and the minerals iron and zinc, also included are the minerals potassium, calcium,

magnesium, manganese, sodium and copper. These minerals were included because they can easily be analysed with iron and zinc at a minimal cost.

Folate will be discussed in chapter 5, whilst the minerals will be discussed in chapter 6.

2.6 References

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Chapter 3

Genetic analysis of aibika biodiversity - random amplification of polymorphic DNA (RAPD) and direct amplification of minisatellite region DNA (DAMD)

Plant genetic resources are essential for food and micronutrient security, the greater the gene pool of a particular genus or species, the greater the chance of selective and effective breeding programs. Since the early 1960s, the FAO has recognized and promoted the sustainable use and conservation of biodiversity to combat hunger and malnutrition (Esquinaz-Alcazar, 2005). In recent years, the importance of biodiversity in human and environmental health as well as in global food security, sustainable development and achieving the United Nations Millennium Development Goals has been recognized (Toledo and Burlingame, 2006).

Aibika is a commonly consumed green leafy vegetable grown in Papua New Guinea. Although it is said (Preston, 1998) to have originated in South East Asia, and there are more varieties of aibika found in PNG than anywhere else in the region. The National Agricultural Research Institute in PNG was tasked by the government to collect the different varieties of aibika from all over the country and preserve them in a central location. The collection of aibika accessions are now maintained at Laloki Research Centre in Port Moresby, PNG, where they are maintained in an ex situ field gene bank and are replanted annually. The different varieties have been classified according to their morphological traits including, leaf shape, colour, flowering patterns and petiole shape and colour. Over the years, the number of original collections has decreased due to the cost of maintenance and natural disasters such as floods and droughts. Although the accessions have been morphologically characterized, such characterization is subject to environmental factors; hence, for the conservation to be effective and efficient, assessment of genotypic variation at the DNA molecular level has to be made. This is because molecular markers have the advantage of being found in all tissues or parts of the plant or organism, they may or may not match the morphological or phenotypic

expression of a trait (Agarwal et al., 2008) and are not subjected to environmental factors.

There is no literature on the genetic diversity on aibika and, therefore, this study was performed in order to make a preliminary screen of the accessions currently held at Laloki with the objective of determining the extent of genetic diversity which would aid effective management of the aibika germplasm. The study being nutrition-oriented would also facilitate breeding and consumption of varieties that are identified to contain high amounts of certain micronutrients in an effort to deal with micronutrient deficiencies. The techniques employed to study the genetic diversity within the accessions of aibika are discussed in detail in this chapter. They are random amplification of polymorphic DNA or RAPD and directed amplification of minisatelite region DNA or DAMD-PCR.

3.1 Random Amplification of Polymorphic DNA (RAPD) The RAPD technique, used to look at genetic diversity, was concurrently developed by Williams et al. (1990) and Welsh and McClelland (1990) and is a polymerase chain reaction (PCR)-based method. RAPD differs from conventional PCR in that only one primer is used, and these primers are usually only 10 base pairs long and are usually designed with an arbitrary sequence. In this technique, the genome of the target DNA to be analyzed is unknown to the researcher, and it is assumed that the primers will bind in several places within the genome (Newbury et al., 1992; de Vicente and Fulton, 2003). For PCR to occur, the primers must anneal in a particular orientation, such that the direction of elongation of the nucleotide chains is towards each other and the primer binding sites must be a reasonable distance from each other. After the PCR reaction is complete, any amplified bands are separated by agarose gel electrophoresis and visualized using ultraviolet (UV) light in combination with a fluorescent dye such as ethidium bromide. The presence or absence of bands is an indication of polymorphism.

3.1.1 Advantages and limitations of the technique

The advantages and limitations of the RAPD technique have been discussed by de Vicente & Fulton (2003), Bardakci (2001), Hadrys et al. (1992), Newbury et al. (1993), and Kumar et al. (2001). The advantages are that a high number of fragments are amplified, it is a simple technique that requires small quantities of target DNA, initial genetic information is not required for the synthesis of specific primers and the arbitrary primers can be easily purchased. Moreover, compared to many other techniques, the cost per assay is low.

The limitations are that the RAPD markers are dominant, meaning that amplification occurs or does not occur resulting in the presence or absence of a band. It is difficult to ascertain the reason for the absence of the bands; it could either be due to poor quality DNA or the absence of the target sequence in the template being studied. Mismatches between the primer and the template DNA can also lead to band absence as well as faint bands contributing to difficulties in the interpretation of the results. With bands being dominant, it is impossible to tell if the amplified band is from a heterozygous or a homozygous locus. Co-migration is another problem with RAPD, the presence of a particular band in a number of varieties does not necessarily mean that these varieties share the same or homologous DNA fragment; by the same token, there is a possibility that a single detected band may constitute different amplification products. This is because though the gel electrophoresis separates DNA according to size, it does not separate equal sized DNA fragments according to their base sequences. Reproducibility is the biggest concern with this technique, PCR components and reagents, like the magnesium concentration, type of polymerase used, temperature profiles, quality and quantity of the template DNA used all have an effect on the results generated. Hence, RAPD is said to be laboratory dependent and so standardized reaction conditions and a good quality template DNA are a must for it to be reproducible.

3.1.2 Applications

Due to its simplicity and low cost, the technique has found a wide range of applications and some applications of RAPD listed by Kumar et al. (2001) include: the study of 35

genetic diversity, characterization of germplasm, cultivar identification, genome mapping, breeding of plants and animals, hybrid purity, and population and evolutionary genetics. RAPD was used in the identification of barley varieties (Weining et al., 1991), Wilde et al. (1992) used RAPD to distinguish both between and within groups of cocoa and other studies have also shown polymorphisms in rice and soybean cultivars using the technique. RAPD is of great value in the management of genetic resources, because it is cost effective and allows for the rapid screening of a large number of accessions or varieties of crops to identify duplicates or core sets of representative accessions which aids effective management of germplasm (Newbury et al., 1993).

3.2.0 Direct Amplification of Minisatellite region DNA (DAMD)

Minisatellites are also referred to as variable number tandem repeats (VNTR) or hypervariable repeats (HVR). They are defined as tandem repeats of DNA sequences of some 10 to 60 base pairs long and found in a number of organisms including both plants and animals. They are sequences of DNA that do not contribute to gene function and variation in the number of these repeats gives rise to polymorphisms. A number of organisms may share some common core sequences of these repeats (Nakamura et al., 1988; Hu et al., 2011), and this makes DAMD an attractive technique for studying a variety of organisms using these core sequences. It is an assumption that since minisatellites sequences occur in diverse species of plants and animals, they should be effective as PCR primers at relatively stringent conditions in a wide range of species. Heath et al. (1993) first used minisatellites as primers in a polymerase chain reaction which resulted in RAPD-like bands in humans, fish and three species of birds.

Minisatellite regions may have become inverted or moved, and so it would be possible to speculate that these repeats would most probably have a single copy DNA between them. Therefore, it is expected that when a PCR is performed using a core sequence as a primer, it is highly likely to amplify sequences previously flanking the highly variable loci (Heath et al., 1993).

3.2.1 Advantages and limitations of the technique

DAMD uses the core sequence of minisatellites as a single primer. The temperature profiles used in DAMD technique is more stringent compared to RAPD, because the DAMD primers are longer. Therefore, DNA profiles generated using DAMD should be more repeatable than those generated using RAPD.

3.2.2 Applications of DAMD-PCR

To date, the DAMD technique has been used successfully to establish DNA fingerprints in a variety of plant species including wheat (Bebeli et al., 1997), rice (Kang et al., 2002), capsicum (Ince et al., 2009) and Salvia species (Ince and Karaca, 2012).

3.3 Materials and methods for both RAPD & DAMD-PCR

3.3.1 Plant materials and DNA extraction

Leaf samples were collected from 23 morphologically different accessions of aibika from the aibika germplasm maintained at the National Agricultural Research Institute (NARI) in Laloki, PNG. The samples were kept at -85oC until the DNA was extracted.

Table 3.0 Aibika accessions used for genetic analysis.

Accession number LAL Am 009, LAL Am 011, LAL Am 016, LAL Am 030, LAL Am 035, LAL Am 039, LAL Am 041, LAL Am 045, LAL Am 082, LAL Am 084, LAL AM 123, LAL Am 134, LAL Am 141, LAL Am 166, LAL Am 170, LAL Am 175, LAL Am 180, LAL Am 200, LAL Am 203, LAL Am 204, LAL Am 206, LAL Am 220, and LAL Am 221

During the extraction stage, it was seen that the aibika DNA extracts had a lot of polysaccharide material which was difficult to remove using the Qiagen plant DNeasy kit. The resultant DNA quality was very poor when measured using the NanoDrop spectrophotometer. To address this problem, a number of different extraction 37

techniques were investigated. Therefore, in this section (Section 3.3), the different DNA extraction methods used or trialled will be discussed and how the DNA quality improved with the different methods will be shown. The different extraction methods start from section 3.3.2.1 through to section 3.3.2.8. Section 3.3.2.9 is a general discussion or description on the problems encountered with aibika DNA extraction. The average DNA concentration is as shown in Table 3.1.

3.3.2 DNA Extraction

Abbreviations CIA Chloroform: iso-amyl alcohol (24:1) CTAB Cetyl trimethylammonium bromide EDTA Ethylenediaminetetraacetic acid (disodium salt) PVP Polyvinylpyrrolidone PVPP Polyvinylpolypyrrolidone Sarkosyl Sodium lauryl sarcosinate SDS Sodium dodecyl sulphate

Buffers and solutions

CTAB buffer

CTAB 2% (w/v) EDTA 20 mM β-mercaptoethanol 0.2% (added just before use) NaCl 1.4 M PVP 1% (w/v) Tris-base 100 mM pH 8

Extraction buffer C EDTA 20 mM

β-mercaptoethanol 0.2% (added just before use) NaCl 1.4 M PVP 1% (w/v) Tris-base 100 mM

Lithium chloride extraction buffer (LCEB) EDTA 10 mM LiCl 0.8 M PVPP 5% Sarkosyl 0.6% pH 9

Modified CTAB buffer (MCTAB) CTAB 3% (w/v) EDTA 20 mM β-mercaptoethanol 0.4% (added just before use) NaCl 1.4 M PVP 2% (w/v) Tris-base 100 mM pH 8

Sodium acetate

CH3COONa 3 M (adjusted to pH 5.2 with acetic acid)

Sodium sulfite extraction buffer (SSEB) EDTA 10 mM Tris-base 10 mM KCl 1 M

Na2SO3 0.65% (w/v) pH 8

TE Buffer

EDTA 1 mM Tris-base 10 mM pH 8

Vitis extraction buffer (VEB) CTAB 2% (w/v) EDTA 20 mM β-mercaptoethanol 0.2% (added just before use) NaCl 1.4 M PVP 1% (w/v) Tris-base 100 mM pH 8

3.3.2.1 CTAB extraction (after Doyle and Doyle, 1994) 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes and 700 µL of CTAB buffer (preheated to 65°C) added. The samples were incubated at 65°C for 10 min and then extracted twice with 1 volume of CIA. The upper phases were then transferred to fresh tubes and the DNA precipitated using 1/10 volume of 3 M sodium acetate and 1 volume of isopropanol. The tubes were centrifuged at 16,000 g for 1 min, the supernatants decanted and the pellets washed twice with 70% ethanol. The pellets were then dissolved in TE buffer.

3.3.2.2 Modified CTAB extraction (after Maguire et al., 1994) 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes, 0.7 mL of MCTAB buffer added and the tubes incubated at 65°C for 45 min. 1 volume of CIA was added and the tubes shaken to form an emulsion. The tubes were centrifuged at 1,200 × g for 15 min at room temperature. The upper phases were transferred to fresh tubes and extracted with CIA as just described. The upper phases were again transferred to new tubes, and then the DNA precipitated with 1/10 3 M sodium acetate and 2 volumes of ice-cold 95% ethanol. The tubes were centrifuged at 1,200 × g, the supernatants decanted and the pellets dissolved in 400 µL TE buffer. 1.6 mL of 2.5 M NaCl was then added to give a concentration of 2 M NaCl and the DNA

precipitated with the addition of 2 volumes of ice-cold 95% ethanol. The tubes were centrifuged at 1,200 × g, the supernatants decanted and the pellets washed twice with 70% ethanol after which the pellets were dissolved in TE buffer.

3.3.2.3 Sodium sulfite extraction (after Prabhu et al., 1998; Baranwal et al., 2003) About 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes, 1 mL of SSEB (pre-heated to 95°C) added and the tubes then incubated at 95°C for 10 min; the tubes were shaken occasionally. After incubation, the tubes were placed on ice for 2 min and then centrifuged at 16,000 × g for 10 min at room temperature. The DNA was precipitated by the addition of 0.6 volumes of ice- cold isopropanol. The tubes were centrifuged at 16,000 g, the supernatants decanted, and the pellets washed twice with 70% ethanol. The pellets were then dissolved in 400 µL of sterile distilled water and the DNA re-precipitated with 2 volumes of ice-cold 100% ethanol and 1/10 volume of 3 M sodium acetate.

3.3.2.4 Vitis DNA extraction (after Lodhi et al., 1994) 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes and 1 mL of VEB added following which the tubes were incubated at 65°C for 10 min. 1 volume of CIA was added and the tubes shaken to form an emulsion. The tubes were centrifuged at 4000 × g for 15 min at room temperature. The supernatants were transferred to new tubes, ½ volume of 5 M NaCl added and the DNA precipitated by the addition of 2 volumes of ice-cold 100% ethanol. The tubes were centrifuged at 16,000 g, the supernatants decanted and the pellets washed twice with 70% ethanol. The pellets were then dissolved in TE buffer.

3.3.2.5 Lithium chloride extraction (after Hong et al., 1995) 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes together with 1 mL of LCEB and 0.05 mL β-mercapotoethanol. The tubes were heated at 55°C for 10 min and then placed at 4°C for 1 h during which time the samples were occasionally shaken. After incubation, the mixtures were centrifuged at 200 × g for 5 min at 4°C and the supernatants placed in a fresh Eppendorf tube. Total DNA was then precipitated by the addition of 1/10 volume of 3 M sodium acetate and 2 volumes

of ice-cold 100% ethanol. The tubes were centrifuged at 1,800 × g for 5 min at 4°C and the pellets washed twice with 70% ethanol. The pellets were then air-dried and re- suspended in TE buffer.

3.3.2.6 Qiagen DNeasy Plant Kit DNA extractions were initially performed using the DNeasy Plant Mini Kit (Qiagen) with the extractions performed according to the manufacturer’s specifications. Triplicate extractions were made from each aibika accession using this technique.

3.3.2.7 SDS extraction (after Dellaporta et al., 1983) 60 mg aliquots of tissue ground in liquid nitrogen were placed into 1.5 mL Eppendorf tubes. 700 µL of extraction buffer C (EBC) and 50 µL of 20% (w/v) SDS were added to the tubes which were then incubated at 65°C for 10; the extraction buffer and SDS were preheated to 65°C prior to use. 230 µL of 5 M potassium acetate were added to the tubes and the tubes placed on ice for 20 min. The tubes were then centrifuged at 16,000 × g for 10 min and the supernatant transferred to a fresh tube. 500 µL of CIA was then added to the tubes which were then shaken to form an emulsion and then centrifuged at 16,000 × g for 5 min. The upper, aqueous phase was then removed and the DNA precipitated with the addition of 1/10 volume of sodium acetate and 1 volume of ice-cold isopropanol and then centrifuged at 16,000 × g for 1 min.

3.3.2.8 Dual extraction method 60 mg aliquots of tissue ground in liquid nitrogen were extracted using the SDS method of Dellaporta et al. (1983). Once the DNA had been precipitated and collected by centrifugation, the pellets were then dissolved in 400 µL of AP1 buffer (Qiagen) and the DNA extracted using Qiagen DNeasy Plant Mini kit according to the manufacturer’s instructions. Triplicate extractions were made from each aibika accession.

3.3.2.9 General consideration on extraction of aibika DNA

Throughout the work presented in this chapter, considerable problems were encountered with inconsistency of band patterns from the different PCR techniques used. Initial

extraction of DNA from all accessions was made using the Qiagen Plant DNeasy kit. Multiple extracts from certain accessions yielded repeatable band patterns whilst variation was seen in the extracts from other accessions. The first part of the discussion details the measures taken to optimize the conditions for DNA extraction and PCR. Aibika leaves produce slimy, mucilaginous sap once they are picked, and initial extractions using the Qiagen Plant DNeasy kit resulted in the extracts from certain accessions becoming viscous and gluey and at times took a long time passing through the spin columns when centrifuged. The centrifuging time and speed specified by the manufacturer of the kit had to be adjusted at times to aid the separation. At the end of the extraction process, some gluey components were eluted with the DNA and so when the concentrations and purity were determined by spectrophotometry at 230, 260 and 280 nm (Wilfinger et al. 1997) using a spectrophotometer (NanoDrop Model 1000, Thermo Scientific), the values showed the presence of impurities. The ratio of absorbance at 260 nm and 280 nm is used to assess the purity of DNA and RNA. A ratio of ~1.8 is generally accepted as ‘pure’ for DNA. If the ratio is lower, it may indicate the presence of proteins, phenols or other contaminants that absorb strongly at or near 280 nm. The ratio of absorbance at 260 and 230 nm is used as a secondary measure of nucleic acid purity, this latter ratio is higher than the 260/280 ratio, and the expected values are normally in the range of 2.0 to 2.2. If the values are lower, then it indicates presence of contaminants which absorb at 230 nm.

As the 260/230 ratios of extracts made using the Qiagen Plant DNeasy kit were low (Table 3.4) and as many of the accessions of aibika produced a mucilaginous sap, it was thought that carbohydrates in the DNA extracts may be contributing to the lack of repeatability of PCR reactions. Contamination with polysaccharides is a common problem that occurs when preparing DNA from plants (Murray and Thompson, 1980), and the contaminants can interfere with molecular processes such as the action of polymerases (Aoki and Koshihara, 1972; Furakawa and Bhavadna, 1983; Shioda and Marakami-Muofushi, 1987). To address the problem of poor quality DNA, a number of different DNA extraction techniques were trialled (described in Section 3.3.2) to improve the purity of the DNA; several of these techniques had been used for species where carbohydrates had interfered with the extraction. The techniques were used to

extract DNA from accession LAL Am 200, an accession that was particularly problematic and whose DNA extracts did not amplify in PCR reactions. Table 3.1 shows the DNA concentrations and ratios for all the extraction methods that were tried out in this study.

Three commonly used methods for plant DNA extraction were trialled. The first extraction method used was that of Doyle and Doyle (1990) which was one of the first techniques developed to quickly and simply extract DNA from plant tissues without the use of a cesium chloride ultracentrifugation step; subsequently, the technique has commonly been used for plant DNA extractions. The second technique used involved sodium sulfite extraction (Prabhu et al., 1998; Baranwal et al., 2003). The use of sodium sulfite has been to reduce the degradation of DNA and its use allowed extracts of Acacia spp. (Worthington et al., 2001) to be digested with restriction enzymes. These authors suggested that, as sodium sulfite is a reducing agent, it may reduce the production of polyphenols that may interfere with subsequent reactions. The final method was based on that of Dellaporta et al. (1983) and has been used and adapted for a wide range of plant species. The use of these three techniques did not result in any improvement in DNA quality as judged by the absorbance ratios, and the resulting DNA did not amplify in PCR reactions.

Two techniques (Lodhi et al., 1994; Maguire et al., 1994) were then trialled that contained high concentrations of NaCl. Both the extraction buffers contained 1.4 M NaCl in addition to PVP; however, in the first technique additional NaCl is added before the DNA is precipitated. The PVP in the buffers used for these techniques forms complex hydrogen bonds with polyphenolic compounds and the resulting complex can be removed from the sample by centrifugation (Maliyakal, 1992). The high concentration of NaCl in these buffers increases the solubility of carbohydrates in ethanol so that they do not co-precipitate when the DNA is precipitated with ethanol (Fang et al., 1992). Despite the high concentrations of NaCl in these two extraction techniques, no change in ratio (260:230) was found and the extracted DNA did not amplify in PCR reactions.

The final extraction technique combined the SDS technique of Dellaporta et al. (1983) with the use of the Qiagen DNeasy Plant kit. This dual technique resulted in DNA extracts with an average 230:260 ratio of ~1.33, substantially higher than that achieved by any of the previous methods. It is assumed that sufficient contaminating materials in the extracts were removed during the first part of this procedure such that the matrix in the second part of the procedure did not become clogged or overloaded. The DNA was extracted using the allowed bands to be amplified in PCR reactions

3.3.3 Assessment of DNA concentration and quality DNA concentrations and purity were determined by spectrophotometry at 230, 260 and 280 nm using NanoDrop spectrophotometer (Model 1000, Thermo Scientific).

Table 3.1 Mean DNA concentrations and ratios for all the extraction methods used in this study

Method DNA 260/280 260/230 concentration ratio ratio (ng/µL) CTAB extraction (after Doyle and Doyle 38.41 1.85 0.66 1990) Sodium sulfite extraction (after Prabhu et al. 12.87 1.43 0.86 (1998); Baranwal et al. 2003) Modified CTAB extraction (after Maguire et 86.71 1.56 0.58 al. 1994) Vitis DNA extraction (after Lodhi et al. 63.60 1.47 0.58 1994) Lithium chloride extraction (after Hong et 11.96 1.33 0.83 al. 1995) SDS extraction (after Dellaporta et al. 1983) 94.24 1.50 0.67 Qiagen Plant mini DNeasy Kit 45.33 1.68 0.51 Dual extraction (SDS followed by Qiagen 64.78 2.07 1.33 kit)

The following sections, i.e., Sections 3.3.4 to Section 3.3.4.3 discuss the DNA amplification of the primers that were used in the techniques of RAPD and DAMD- PCR used in this study. Since no previous work has been done on the genetics of aibika and this being a preliminary study, a number of trials were done on the components of

PCR composition and thermocycling parameters to select a suitable option applicable to aibika. The choice of primers used did not depend on any previous study on aibika except that those primers worked well when used to study other green leafy vegetables as well as the Murraya species in the laboratory that was used to do the aibika study. The structure of these sections (3.3.4–3.3.4.3) includes the following; first comes the tabulation of the different primers used, then the description of the PCR components and the thermo cycling parameters, beginning with the initial values used followed by the optimised values. It is also to be noted here that apart from optimising the temperature profile and the PCR components like the magnesium chloride component and the amount of primer used, the quantity of the extracted DNA used was also trialled. DNA extracts from some accessions were just too viscous to separate effectively. Section 3.3.7 highlights the rationale behind the optimisation of the magnesium chloride in the PCR preparations. It also shows the trials done during the study using the RAPD, RAPD long primers and the DAMD-PCR primers with the examples of the gel photos in Figures 3.1, 3.2, 3.3. Section 3.3.4.5 documents the final optimised thermocycling conditions that were used for each of the different sets of primers used in this study.

3.3.4 DNA amplification for RAPD and DAMD primers

Table 3.2 Sequences of RAPD primers used to amplify DNA fragments from accessions of aibika

Primer ID Sequence (5’ →3’) s

OPB01 GTTTCGCTCC OPB02 TGATCCCTGG OPB03 CATCCCCCTG OPB04 GGACTGGAGT OPB05 TGCGCCCTTC OPB06 TGCTCTGCCC OPB07 GGTGACGCAG OPB08 GTCCACACGG OPB09 TGGGGGACTC OBP10 CTGCTGGGAC

3.3.4.1 Optimizing PCR composition and thermo cycling parameters for RAPD primers

The initial PCR reaction mixture used for RAPD with primers OPB01-OPB10 was:

DNA 1 µL 10 × PCR buffer 2 µL Primer 1 µL dNTPs (10 mM) 0.40 µL Taq (Thermopol) 0.2 µL Water 15.40 µL Total 20 µL

The 10 × buffer used (Thermopol) contained 2 mM MgSO4. The bands from some samples were not clear so the DNA concentration for all samples was adjusted to 50 ng and the amount of water added adjusted accordingly.

The temperature profile on the thermocycler was:

Denature at 95oC for 5 min Denature at 92oC for 30 sec Anneal at 36oC for 30 sec 44 cycles Extend at 72oC for 1 min and 30 sec Extend at 72oC for 5 min

Due to continued variation within the duplicates of the same sample, the amount of DNA added to the reaction mixture was varied using up to 5–10 µL of sample.

Go Taq Flexi Taq and 5 × colour-less reaction buffer (Promega, Madison, USA) were then used. The magnesium in the reaction buffer was varied to give final concentrations of 1, 2, 3 or 4 mM magnesium. The temperature profile and other PCR reaction components were kept the same as above.

3.3.4.2 Optimizing PCR composition and thermocycling parameters for RAPD long primers In addition to the use of the 10mer RAPD primers described above, long RAPD primers were also studied to see if more consistent results could be obtained from these primers. 47

Table 3.3 Long RAPD primer sequences used to amplify DNA profiles from aibika

Primer ID Sequence (5’ →3’)

BOXA1R CTACGGCAAGGCGACGCTGACG ERIC 1R ATGTAAGCTCCTGGGGATTCA ERIC 2 AAGTAAGTGACTGGGGTGAGC REP1 IIIGCGCCGICATCAGGC REP2 ACGTCTTATCAGGCCTAC

Initial PCR components and conditions for RAPD long primers

DNA 1 µL 10 × PCR buffer 2.5 µL Primer 1 µL dNTPs (10 mM) 0.50 µL Taq 0.25 µL Water 19.75 µL Total 25 uL

The amount of DNA added was adjusted over each trial when the bands were not clear adding between 1–10 µL of sample.

The initial temperature profile used was:

Denature at 95°C for 5 min, 1 cycle Denature at 95°C for 30 sec Anneal at 50°C for 30 sec 35 cycles Extend at 65°C for 8 min Extend at 65°C for 8 min, 1 cycle

Using this temperature profile, there were still some bands not being resolved properly and much variability was seen, and so a touchdown stage was incorporated into the thermocycling as below:

Denature at 95°C for 5 min 1 cycle Denature at 94°C for 1 min Anneal at 53°C for 1 min Decrease by 1.0°C every cycle 10 cycles (touchdown) Extend at 72°C for 2 min and 30 sec

Denature at 94°C for 1 min Anneal at 53°C for 1 min 35 cycles Extend at 72°C for 2 min and 30 sec Extend at 72°C for 5 min 1 cycle

To further resolve the band patterns the annealing temperature was further reduced to 42°C, as shown below:

Denature at 95°C for 5 min 1 cycle Denature at 94°C for 1 min Anneal at 52°C for 1 min Decrease by 1.0°C every cycle 10 cycles Extend at 72°C for 2 min and 30 sec Denature at 94°C for 1 min Anneal at 42°C for 1 min 35 cycles Extend at 72°C for 2 min and 30 sec Extend at 72°C for 5 min 1 cycle

When Gotaq flexi buffer was ordered (no added MgCl2), the PCR components were changed to:

Buffer 4 µL MgCl2 1.2 µL dNTP 0.4 µL Primer 1 µL Go Taq 0.1 µL Water 12.3 µL DNA 1 µL Total 20 µL

In addition, PCRs were also performed where the reaction mixtures had varying magnesium concentrations of 1, 2, 3, 4 and 5 mM. The components of PCR finally used are described here; DNA amplification was carried out in a 20 µL reaction volume containing 50 ng of genomic DNA from individual accessions as templates, 1 µL of the RAPD primers (as listed in Table 3.2), 4 µL of the 5x colour-less Go Taq Flexi reaction buffer (Promega, Madison, USA), 4 µL of 25 mM MgCl2 (Promega, Madison, USA), 0.5 µL of equimolar mix of 10 mM dNTPs (Fisher Biotech) and 0.2 µL of Taq DNA polymerase (Go Taq Flexi, Promega).

Table 3.4 DAMD PCR primers and their sources used to amplify DNA profiles from aibika

Primer ID 5’ →3’ Sequences Source Reference URP9F ATGTGTGCATCAGTTGCTG Rice (Oryza sativa L.) Kang et al. (2002) URP25F GATGTGTTCTTGGAGCCTGT Rice (Oryza sativa L.) Kang et al. (2002) URP4R AGGACTCGATAACAGGCTCC Rice (Oryza sativa L.) Kang et al. (2002) URP6R GGCAAGCTGGTGGGAGGTAC Rice (Oryza sativa L.) Kang et al. (2002) URP13R TACATCGCAAGTGACACAGG Rice (Oryza sativa L.) Kang et al. (2002) URP17R AATGTGGGCAAGCTGGTGGT Rice (Oryza sativa L.) Kang et al. (2002) M13 GAGGGTGGCGGCTCT Phage M13 Vassaet et al (1987) 6.2H (-) CCCTCCTCCTCCTTC Human (Homo sapiens) Jeffreys et al (1985) HBV3 GGTGAAGCACAGGTG Human (Homo sapiens) Jeffreys et al (1985) HBV5 GGTGTAGAGAGGGGT Human (Homo sapiens) Jeffreys et al (1985) YNZ22 CTCTGGGTGTGGTGC Human (Homo sapiens) Jeffreys et al (1985) URP1F ATCCAAGGTCCGAGACAACC Rice (Oryza sativa L.) Kang et al. (2002) URP2F GTGTGCGATCAGTTGCTGGG Rice (Oryza sativa L.) Kang et al. (2002) URP30F GGACAAGAAGAGGATGTGGA Rice (Oryza sativa L.) Kang et al. (2002) URP38F AAGAGGCATTCTACCACCAC Rice (Oryza sativa L.) Kang et al. (2002) URP32F TACACGTCTCGATCTACAGG Rice (Oryza sativa L.) Kang et al. (2002) FVIIEX8 ATGCACACACACAGG Human (Homo sapiens) Jeffreys et al (1985)

3.3.4.3 Optimizing PCR composition and thermo cycling parameters for DAMD primers

Initially ,the following PCR components were used for the amplification using the DAMD primers: 1 µL each of the DAMD primers (as listed in Table 3.3), 2 µL of the 5 x colour-less Go Taq Flexi reaction buffer (Promega, Madison, USA), 4 mM MgCl2, 0.4 µL of equimolar mix of 10 mM dNTPs (Fisher Biotech) and 0.1 µL of Taq DNA polymerase. (Go Taq Flexi, Promega).

The magnesium chloride concentration of the PCR reaction for the DAMD primers was adjusted to give concentrations of 1, 2, 3, or 4 mM.

Work on optimizing the thermocycling parameters for DAMD primers included a touch-down temperature profile (Td-DAMD-PCR) as described below:

Denature at 94°C for 5 min Denature at 94°C for 30 sec Anneal at 60°C for 45 sec 9 cycles Decrease by 0.5 °C every cycle Extend at 72°C for 3 min Denature at 94°C for 30 sec Anneal at 55°C for 45 sec 30 cycles Extend at 72°C for 3 min Extend at 72°C for 5 min

The annealing temperature was also adjusted to 58°C. The final thermocycling conditions used for DAMD primers in this study is as follows:

Denature at 94°C for 3 min 1 cycle Denature at 94°C for 1 min Anneal at 55°C for 1 min and 30 sec Decrease by 0.5 every cycle 10 cycles Extend at 72°C for 2 min Denature at 94°C for 1 min Anneal at 45°C for 1 min and 30 sec 35 cycles Extend at 72°C for 2 min Extend at 72°C for 10 min 1 cycle

3.3.4.4 Optimizing magnesium chloride concentration According to Innis et al. (1990), the concentration of magnesium in PCR mixtures affects the annealing of primers, the temperature at which both template and amplicon DNA dissociate, amplicon specificity, the formation of primer dimers as well as enzyme activity and specificity. In addition, as both DNA template and dNTPs can bind magnesium, the reaction mixture must contain an excess of magnesium to that bound, as thermostable DNA polymerase requires magnesium as a co-factor (Markoulatos et al., 2002). Thus, insufficient magnesium in a PCR mixture can cause the reaction to fail whilst excess can result in the generation of unwanted products due to a reduction in the fidelity of DNA polymerases. Most PCRs are run at magnesium concentrations of ~1.5 mM (Coen, 1992; Chamberlain and Chamberlain, 1994), but PCRs should be optimized with respect to magnesium. For the primers used for DAMD:

(1) URP9F, URP6R and URP17 required 1–2 mM Mg2+; (2) URP25F required 3–4 mM Mg2+; whilst 51

(3) URP4R and URP13R worked well in all magnesium chloride concentrations (Fig. 3.0).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Figure 3.0 Six DAMD-PCR primers with variable MgCl2 concentrations

Lane 1 = molecular weight marker; lanes 2-5 = URP9F; lanes 6-9 = URP17R; lanes 10- 13 = URP6R; lanes 14-17 = URP25F; lanes 18-21 = URP4R; lanes 22-25 = URP13R; lanes 2, 6, 10, 14, 18 & 22 = 1 mM Mg2+; lanes 3, 7, 11, 15, 19 & 23 = 2 mM Mg2+; lanes 4, 8, 12, 16, 20 & 24 = 3 mM Mg2+; lanes 5, 9, 13, 17, 21 & 25 = 4 mM Mg2+.

For the 10mer RAPD primers, primers OPB01 to OPB06 gave the clearest patterns at 1– 3 mM Mg2+ (Fig.3.1) whilst OPB primers OPB07 and OPB10 worked well with the 4 mM Mg2+. All the RAPD long primers gave better band patterns at the higher concentration of 5 mM Mg2+ (Fig. 3.2).

1 23 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18192021 22 23 2425

Figure 3.1 OPB primers OPB1, OPB2, OPB3, OPB4, OPB5, OPB6 with variable

MgCl2 concentrations using DNA extracted from accession LAL AM 167 as the target.

Lane 1 = molecular weight marker; lanes 2-5 = OPB1; lanes 6-9 = OPB2; lanes 10-13 = OPB3; lanes 14-17 = OPB4; lanes 18-21 = OPB5; lanes 22-25 = OPB6; lanes 2, 6, 10, 14, 18 & 22 = 1 mM Mg2+; lanes 3, 7, 11, 15, 19 & 23 = 2 mM Mg2+; lanes 4, 8, 12, 16, 20 & 24 = 3 mM Mg2+; lanes 5, 9, 13, 17, 21 & 25 = 4 mM Mg2+.

1 mM 2 mM 3 mM 4 mM5 mM

Figure 3.2 Band patterns produced with primer long RAPD primer BOXA1R with 1-5

mM MgCl2

3.3.4.5 Optimized temperature conditions used for the primers used in this study

The thermocycling conditions that gave the best band patterns for the three techniques used are presented below.

RAPD primers

Denature at 95oC for 5 min Denature at 92oC for 30 sec Anneal at 36oC for 30 sec 44 cycles Extend at 72oC for 1 min and 30 sec Extend at 72oC for 5 min

RAPD long primers

DAMD-PCR primers

The PCR thermocyling conditions detailed above for RAPD are similar to those used by Williams et al. (1990), one of the two studies that developed RAPD using accessions of Glycine max and Glycine soja. The conditions are also similar to those used by Nagaoka and Ogihara (1997) and Vierling and Nguyen (1992) who used annealing temperatures of 36ºC and 37ºC, respectively, to look for genetic markers in wheat. The

band patterns resulting from long primer RAPD and DAMD-PCR were improved after the addition of a touchdown stage. During the touchdown stage, the annealing temperatures are high and reduce with each cycle. As a result, the primers will bind at the least-permissive temperature ensuring that the first sequences amplified are between regions of greatest primer specificity, thus reducing the chances of spurious binding (Korbie and Mattick, 2008; Roux, 2009) and reducing variation between band patterns produced by the same sample as was found in this study.

3.3.5. Agarose gel electrophoresis

PCR products were subjected to electrophoresis in 1% agarose gels containing 0.5 µg/mL ethidium bromide and the gels visualized using the Gel Documentation System (Bio-Rad) to identify the success of DNA amplifications and fragment sizes.

3.3.6 Data analysis

The presence or absence of DNA fragments generated by RAPD and DAMD from each isolate was assessed and given a score of 1 if present and 0 if absent. The data matrix was used to generate genetic distances between isolates using the method of Nei and Li (1979). These distances were used for analysis by multidimensional scaling using STATISTICA (Version 6, StatSoft, Inc.). The data matrix generated from RAPD and DAMD was used for cluster analysis using the unweighted pair group method with arithmetic mean (UPGMA) algorithm using DendroUPGMA (http://genomes.urv.cat/UPGMA/). The resulting tree was drawn using TreeView (http://taxonomy.zoology.gla.ac.uk/rod/rod.html).

3.4 Results and Discussion

3.4.1 Production of band patterns

Even though a number of steps were undertaken to optimize the PCRs, many primers using either the RAPD (Table 3.1), long primer RAPD (Table 3.2) or DAMD-PCR (Table 3.3) techniques did not generate consistent band patterns within the triplicate extracts made. Repeatable triplicate band patters were only obtained using primers OPB07 (RAPD), ERIC2, BOXAIR 1, and REP1 (long primers RAPD) and URP9F and URP25F (DAMD-PCR) primers. The PCRs using these primers resulted in the production of 46 scorable bands. The band patterns produced by a pair of accessions (LAL Am 203 and 206) were identical (see Table 3.5). This suggests that these accessions are genetically similar and may represent a pair of duplicate accessions within the collection. Further work on the genetic, morphological and chemical similarity of these accessions should be performed to determine if they are, indeed, duplicates.

Figure 3.3 Band patterns produced using primer BOXA1R with samples: LAL AM 009, LAL Am 011, LAL Am 030, LAL Am 035, LAL Am 041, LAL Am 082, LAL Am 123, LAL Am 141, LAL Am 204 all in triplicate.

Figure 3.4 Band patters produced using DAMD primer URP9F with duplicates of 14 samples.

The data matrix generated from the RAPD and DAMD band patters was analysed using the DendroUPGMA software (http://genomes.urv.cat/UPGMA/). This program calculates a similarity matrix, transforms similarity coefficients into distances and makes a clustering using the unweighted pair group method with arithmetic mean algorithm. The results of this analysis are shown in Fig. 3.5. The analysis suggests that five loose groups may exist:

• Group 1 (red): accessions 170, 180, 200, 203, 204, 206 and 220; • Group 2 (yellow): accessions 9, 11, 30, 41, 45 and 221; • Group 3 (green): accessions 16 and 35; • Group 4 (blue): accessions 134, 141 and 166; and • Group 5 (black): accessions 82 and 123.

Three accessions did not cluster with these groups (accessions 39, 84 and 175) and they appeared to be distantly related to the other accessions.

Figure 3.5 Clustering determined by UPGMA analysis of accessions of 23 accessions of aibika in the NARI collection from data based on the presence or absence of bands generated from RAPD and DAMD.

LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL LAL AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM AM 9 11 16 30 35 39 41 45 84 134 141 166 170 175 180 200 203 204 206 220 221 82 123 LAL AM 9 1.0000 0.9688 0.8889 0.9355 0.8750 0.8529 0.9538 0.9524 0.7719 0.8696 0.8696 0.8857 0.8923 0.8197 0.8571 0.8615 0.8710 0.8525 0.8710 0.8710 0.9375 0.7451 0.9048 LAL AM 11 0.9688 1.0000 0.8923 0.9063 0.9091 0.8571 0.9552 0.9231 0.7458 0.9014 0.9014 0.9167 0.8955 0.8254 0.8615 0.8657 0.8750 0.8571 0.8750 0.8750 0.9394 0.7925 0.9091 LAL AM 16 0.8889 0.8923 1.0000 0.8571 0.9231 0.8406 0.8788 0.8750 0.7931 0.8286 0.8286 0.8451 0.8485 0.7419 0.8750 0.8788 0.9206 0.8710 0.9206 0.8889 0.8615 0.8462 0.7907 LAL AM 30 0.9355 0.9063 0.8571 1.0000 0.8438 0.8529 0.9231 0.9524 0.7719 0.8116 0.8406 0.8571 0.8923 0.7869 0.8571 0.8308 0.8387 0.8197 0.8387 0.8387 0.9063 0.6800 0.8293 LAL AM 35 0.8750 0.9091 0.9231 0.8438 1.0000 0.8571 0.8955 0.8615 0.7458 0.8169 0.8169 0.8611 0.8358 0.7619 0.8615 0.8955 0.9063 0.9206 0.9063 0.9063 0.8485 0.8462 0.8372 LAL AM 39 0.8529 0.8571 0.8406 0.8529 0.8571 1.0000 0.9014 0.8406 0.6349 0.8000 0.8267 0.8421 0.8169 0.7164 0.7826 0.7887 0.7647 0.7761 0.7647 0.7647 0.8000 0.7143 0.8511 LAL AM 41 0.9538 0.9552 0.8788 0.9231 0.8955 0.9014 1.0000 0.9394 0.7333 0.8889 0.8889 0.9315 0.8529 0.7813 0.8182 0.8235 0.8308 0.8125 0.8308 0.8308 0.8955 0.7925 0.9545 LAL AM 45 0.9524 0.9231 0.8750 0.9524 0.8615 0.8406 0.9394 1.0000 0.7931 0.8571 0.8286 0.9014 0.8788 0.8387 0.8438 0.8788 0.8889 0.8387 0.8889 0.8889 0.9538 0.7451 0.8571 LAL AM 84 0.7719 0.7458 0.7931 0.7719 0.7458 0.6349 0.7333 0.7931 1.0000 0.7500 0.7500 0.8000 0.7667 0.7143 0.7931 0.8333 0.8421 0.7857 0.8421 0.8421 0.8136 0.7917 0.7179 LAL AM 0.8696 0.9014 0.8286 0.8116 0.8169 0.8000 0.8889 0.8571 0.7500 1.0000 0.9474 0.9351 0.8611 0.8529 0.8286 0.8611 0.8406 0.7941 0.8406 0.8406 0.9014 0.8814 0.9362 134 LAL AM 0.8696 0.9014 0.8286 0.8406 0.8169 0.8267 0.8889 0.8286 0.7500 0.9474 1.0000 0.9351 0.8889 0.8235 0.8571 0.8333 0.8116 0.7941 0.8116 0.8116 0.8732 0.8136 0.9167 141 LAL AM 0.8857 0.9167 0.8451 0.8571 0.8611 0.8421 0.9315 0.9014 0.8000 0.9351 0.9351 1.0000 0.8767 0.8406 0.8451 0.8767 0.8571 0.8116 0.8571 0.8571 0.9167 0.8276 0.8936 166 LAL AM 0.8923 0.8955 0.8485 0.8923 0.8358 0.8169 0.8529 0.8788 0.7667 0.8611 0.8889 0.8767 1.0000 0.8438 0.9697 0.9118 0.8923 0.9063 0.8923 0.8615 0.9254 0.7407 0.7907 170 LAL AM 0.8197 0.8254 0.7419 0.7869 0.7619 0.7164 0.7813 0.8387 0.7143 0.8529 0.8235 0.8406 0.8438 1.0000 0.8065 0.8750 0.8197 0.8000 0.8197 0.8525 0.8889 0.6667 0.7500 175 LAL AM 0.8571 0.8615 0.8750 0.8571 0.8615 0.7826 0.8182 0.8438 0.7931 0.8286 0.8571 0.8451 0.9697 0.8065 1.0000 0.9394 0.9206 0.9355 0.9206 0.8889 0.8923 0.7692 0.7317 180 LAL AM 0.8615 0.8657 0.8788 0.8308 0.8955 0.7887 0.8235 0.8788 0.8333 0.8611 0.8333 0.8767 0.9118 0.8750 0.9394 1.0000 0.9538 0.9375 0.9538 0.9538 0.9254 0.8148 0.7907 200 LAL AM 0.8710 0.8750 0.9206 0.8387 0.9063 0.7647 0.8308 0.8889 0.8421 0.8406 0.8116 0.8571 0.8923 0.8197 0.9206 0.9538 1.0000 0.9508 1.0000 0.9677 0.9375 0.8627 0.7317 203 LAL AM 0.8525 0.8571 0.8710 0.8197 0.9206 0.7761 0.8125 0.8387 0.7857 0.7941 0.7941 0.8116 0.9063 0.8000 0.9355 0.9375 0.9508 1.0000 0.9508 0.9508 0.8889 0.8000 0.7500 204 LAL AM 0.8710 0.8750 0.9206 0.8387 0.9063 0.7647 0.8308 0.8889 0.8421 0.8406 0.8116 0.8571 0.8923 0.8197 0.9206 0.9538 1.0000 0.9508 1.0000 0.9677 0.9375 0.8627 0.7317 206 LAL AM 0.8710 0.8750 0.8889 0.8387 0.9063 0.7647 0.8308 0.8889 0.8421 0.8406 0.8116 0.8571 0.8615 0.8525 0.8889 0.9538 0.9677 0.9508 0.9677 1.0000 0.9375 0.8235 0.7805 220 LAL AM 0.9375 0.9394 0.8615 0.9063 0.8485 0.8000 0.8955 0.9538 0.8136 0.9014 0.8732 0.9167 0.9254 0.8889 0.8923 0.9254 0.9375 0.8889 0.9375 0.9375 1.0000 0.7925 0.8372 221 LAL AM 82 0.7451 0.7925 0.8462 0.6800 0.8462 0.7143 0.7925 0.7451 0.7917 0.8814 0.8136 0.8276 0.7407 0.6667 0.7692 0.8148 0.8627 0.8000 0.8627 0.8235 0.7925 1.0000 0.8444 LAL AM 0.9048 0.9091 0.7907 0.8293 0.8372 0.8511 0.9545 0.8571 0.7179 0.9362 0.9167 0.8936 0.7907 0.7500 0.7317 0.7907 0.7317 0.7500 0.7317 0.7805 0.8372 0.8444 1.0000 123

Table 3.5 Genetic distances among 23 of aibika accessions in the NARI collection calculated according to the method of Nei and Li (1979) using data from RAPD and DAMD profiles.

In addition to the UPGMA analysis, the data matrix was used to generate genetic distances using the method by Nei and Li (1979); the matrix of distances is shown in Table 3.5. The distance matrix was then used for multidimensional scaling and the clustering revealed using this technique is shown in Fig. 3.6. Accessions on the plot that are close to each other are closely related; conversely, accessions that are distantly located on the plot are distantly related. For the data as a whole, the three accessions that did not cluster in the UPGMA (LAL Am 039, 084 and 175) were widely dispersed and appeared to be distantly related to all other accessions. With respect to the data as a whole, there is also some suggestion that Dimension 1 separates the remainder of the accessions into two groups with one group having negative value for this dimension and the other group having positive values; however, this grouping is weak. The accessions that group together in the UPGMA analysis are also closely located with respect to each other in the MDS analysis. Hence, there is a good agreement between the two sets of analyses.

The groupings found by the UPGMA and MDS analyses need to be confirmed through further genotyping. If the relationships are verified, then the information can be used to inform breeding programs. For example, if a group of genotypes contain a trait or group of traits that are desired by a breeder, further crosses can be made within the group to produce new types that still contain the desired trait(s). However, if novel variation is desired, crosses can be made between accessions that are distantly related. The accessions that did not cluster with the others (LAL Am 039, 084 and 175) may represent interesting sources of germplasm for further work.

2.0

175 1.5

1.0 30 170 180 0.5 45 204 9 221 200 39 220 0.0 11 206 203 41 166 Dimension Dimension 2 -0.5 84 141 123 134 -1.0

-1.5 82

-2.0 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Dimension 1

3.5 Conclusion

Although many primers were studied which, included primers used for both the RAPD and DAMD techniques, there were a number of problems encountered throughout this work. There was considerable work done to improve the quality and quantity of the DNA, optimization of the thermocycling parameters as well as the magnesium concentration. With all these efforts, only seven out of a total of 32 primers gave scorable bands. Analysis of bands divided the 23 varieties into 5 main groups with three accessions that did not group with the rest. However, the groups do not match the morphological characterization of the leaves.

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Chapter 4 DNA Sequencing

Introduction

Plants have three sources of DNA available for genetic studies, the maternally inherited mitochondrial and chloroplastal genomes and the biparentally inherited nuclear genome. In contrast to genetic studies on animals, the plant mitochondrial genome has been little used due to its unstable and variable structure and a low rate of nucleotide substitutions (Palmer and Herbon1989; Fauronet al. 2004). Most studies have concentrated on chloroplast sequences and, more latterly, on nuclear encoded genes.

Chloroplast DNA (cpDNA) has been used to examine plant phylogenetic relationships at different taxonomic levels (Geilly and Taberlet 1994). Noncoding cpDNA (intron and intergenic spacer regions) tend to evolve more rapidly than coding sequences and accumulate insertion/deletions at least equal to that for nucleotide substitutions (Zurawski and Clegg 1987; Clegg and Zurawski 1991; Geilly and Taberlet 1994), and Geilly and Taberlet (1994) found that trnL intron and trnLF intergeneric region evolve 1.9 and 11.7 times faster than the gene encoding the large subunit of ribulose-1,5- bisphosphate carboxylase oxygenase RUBISCO. For this reason, noncoding regions of cpDNA are appropriate for studies of low taxonomic levels and numerous cases of intraspecific variation have been reported (Soltis et al. 1991). Primers have been designed for various different noncoding regions that work on a wide taxonomic range of plants and the regions are small enough to allow sequencing using the amplification primers facilitating the use of these regions for genetic studies.

The most commonly used region of the nuclear genome for genetic studies is the internal transcribed spacer (ITS) region of nuclear ribosomal DNA. The rRNA genes are arranged in tandem repeats and, despite their large copy number, are usually homogenous due to concerted evolution (Buckler et al. 1997). Between the 18S small ribosomal subunit and the 28S large subunit lies the two internal transcribed spacers

separated by the 5.8S subunit. The RNAs encoded by these regions are not incorporated into ribosomes, but appear to be involved with ribosome maturation (Baldwin et al. 1995). These spacers, therefore, must be under some evolutionary constraint; however, they are frequently used to infer relationships at the interspecific level (Baldwin et al. 1995) and may also show some level of intraspecific variation (Baldwin et al. 1995; Mayer and Soltis 1999).

This chapter explores the use of two cpDNA regions, the psbM-trnD and the trnL-trnF intergenic spacer regions, and the nuclear encoded ITS region to determine if genetic variation could be found among the accessions of aibika in the collection at National Agricultural Research Institute.

The materials and methods section as well as the results are discussed or described separately for each of the three regions mentioned above. It should also be noted that under ITS region, some accessions though small were collected only once from Bubia which were included.

4.1 Materials and methods

4.1.1 Plant materials and DNA extraction

Total DNA from the accessions given in Table 4.0 was extracted from 100 mg aliquots of tissue ground in liquid nitrogen using the DNeasy Plant Mini kit (Qiagen) following the manufacturers’ instructions.

Table 4.0 Accession used for sequencing

Target Sequence trnL-F region

LAL Am 009, LAL Am 011, LAL Am 016, LAL Am 030, LAL Am 035, LAL Am 039, LAL Am 041, LAL Am 045, LAL Am 060, LAL Am 082, LAL Am 084, LAL Am 123, LAL Am 134, LAL Am 141, LAL Am 154, LAL Am 162, LAL Am 164, LAL Am 166, LAL Am 167, LAL Am 170, LAL Am 175, LAL Am 186, LAL Am 220, LAL Am 221

Target Sequence psbM-trnDGUC and trnCGCA-ycf6 regions

LAL Am 009 LAL Am 011 LAL Am 016 LAL Am 030 LAL Am 035 LAL Am 039 LAL Am 041 LAL Am 045 LAL Am 060 LAL Am 082 LAL Am 084 LAL Am 123 LAL Am 68

134 LAL Am 141 LAL Am 154 LAL Am 162 LAL Am 164 LAL Am 166 LAL Am 167 LAL Am 170 LAL Am 175 LAL Am 186 LAL Am 191 LAL Am 200 LAL Am 203 LAL Am 204 LAL Am 206 LAL Am 207 LAL Am 220 LAL Am 221

Target Sequence ITS regions

Laloki accessions: LAL Am 009, LAL Am 011, LAL Am 016, LAL Am 032, LAL Am 035, LAL Am 035, LAL Am 039, LAL Am 041, LAL Am 60, LAL Am 081, LAL Am 122, LAL Am 123, LAL Am 134, LAL Am 141, LAL Am 164, LAL Am 166, LAL Am 167, LAL Am 203, LAL Am 221, LAL Am 221, LAL Am 222. Bubia accessions: B4, B5, B6, B7, B9, B10, BPS 001, BPS 004, BPS 006, NAR 004, ONO 001, KISU 002, HLB 003

4.1.2 DNA amplification

Two spacer regions of the maternally-inherited chloroplast genome and part of the nuclear-encoded ITS region were amplified from DNA extracts using the polymerase chain reaction (PCR). PCR was performed using: Taq DNA polymerase (5 U/µL) (New

England Biolabs); 10 × Thermopol buffer (New England Biolabs, [MgSO4] = 2 mM); an equimolar mix of 10 mM dNTPs (Fisher Biotech); and acetylated bovine serum albumin (BSA, 10 mg/mL) (Promega) as an enzyme stabilizer. All primers were diluted to 10 µM before use.

Table 4.1 List of primer sequences and references used for sequence analysis

Target Forward 5′ – 3′ primer sequence Reference sequence and reverse primer names trnL-F C CGA AAT CGG TAG ACG CTA CG Taberlet et al. (1991) F ATT TGA ACT GGT GAC ACG AG Taberlet et al. (1991) psbM- trnDGUCR GGG ATT GTA GYT CAA TTG GT Shaw et al. trnDGUCspacer (2005): modified from Demesure et al. (1995) psbMF AGC AAT AAA TGC RAG AAT ATT TAC Shaw et al. (2005) TTC CAT ITS ITS1 TCC GTA GGT GAA CCT GCG G White et al. (1990) ITS4 TCC TCC GCT TAT TGA TAT GC White et al. (1990) 69

4.1.3 PCR conditions for trnL-F

The chloroplast trnL (UAA) 5’ exon and trnF (GAA) region was amplified from total genomic DNA using the universal primers c and f (Table 4.1 and Figure 4.0). The expected size of PCR products is from 300 bp to 650 bp with primers c & d and 250 bp to 650 bp with primers e & f depending on the species (Taberlet et al. 1991). The accessions of aibika used are listed in Table 4.0. The PCR reaction mixture contained 2.5 L of Thermopol buffer, 1 L dNTPs, 0.5 L Taq polymerase, 3 L each primer, 0.5 L BSA and 50 ng of template DNA in a total reaction volume of 25 L. The thermal cycling parameters were: an initial denaturation for 5 min at 94°C; 30 cycles of 94°C for 1 min, annealing at 55°C for 1 min, and elongation at 72°C for 2 min; followed by an elongation step of 72°C for 5 min.

trnT (UGU) trnL (UAA) 5´exon trnL (UAA) 3´exon trnF(GAA)

a c e

b d f

Figure 4.0 Positions and directions of universal primers for trnL-F region (Taberlet et al. 1991).

4.1.4 PCR conditions for psbM-trnDGUC

The psbM-trnDGUC spacer region (Figure 4.1) was amplified using primers psbMF and trnDGUCR (Table 4.1; Shaw et al. 2005). The accessions of aibika used in this region are listed in Table 4.0. The concentration of reagents in each 25 L reaction were: 2.5 µL of 10 × Thermopol buffer; 1 µL dNTPs; 0.5 µL Taq polymerase; 1 L each primer; 0.5 µL BSA; and 50 ng of template DNA. The mixture was initially denatured at 94°C for 5 min, followed by 35 cycles of 1 min denaturation at 94°C, 1 min annealing at 55°C, 3.5 min extension at 72°C and a final elongation period at 72°C for 5 min. According to Shaw et al. (2005), the average length of this spacer is 965 bp and ranges from 506– 1801 bp.

psbMR ycf6R trnDGUCR Taxodium-psbMF2 psbMF ycf6F trnCGCAF

trnD psbM ycf6 trnC

Figure 4.1. Positions and directions of primers for psbM-trnDGUC and trnCGCA-ycf6 regions (Shaw et al. 2005).

4.1.5 PCR conditions for ITS

The ITS region of rDNA (Figure 4.2) was amplified using primers ITS1 and ITS4 (Table 4.1; White et al. 1990). The accessions of aibika used in ITS study are listed in Table 4.0, included with the main aibika collection from Laloki (PNG) were 15 other accessions from Bubia which has a smaller aibika germplasm collection. The reaction mixture (25 L) contained: 2.5 L of 10 × Thermopol buffer; 0.5 L mixed dNTPs; 0.25 L Taq polymerase; 0.5 L BSA; 1 L of each primer; and 50 ng of extracted DNA. The samples were denatured at 94°C for 90 sec, followed by 30 cycles of denaturation (95°C for 50 sec), annealing (55°C for 70 sec) and extension (72°C for 90 sec) and then by an elongation step of 3 min at 72°C.

NS5 ITS1 ITS2

5.8S 18S rRNA rRNA 28S rRNA gene gene gene

NS6 ITS4

ITS regions

Figure 4.2 Positions and directions of primers for ITS regions (http://www.fao.org/ DOCREP/005/ X4946E/x4946e06.gif).

4.1.6 DNA sequencing and sequence analysis

PCR products from all the three regions were subjected to electrophoresis in a 1% agarose gel containing 0.5 µg/ml ethidium bromide and the gel visualised using the Gel Documentation System (Bio-Rad) to identify the success of DNA amplifications. Successful amplifications were purified using the Wizard® SV Gel and PCR Clean-Up System (Promega) following the manufacturer’s instructions. The purified PCR products were quantified using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific) and diluted to 50 ng/L. Both strands of purified fragments were sequenced using the same primers as were used for amplification (Table 4.1) by automated sequencing using an Applied Biosystems 3730XL sequencer at Macrogen Inc. (908 World Meridian Venture Center, #60–24, Gasan-dong, Geumchun-gu, Seoul 153–781, Korea).

The sequence data obtained were compared to those in DNA databases using the Basic Local Alignment Search Tool (BLAST) (Altschul et al. 1990) searches via the National Center for Biotechnology Information website (http://www.ncbi.nlm.nih.gov/). DNA Baser software (Version V.2.91, Heracle BioSoft) was used to compile contiguous sequences (contigs) and sequence alignments were obtained using ClustalW (Thompson et al. 1994) as implemented in Bioedit (Hall 2001, Version 5.0.6); each alignment was subsequently checked by eye.

4.2 Results

4.2.1 trnL-F spacer

Sequence data from 20 accessions of A. manihot were obtained. From these sequences, 18 contig were made with an average length of ~1000 nt. Comparisons of the sequencing data showed no differences in sequence among the 20 accessions. The contig from LAL Am 141 was submitted to GenBank (accession number KC488172). No sequences from Abelmoscus spp. for the trnL-F spacer have been placed in GenBank. However, a BLAST search showed that the contig has 95% identity over 229 nt for the 1st half of the intron and 98% identity over 739 nt for the remainder of the intron, the 2nd exon and part of the intergenic region from Hibiscus rosa-sinensis (AY328142). The contig also has 94% similarity over 1021 nt for all regions of the spacer from Hibiscus syriacus (AY328143).

The structure of the spacer is shown in Figure 4.3. The major differences among the three species occur in the intron of the trnL gene. The sequences from A. manihot share a small insert of 4 nt and a larger insert of 40 nt compared with that from H. syriacus. However, the sequence from H. syriacus has an insert of 20 nt not found in A. manihot or in H. rosa-sinensis. There is also a region from 808–821 nt where the sequences from H. syriacus differs from that of the other two species due to the presence of insertions and base changes.

------trnL gene------><------intron------

10 20 30 40 50 60 70 80 90 100

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142CGAAATCGGTAGACGCTACGAACTTAATTGGATTGAGCCTTGGTATGGAAACCTACTAAGTGATAACTTTCAAATTCAGAGAAACCCTGGAATGAAAAAT

AY328143...... G......

LAL AM 141------......

------intron------

110 120 130 140 150 160 170 180 190 200

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142GGGCAATCCTGAGCCAAATCCTATTATTTTACGAAAATAAACATAAACAAAAGTTCAGCAAGCGAGAATAATAATAATAAA----GGAAAGGATAGGTGC

AY328143...... G...... A...... AAAA......

LAL AM 141 ...... AAAA......

------intron------

210 220 230 240 250 260 270 280 290 300

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142AGAGACTCAATGGAAGCTATTCTAACAAATGGGGTTGACTGTTGGTAAAGGAATCCTTATATCGAAACTCCGGA------

AY328143...... A..AAGGATGCAAGATATACCTATATAAA

LAL AM 141...... -----...... T...A..AAGGATGCAAGATATACCTATATAAA

------intron------

310 320 330 340 350 360 370 380 390 400

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142------TAGGTATACTAACGAAAAACTATCTCAAAAAA------GACGACCCGAACCCGTATTTTTTTTATATGCAAA

AY328143-TAATAAAAAAGAA...... T...... TGAAAAACTATCTCAAAAAA......

LAL AM 141ATAAAAAAAAAAAA...... ------...... -......

------intron------

410 420 430 440 450 460 470 480 490 500

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142ATCTATTTATATGAAATATGAAAAATAAAAAGAATTGTTGTGAATCGATTCCAAGTTGAAGAAAGAATCGAATAGAATATTCATTAATCAAATCATTCAC

AY328143...... ------...... C......

LAL AM 141...... ------..--......

------intron------

510 520 530 540 550 560 570 580 590 600

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142TCCATAGTCTGATAAATCTTTTGAAAAAACTGATTAATCGGACGAGAATAAAGATAGAGTCCCGTTCTACATGTCAATATCAATACCGACAACAATGAAA

AY328143...... -......

LAL AM 141...... -......

----intron---><------trnL gene------><------intergenic spacer------

610 620 630 640 650 660 670 680 690 700

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142TTTATAGTAAGAGGAAAATCCGTCGACTTTAAAAATCGTGAGGGTTCAAGTCCCTCTATCCCCAACCCCAAAAAGTCCGTTTGCTATCTATTTATTTTAT

AY328143...... C......

LAL AM 141......

------trnL-trnF intergenic spacer------

710 720 730 740 750 760 770 780 790 800

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142CCTACCTTTT--TTTGTTAGGGGTTCAAAGTTCCTTCTGTTTCTCATTCATCCTATTCTTTGCCATTTTACAAGCGTATCCTAGCAGAATTTTGTTCTCT

AY328143...... C...---...... T......

LAL AM 141...... TT...... G......

------trnL-trnF intergenic spacer------

810 820 830 840 850 860 870 880 890 900

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142TATCACA----TCACAA-GTCTTGTGATATATTGTGATATATATAT--GATATACGTACAAATCTCTTGAGCAAGGAATACCTATTTGAATGATTCATAA

AY328143...... AGTC.TGTG.TA.A...... --......

LAL AM 141...... ----...... -...... AT......

------trnL-trnF intergenic spacer ------

910 920 930 940 950 960 970 980 990 1000

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142TCCATATGATTACTCATATGGAAATTTACAAAGTCTTCCTTTTAAAGATCCAAGAAATTTCCGTTCGAGACTTTTCATTTAATACTTTTTCGTTTTTTTT

AY328143...... A....C...... ----CG.....

LAL AM 141 ...... -......

------trnL-trnF intergenic spacer ------

1010 1020 1030 1040 1050 1060 1070 1080 1090 1100

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

AY328142TTGTTTTCATTTTTAATTGACATAGACCCAAGTCATCTAGTATTATGAGGATAATGCGTCGGTAATGGTCGGGATAGTTAAGTTGGTAGAGCAGAGGACT

AY328143...... C.C......

LAL AM 141...... A...... C.------

------

1110 1120

....|....|....|....|....|..

AY328142GAAAATCCTCGTGTCACCAGTTCAAAT

AY328143......

LAL AM 141------

Figure 4.3 The trnL-F regions from A. manihot (LAL Am 141), H. rosa-sinensis (AY328142) and H. syriacus (AY328143)

4.2.2 psbM-trnDGUC spacer

Sequence data was obtained for 30 forward sequences and 9 reverse sequences. No sequence variation was found among the accessions at this region. Data from one of the accessions, LAL Am 167 was contig and submitted to GenBank (accession number KC488171). This contig was used for a BLAST search and the search showed that the contig had identities of 97, 97 and 96% over 495–499 nt for H. mechowii (AY727113), H. cannabinus (AY727114) and H. macrophyllus (AY727112), respectively. In general, these sequences were similar to each other (Fig. 4.4) with the main differences occurring in regions where there were repeats of single nucleotides. The sequence from A. manihot differed from the others in that it had a small deletion at nucleotides 321– 333 and variation in sequence at bases 390–339.

10 20 30 40 50 60 70 80 90 100

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

LAL AM 167--TTTTTTTTTTCCTTCGCAATAACTCGGGATTTAATCCCATAGAGATGATAAATTTGTCGCTTGTAAATTCAATGCAATGACTTACATTTCAATGACAT

AY727113TTGTTTTTTTT-CCTTCGCAATAACTCGGGATTTAATCCCATAGAGATGAAAAATTTGTCGCTTGTAAATTCAATGCAATGACTTACATTTCAATGACAT

AY727114TTGTTTTTTTTTCCTTCGCAATAACTCGGGATTTAATCCCATAGAGATGAAAAATTTGTCGCTTGTAAATTCAATGCAATGACTTACATTTCAATGA-AT

AY727112TTGTTTTTTTT-CCTTCGCAATAACTCGGGATTTAATCCCATAGAGATGATAAATTTGTCGCTTGTAAATTCAATGCAATGCCTTACATTTCAATGACAT

110 120 130 140 150 160 170 180 190 200

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

LAL AM 167CGAATCGGATCAATATCATGAATAACAATATCTAAGCTATCAAATCGATTCACCGTCGAGAATTGAATAGTATAACATAGGAAGATCTTTTATCCACACC

AY727113CGAATCGGATCAATATCATGAATAACAATATCTAAGCTATCAAATCGATTCACCGTCGAGAATTGAATAGTATAACATAGGAAGATCTTTTATCCACACC

AY727114CGAATCGGATCAATATCATGAATAACAATATCTAAGCTATCAAATCGATTCACCGTCGAGAATTGAATAGTATAACATAGGAAGATCTTTTATCCACACC

AY727112CGAATCGGATCAATATCATGAATAACAATATCTAAGCTATCAAATCGATTCACCGTCGAGAATTGAATAGTATAACATAGGAAGATCTTTTATCCACACC

210 220 230 240 250 260 270 280 290 300

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

LAL AM 167GAATACAAAAATGGATTCCTGGTCCAATCAAAAGAATTCCTTTCCTTTATTTAT------ATATTCTTTTCCACTCTTTCTTTTCGATAATCTACCGTCT

AY727113GAATACAAAAATGGATTCCTGGTCCAATCAAAAGAATTCCTTTCCTTTATTTAT------ATATTCTTTTCCACTCTTTCTTTTCGATAATCTACCGTCT

AY727114GAATACAAAAATGGATTCCTGGTCCAATCAAAAGAATTCCTTTCCTTTATTTAT------ATATTCTTTTCCACTCTTTCTTTTCGATAATCTACCGTCT

AY727112GAATACAAAAACGGATTCCTGGTCCAATCAAAAGAATTCCTTTCCTTTATTTATATATATATATTCTTTTCCACTCTTTCTTTTCGATAATCTACCGTCT

310 320 330 340 350 360 370 380 390 400

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

LAL AM 167TCCTTGTACAATCATCTGAT---GTATCATCTGACTACTTTTCCACTTTCACCGTTTACAAATAGTTTACAAATAAACCCCAACAAAAACAAAAAATAGA

AY727113TCCTTGTACAATCATCTGATGATGTATCATCTGACTGCTTTTCCACTTTCACCGTTTACAAATAGTTTACAAATAAACCCCAACAAAAAATAGAAAGGAA

AY727114TCCTTGTACAATCATCTGATGATGTATCATCTGACTGCTTTTTCACTTTCACCGTTTACAAATAGTTTACAAATAAACCCCAACAAAAAATAGAAAGGAA

AY727112TCCTTGTACAATCATCTGATGATGTATCATCTGACTGCTTTTCCACTTTCACCGTTTACAAATAGTTTACAAATAAACCCCAACAAAAA-TAGAAAGAAA

410 420 430 440 450 460 470 480 490 500

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

LAL AM 167AAGAAAAAAAAAAA---GATATCGTTGGGAATGAAATTCTATCATTTGTATCCCCTTTGACAGAAAACGGAGGGATCGATTGATGTATTTTTTTAATTGT

AY727113AAAATAAAAAAAAAA--GATATCGTTGGGAATGAAATTCTATCATTTATATCCCCTTTGACAGAAAACGGAGGGATCGATTAATGTATTTTTTTAATTGT

AY727114AAAAAAA------GATATCGTTGGGAATGAAATTCTATCATTTATATCCCCTTTGACAGAAAACGGAGGGATCGATTGATGTATTTTTTTAATTGT

AY727112AAAATAAAAAAAAAAAAGATATCGTTGGGAATGAAATTCTATCATTTATATCCCCTTTGACAGAAAACGGAGGGATCGATTGATGTATTTTTTTAATTGT

510 520 530

....|....|....|....|....|....|...

LAL AM 167ATCCGTCGGGACTGACGGGGCTCGAACCCGCAG

AY727113ATCCGT------

AY727114ATCCGT------

AY727112ATCCAT------

Figure 4.4 Sequence data from LAL Am 167, H. mechowii (AY727113), H. cannabinus (AY727114) and H. macrophyllus (AY727112) for the psbM-trnDGUC spacer region

4.2.3 ITS

The sequencing of the ITS region using the reverse primer was successful for accessions LAL Am 084, LAL Am141, LAL Am 011, LAL Am60, KISU 002, NAR 004, HLB 003, LAL Am 122, B6, B9, B10, BPS006, LAL Am 016 LAL Am 203 and LAL Am 221. However, sequence data using the forward primer was poor and only gave readable sequences for accessions LAL Am 011, LAL Am 016 and LAL Am 122. The data from accession LAL Am 122 was submitted to GenBank (accession number KC48173). Analysis of the whole data set using DNA Baser showed that the sequences from all accessions were identical with the exception of LAL Am 221 where the sequence data from the reverse primer suggested that there were 11 differences from the rest of the data (Fig. 4.5). The contig from LAL Am 122 was used for BLAST searches. This contig had 98% identity with the sequence, JF421456, from A. manihot over 352 nt which contains the ITS2 region and parts of the 5.8S and 28S ribosomal RNA genes. The contig from LAL Am 122 also had 94% identity over 680 nt with sequence, JQ230968, from A. moschatus; this sequence contains the complete sequences of the ITS1 and ITS2 regions and 5.8S ribosomal RNA gene as well as part of the 28S ribosomal RNA gene. No other ITS sequences from Abelmoschus species are found within GenBank.

------internal transcribed spacer 1------

10 20 30 40 50 60 70 80

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456 ------

LAL AM 122TGTTATMGAAAAACAACGGGACGGGCGAGGYGGGATCCCCKCCCCTCRTCCCGCCCCGCCCCGGTGCCCCTCGCCGTCGC

LAL AM 221------CCTCSTCCCGCCTCGCCCCGGTGCCCTTSTCCGCCCC

------internal transcribed spacer 1------

90 100 110 120 130 140 150 160

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456 ------

Contig 122CTCCCCCTCGCCTCACGGTGTCGCGGGATGCACGGCCCCGGGCCTTCGGGGCGAAACGAACAACCCCCGGCGCGAATCGC

Contig L221 CTCCCCCTCGCCGCACGGTGTCGCGGGATGCACGGCCCYGGGCCTCCGTGGSGAAACGAACAACCCCCGGCGCGAATCGC

------internal transcribed spacer 1------

170 180 190 200 210 220 230 240

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456 ------

Contig 122 GCCAAGGAATCTGAATTGAAAGGAGCACGTCCCCCGTCGCCGCCCCGTCCGCGGTGCGCGTGCCGCGGGGACGCTGCGAC

Contig L221 GCCAAGGAATCTGAATAGAAAGAAGCACGTCCCCCGTCGCCGCCCCGTCCGCGGTGCGCGTGCTGCGGGGACGCTGCGAC

------><------5.8S ribosomal RNA------

250 260 270 280 290 30 310 320

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456------

Contig 122TTCGTCGTGAATACACAAAACGACTCTCGGCAACGGATATCTCGGCTCTCGCATCGATGAAGAACGTAGCGAAATGCGAT

Contig L221 TTCGTCGTGAATACACAAAACGACTCTCGGCAACGGATATCTCGGCTCTYGCATCGATGAAGAACGTAGCGAAATGCGAT

------5.8S ribosomal RNA------

330 340 350 360 370 380 390 400

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456------TGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCCAAGCCGTCAGGCCGAGGGCA

Contig 122ACTTGGTGTGAAT......

Contig L221 ACTTGGTGTGAAT......

------><---- internal transcribed spacer 2------

410 420 430 440 450 460 470 480

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456CGTCTGCCTGGGTGTCACGCATCGTCGCTCCCATCCAACCCCTCCCCCC--GGGGACGGGCTGCGGTGTGGGCGGACAAT

Contig 122 ...... T...... GAAC...... T......

Contig L221 ...... T...... T.....GAA-...A.....T....T......

------internal transcribed spacer 2------

490 500 510 520 530 540 550 560

....|....|....|....| ....|....|....|....|....|....|....|....|....|....|....|....|

JF421456GGCCTCCCGTTCGCACACCGCTCGCGGTTGGCCCAAAATCGAGTCATCGGCGACCACGGTGCCGCGACGATCGGTGGTAAC

Contig 122......

Contig L221 ...... T...... Y......

------internal transcribed spacer 2------

570 580 590 600 610 620 630 640

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456GCTTCGAGCTGCCTCTTTCGTAGTCGCGCGCTAACGTCGTCCCCGGCTCCCCGACCCTTTCGGCACCGCAAGCACGGTGC

Contig 122...... A......

Contig L221 ....T...... Y...... G...... A...... ATT...... Y...... A......

-----><------28S ribosomal RNA------

650 660 670 680 690 700 710 720

....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456CCGCGTCGCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAAGCATATCAATAAGCGGAGGAAAAGAAACTTACCAG

Contig 122...... Y...... ------

Contig L221 T...... ------

------28S ribosomal RNA ------

730 740 750 760 770 780 790

....|....|....|....|....|....|....|....|....|....|....|....|....|....|

JF421456GATTCCCTTAGTAACGGCGAGCGAACCGGGAATAGCCCAGCTTGAGAATCGGTCGCCCACGGCGTCCGA

Contig 122------

Contig L221 ------

Figure 4.5 Comparison of sequences of the internal transcribed spacer regions from accessions LAL Am 122 and 221 from the collection at National Agricultural Research Institute with sequence JF421456 from A. manihot obtained from GenBank

4.3 Discussion

A number of studies have found variation at the infraspecific level using sequence data obtained from the ITS region or from cpDNA sequences. Systma and Schall (1990) found length variation in the five out of seven populations of Lisianthus skinneri. Balwin (1993) found up to 3.7% nucleotide sequence divergence within species of Calycadenia and seven ITS types were found in Stylosanthes guianensis guianensis (van der Stappen et al. 1998) and 127 ITS types were distributed among three species of Arabis (Koch et al. 2003). Using the same primers as this current study (c and f), Widmer and Baltisburger (1999) were able to detect nine cpDNA haplotypes of Draba aizoides based on sequencing the trnL-trnF spacer region andFujii et al 1997) found 15 cpDNA haplotypes from 25 individuals of Pedicularius chamissonis and the the trnL- trnF integenic spacer varied from 373–398 bp. However, despite the intraspecific variation found in these studies, no sequence variation was found among the accessions of aibika used in this study. Therefore, the use of chloroplastal or ITS regions would not be a suitable approach for further studies on the genetic variability within aibika.

The ITS primers used in this study are designed against highly conserved regions of the 18 and 28S rRNA genes. Therefore, it is possible to amplify sequences from other organisms. Previous studies have inadvertently amplified sequences from algal contaminants (Hershkovitz and Lewis 1996) or from endophytic fungi (Camacho et al. 1997). BLAST searchers were performed on all sequences obtained in this study and all sequences matched either those from Abelmoschus or Hibiscus and, therefore are presumed not to be from contaminants.

A review of the sequences within GenBank show that few have been submitted for the genus Abelmoschus.

4.4 Conclusion

It can be concluded that the sequencing work done on the 20 accessions investigating the ITS and the two chloroplastal gene sequences, in general, did not show any variation among the aibika accessions. It can also be seen that when contigs from some of the accessions using the chloroplastal and the ITS regions were searched online using BLAST, the contigs had substantial identity with accessions from the genera Abelmoschus and Hibiscus. Due to the fact that no work has been done on the sequencing of aibika and this study being the preliminary study, there was no specific reason for the choice of the chloroplastal or the ITS regions studied and the primers used. Other primers or chloroplastal regions may give better results.

4.5 References

Altschul, S. F., Gish, W., Miller, W., Myers, E. W., Lipman, D. J. (1990). “Basic local alignment search tool”. J. Mol. Biol. 215:403-410.

Baldwin, B. G., Sanderson, M. J., Porter, J. M., Wojciechowski, M. F., Campbell, C. S., Donoghue, M. J. (1995). “The ITS Region of nuclear ribosomal DNA: a valuable source of evidence on angiosperm phylogeny”. Annals of the Missouri Botanical Garden82: 247-277.

Balwin, B. G. (1993). “Molecular phylogenetics of Calycadenia (Compositae) based on ITS sequences of nuclear ribosomal DNA: chromosomal and morphological evolution examined”. American Journal of Botany80: 222-238.

Buckler, E. S., Ippolito, A., Holtsford, T. P. (1997). “The evolution of ribosomal DNA: divergent paralogues and phylogenetic implications”. Genetics145: 821-832.

Camacho, F. J., Gernandt, D. S., Liston, A., Stone, J. K., Klein, A. S. (1997). “Endophytic fungal DNA, the source of contamination in spruce needle DNA”. Molecular Ecology6: 983–987

Clegg, M. T., Zurawski, G. (1991). Chloroplast DNA and the study of plant phylogeny. Soltis, P. S, Soltis, D. E. and Doyle, J. J. (eds). In: Molecular Systematics of Plants. Chapman and Hall pp 1-13.

Demesure, B., Sodzi, N., Petit, R. J. (1995). “A set of universal primers for amplification of polymorphic non–coding regions of mitochondrial and chloroplast DNA in plants”. Molecular Ecology4: 129–131.

Fauron,C., Allen,J., Clifton,S., Newton,K. (2004). Plant Mitochondrial Genomes. Daniell, H., Chase, C. D. (eds.). In:Molecular Biology and Biotechnology of Plant Organelles Chloroplasts and Mitochondria pp 151-177, Springer.

Geilly, L., Taberlet, P. (1994). “The use of chloroplast DNA to resolve plant phylogenies: non-coding versus rbcL sequences”. Molecular Biology and Evolution11: 769-777.

Hall, T. (2001). Bioedit Version 5.0.6. North Carolina State University, Department of Microbiology.

Hershkovitz, M. A., Lewis, L. A. (1996). “Deep level diagnostic value of the rDNA-ITS region: the case of an algal interloper”. Molecular Biology and Evolution13: 1276- 1295.

Koch, M. A., Dobeš, C., Mitchel-Olds, T. (2003). “Multiple hybrid formation in natural populations: concerted evolution of the internal transcribed spacer of numclear ribosomal DNA (ITS) in North American Arabis divaricarpa (Brassicaceae)”. Molecular Biology and Evolution20: 338-350.

Mayer, M. S., Soltis, P. S. (1999). “Intraspecific phylogeny using ITS sequences: insights from studies of the Streptanthus glandulosus complex (Cruciferae)”. Systematic Botany84: 47-61.

Palmer, J. D., Herbon,L. A. (1989). “Plant mitochondrial DNA evolved rapidly in structure, but slowly in sequence”. Journal of Molecular Evolution28: 87-97

Ritland, C. E., Ritland, K., Straus, N. A. (1993). “Variation in the ribosomal transcribed spacers (ITS 1 and ITS 2) among eight taxa of the Mimulus guttatus species complex”. Molecular Biology and Evolution.10: 1273-1288.

Shaw, J., Lickey, E. B., Miller, J., Siripun, K. C., Winder, C. T., Schilling, E. E., Small, R. (2005). “The tortoise and the hare II: Relative utility of 21 noncoding chloroplast DNA sequences for phylogenetic analysis”. American Journal of Botany92: 142–166.

Soltis, D. E., Soltis, P. S., Milligan, B. G. (1991). Intraspecific chloroplast variation: systematic and phylogenetic implication. In: Soltis PS, Soltis DE and Doyle JJ (eds) Molecular Systematics of Plants. Chapman and Hall pp 117-150.

Systma, K. J., Schall, B. A. (1990) “Ribosomal DNA variation within and among individuals of Lisianthus (Gentianaceae) populations”. Plant Systematics and Evolution170: 97-106.

Taberlet, P., Gielly, L., Pauton, G., Bouvet, J. (1991). “Universal primers for amplification of three non-coding regions of chloroplast DNA”. Plant Molecular Biology17: 1105–1109. van der Stappen, J., van Campenhout, S., Gama Lopez, Volckaert, G. (1998) “Sequencing of the internal transcribed spacer region ITS1 as a molecular tool detecting variation in the Stylosanthes guianensis species complex”. Theoretical and Applied Genetics 96: 869-877.

White, T. J., Bruns, T., Lee, S., Taylor, J. (1990).Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. Innis, M. A., Gelfand, D. H., Sninsky, J. J., White, T. J. (eds.). In: PCR Protocols: A Guide to Methods and Applications. New York: Academic Press. pp. 315–322.

Widmer, A., Baltisburger, M. (1999) “Extensive intraspecific chloroplast DNA (cpDNA) variation in the alpine Draba aizoides L. (Brassicaceae: haplotype relationships and population structure”. Molecular Ecology 8(9): 1405-1415

Zurawski, G., Clegg, M. T. (1987) “Evolution of higher-plant chloroplast DNA- encoded genes: implications for structure-function and phylogenetic studies”. Nucleic Acids Research12:2549-2559.

Chapter 5 Total Folate Composition

Vitamins are organic nutrients and include 13 different forms each of which have highly significant roles to play in the body to sustain normal growth, development and various metabolic and functional activities. Though some vitamins can be synthesised by the body, the amounts made are not sufficient and so have to be obtained from the foods in the diet. Specific deficiency diseases are manifested when the amounts provided by the diet is inadequate. Vitamins are categorised as either water-soluble or fat soluble.

In recent years, folate and/or folic acid has been a micronutrient of much discussion and research due to its established function in the prevention of foetal neural tube defects (NTD) as well as its other important roles in the body. The global prevalence of folate deficiency is not known because there is inadequate information, few countries having collected the necessary biochemical data (WHO 2008). Due to its recognised role in prevention of NTDs, several countries have adopted mandatory fortification of some commonly consumed food items such as bread and breakfast cereals, whilst a number of countries allow voluntary fortification of selected foods.

The folate status of the PNG population is not known and the local foods consumed in the country have never been analysed for folate. As discussed in Chapter 2 under the section on nutritional status in PNG anaemia is a major public health issue and it is known that folate deficiency does cause megaloblastic anaemia. In PNG, there is no food fortification with folic acid and the importance of the vitamin is not well known. More than half of the population live in rural areas so they have no access to or cannot afford folic acid fortified foods, therefore it is imperative that they are aware of sources of folate in the diet. According to the 2005 National Nutrition Survey, the iron supplement that is given to women at antenatal clinics does contain folic acid. Attendance at such clinics can be low especially for the rural women due to problems of accessibility most rural areas lack the basic infrastructures like roads and basic health services. There is no published literature on the folate status of the PNG population. A study by Dryden (1997) looked at birth defects in 10,000 babies born between the

periods of January 1985 to May 1986 in Port Moresby General Hospital. He found an overall prevalence of 1.16%, limbs, head and neck and central nervous system were the most commonly affect regions of the body. Neural tube defects accounted for 13.96% of the total 165 recognised defects. The PNGNNS 2005 did not include record of food intakes, it concentrated on micronutrient deficiencies especially that of iron deficiency, iodine and vitamin A deficiency diseases. Green leafy vegetables are very good source of the vitamins and because green leafy vegetables like aibika and various others are commonly consumed as part of main meals, they would likely be the largest contributors of folate in the PNG diet. Hence determination of folate in aibika would not only indicate the level of folate that is available in this popular plant, but also initiate the collection of folate data on other commonly consumed plant foods in the country.

This chapter discusses the importance of folate in humans, sources of folates in foods, deficiency disorders resulting from deficiency; the materials and methods used to determine folate in aibika leaves. The results of the analyses are presented, followed by discussion and conclusion.

5.1 Folate

The term folate encompasses all the derivatives of folic acid and includes both, the synthetic form of folic acid and the natural form of folates, the polyglutamates. Figure 5.1 shows the formula of the different forms of natural folates as well the folic acid, natural folates are mostly 5,6,7,8 – tetrahydro-pteroylpolyglutamates, they contain a pteridine ring along with additional glutamic acid molecules linked by γ-peptide bonds. Folates are also substituted at the N-5 or N-10 so folates forms would include 5-methyl, 5 fomyl or 10-fomyl positions (Finglass et al., 2003) Folic acid, which does not occur in nature, is the most stable and bioavailable form usually used in folic acid supplements and in folic acid fortified foods (Ramya and Tomar, 2009). Folate functions as a carrier of one carbon units generated in the cell during various metabolic reactions, the one carbon units are carried from one reaction to another (Wagner, 1995). The role of folate coenzymes are vital for the metabolism of nucleic acids and amino acids (Bailey & Gregory, 1999), biosynthesis of purine and thymidine as well as the remethylation of DNA which is vital for the regulation of gene expression, essential amino acid 92

methionine is also generated amongst other important products, via the methylation reactions (Wagner, 1995).

N "N _...... ,_c ~' c /'c'H /.._

!~/"'-/ ~ ~-~-N-o-CO--- l - cI "I "

"" "" Figure 5.0 Chemical formula of folic acid and the important natural folates Source: FAO/WHO 2002 93

5.1.1 Food sources and bioavailability of folate Folate is present in a variety of foods, but legumes, green leafy vegetables and some fruits are some of the best sources (De Benoist, 2008). Fortified cereals and bread products would be one of the major contributors in the western world or in the countries where some form of folic acid fortification is being done. Though milk itself contains a low amount of folate, the high affinity folate binding proteins in milk make it an important source. Fermented milk products on the other hand contribute considerable amounts (Witthoft et al, 1999). So eating a wide variety of foods daily should be sufficient to meet the folate requirements.

5.1.2 Dietary Folate Requirements The folate requirement is expressed as dietary folate equivalent (DFE). This is because the bioavailability of the several forms of natural occurring folate differ when compared to synthetic folic acid. DFE converts the dietary intake of both naturally occurring folate and folic acid to an equal amount of food folate (Bailey, 1998; Bailey, 2009). On this basis, folate requirement is calculated as the sum of µg food folate + (1.7 x µg folic acid), the factor 1.7 (85/50) is proposed for folic acid, which means folic acid is 1.7 times more bioavailable (Rogers, Pfeiffer, Bailey, & Gregory III, 1997). Several studies in literature show that naturally occurring folates are only 50-80% bioavailable when compared to synthetic folic acid (Pfeiffer et al, 1997; Pfeiffer, Rogers, Bailey, & Gregory III, 1997; Winkels et al, 2007) It has been suggested that folic acid should not be used as a reference folate (Wright, Dainty, & Finglas, 2007; Wright & Finglas, 2005).

It has always been accepted that biotransformation of folic acid doses to 5- methyltetrahydrofolic acid occur in the upper small intestine and this is said to be the same for all reduced naturally occurring reduced folate. Therefore, to assess relative absorption of folate in humans, folic acid is used as the reference folate. Test doses of food folates are given and the plasma response of 5-methyltetrahydrofolic acid is compared to plasma response given by a similar reference dose of folic acid (Wright & Finglas, 2005).

However, some recent studies on stable isotope studies have shown that a huge component of plasma response does not come from the test dose. Recent studies have also shown that liver is the initial biotransformation site and not the upper small intestine as once accepted. From these studies it has been concluded in principle that in long term human interventions studies, folic acid should not be used to give an estimate of the relative bioavailability of natural food folates (Wright, Dainty, & Finglas, 2007; Wright & Finglas, 2005, Wright et al., 2010).

One of the factors to consider in micronutrient deficiencies is the bioavailability of the micronutrients and factors that affect it. Folate bioavailability is an area of interest to many researchers especially in the area of establishing or calculating folate dietary requirements or reference dietary intakes. Bioavailability is a term that describes the proportion of ingested nutrient that is absorbed and becomes accessible for metabolic processes or storage (Ramya and Tomar, 2009, McNulty et al. 2004). McNulty and Pentieva (2004), list a number of factors that affect the bioavailability of folate from various foods, including; the type of food, deconjugation of polyglutamyl folates in the intestine, dietary folate stability, enhancers like ascorbate and folate binding protein and instability of the natural folates. Witthoft et al. (1999) classify the factors affecting folate bioavailability into extrinsic and intrinsic factors: intrinsic factors or those factors inherent to an individual include their folate status, gender and age, gastrointestinal functions, use of substances or medications. The extrinsic factors are similar to the ones listed in McNulty and Pentieva (2004).

There are considerable folate losses during the processes of cooking and preparation of food items. Some studies have also alluded to the fact that due to the natural folates being chemically very labile, the post-harvest processes of preparation, storage and processing would contribute to considerable loss (FAO & WHO, 2002). DeSouza and Eitenmiller (1986) studied several processing steps including comparing the effects of water and steam blanching on the retention of folate in spinach and broccoli. Their results showed greater retention of folate in steam blanched vegetables along with lowest per cent of leaching into the cooking medium. Dang et al (2000) did a study on the stability of folates in peas and chickpeas subjected to differing process conditions including soaking, boiling and pressure cooking; results showed that shorter heat 95

exposure of high pressure cooking contributed to higher retention and lower leaching into the soaking and cooking medium. McKillop et al. (2002) determined the effects of different cooking methods on the retention of folates in a number of foods consumed in the UK including spinach and broccoli. The treatments included differing cooking times and the cooking treatments used were boiling and steaming. The study showed more than 50 percent loss of folate in both vegetables when compared with the raw values and increased boiling time meant greater loss in both vegetables. Steaming on the other hand did not amount to significant loss even after the maximum period of 45 minutes. Holasova et al. (2008) did a study on determining folate values in vegetables and assessed their retention during the process of boiling. Some of their conclusions were that weight or surface ratio of the vegetables themselves and presence of endogenous antioxidants may influence folate retention during cooking and they also found that non-leafy vegetables tended to retain more folates compared to leafy vegetables during boiling.

5.1.3 Health consequences of folate deficiency

Inadequate intake of folate from the diet is the leading cause for folate deficiency diseases; dependence on a monotonous diet that lacks diversity because there is no one food that provides all the micronutrients and so eating a varied diet would ensure a supply of different micronutrients. Other causes of deficiency include: inadequate absorption due to gastrointestinal problems, or alcoholism or use of certain medications; also in the case of increased requirements, especially for pregnant and lactating women.

5.1.3.1 Megaloblastic-anaemia Storage of folate in the body is small and there is substantial amount of folate catabolism as well as losses from skin, bile and urine. Folate deficiency affects cell division, reduced availability of 5,10-methylene-tetrahydrofolate (Figure 5.2) affects DNA biosynthesis, cell division in the red blood cells is greatly affected because these cells have a high turn-over rate (FAO/WHO, 1998, Ramya & Tomar, 2009, Stanger, 2002). The red blood cells grow larger but are unable to divide in the absence of DNA synthesis. This abnormality would ultimately affect their function of oxygen transportation to the rest of the body leading to megaloblastic anaemia. Megaloblastic 96

anaemia from folate deficiency is similar to that from vitamin B12 deficiency, therefore clinical testing is integral to proper diagnosis and treatment (Wardlaw & Smith, 2013). Prolonged folate deficiency affects cell division of the white blood cells as well as the intestinal cells resulting in malabsorption, diarrhoea and an impaired immune system (Wardlaw & Smith, 2013).

5.1.3.2 Neural Tube Defects (NTDs) Neural Tube Defects are congenital malformations of the central nervous system and it is a consequence of a disruption to the formation of the neural plate, its closure and the development of the neural tube (National Academy of Sciences, 1998). All this occurs in the very early stages of pregnancy; about 21 days post fertilisation and ends at 28 days after conception (National Academy of Sciences, 1998). Incomplete closure of the spinal cord leads to spina bifida which is characterised by an opening in the spinal cord; anencephaly is as a result of incomplete closure of the cord at the skull; the former accounts for 50% of NTD cases whilst the latter 40%, other forms of NTDs account for the remaining 10% (Scott et al, 1995). Studies have shown that environmental and genetic factors also influence the causation of NTDs. Scott et al. (1995), discuss the various studies that have been done to establish the role of folate in causation of NTD. The actual mechanism of this is still being studied. The study that is most central to the supplementation and fortification of foods with folic acid is the UK Medical Research Council Trial which was a randomised, double blind study conducted in 33 centres in seven countries to study the effectiveness of folic acid supplementation on prevention of NTDs (MRC Vitamin Study Research Group, 1991). The evidence was conclusive on the efficacy of folic acid supplementation (Scott et al. 1995) based on the study countries such as the UK, the USA and most other countries who have increased the reference dietary intake of folate for women planning to be pregnant as well as for pregnant and lactating women. The link between folate deficiency and NTDs has been established by a number of studies (Wald, 1991 and Bailey et al. 2003).

5.1.3.3 Folate and homocysteine Homocysteine is found in trace amounts in the diet but is formed in the body when methionine is demethylated in the methionine cycle (Figure 5.2). Methionine is an

essential amino acid needed by the body for various protein functions. About 50 % of the homocysteine formed in the methionine cycle is remethylated to methionine. Homocysteine is also metabolised in another pathway (Figure 5.2) that leads to the formation of cysteine (Green & Jacobsen, 1995). Folate is used as a substrate in the remethylation cycle where homocysteine is converted to methionine and S-adenosyl- methionine (SAM) therefore folate deficiency leads to accumulation of homocysteine (Stanger, 2002). Remethylation to methionine depends on both folate and vitamin B12. In recent years, elevated homocysteine has attracted a lot of attention as an independent risk factor for vascular diseases (Green & Jacobsen, 1995).There is ongoing research in this area and there are some promising data showing inverse relationship between folic acid and clinical markers for vascular disease (Bailey et al. 2003). Although, the process by which folate reduces the risk of some form of cancer is not known, animal and human studies show folate depletion enhances carcinogenesis especially that of colorectal cancer (Choi & Mason, 2000).

Figure 5.1 The role that folate and its co-factors play in the DNA and methylation cycles. Source: FAO/WHO, 2002

5.1.3.4 Food based approach to increasing folate intake

Consumption of diet that is adequate in meeting the recommended folate intake is the long-term strategy for addressing the folate deficiency problem as advocated by conclusions of a WHO consultation on folate and vitamin B12 deficiencies. Supplementation and food fortification are strategies that are important in meeting needs of the populations that are not able to meet the recommended folate intake from the diet (De Benoist, 2008). Combination of all these three strategies aid in the achievement of optimum folate status.

In PNG, folic acid supplementation is included in the iron supplement that is given to women in antenatal clinics, accessibility of this supplement by women is a problem especially in the rural areas due to lack of basic infrastructure and services and can also be a problem in the urban areas due to lack of awareness and understanding of the importance of micronutrients. Fortification of foods with folic acid is currently not done in the country, there is however, mandatory iodization of all salts and there have been discussions on fortifying foods with iron in the PNGNNS 2005.

Food based strategies harness the biodiversity of food crops already available in the local diets. For this to be successful, the crops which contain folate have to be analysed to find the varieties or genotypes which are naturally high in folate. The genetic pathways, genes, enzymes etc are studied, isolated, characterised and the specific traits are introduced into other varieties. In recent years, there has been a great deal of interest and research into the area of biofortification as part of the food based strategies that can be used to address the micronutrient deficiencies in the world. Folate biofortification involves enhancing the folate content of commonly consumed foods through plant breeding or biotechnology (Dieter Blancquaert et al. 2010). The advantages are that there would be a single investment cost with the seeds being used in subsequent seasons; once the trait of interest has been introduced into the local varieties, it is highly likely to reach even the poorest populations (Dieter Blancquaert et al., 2010). For food based approach and/or biofortification to be effective or successful, food crops have to

be analysed to identify the varieties that have high folate which can then be promoted for breeding and consumption.

Green leafy vegetables are some of the very good sources of folate in the diet and since varieties of aibika and other green leafy vegetables are consumed all over the country, analysing and promoting the nutrient rich varieties for local communities to grow and consume would go a long way to contribute to folate intake in the diets. Staple diets of roots and tubers and cereals contain very little folate, green leafy vegetables, legumes and beans, other fruits and vegetables have to be incorporated into those diets to boost folate status. Inclusion of organ meats in the diet as well as awareness on the appropriate cooking, storage and processing processes are some of ways to increase folate retention and intake (FAO & WHO 2002).

In the light of the preceding discussion (food based approach), analysis of aibika varieties for folate as done in this study contributing to folate data of foods in PNG that can be used to promote nutrient rich varieties.

5.2 Materials and methods

5.2.1 Sample collection, preparation at Laloki aibika germplasm in PNG

Aibika leaves were collected from the accessions of aibika germplasm maintained at the Laloki Dry Lowlands research station located outside Port Moresby, PNG. It is one of the research stations of the PNG National Agricultural Research Institute (NARI). About 30 aibika accessions are held there in a field gene bank, the accessions are planted ten plants per accession and are harvested and replanted annually in a different plot of land.

In preparation for importing into Australia, leaves were collected from each of the ten plants for every accession. They were then cleaned and washed with water and vacuum packed and kept frozen at -20oC degrees for three (3) days to satisfy the Australian Government Quarantine requirements before being air freighted to Sydney, Australia 100

packed in ice. Upon arrival the leaves were stored at -20oC degrees in the quarantine laboratory.

5.2.2 DAFF regulations and quarantine process

Department of Fisheries, Forestry and Agriculture (DAFF) Australia, as part of their quarantine procedure also issued a pre-sample preparation procedure. According to that regulation, the leaves were to be completely homogenized and processed into a paste using a food processor, before they can be taken out of the quarantine laboratory for other sample preparation and analysis. This was done under subdued light and all glassware was wrapped with aluminium foil to prevent folate loss.

5.2.3 Moisture determination Duplicates of samples from each of the accessions were analyzed for moisture content according to the AOAC (2002) vacuum drying method. Samples were homogenized, weighed and kept overnight in a vacuum oven at 70oC after which the weights were taken and the moisture values calculated. The moisture content of the aibika samples was determined within 24 hours of their arrival in Sydney.

5.2.4 Preliminary sample preparation for micronutrient analysis

The samples were homogenized into a paste in a food processor then freeze-dried, ground into powder and stored at -20oC prior to all micronutrient analysis. This was done under subdued light and all glassware was wrapped with aluminium foil to prevent folate loss.

5.2.5 Microbiological assay procedure

Microbiological assay was done to determine the level of total folate in the accessions of aibika. The protocol used was based on Shrestha et al. (2000), Tamura et al. (1997) and Rader et al. (1998).

101

5.2.5.1 Preparation of extraction buffer (0.1 N phosphate, 1.0% ascorbic acid, pH 6.1)

13.61 g of KH2PO4 (Sigma Chemicals, St. Lois), 17.42 g K2HPO4 (Ajax Chemicals, NSW) and 10 g L-ascorbic acid (BDH Chemicals, Victoria) were dissolved in 1000 ml of milli Q water and the pH was adjusted to pH 6.1 using 0.1 M NaOH (Ajax Chemicals, NSW).

5.2.5.2 Preparation of sample All sample extractions were carried out in subdued light and all the glassware was wrapped with aluminium foil to prevent light destruction of folate. A gram (1 g) of each sample was weighed into 250 ml Erlenmeyer flask, to which 25 ml of the extraction buffer (0.1 M potassium phosphate, 1% ascorbic acid and pH 6.1) was added. Heat extraction was done in a water bath at 100oC for 10 minutes, followed by immediate cooling.

5.2.5.3 Tri-enzyme treatment and deconjugation The sample extracts were treated with three enzymes, protease, (Megazyme, subtilisin A and B. licheniformis) (2 mg/ml), α-amylase (A-3176, Sigma Chemical Co., St Lois, MO 63178) (20 mg/ml) and rat serum as the conjugase. The preparations of the enzymes were done according to Shrestha et al. (2000). The pH of the cooled extract was adjusted to 4.5 with 0.1 M HCl, and to a 10 ml of the extract, 1.6 ml of protease preparation was added and incubated at 37oC for 16 h. The protease reaction mixture was then heated in a boiling water bath for 5 min to inactivate the enzyme, cooled and 1.6 ml of α-amylase was added and the extract incubated at 37oC for another 4 h. The pH of the enzyme-hydrolyzed extract was adjusted to 7.2 and 10 ml of it was treated with 100 µl of rat serum and incubated for 3 h at 37oC. The deconjugated extract was then heated in a boiling water bath for 5 min, cooled and centrifuged at 3000 rpm for 15 min and the supernatant was stored at -85oC.

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5.2.5.4 Total Folate assay The folic acid assay was done using the VitaFast® Folic acid Kit, Microbiological microtitre plate test to quantitate total folate. The assay was done according to the manufacturer’s instructions (ifp Institut fur Produktqualitat GmbH, Berlin, Germany).

5.2.5.5 Quality control Enzyme blanks were run to correct for the endogenous folate that may be present in the enzyme treatments. Certified Reference Material – BCR®- 485 Mixed Vegetables (Institute of Reference Materials and Measurements, European Commission Joint Research Centre) was analyzed along with the samples to confirm the accuracy of the folate quantification. Analyses were done in triplicates in duplicate extractions of the samples.

5.3 Results/Discussion

The table below shows results from two (2) imports of aibika only. The samples in the first import were not analyzed for total folate because of problems with the lyophilized Lactobacillus casei subspecies rhamnosus (ATCC7469) obtained from the School of Microbiology and Immunology, The University of New South Wales, Sydney, Australia. Folate is chemically very labile and so prolonged storage of the leaves whilst cryoprotecting and assessing the activity of the many batches of the culture meant significant loss of the nutrient and hence total folate analysis was not done.

In the second import, not all the accessions as in the previous import were brought in, due to a drought which destroyed a good number of the accessions. There were also some newer accessions imported in September of 2012 which were absent in February 2011 contributing to the missing (NA) values.

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5.3.1 Total Folate analysis

Table 5.0 The total folate content of accessions of aibika (µg/100g) on a fresh weight basis.

Accession Number 2nd import (Feb 2011) 3rd import (Sept 2012) Total folate Moisture Total folate Moisture (µg/100g) (mg/100g) (µg/100g) (mg/100g) LAL AM 009 NA NA 75 87 LAL AM 011 34 82 64 86 LAL AM 016 NA NA 79 84 LAL AM 030 35 84 121 75 LAL AM 035 NA NA 82 84 LAL AM 039 36 83 62 88 LAL AM 041 37 83 74 86 LAL AM 045 NA NA 91 82 LAL AM 082 NA NA 60 89 LAL AM 084 42 82 132 74 LAL AM 123 43 85 62 89 LAL AM 134 NA NA 90 83 LAL AM 141 NA NA 108 79 LAL AM 166 51 83 81 84 LAL AM 170 NA NA 96 81 LAL AM 175 NA NA 84 84 LAL AM 180 NA NA 87 84 LAL AM 200 NA NA 89 83 LAL AM 203 58 85 71 86 LAL AM 204 NA NA 96 82 LAL AM 206 43 82 69 86 LAL AM 220 NA NA 71 87 LAL AM 221 NA NA 65 87 LAL AM 222 36 87 NA NA LAL AM 207 37 83 NA NA LAL AM 186 57 87 NA NA LAL AM 081 41 81 NA NA LAL AM 122 40 83 NA NA The values are means of triplicate determination of duplicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 5.1 Summary of statistics

Total folate concentration (µg/100 g) Statistic First Second Third importation importation importation (2010) (2011) (2012) Number of samples ND 14 23 Average ND 42.1 83.0 Standard error ND 2.1 3.9 Minimum ND 34 60 Maximum ND 58 132 ND – analysis not done

It should be noted here that only 9 samples were analyzed from both imports. The aibika accessions were all grown in Laloki, however, every year the accessions are replanted in a different plot of cleared land. Therefore, the data in Table 5.0 is that of folate in aibika grown in 2 different blocks of land and 2 different years. The percent water content of the samples from the second and third imports were similar (83.6 ± 0.5 vs. 83.9 ± 1.0). Generally the total folate values were higher for the samples analyzed in the third import ( = 83.0 µg/100 g; n =23) than for the second import ( = 42.1 µg/100 g; n =14). The range of total folate contents in the second import (34–58 µg/100 g) was lower than the third import (60–132 µg/100 g). Regression analysis was performed on the data from the accessions that were common between the two imports. The coefficient of determination (r2) for this analysis was 0.012 and the regression ANOVA was not significant (F1,7 = 0.088; P = 0.78). Therefore, it is obvious that the folate content varied from year to year and from one accession to another and there appears to be either little effect of genotype on total folate content or a large effect of the environment.

Climate, soil type, weather conditions, water and air surrounding the growing plants can influence the nutrient composition, growth and metabolic activities that occur in the plants as they grow. It is also understood that plants and microorganisms synthesize folates (de novo synthesis), and enzymes and the biosynthetic pathways in plants and bacteria have been partially characterized (Blancquaert et al. 2010). There may be traits 105

other than genotype that influence folate accumulation in the accessions. Lester (2002), did a study on the effect of soil type, cultivar, fruits size on ascorbic acid, folic acid and potassium in four cultivars of green fleshed honeydew muskmelons, and found that though the effect of genotype was significant, soil type and fruit size also influenced the folic acid level. There have been several studies on the total folate content of cereals which showed differences according to species, genotypes and growing conditions (Kariluoto et al., 2010). Variations in total folate content have also been observed in wheat cultivars grown in the same location in the same year (Piironen et al., 2008).

The other factor to consider in this study is that folate is chemically very labile so it may be assumed that there were substantial losses between the stages of picking of aibika leaves in the field at Laloki (PNG), and its subsequent analysis in UNSW, Sydney.

There are few data on either folic acid or total folate content of aibika in the literature for comparison. Devi et al (2008) determined both folic acid and total folates in some selected Fijian foods which included aibika or bele as it is known in Fiji and the values along with the values for other green leafy vegetables are in Table 5.1 below. All the green leafy vegetables listed are commonly consumed in PNG as well.

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Table 5.2 Folate content of green leafy vegetables from Fiji (µg/100 g ± SD on a fresh weight basis Foods Moisture Folic acid Total (g/100 g) folate Chinese cabbage 95 65 ± 9 81 ± 2 (Brassica chinensis) English cabbage 90 30 ± 5 33 ± 2 (Brassica Oleracea var. bullata) Drumstick leaves 81 86 ± 6 101 ± 13 (Moringa oleifera) Amaranth leaves 89 40 ± 3 57 ± 7 (Amaranthus sp.) Bele 89 131 ± 14 177 ± 5 (Abelmoschus manihot) Fern (Ota) (Athyrium esculenta) 91 3 ± 0.2 3 ± 0.09 *All values are means of triplicate determinations **Total folate analysed using the microbiological method Source: Devi et al (2008)

Aibika leaves can be considered very good contributors of total folate to the PNG diet based on the values shown in this study. In the above results (Table 5.2), it can be seen that bele has the highest total folate or folic acid content compared to all the green leafy vegetables analyzed. Consumption of these green leafy vegetables alone or in combination would increase the total folate content of the diet. The range of total folate in the accessions in this study is comparable to that of the other green leafy vegetables in Table 5.2. The Pacific Islands Food Composition Tables do not have values for folate for the green leafy vegetables so it is difficult to compare the values of aibika with other values in the literature.

The values of total folate determined in this study are obviously in the raw vegetable, and preparation and cooking would amount to certain losses depending very much on the cooking method, including the amount of liquid used because aibika is rarely consumed raw.

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5.4 Conclusion

It can be concluded from this study that total folate content varied from one accession to another and from year to year. The accession which had a high total folate value in one year did not necessarily have an equally high value in the following year indicating that changes in morphological characteristics did not reflect on the total folate content. This conclusion is subject to the fact that not all accessions were collected throughout the 2 year period and, may be the results would have been different if otherwise. Aibika is a very good source of total folate in the PNG diet as it compared well with the total folate content of other green leafy vegetables consumed in Fiji. The total folate value of aibika is high as was found for bele in Fiji (Table 5.2). Consumption of a combination of different green leafy vegetables, beans would increase total folate intake in the population.

Nutrition education on how best to cook and prepare the green leafy vegetables for consumption should be an integral part of addressing micronutrient deficiencies. Reduced cooking time and less amount water use in boiling or steaming of the aibika is to be encouraged in the local women so that maximum vitamin is absorbed. In addition, the cooking water must be used in other dishes because folate leaches into the cooking water during boiling.

5.5 Future work

Since the accessions have not been fully characterized genetically as yet, and the accessions have not being grouped genetically so it is difficult to tell if a specific gene is controlling the folate biosynthesis of the aibika accessions. Therefore other factors that may contribute to the difference in the folate content of the aibika accessions should be minimized as much as possible to study the extent of the genetic factor. Some of such activities would be to plant and harvest all accessions at the same time in the same plot of land. In this study due to flood and drought, some accessions were not harvested with the others in same year due to their unavailability or condition of the leaves and hence it is hard to appreciate the influence of the genes. The maturity or age of the leaves at time

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of harvest should be similar and all other agricultural practices should be similar. It may be also helpful to leave the plants to grow in the same plot of land for more than a year to study the effect of the different weather patterns; the wet and the dry seasons. Doing so might help us to see if the differences in the weather conditions had any effect on the folate content of the accessions. In the present study this could not be done, the plants were propagated every year in a different plot of land. Efficient cold storage and transportation of the leaves between the place of harvest and analysis is also very important due to the chemically labile nature of the folate compounds.

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Bailey, L. B. (1998). “Dietary reference intakes for folate: The debut of dietary folate equivalents”. Nutrition Reviews, 56(10), 294-299.

Blancquaert, D., Storozhenko, S., Loizeau, K., De Steur, H., De Brouwer, V., Viaene, J., Ravanel, S., Rebeille, F., Lambert, W., Van Der Straeten, D. (2010). “Folates and folic acid: from fundamental research toward sustainable health”. Critical Reviews in Plant Sciences 29:14-35

Brown, R. D., Langshaw, M. R., Uhr, E. J., Gibson, J. N., and Joshua, D. E. (2011). “The impact of mandatory fortification of flour with folic acid on the blood folate levels of an Australian population”. Medical Journal of Australia 194(2): 65-67

Calvaresi, E., and Bryan, J.B. (2001). “Vitamins, cognition and aging: a review”. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 56: 327- 39

Choi, Sang-Woon and Mason, Joel.B. (2000). “Folate and carcinogenesis: An integrated Scheme”. The Journal of Nutrition 130: 129-132

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Dang, J., Arcot, J., and Shrestha, A. (2000). “Folate retention in selected processed legumes”. Food Chemistry 68(3): 295-298

De Bonoist (2008). Conclusions of a WHO Technical Consultation on Folate and Vitamin B12 Deficiencies. Food and Nutrition Bulletin 29(2) Retrieved 20/03/2013 from: http://www.who.int/nutrition/publications/micronutrients/FNBvol29N2supjun08.pdf

Devi, R., Arcot, J., Sotheeswaran, S. And Ali, S. (2008). “Folate contents of some selected Fijian foods using tri-enzyme extraction method.” Food Chemistry106: 1100- 1104

DeSouza, S., and Eitenmiller, R. R. (1986). “Effects of processing and storage on the folate content of spinach and broccoli”. Journal of Food Science51:626-628

De Wals, P., Tairou, F., Van Allen., Uh, S., Lowry, R.B., Sibbald, B., Evans, J.A., Van den Hof, M.C., Zimmer, P., Crowley, M., Fernandez, B., Lee, N.S., Niyonsenga, T. (2007) “Reduction in neural tube defects after folic acid fortification in Canada”. New Engl. J. Med.357:135-142

Dryden, Richard (1997). “Birth defects recognised in 10,000 babies born consecutively in Port Moresby General Hospital, Papua New Guinea”. PNG Medical Journal41(1):4- 13

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Finglas, P. M., Wright, A. J. A., Wolfe, C. A., Hart, D. J., Wright, D. M., and Dainty, J. R. (2003). “Is there more to folates than neural tube defects?”Proceedings of the Nutrition Society.62:591-598.

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Food and Drug Administration. (1996). Food Standards: amendments of standards of identity for enriched grain products to require addition of folic acid. Final Rule. 21 CFR Parts 136, 137, 139: 8781-8807

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Holasova, M., Fiedlerova, V., and Vavreinova, S. (2008). “Determination of folates in vegetables and their retention during boiling”. Czech Journal of Food Sciences 26: 31- 37

Kariluoto, S., Edelmann, M., Piironen, V. (2010). “Effects of environment and genotype on folate contents in wheat in the HealthGRAIN Diversity Screen”. Journal of Agricultural and Food Chemistry.56:9324-9331

Kennedy, G., Nantel, G., and Shetty, P. (2003). “The scourge of “hidden hunger: global dimensions of micronutrient deficiencies”. Food, Nutrition and Agriculture. 32:8-16

Lester, Gene, E. (2002). “Ascorbic Acid, Folic Acid and Potassium Content in Postharvest Green-Fleshed Honeydew Muskmelons: Influence of Cultivar, Fruit Size, Soil Type, and Year”. Journal of the American Society for Horticultural Science.127(5):843-847

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McKillop, D.J., Pentieva, K., Daly, D., McPartlin, J.M., Hughes,J., Strain, J.J., Scott, J.M., McNulty, H. (2002). “The effect of different cooking methods on folate retention in various foods that are amongst the major contributors to folate intake in the UK diet”. British Journal of Nutrition 88: 681-688.

McNulty, H., and Pentieva, K. (2004). “Folate bioavailability”. Proceedings of the Nutrition Society 63: 529-536

MRC Vitamin Study Research Group. (1991). Prevention of neural tube defects: results of the Medical Research Council Vitamin Study. Lancet 338: 131-137 National Academy of Sciences (1998).Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin and Cholin. Retrieved 5/01/2013 from: http://www.nap.edu/catalog/6015.html.

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Piironen, V., Edelmann, M., Kariluoto, S., Bedo., Z. (2008). “Folate in wheat genotypes in the HEALTHGRAIN diversity screen”. Journal of Agricultural and Food Chemistry 56:9726-9731

Pfeiffer, C. M., Rogers, L. M., Bailey, L. B., & Gregory III, J. F. (1997). “Absorption of folate from fortified cereal-grain products and of supplemental folate consumed with or without food determined by using a dual- label stable-isotope protocol”. American Journal of Clinical Nutrition, 66(6), 1388-1397.

Rader, J. I., Weaver, C. M., and Angyal, G. (1998). “Use of microbiological assay with tri-enzyme extraction for measurement of pre-fortification levels of folates in enriched cereal-grain products”. Food Chemistry 62(4): 451-465

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Rogers, L. M., Pfeiffer, C. M., Bailey, L. B., & Gregory III, J. F. (1997). “A dual-label stable-isotopic protocol is suitable for determination of folate bioavailability in humans: Evaluation of urinary excretion and plasma folate kinetics of intravenous and oral doses of [13C5] and [2H2] folic acid”. Journal of Nutrition, 127(12), 2321-2327.

Ross, J., Green, J., Baugh, C. M., MacKenzie, R. E., and Matthews, R. G. (1984). “Studies on the polyglutamate specificity of methylenetetrahydrofolate dehydrogenase from pig liver”. Biochemistry 23:1796-1801

Sanderson, P., McNulty, H., Mastroiacovo, P., McDowell, I.F.W., Melse-Boonstra,A., Finglass, P.M., and Gregory lll, J.F. (2003). “Folate bioavailability: UK Food Standards Agency workshop report”. British Journal of Nutrition90: 473-479

Shrestha, A. K., Arcot, J., Paterson, J. L. (2000). “Folate assay of foods by traditional and tri-enzyme treatments using cryoprotected Lactobacillus casei”. Food Chemistry71: 545-552

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Scott, J., Rebeille, F., and Fletcher, J. (2000). “Folic acid and folate: the feasibility for nutritional enhancement in plant foods”. Journal of the Science of Food and Agriculture..80: 795-824

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Tamura, T., Mizuno, Y., Johnson, K. E., and Jacob, R. A. (1997). “Food folate assay with protease, a-amylase and folate conjugase treatments”. Journal of Agriculture and Food Chemistry45: 135-139.

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Wagner, C. (1995) Biochemical Role of Folate in Cellular Metabolism. In: Folate in Health and Disease. Bailey. LB. (editor). Marcel Dekker Inc, USA.

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Wardlaw, Gordon M & Smith, Anne M (2013). Wardlaw's nutrition, Australia/New Zealand ed., McGraw-Hill Education, North Ryde, N.S.W

Weir, D., and Scott, J. (1998). “Homocysteine as a risk factor for cardiovascular and related disease: nutritional implications”. Nutrition Research Reviews11:311-338

WHO/FAO (2004). Vitamin and Mineral nutrition in human nutrition, report of a joint FAO/WHO Expert Consultation. Bangkok, Thailand. Joint FAO/WHO Expert Consultation on Human Vitamin and Mineral Requirements. Retrieved 20/02/2013 from: http://whqlibdoc.who.int/publications/2004/9241546123.pdf

Winkels, R. M., Brouwer, I. A., Siebelink, E., Katan, M. B., & Verhoef, P. (2007). “Bioavailability of food folates is 80% of that of folic acid”. American Journal of Clinical Nutrition, 85(2), 465-473.

Witthӧft, C. M., Forssen, K., Johanesson, L., Jagerstad, M. (1999). “Folates- Food sources, analyses, retention and bioavailability”. Scandinavian Journal of Nutrition.43:138-146

Wright, A. J. A., Dainty, J. R., & Finglas, P. M. (2007). “Folic acid metabolism in human subjects revisited: Potential implications for proposed mandatory folic acid fortification in the UK”. British Journal of Nutrition, 98(4), 667-675.

Wright, A. J. A., & Finglas, P. M. (2005). “New results from stable isotope studies show that folic acid should not be used as a reference folate for estimating relative absorptions of natural food folates”. Nutrition Bulletin, 30(3), 282-289.

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Chapter 6 Mineral composition

Minerals are inorganic nutrients made up of major and trace elements. Major elements include calcium, phosphorus, potassium and sodium, whilst the trace elements include iron, selenium, zinc, iodine, magnesium, manganese and copper. They are required in small amounts but are essential and have to be obtained from the foods consumed. They are found in body tissues and fluids and are essential for a number of physiochemical processes that takes place in the body (Soetan et al., 2010). Some of those processes include: the maintenance of osmotic pressure by sodium, chloride and potassium; rigidity of the body supported by calcium and phosphorus; and chlorine in hydrochloric acid in the stomach (Latham, 1997). Although all mineral elements are important, iron, iodine and zinc are the three minerals that are almost frequently lacking in the diet. The prevalence of iron deficiency and iron deficiency- anaemia in the world is well researched and documented. Recognition of implications of zinc deficiency has also gained momentum in the recent years; in 2002, zinc deficiency was included with the deficiencies of vitamin A, iron and iodine as major contributors to the global and regional burden of diseases (Ezzati et al., 2002, Gibson, 2006). Micronutrient deficiencies can occur as a result of inadequate diet or as a result of malabsorption and utilisation of the micronutrients. There are many factors affecting absorption and utilisation of micronutrients, some of which include; inhibitors and enhancers of particular nutrients, physiological states of individuals, disease state or other factors that may hinder the effective absorption and utilisation of nutrients. Therefore, eating adequate amount of wide variety of food as well as being aware of the interaction of factors that affect bioavailability, absorption and utilisation of these micronutrients will ensure that micronutrient needs are met.

Diversification of the diet is the main strategy being promoted to address the deficiency problems and there is strong universal support for a food-based approach (FAO, 1996) to increase micronutrient intake from the diet.

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From the perspective of nutritional status in PNG, the mineral of most importance is obviously iron due to the high prevalence of iron deficiency and iron deficiency- anaemia amongst the population as shown by the 2005 PNG National Nutrition Survey. Zinc may also be considered to be an important mineral in PNG as an increased number of cases of growth retardation, wasting, suppressed immune system, diarrhoea and high childhood morbidity and mortality rates was shown in the recent 2005 PNG National Nutrition Survey (PNGNNS 2005). Iron supplementation is available especially for pregnant women; however, accessibility, availability and adherence limit its effectiveness. There is currently no food fortification program in the country; there have been discussions on iron fortification of foods. A food-based approach is generally one of the workable strategies to deal with micronutrient deficiency in the country, whilst awaiting the implementation of food fortification programs. However, these strategies will only be effective, if there are improvements in other factors that affect diet, health and wellbeing of the population. These include; health care, socioeconomic issues, culture, agricultural practices and nutrition education.

Recently biofortification, which involves breeding of food crops with increased amounts of specific micronutrients (Pandian et al., 2011), has also been discussed as a way of reaching the poor in the world with commonly consumed food crops that have introduced traits of high nutrient content. For a food-based approach to be effective, the composition of commonly consumed foods as well as the nutrient composition of the varieties and cultivars of species of food crops in terms of biodiversity has to be determined. This is because variation exists between and within varieties of a genus/species. At this stage, there are no published analytical data on the mineral or micronutrient composition of foods consumed in PNG, so this study will not only initiate a collection of food composition data for a commonly consumed green leafy vegetable in the country but also as initial indication of selected nutrient composition of aibika biodiversity in PNG.

In this chapter, the minerals being discussed include: iron, zinc, calcium, sodium, potassium, magnesium, manganese and copper. For each of these minerals, discussion includes a description of their functions and important diseases related to their

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deficiency and their food sources. Iodine was not analysed in this study, the expected values would be too low and the analysis method is quite different from the minerals analysed in this study which means the cost would have been higher.

6.1.1 Iron Iron is a vital constituent of a large number of proteins and enzymes. The majority of iron in the body is in the form of haemoglobin in the erythrocytes. Haemoglobin is the haem containing protein in the blood corpuscles that transports oxygen from the lungs to the rest of the body and myoglobin transports oxygen to the muscle cells; it also serves as a temporary storage for oxygen in the muscle cells (FAO/WHO, 2002). Iron functions as part of many enzymes, enzymes that are involved in vital oxidation- reduction reactions as well as synthesis and catabolism of neurotransmitters need iron to function (Hulthen, 2003). Catalase and peroxidase protect cells as antioxidants, cytochromes facilitate energy metabolism as electron carriers and cytochrome P450 is involved in making steroid hormones, bile acids and drug detoxification in the liver (FAO & WHO, 2002).

6.1.1.1 Deficiency diseases Iron deficiency is the most common cause of anaemia and a recognised public health problem world-wide, affecting more than two billion people world-wide (Kennedy et al., 2003). Significant predisposing factors for iron deficiency anaemia include: low dietary intake, poor absorption from diets and individuals who have increased need for it. Certain groups of people are at a high risk for iron deficiency and anaemia, this includes the following: young children aged between 6 months and 8 years; adolescents due to their rapid growth at this stage; pregnant and lactating women; people suffering from blood loss; those with celiac disease or suffering from some form of parasitic infections, or intestinal worms; vegetarians; and athletes in intense training (FAO & WHO, 2002; Anaemia can also be caused by lack of folate and vitamin B12; however, the most common cause is an inadequate dietary intake of iron. Iron deficiency anaemia is characterised by a decline in the production of haemoglobin and a decreased number of red blood cells in the circulation. Since iron is required for the production of haemoglobin and, hence, the transportation of oxygen to the rest of the body, apart from

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disrupting various other vital functions of the body, anaemia disrupts oxygen delivery, electron transportation, oxidative metabolism in the muscle cells and energy metabolism in the cells, all of which have serious consequences to the functions of various cells and tissues. Effects of iron deficiency and iron deficiency anaemia include the following: increased rates of morbidity and mortality amongst the pregnant women and increased risk of premature births(Lieberman et al., 1988, Scholl & Hediger, 1994), reduced physical ability to work; retardation of physical and mental development; and impaired cognitive development in young children (Thompson, 2011, Milman, 2011). Period of infancy which corresponds with brain growth and development of the central nervous system is most vulnerable in situations of iron deficiency; animal and human studies show that adequate iron intake during this period of growth is vital for normal cognitive and behavioural functions (Hulthen, 2003).There are a variety of other factors which contribute to problems of cognition and behaviour and there are on-going studies in this area. Levels of education, how much money an individual earns, poverty, reliance on monotonous diets were observed to correlate with the prevalence of anaemia. Prevalence of iron deficiency anaemia is most significant in women of childbearing age, very young children and adolescents (Thompson, 2011).

6.1.1.2 Sources of iron in the diet Iron is found in a variety of foods both from animal and plant sources; foods of animal origin provide the haem iron which has high bioavailability and include meat, poultry, egg yolk and fish; liver is a rich source. Non-haem iron is normally found in foods derived from plant origin like vegetables, grains, legumes, nuts and cereals (Milman, 2011). Non-haem iron constitutes the main form of dietary iron, especially in developing countries where foods of animal origin are limited by affordability, accessibility and availability. The following discussion on the enhancers and inhibitors of non-haem iron is from the following sources: Latham (1997) Kennedy et al.(2003), FAO & WHO (2002). Non-haem iron absorption is influenced by a number of factors, including iron status; in an iron deficient state, more is absorbed from the diet than in a healthy state. Factors that enhance the absorption of non-haem iron include: ascorbic acid which is found in a variety of fruits and vegetables and juices; other organic acids;

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fermented vegetables. Incorporating some haem iron together with plant based foods will enhance the absorption of non-haem iron. The inhibitors include: phytate found in legumes, bran products, whole-grains, seeds and nuts; and polyphenolic compounds present in some fruits, vegetables, wines and tannins in tea. Soy protein is also said to have some inhibitory effect, along with calcium from milk and cheese products.

6.1.1.3 PNG perspective Iron deficiency and iron deficiency anaemia are a public health problem (PNGNNS 2005 as discussed in chapter 2) in the country affecting not just children and the women of child bearing age but also men. Non-haem iron is the main dietary source especially in the rural and remote areas where there is little or no animal origin foods in the everyday diet. Green leafy vegetables are the major components of the diet, fruits or fruit juices are rarely consumed with main meals and tea is almost always consumed with the main meals especially in the villages in most provinces. Malarial and worm infections are an important consideration, especially in the coastal provinces or regions of the country. Nutrition education on the interaction between nutrients, the enhancers and inhibitors of iron absorption and importance of varied diet is essential.

6.1.2 Zinc Zinc is a trace element that is involved in many important functions in the human body, some of which include; growth and mental development, cell division and activation, fertility, function of the immune system, wound healing, taste acuity, smell and appetite, vision, facilitates collagen formation which is vital for skin, hair and nails, foetal growth, cognitive functions (Chasais et al., 2012; International Zinc Association, date). Its role in the immune response, to oxidative stress, in apoptosis and aging has been discussed by Stefanidou et al. (2006) and Prasad (2009). A number of publications divide the biological roles of zinc into three main areas: catalytic, structural and regulatory. In its catalytic role zinc serves as an important constituent of the catalytic sites of a large number of enzymes. In its structural role, it stabilises structures of a large number of proteins, enzyme molecules and other cell membranes which support cellular and sub-cellular metabolism. Superoxide dismutase, an important antioxidant, has two atoms each of zinc and copper (Sharp, 2005). Finally, in its regulatory role, zinc

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containing proteins known as zinc finger proteins bind to nucleic acids and facilitate the process of transcription and gene expression (Hambidge, 2000; Chasapis et al. 2012;). Zinc also said to play a role in the secretion of insulin from the pancreas as zinc deficient animals were found to have considerable problems with glucose tolerance (Sharp, 2005).

6.1.2.1 Deficiency diseases The first description of zinc deficiency was given in a study of male adolescent dwarfs in the Middle East in the 1960s; their diets were heavily dependent on plants containing high levels of phytate with less inclusion of animal foods (Gibson, 2006, Prasad et al., 1963). The impact of zinc deficiency as a major risk factor on the global and regional burden of disease was included with that of the iron, iodine, and vitamin A deficiency in 2002 (Gibson, 2005, Ezzati et al., 2002). Deficiency arises due to three main factors: inadequate diet, physiological states where need for zinc is high and disease states which is manifested by increased losses, and impaired absorption or utilization of zinc (Gibson, 2006). Inadequate diets in the developing countries are very much plant based with little animal protein and problems are associated with financial constraints as well as cultural and other factors. Low soil zinc content can also lead to low zinc in plant foods. Cereal-based diets tend to be good sources of zinc compared to starchy root/tuber-based diets; however, phytates hinder the bioavailability of the cereal and legume-based diets. Using leavening agents and fermentation processes in the preparation of cereals and legumes reduces phytates. High amounts of calcium may also hinder zinc bioavailability; however, bioavailability is enhanced by the addition of animal protein and organic acids in the diet (Gibson, 2006; FAO/WHO, 2002).

Physiological states where increased zinc is required include infants, children and, pregnant women, because these are the periods of rapid growth and development and or older adults due to impairment of absorption and utilisation of zinc (FAO/WHO, 2002; Gibson, 2006). Disease states where increased zinc is required include individuals suffering from disease conditions such as severe diarrhoea, inflammatory bowel disease, mal-absorption syndromes (Gibson, 2006, FAO/WHO, 2002).

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Mild zinc deficiency is manifested in growth retardation in children. Studies in Colorado in the 1970 and 1980s showed increased growth in children who had zinc supplements compared to those who did not (Walravens and Hambidge, 1976). Physical growth retardation in children has been one of the most studied areas in relation to zinc deficiency diseases. Zinc deficiency impairs foetal growth and development due to its vital roles in DNA/RNA synthesis and facilitating the production of growth hormones and activity of insulin-like growth factor (Nriagu, 2007).One important function of zinc is in immunity, so deficiency places young children at a high risk of diarrhoea and pneumonia, two of the most common causes of increased mortality and morbidity within that group. Other factors which may be linked to this include the nutritional quality of the complementary or weaning foods given to children, the type of infant formulae and the diet of the mother. In developing countries, where diet may in most times lack animal protein and be of high fibre or phytate content, the risk is of zinc deficiency is greater and is compounded with poor sanitation practices. Studies have shown that zinc supplementation reduces the occurrence of malaria in children. A placebo-controlled study on zinc supplementation in Papua New Guinea found a 38% reduction in attendance of children at health centre due to malaria (Shanker, 2000).

6.1.2.2 Sources of zinc in the diet Zinc is found in a variety of foods and the best sources include liver, seafood and meats; eggs and dairy products are also fairly good sources. The best sources from plant origin are legumes, nuts and whole grain cereals whereas modest sources include green leafy vegetables, roots and tubers and fruits. The presence of phytate in the diet especially in whole grain cereals and legumes and a number of other vegetables inhibits the absorption of zinc; however, inclusion of animal protein in the diet containing phytate was shown to increase zinc absorption (FAO/WHO, 2002).

6.1.2.3 PNG perspective Protein energy malnutrition is still a big problem in PNG affecting especially children and this makes the children prone to many other diseases. Diarrhoea, malarial infections, stunting and wasting are still a significant problem affecting the very young. Zinc deficiency has been implicated in health problems in the country, although there is

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no national data or coverage of its status. The recent 2005 PNG National Nutrition Survey revealed that stunting and wasting are still a huge problem in the country (PNGNNS, 2005). Green leafy vegetables and roots and tubers are the main sources of zinc in a typical PNG diet. Therefore, nutrition education should stress the importance of inclusion of animal protein, legumes and nuts in the diet and the best way to prepare foods so as to limit the presence of phytates.

6.1.3 Calcium Calcium is mineral that is very important to normal human health, it is the fifth most abundant mineral in the human body, majority of the body calcium is in the skeleton, and has a vital role in skeletal mineralisation. Calcium in the bone has two vital roles and that is to strengthen the skeleton and to serve as a store to maintain intra- and extracellular calcium pools (Peacock, 2010). Campbell (1990), divides the roles of calcium in the body into structural and regulatory; the former includes its role in mineralisation of bones and teeth and latter refers to its role in the regulation of enzymes and proteins which are important to a number of essential biochemical functions. Regulatory functions include intra and extracellular signalling, muscle contraction and nerve impulse transmission (Peacock, 2010). Calcium facilitates nerve transmission by releasing neurotransmitters and allowing the movement of ions in and out of nerve cells, without which nerve function is impaired. (Wardlow, 2013). Requirement is depended on metabolism which is regulated by intestinal absorption, renal re-absorption and bone turn over which is in turn regulated by a number of hormones (Peacock, 2010).

Dairy products are rich sources of this mineral; green leafy vegetables only supply a little of this mineral. Dietary needs vary with age and with pregnancy (Awumey & Bukoski, 2006). Most potent inhibitor to absorption is oxalic acid, which forms an insoluble salt with calcium. Spinach calcium is less absorbable because of the plant’s oxalic acid content. Vegetables in the Brassica family have more calcium compared to other vegetables, and this calcium is highly absorbable due to low level of oxalic acid. Hence, the measurement of the contribution of calcium from vegetables to a diet will have to have to be accompanied by measurements of the level of oxalic acid to ascertain bioavailability. Phytic acid is the other inhibitor, although it is less potent compared to

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oxalic acid. Vegetable sources which are low in oxalate and phytate frequently have greater calcium bioavailability than milk (reason unclear). However, the concentration of calcium in these vegetables (e.g. kale) is so low that an appreciably large amount has to be consumed before consumption can meet the calcium requirement (Weaver & Heaney, 1997). Vitamin D enhances calcium absorption whilst increased sodium and protein intake elevates calcium excretion (FAO/WHO, 2002).

Low calcium status is associated with osteoporosis or low bone density which is a predisposing risk factor to bone fractures, osteoporosis contributes to morbidity amongst the older people especially women at postmenopausal stage (NHMRC, 2006). There is reduced absorption and increased excretion of the mineral at menopause hence putting this group of population at risk (NHMRC, 2006). People at risk of calcium deficiency include postmenopausal women, pregnant and lactating women, infants and adolescence (FAO/WHO, 2002).

6.1.4 Magnesium Magnesium is the second most abundant divalent intracellular cation and is involved in large number of metabolic processes in the body (Laires et al., 2004). The main function in muscle and other soft tissues is the stabilisation of the structure of adenosine triphosphate or ATP; this is done by being chelated by phosphate groups. A large component of the intracellular magnesium is bound to ATP, membranes or proteins or is inside mitochondria (Bender & Bender 1997), so this mineral plays vital roles in the metabolic or energy producing reactions that use or form ATP. Oxidation of glucose, fats and proteins for energy metabolism is facilitated by chemical reactions that require magnesium. Making proteins and nucleic acids is also dependent on magnesium, as are structure of bones and teeth. At a cellular level, magnesium facilitates active transportation of potassium and calcium across cell membranes (FAO/WHO, 2002, Laires et al., 2004). Forming chelates with ATP and other intracellular anionic ligands as well competing with calcium for binding sites on proteins and membranes enable magnesium to influence many functions in the body (Swaminathan, 2003). Deficiency results in irregular heartbeat, diabetes and hypertension have been linked to magnesium deficiency though the mechanism is still unclear (Wardlow, 2013).

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Swaminathan (2003), describes to certain detail the roles of magnesium as well as deficiency diseases and their causes. Magnesium is found in a wide range of foods, so deficiency in most cases is unlikely. Individuals likely to suffer deficiency are those in intensive care units and in patients suffering from kidney diseases, users of certain diuretics, sufferers of persistent or continuous bouts of diarrhoea, all of which disrupts magnesium absorption (Bender & Bender,1997), alcoholics and certain diuretic users are also at risk of deficiency (Wardlow, 2013). Green leafy vegetables are rich sources, along with whole grains and nuts, legumes, some shell fish and soy flour, milk products and meats are intermediate sources, refined foods generally contain lowest magnesium. High fibre intake decreases its absorption (FAO/WHO, 2002).

6.1.5 Manganese The biochemical roles of manganese in the human body is as a component of a number of enzymes including: arginase - which is needed by the liver for the urea cycle (Leach, 1997), pyruvate carboxylase - which is vital in gluconeogenesis and synthesis of fatty acids; and manganese superoxide dismutase - an important antioxidant (WHO, 1996; Bender & Bender 1997). Moreover, manganese also activates enzymes such as transferases, kinases, hydrolases, phosphatases and some dehydrogenases, peptidases and decarboxylases. These enzymes are essential for metabolic reactions involving carbohydrates, amino acids and cholesterol and facilitate the synthesis of bio-molecules which aid bone development (Keen et al., 1996) and wound healing (Shetlar & Shetlar, 1994; WHO, 1996, Watts, 1990). Manganese also regulates activity of number of neurotransmitter regulators (Bender & Bender 1997). Deficiency in humans is a rare, but signs would include reproductive problems, impaired fat and carbohydrate metabolism, the malformation of bones and impaired growth (WHO, 1996, NHMRC, 2006, Watts, 1990).

Leafy vegetables, unrefined cereals and tea are amongst the best sources; dairy products, refined cereal grains and meats are low (WHO, 1996). Fruits, like pineapple, raspberries, tropical fruits, and banana are some of the good sources of the mineral as are nuts and green beans. Phytic acid and oxalic acid may decrease its absorption and

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inclusion of other minerals in the diet such as calcium and iron limit its absorption (Bender & Bender 1997).

6.1.6 Copper The role of copper in the body is through facilitating various enzyme activities, both as a cofactor and as an allosteric component of several cupro-enzymes. Copper is also said to be involved in gene expression as evident on studies on yeast (Uauy, 1998). Some of the cupro-enzymes and their vital roles in the human body include: superoxide dismutase, an antioxidant that prevents against accumulation of free radicals; dopamine- β-monoxygenase which aids neurotransmitter synthesis; ceruloplasmin which is vital for the activity of ferroxidase which is important to the mobilisation of iron reserves; cytochrome c oxidase which aids electron transport and, hence, cellular energy production; protein-lysine 6-oxidase which is needed for the cross-linking of collagen and elastin that have roles in supporting connective tissues especially in the heart and blood vessels (Uauy, 1998, Angelova et al., 2011). The formation of the skin pigment, melanin, is dependent on tyrosinase, a copper-dependent enzyme; a cuproenzyme, cytochrome-c oxidase is vital for the making and maintenance of the myelin sheath which is important for insulation of nerve cells; cupro-enzymes are also crucial for normal development of the brain and the nervous system and protects the body against free radicals through its role in superoxide dismutase which is a copper-zinc dependent metallo-enzyme (Underwood, 1977,Angelovaet al., 2011). Copper deficiency leads to a disease similar to iron deficiency-induced anaemia but does not respond to iron therapy; deficiency also affects bone health and immune system (Angelova et al., 2011). Copper is available in a wide variety of foods of both of plant and animal origin. Copper pipes used in water supply can also contribute to copper intake. Excess zinc intake seems to impair copper absorption presumably by competing for the same binding protein in the intestinal mucosa. Calcium supplements also impair absorption by increasing pH of intestinal contents which makes copper salts less soluble (Bender & Bender, 1997).

6.1.7 Sodium Sodium is the primary cation of the extracellular fluid and is important in controlling the volume of the intravascular fluid (Logan, 2006), including blood volume and

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pressure. Along with chloride, sodium maintains the concentration and charge differences across cell membranes, as well as aiding the active transport of molecules across cell membranes (NHMRC, 2005). The transmission of nerve impulses, muscle contraction and cardiac function is facilitated by the role sodium plays in controlling the cell membrane potential. The absorption of sodium facilitates the absorption of other molecules like chloride, glucose, amino acids and water (NHMRC, 2005, Wardlow, 2013).

Sodium in the diet is largely in the form of sodium chloride from foods. Processed foods, including bread, breakfast cereals and crisps, provide large amounts of sodium in the diet. Un-processed foods like vegetables, fruits provide the least amount of sodium. Deficiency diseases do not usually result from inadequate intake, but certain circumstances may put people at risk; intense physical activity which leads to increased loss of sodium in sweating(NHMRC, 2006)

The association of high sodium intake and blood pressure has been extensively studied and has established that a high intake has a causal effect on hypertension or high blood pressure. INTERSALT, the largest study which included 10000 men and women in 32 countries confirmed that sodium intake correlates with blood pressure (Intersalt Cooperative Research Group, 1988). The Dietary Approaches to Stop Hypertension or DASH trial, a randomised feeding study showed a reduced blood pressure in both hypertensive and non-hypertensive people when they consumed wholesome foods like fruits, vegetables, wholegrain, fish, nuts, and poultry (Appel et al., 1997).

6.1.8 Potassium Potassium is the chief cation in the intracellular fluid, as sodium is in the extracellular fluid, and the differences in their concentration across the cell membrane generates membrane potential; this is vital for the function of the heart, the contraction of the muscles and the transmission of the nerve impulses (Sheng, 2000, Brody 1999). A sodium-potassium pump keeps the membrane potential of the cells intact (NHMRC 2006). Potassium is also essential for the activity of some enzymes including sodium-

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potassium ATPase and pyruvate kinase which facilitate carbohydrate metabolism (Sheng, 2000).

The richest food sources of the mineral include green leafy vegetables, root vegetables, and fruits, milk and milk products, legumes and meats. Factors which may influence requirement include climate, physical activity, use of diuretics, and intake of other electrolytes (NHMRC, 2006). A low plasma concentration of potassium is associated with alcoholism, severe cases of vomiting and diarrhoea, the use of diuretics and laxatives, eating disorders (Wardlow, 2013). Symptoms of potassium deficiency include; water retention, heart arrhythmias, continual thirst, hypertension, nerve and muscle dysfunction and vomiting (Bhaskarachary, 2011).

6.2 Materials and methods

Mineral analysis was done using Inductively Coupled Plasma Optical Emission Spectrometry (ICPOES). The technique is used to determine metals in a variety of sample matrices; the basis of the technique is spontaneous emission of photons from atoms and ions (Hou & Jones, 2000). It is a commonly used technique in elemental analysis, some of its characteristics include, high specificity, multi-element capability, and good detection limits. What happens in ICPOES is that the samples are broken down into their constituent atoms or ions and excited to a high energy level by the plasma source. When these atoms or ions return to their ground state, they emit photons that have a characteristic wavelength to the element present in the sample matrix, which is then recorded by an optical spectrometer (Warra & Jimoh, 2011, Hou & Jones 2000).Calibration of the ICPOES with standards aids quantitative analysis of the original sample (Warra & Jimoh, 2011).

The United States Environmental Protection Agency (US EPA) methods 3050B describes methods used for the digestion of sediments, soils, sludges for analysis by ICPOES and flame atomic absorption spectrometry (FLAA) for a number of elements.

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The method employed in the digestion of the aibika samples for ICPOES analysis was hot plate digestion in an open vessel.

Freeze-dried, ground and homogenised aibika samples were stored at -20ºC until required for mineral analysis. Each sample was a composite of 10 plants per accession. About 0.5 g of each sample was weighed into 250 ml beakers and 10 ml of concentrated nitric acid (70%) (Ajax Finechem Pty Ltd, Australia) was added. A ribbed watch glass was used as cover to act as a vapour recovery device and the flask and cover were then left in the fume cupboard overnight. The beaker with the mixture was then heated at 95 ºC and allowed to reflux for 2 h without boiling, until the brown fumes from the oxidation of the samples by nitric acid had subsided. The samples were then allowed to cool and 2 ml of hydrogen peroxide (30%, Ajax Finechem Pty Ltd, Australia) was added to the mixture and the flask returned to the heat source to start the peroxide reaction until the effervescence stopped. The sample was then cooled and transferred to a 250 ml volumetric flask and made up to the mark with MilliQ water. This was then filtered though Whatman No. 541 filter paper and about 10 ml of it sent to the Mark Wainwright Analytical Centre UNSW in 10 ml sample bottle for analysis by ICP-OES. The sample digestions were done in duplicate. The reference material used with all digestions was SRM 1573a tomato leaves from the National Institute of Standards and Technology, results presented in Table 6.11.

The following are instrument specifications of the ICPOES instrument used at the Mark Wainwright Analytical Centre, UNSW used in this analysis; the instrument is an Optima7300DV – ICPOES Perkin Elmer, USA, detector used is segmented-array charged-coupled device with the detection limit of 0.05ppm, the detection limit may vary depending on the elements, concentration and the sample matrix. Normal setting of the instrument: forward power, 1200-1400W; reflected power, 20.0W; Nebulizer gas flow, 0.70 l/min; plasma gas flow, 10.0 -15 l/min; aux gas flow, 0.30 l/min; pump speed, 15%. Wavelength used: Ca 317.933 , Cu 327.393, Fe 238.204, K 766.490, Mg 285.213 , Mn 257.610, Na 589.592 , Zn 206.200

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6.3 Results and discussion

Table 6.0 Calcium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Calcium Moisture Calcium Moisture Calcium Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 339 85 NA NA 238 87 LAL AM 011 321 83 318 82 286 86 LAL AM 016 303 86 NA NA 342 84 LAL AM 030 333 85 310 84 535 75 LAL AM 035 412 83 NA NA 378 84 LAL AM 039 393 84 297 86 218 88 LAL AM 041 259 85 259 83 246 86 LAL AM 045 413 81 NA NA 432 82 LAL AM 060 358 84 NA NA NA NA LAL AM 081 NA NA 319 83 NA NA LAL AM 082 281 87 NA NA 214 89 LAL AM 084 403 84 301 83 635 74 LAL AM 122 NA NA 354 85 NA NA LAL AM 123 465 79 318 84 249 89 LAL AM 134 410 82 NA NA 405 83 LAL AM 141 426 81 NA NA 454 79 LAL AM 154 372 82 NA NA NA NA LAL AM 162 424 83 NA NA NA NA LAL AM 164 304 85 NA NA NA NA LAL AM 166 437 84 301 83 330 84 LAL AM 167 354 78 NA NA NA NA LAL AM 170 472 77 NA NA 339 81 LAL AM 175 282 87 NA NA 242 84 LAL AM 180 NA NA NA NA 345 84 LAL AM 186 397 86 340 87 NA NA LAL AM 191 441 83 NA NA NA NA LAL AM 200 336 84 NA NA 292 83 LAL AM 203 222 86 250 85 250 86 LAL AM 204 350 83 NA NA 372 82 LAL AM 206 401 82 302 82 281 86 LAL AM 207 329 86 268 83 NA NA LAL AM 220 374 82 NA NA 311 87 LAL AM 221 226 88 NA NA 197 87 LAL AM 222 NA NA 224 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.1 Iron values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Iron Moisture Iron Moisture Iron Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 1.01 85 NA NA 1.05 87 LAL AM 011 2.41 83 4.19 82 1.62 86 LAL AM 016 1.06 86 NA NA 2.93 84 LAL AM 030 1.06 85 3.32 84 3.15 75 LAL AM 035 1.29 83 NA NA 2.36 84 LAL AM 039 1.83 84 3.78 86 1.62 88 LAL AM 041 1.11 85 8.68 83 1.49 86 LAL AM 045 1.28 81 NA NA 1.60 82 LAL AM 060 1.58 84 NA NA NA NA LAL AM 081 NA NA 1.74 83 NA NA LAL AM 082 1.30 87 NA NA 1.07 89 LAL AM 084 1.32 84 4.99 83 2.95 74 LAL AM 122 NA NA 2.38 85 NA NA LAL AM 123 2.15 79 2.56 84 1.01 89 LAL AM 134 1.17 82 NA NA 1.94 83 LAL AM 141 1.34 81 NA NA 2.28 79 LAL AM 154 2.24 82 NA NA NA NA LAL AM 162 0.99 83 NA NA NA NA LAL AM 164 1.09 85 NA NA NA NA LAL AM 166 1.34 84 5.56 83 1.36 84 LAL AM 167 1.38 78 NA NA NA NA LAL AM 170 1.26 77 NA NA 1.85 81 LAL AM 175 0.88 87 NA NA 1.29 84 LAL AM 180 NA NA NA NA 1.56 84 LAL AM 186 1.10 86 3.38 87 NA NA LAL AM 191 1.60 83 NA NA NA NA LAL AM 200 1.14 84 NA NA 1.62 83 LAL AM 203 0.90 86 2.64 85 1.32 86 LAL AM 204 0.91 83 NA NA 1.66 82 LAL AM 206 1.03 82 3.30 82 1.23 86 LAL AM 207 0.82 86 1.67 83 NA NA LAL AM 220 1.40 82 NA NA 1.75 87 LAL AM 221 0.91 88 NA NA 1.32 87 LAL AM 222 NA NA 2.42 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.2 Manganese values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Manganese Moisture Manganese Moisture Manganese Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 0.63 85 NA NA 0.84 87 LAL AM 011 0.84 83 0.84 82 1.16 86 LAL AM 016 0.53 86 NA NA 1.22 84 LAL AM 030 0.69 85 0.63 84 2.09 75 LAL AM 035 0.70 83 NA NA 1.52 84 LAL AM 039 0.66 84 0.79 86 0.95 88 LAL AM 041 0.62 85 0.80 83 1.01 86 LAL AM 045 0.67 81 NA NA 1.40 82 LAL AM 060 0.81 84 NA NA NA NA LAL AM 081 NA NA 0.66 83 NA NA LAL AM 082 0.69 87 NA NA 0.88 89 LAL AM 084 0.54 84 0.73 83 1.63 74 LAL AM 122 NA NA 0.81 85 NA NA LAL AM 123 1.26 79 0.92 84 1.55 89 LAL AM 134 0.42 82 NA NA 1.33 83 LAL AM 141 0.54 81 NA NA 1.55 79 LAL AM 154 0.70 82 NA NA NA NA LAL AM 162 0.54 83 NA NA NA NA LAL AM 164 0.60 85 NA NA NA NA LAL AM 166 0.50 84 0.61 83 1.01 84 LAL AM 167 1.06 78 NA NA NA NA LAL AM 170 0.84 77 NA NA 1.26 81 LAL AM 175 0.44 87 NA NA 0.85 84 LAL AM 180 NA NA NA NA 1.13 84 LAL AM 186 0.50 86 0.86 87 NA NA LAL AM 191 0.63 83 NA NA NA NA LAL AM 200 0.42 84 NA NA 1.02 83 LAL AM 203 0.85 86 0.72 85 0.68 86 LAL AM 204 0.42 83 NA NA 1.08 82 LAL AM 206 0.45 82 0.70 82 1.16 86 LAL AM 207 0.50 86 0.56 83 NA NA LAL AM 220 0.49 82 NA NA 1.11 87 LAL AM 221 0.51 88 NA NA 0.59 87 LAL AM 222 NA NA 0.66 87 NA NA All values are mean of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.3 Sodium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Sodium Moisture Sodium Moisture Sodium Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 13 85 NA NA 4 87 LAL AM 011 6 83 7 82 5 86 LAL AM 016 5 86 NA NA 16 84 LAL AM 030 1 85 5 84 5 75 LAL AM 035 5 83 NA NA 4 84 LAL AM 039 6 84 7 86 5 88 LAL AM 041 13 85 12 83 7 86 LAL AM 045 4 81 NA NA 12 82 LAL AM 060 3 84 NA NA NA NA LAL AM 081 NA NA 5 83 NA NA LAL AM 082 5 87 NA NA 3 89 LAL AM 084 1 84 4 83 4 74 LAL AM 122 NA NA 3 85 NA NA LAL AM 123 2 79 4 84 2 89 LAL AM 134 5 82 NA NA 26 83 LAL AM 141 16 81 NA NA 22 79 LAL AM 154 5 82 NA NA NA NA LAL AM 162 5 83 NA NA NA NA LAL AM 164 4 85 NA NA NA NA LAL AM 166 4 84 6 83 5 84 LAL AM 167 4 78 NA NA NA NA LAL AM 170 9 77 NA NA 7 81 LAL AM 175 6 87 NA NA 21 84 LAL AM 180 NA NA NA NA 6 84 LAL AM 186 9 86 7 87 NA NA LAL AM 191 1 83 NA NA NA NA LAL AM 200 4 84 NA NA 41 83 LAL AM 203 4 86 6 85 6 86 LAL AM 204 2 83 NA NA 6 82 LAL AM 206 6 82 7 82 17 86 LAL AM 207 6 86 6 83 NA NA LAL AM 220 9 82 NA NA 17 87 LAL AM 221 3 88 NA NA 5 87 LAL AM 222 NA NA 7 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.4 Magnesium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Magnesium Moisture Magnesium Moisture Magnesium Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 102 85 NA NA 87 87 LAL AM 011 97 83 113 82 108 86 LAL AM 016 101 86 NA NA 168 84 LAL AM 030 124 85 102 84 230 75 LAL AM 035 135 83 NA NA 148 84 LAL AM 039 130 84 113 86 83 88 LAL AM 041 106 85 108 83 103 86 LAL AM 045 134 81 NA NA 158 82 LAL AM 060 143 84 NA NA NA NA LAL AM 081 NA NA 121 83 NA NA LAL AM 082 112 87 NA NA 96 89 LAL AM 084 162 84 147 83 264 74 LAL AM 122 NA NA 146 85 NA NA LAL AM 123 193 79 102 84 126 89 LAL AM 134 133 82 NA NA 164 83 LAL AM 141 134 81 NA NA 188 79 LAL AM 154 114 82 NA NA NA NA LAL AM 162 155 83 NA NA NA NA LAL AM 164 108 85 NA NA NA NA LAL AM 166 144 84 135 83 153 84 LAL AM 167 137 78 NA NA NA NA LAL AM 170 184 77 NA NA 146 81 LAL AM 175 101 87 NA NA 123 84 LAL AM 180 NA NA NA NA 137 84 LAL AM 186 131 86 100 87 NA NA LAL AM 191 105 83 NA NA NA NA LAL AM 200 134 84 NA NA 170 83 LAL AM 203 101 86 109 85 112 86 LAL AM 204 130 83 NA NA 179 82 LAL AM 206 137 82 143 82 134 86 LAL AM 207 114 86 111 83 NA NA LAL AM 220 134 82 NA NA 137 87 LAL AM 221 88 88 NA NA 103 87 LAL AM 222 NA NA 79 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.5 Potassium values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Potassium Moisture Potassium Moisture Potassium Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 402 85 NA NA 387 87 LAL AM 011 555 83 382 82 431 86 LAL AM 016 436 86 NA NA 335 84 LAL AM 030 466 85 441 84 741 75 LAL AM 035 522 83 NA NA 528 84 LAL AM 039 431 84 362 86 295 88 LAL AM 041 478 85 374 83 465 86 LAL AM 045 581 81 NA NA 518 82 LAL AM 060 381 84 NA NA NA NA LAL AM 081 NA NA 375 83 NA NA LAL AM 082 480 87 NA NA 369 89 LAL AM 084 384 84 348 83 535 74 LAL AM 122 NA NA 389 85 NA NA LAL AM 123 543 79 319 84 306 89 LAL AM 134 469 82 NA NA 388 83 LAL AM 141 550 81 NA NA 560 79 LAL AM 154 516 82 NA NA NA NA LAL AM 162 426 83 NA NA NA NA LAL AM 164 435 85 NA NA NA NA LAL AM 166 438 84 352 83 415 84 LAL AM 167 630 78 NA NA NA NA LAL AM 170 525 77 NA NA 377 81 LAL AM 175 434 87 NA NA 406 84 LAL AM 180 NA NA NA NA 437 84 LAL AM 186 395 86 265 87 NA NA LAL AM 191 449 83 NA NA NA NA LAL AM 200 466 84 NA NA 401 83 LAL AM 203 443 86 353 85 429 86 LAL AM 204 465 83 NA NA 529 82 LAL AM 206 493 82 392 82 330 86 LAL AM 207 422 86 443 83 NA NA LAL AM 220 566 82 NA NA 310 87 LAL AM 221 468 88 NA NA 387 87 LAL AM 222 NA NA 329 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.6 Zinc values for aibika accessions collected and analysed over 3 year period, values in fresh weight basis

Accession 1st import (May 2010) 2nd import (Feb 2011) 3rd import (Sept 2012) Number Zinc Moisture Zinc Moisture Zinc Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 0.55 85 NA NA 0.69 87 LAL AM 011 0.62 83 1.01 82 1.20 86 LAL AM 016 0.66 86 NA NA 0.98 84 LAL AM 030 0.44 85 0.71 84 1.33 75 LAL AM 035 0.51 83 NA NA 1.13 84 LAL AM 039 0.49 84 1.09 86 0.83 88 LAL AM 041 0.32 85 1.09 83 0.85 86 LAL AM 045 0.68 81 NA NA 1.01 82 LAL AM 060 2.31 84 NA NA NA NA LAL AM 081 NA NA 0.86 83 NA NA LAL AM 082 0.49 87 NA NA 0.65 89 LAL AM 084 0.89 84 1.44 83 1.88 74 LAL AM 122 NA NA 1.01 85 NA NA LAL AM 123 0.48 79 0.95 84 0.71 89 LAL AM 134 1.00 82 NA NA 1.26 83 LAL AM 141 0.89 81 NA NA 1.59 79 LAL AM 154 1.20 82 NA NA NA NA LAL AM 162 0.52 83 NA NA NA NA LAL AM 164 0.66 85 NA NA NA NA LAL AM 166 1.27 84 0.90 83 1.00 84 LAL AM 167 0.54 78 NA NA NA NA LAL AM 170 0.65 77 NA NA 1.13 81 LAL AM 175 0.47 87 NA NA 0.84 84 LAL AM 180 NA NA NA NA 0.76 84 LAL AM 186 0.59 86 1.03 87 NA NA LAL AM 191 0.92 83 NA NA NA NA LAL AM 200 0.73 84 NA NA 1.17 83 LAL AM 203 0.64 86 0.98 85 0.80 86 LAL AM 204 0.62 83 NA NA 1.14 82 LAL AM 206 0.74 82 0.98 82 0.78 86 LAL AM 207 0.32 86 0.89 83 NA NA LAL AM 220 0.88 82 NA NA 0.80 87 LAL AM 221 0.54 88 NA NA 0.74 87 LAL AM 222 NA NA 0.97 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.7 Copper values for aibika accessions collected and analysed over 2 year period, values in fresh weight basis

Accession 2nd import (Feb 2011) 3rd import (Sept 2012) Number Copper Moisture Copper Moisture (mg/100g) (g/100g) (mg/100g) (g/100g) LAL AM 009 NA NA 0.26 87 LAL AM 011 0.36 82 0.37 86 LAL AM 016 NA NA 0.31 84 LAL AM 030 0.32 84 0.47 75 LAL AM 035 NA NA 0.34 84 LAL AM 039 0.34 86 0.24 88 LAL AM 041 0.50 83 0.29 86 LAL AM 045 NA NA 0.41 82 LAL AM 060 NA NA NA NA LAL AM 081 0.33 83 NA NA LAL AM 082 NA NA 0.39 89 LAL AM 084 0.36 83 1.70 74 LAL AM 122 0.17 85 NA NA LAL AM 123 0.29 84 0.30 89 LAL AM 134 NA NA 0.83 83 LAL AM 141 NA NA 0.54 79 LAL AM 154 NA NA NA NA LAL AM 162 NA NA NA NA LAL AM 164 NA NA NA NA LAL AM 166 0.34 83 0.42 84 LAL AM 167 NA NA NA NA LAL AM 170 NA NA 0.43 81 LAL AM 175 NA NA 0.34 84 LAL AM 180 NA NA 0.30 84 LAL AM 186 0.26 87 NA NA LAL AM 191 NA NA NA NA LAL AM 200 NA NA 0.42 83 LAL AM 203 0.76 85 0.30 86 LAL AM 204 NA NA 0.45 82 LAL AM 206 0.37 82 0.50 86 LAL AM 207 0.17 83 NA NA LAL AM 220 NA NA 0.27 87 LAL AM 221 NA NA 0.94 87 LAL AM 222 0.13 87 NA NA All values are means of replicate extractions NA – these accessions were not imported in the years indicated due to unavailability

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Table 6.8 Statistics of the mineral data (tables 6.1- 6.7)

Mineral concentration (mg/100 g)

Mineral Statistic First Second Third importation importation importation (2010) (2011) (2012) Calcium Number of samples 30 14 23 Average 361.2 297.2 330.0 Standard error 12.2 9.5 22.5 Minimum 222.0 224.0 197.0 Maximum 472.0 354.0 635.0 Zinc Number of samples 30 14 23 Average 0.72 0.99 1.01 Standard error 0.07 0.04 0.06 Minimum 0.32 0.71 0.65 Maximum 2.31 1.44 1.88 Potassium Number of samples 30 14 23 Average 475.0 366.0 429.5 Standard error 11.3 12.3 21.5 Minimum 381.0 265.0 295.0 Maximum 630.0 443.0 741.0 Sodium Number of samples 30 14 23 Average 5.5 6.1 10.7 Standard error 0.7 0.6 2.0 Minimum 1.0 3.0 2.0 Magnesium Number of samples 30 14 23 Average 127.4 116.4 144.2 Standard error 4.5 5.3 9.2 Minimum 88.0 79.0 83.0 Maximum 193.0 147.0 264.0 Manganese Number of samples 30 14 23 Average 0.64 0.74 1.17 Standard error 0.04 0.03 0.07 Minimum 0.42 0.56 0.59 Maximum 1.26 0.92 2.09 Copper Number of samples ND 14 23 Average ND 0.34 0.47 Standard error ND 0.04 0.07 Minimum ND 0.13 0.24 Maximum ND 0.76 1.70 Iron Number of samples 30 14 23 Average 1.3 3.6 1.7 Standard error 0.1 0.5 0.1 Minimum 0.8 1.7 1.0 Maximum 2.4 8.7 3.2 139

ND – Not determined in first year of import

Table 6.9 Statistics of the moisture content over the 3 year period

Water content (%) First Second Third importation importation importation (2010) (2011) (2012) Number of 30 14 23 samples Average 83.5 84.1 83.9 Standard error 0.5 0.5 0.8 Minimum 77.0 82.0 74.0 Maximum 88.0 87.0 89.0

6.4 Statistical analysis All data from the three importations were subjected to analysis of variance (ANOVA) using Excel (Microsoft). In addition, the data (for Ca, Zn, K, Na, Mg, Mn, Fe) from accessions that were common among all importations or between importations 2 and 3 (Cu) were also subjected to the same statistical analysis procedure. In addition, data from accessions that were common between importations were also subjected to correlation analysis using Excel.

The water contents of the samples from the three importations were similar among the three years being between 83.5 and 84.1% (Table 6.8). In addition, the variation in water content was similar amongst the samples from the first two importations but was slightly greater among the samples from the third importation.

From Table 6.0 and 6.8, the range of calcium in all the 3 years was between 200 and 472 mg/100g fresh weight. The concentrations of calcium in all samples from the three importations were subjected to ANOVA. The calcium contents of the samples from the first importation were lower than those from the other two importations (F2,64 = 3.25; P = 0.045). The calcium contents from the nine samples for which there was data for all three importations was also subjected to ANOVA. This analysis showed that there were

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no differences in calcium content among the importations (F2,24 = 0.99; P = 0.38). Correlation analysis was also used to study the relationships between the nine samples from the three importations. The coefficient of correlation between samples from importations was large (r = 0.75; P = 0.02) suggesting a relationship between the calcium contents of these varieties. However, the correlation coefficients between the calcium contents for importations 1 & 3 and 2 & 3 were low being 0.15 (P = 0.69) and 0.28 (P = 0.45).

The iron contents are shown in Tables 6.1 and 6.8 and the statistical analyses described for calcium were performed on the data for iron and on all subsequent minerals. For all of the data, ANOVA showed that there were significant differences among imports

(F2,64 = 29.5; P < 0.001). For the data from the nine accessions common to each importation (the nine common accessions), the average concentrations were found to be significantly different among the years (F2,24 = 22.5; P < 0.001), being 1.46, 4.33 and 1.75 mg/100 g for the three years, respectively. Correlation analysis showed no correlation in iron contents between the accessions from each of the importations with correlation coefficients being 0.18 (P = 0.63) for importations 1 and 2, 0.24 (P = 0.52) for importations 1 and 3 and 0.04 (P = 0.93) for importations 2 and 3. The zinc contents are shown in Tables 6.6 and 6.8 and were between 0.3 and 2.31 mg/100 g for the three importations although most values for zinc were between 0.3 and 1 mg/100 g. For all accessions, average zinc contents in the first importation (0.72 mg/100 g) were significantly (F2,64 = 6.59; P < 0.003) lower than from the subsequent two importations (0.99 and 1.01 mg/100 g). The values in the first importation ranged widely from 0.32 to 2.31 mg/100 g, whilst in the second import, the range is much tighter between 0.71 and 1.44 mg/100 g (the smaller number of accessions in that collection may have influence this) and the range in the last collection was between 0.65 and 1.88 mg/100 g. For the nine common accessions, zinc contents were also significantly lower (F2,24 = 4.85; P < 0.017)in the first importation (0.65 mg/100 g) than the subsequent ones (1.01 and 1.04 mg/100 g). No significant correlations were found among the zinc contents of the accessions for each of the combinations of imports (r = 0.14, P = 0.70 for importations 1 and 2; r = 0.38, P = 0.46 for importations 1 and 3; and r = 0.48, P = 0.19 for importations 2 and 3).

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The potassium contents of the accessions are shown in Table 6.5 and summarised in Table 6.8. From table 6.3, the values in the first import ranged between 381 and 630 mg/100 g, in the second import the range was between 265 and 443 mg/100g whilst in the third import the potassium values ranged between 295 and 741 mg/100 g, although generally most values were clustered between the values 355 to 550 mg/100g. There were significant differences in the average values for each of the three importations

(F2,64 = 9.89; P < 0.001). However, the differences in average potassium content for the nine common accessions (Importation 1 = 470, importation 2 = 368 and importation 3

439 mg/100 g) just failed to be significant (F2,24 = 3.10; P < 0.06). Correlations between values for individual accessions were not significant between importation 1 and 2 (r =0.05; P = 0.89) and between 1 and 3 (r = 0.26; P = 0.50); however, the correlation between importations 2 and 3 just reached significance (r = 0.67; P = 0.47).

The values for sodium are shown in Table 6.3 and summarised in Table 6.8. They varied between accessions and year of collection, the range was between 1 and 41 mg/100g. The average values for importations 1 and 2 for all accessions were significantly lower (F2,64 = 4.91; P = 0.01) than for importation 3. However, there were no significant differences for the average values for the nine common accessions (F2,24 = 0.59; P = 0.56). There was a highly significant correlation between the sodium values for the nine common accessions for importations 1 and 2 (r = 0.98; P < 0.001); however, the correlations were not significant for the two other combinations of accessions (r = 0.33 and P= 0.38 for both combinations).

The values for magnesium are shown in Table 6.4 and summarised in Table 6.8. For all the data there were significant differences between importations (F2,64 = 3.621; P = 0.03) with lower concentrations occurring in the first two importations. The values for the nine common accessions followed a similar trend (importation 1 = 132.7; importation 2 = 119.1; importation 3 = 145.9 mg/100 g) though the differences were not significant (F2,24 = 0.59; P = 0.56). None of the correlations of the values of the common accessions were significant between importations (R =0.2-0.4; P = 0.29-0.52).

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The statistics for manganese concentrations are presented in Table 6.2 and summarised in Table 6.8. For all of the data, as with magnesium, the average concentrations in the material from importations 1 and 2 were significantly lower than from importation 3

(F2,64 = 33.6; P < 0.001) as were the average concentrations in the common accessions

(Importation 1 = 6.41, importation 6.74 and importation 3 11.24 mg/100 g) (F2,24 = 9.44; <0.001). The correlation between the data from importation 1 and 2 was significant for the nine accessions (r = 0.72; P = 0.02) but not for the correlations between the other combinations of data (r = 0.12, P = 0.76, importations 1 & 3; r = 0.10, P = 0.80, importations 1 & 3).

Lastly, the copper concentrations are shown in Table 6.7 and summarised in Table 6.8. The copper values ranged between 0.17 to 1.7 mg/100g. There was no significant difference in the average values for all accessions for the two importations assessed (F1,

35 = 2.19; P = 0.15) nor for the eight accession that were common between the two importations (F1,14 = 0.44; P = 0.51). In addition, there was no correlation between the values for the two importations.

Overall from the analyses described above, average concentrations of calcium and potassium tended to be highest in importation 1 and lowest in importation 2. Average concentrations of sodium, magnesium and manganese tended to be highest in importation 3 with little difference between importations. The soil type, weather and the growing conditions may have contributed substantially to the difference in the values of mineral nutrients assayed in this study, because the accessions were not grown under controlled conditions. The plants were harvested at different times of the year, in February, 2011, there was a flood which affected a number of accessions so only 15 out of the 30 accessions were collected and imported into Sydney for analysis. In October of the same year (2011), a sampling attempt was made for the accessions that were not collected, but the dry weather was severe and irrigation problems lead to poor growth of the plants. The soil at Laloki is loamy in nature with some percentage of clay, features of local climate include a marked dry season with dry SE winds from May to October and the wet season with variable NE winds from December to April. The centre is prone to

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floods every 2-3 years (Kambuou, pers. comm. 2011).So the September 2012 and May 2010 collections were done during the dry season whilst the February 2011 sample collection was done during the wet season at Laloki.. According to Alam (1999), availability of iron and manganese is improved under flooding conditions; this occurs when they form metallo-organic complexes with organic substances and hence is converted to more reduced and soluble forms to be taken up by plants. On the other hand, uptake of nutrients by the roots of plants and their transportation to the shoots declines during drought periods; this is because of the negative impact of drought on the processes of transpiration, active transportation and membrane permeability (Viets 1972, Alam 1999). Decreased water content of the soil reduces the availability of potassium to plants, calcium uptake is decreased; however, on the whole, its accumulation is mildly affected compared to that of phosphorus and potassium, whilst magnesium uptake is reduced (Hu, 2005).

6.5 Environmental and or other factors which may influence the variability in the mineral content of aibika accessions.

Plant species, genotype, growth conditions, agricultural practices are some of the factors influencing the micronutrient concentrations in plants; the changes in the concentration of the micronutrients in a plant is impacted by the interaction of the environmental and physiological factors as well as the genetic makeup of the plant species itself (Welch et al. 1995). Type of iron, soil pH, ion pair solubility, water, soil oxygen, plant sugar supply, plant stress, temperature and soil nutrient levels are some of the factors that affect nutrient absorption in plants. (the availability of nutrients for uptake by plants is influenced by the soil pH and texture, the texture of the soil determines the retention of nutrients and water in the soil, classification of soil depends on percentage of sand, silt and clay, soils with high clay content tend to hold water more and retain nutrients more (Jones & Jacobsen, 2001). The soil types are also classified according to their total negative charge or the ‘cation exchange capacity’ or CEC—this value indicates how well a soil can retain and supply nutrients to crops. Soil pH is very important because it influences the availability of nutrients; copper, iron, zinc and manganese for instance are more available at low pH, whilst calcium, magnesium,

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sodium and potassium are not and hence are prone to leaching out at low pH (Jones & Jacobsen, 2001).

The soil at Laloki is loamy in nature with some percentage of clay (Kambuou, pers. comm. 2011). A profile of the soil at Laloki was done in 2011 by Richard Doyle from UTAS & ACIAR, (Kambuou, pers. comm. 2011). Soil test indicated the pH at a favourable range of 5.9-6.1 with a moderate CEC value. Evidence of excessive cultivation and declining soil organic carbon levels was also noted.

One other factor that influences uptake of nutrients is genetic composition of a particular variety. Some varieties within a species can have specific genes that allow them to absorb or accumulate more of certain nutrients and, during the recent years, many studies have been done to increase availability of certain micronutrients especially iron, zinc and vitamin A in some commonly consumed foods including, wheat, rice, and maize; Welch and Graham (2004) summarise these studies. It is well established that the interaction of environmental and cultural factors with gene expression influences the micronutrient uptake and accumulation in plants (Bouis and Welch, 2010).

The results in Tables 6.0 to 6.9 all show that there is little relationship between the genotype of a particular accession and nutrient uptake and accumulation as in general there was no correlation between concentrations on minerals in a particular accession from a particular importation with concentrations in that accession from the other importations.

6.6 Comparing the analysed aibika data with nutrient data from the Pacific Islands Food Composition Tables

There is no analytical data on the nutrient composition or for that matter mineral composition of aibika or any other green leafy vegetables consumed in PNG to compare, the next best comparison would be with the data from similar foods consumed in other Pacific Island countries. Although, most foods in the Pacific Island Food Tables are from Fiji, it would be relevant to compare with because of similarities between the two countries. Most foods grown and consumed in Fiji are also grown and consumed in 145

PNG, the nutrient composition would not be the same due to environmental, climatic or cultural factors in growing of the crops.

Table 6.10 Mineral composition of several green leafy vegetables consumed in the Pacific Green leafy Na Mg K Ca Fe Zn Vegetable (mg) (mg) (mg) (mg) (mg) (mg) Amaranth 34 130 646 310 4.9 0.7 Choko leaves 3 51 352 70 7.2 0.2 Edible hibiscus leaves a 18 118 484 268 1.9 1.4 Edible hibiscus leaves boiled 6 108 201 216 1.5 1.2 Fern leaves 11 43 562 27 4.0 2.8 Fig, poke leaves 10 106 435 5 1.0 0.4 Nightshade leaves 4 61 346 225 19.0 0.3 Pumpkin leaves 17 78 438 480 2.5 0.9 Water dropwort leaves 1 65 156 134 1.8 0.5 Watercress leaves 4 15 399 119 3.0 0.8 Spinach tropical leaves 2 119 259 309 8.7 0.5 a Edible hibiscus is a synonym for aibika Source: Pacific Islands Food Composition Tables (2ed., 2004)

Comparing the range of values for the minerals in the aibika accessions studied to the other green leafy vegetables consumed in PNG and Pacific, (Table 6.10) the following conclusions can be made: - That the iron content of aibika accessions (0.8-8.7) in this study were similar to the data from Fiji in Table 6.10, although some accessions have higher values. Other vegetables like nightshade, choko and amaranth have higher iron contents than aibika, so a diet that includes a variety of these green leafy vegetables would increase iron intake. - The range of 0.3 to 2.3 mg/100 g of zinc in aibika (Table 6.8) is within the range of the data of zinc content of the vegetables listed in Table 6.10. The average values for sodium, potassium and magnesium are also similar to the values for aibika in Table 6.8 in the literature as well as that for the other vegetables, certain accessions had higher or lower values. - The mineral values in the boiled aibika are much less, compared to the raw values. The loss is less pronounced in iron and zinc compared to the other

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mineral; however, because of the nutritional importance of these minerals and low levels found in plants, the minimal loss can be significant.

6.7 Quality control for mineral analysis

The table below shows the values for the standard reference method used with the analysis of minerals using ICPOES. Some of the minerals have results have the certified values expressed in mass fractions whilst others are expressed as milligrams per kilogram values.

Table 6.11 Mineral values of SRM 157a Tomato leaves Mineral Values from material Average Values from database (NIST experiment (average of 4 certificate of Analysis) values)

Calcium 5.05 ± 0.09 mass fraction 45.55 mg/g (%)

Sodium 136 ± 4 mg/kg 0.215 mg/g or 215 mg/kg

Iron 368 ± 7 mg/kg 0.28 mg/g or 280 mg/kg

Zinc 30.9 ± 0.7 mg/kg 0.03 mg/g or 30 mg/kg

Potassium 2.70 ± 0.05 mass fraction 25.4 mg/g (%)

Magnesium No certified value 10.475 mg/g

Manganese 246 ± 8 mg/kg 0.225 mg/g or 225 mg/kg

Copper 4.70 ± 0.14 mg/kg 0.01 mg/g or 10 mg/kg

6.8 Conclusion

The mineral values in aibika accessions grown in Laloki and analysed in this study showed variability in both accessions and between collection periods. The accession that had a higher value of one mineral in the first collection did not necessary have the highest value in the consecutive collections, which implies that genotype and its

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phenotypic expression may not affect mineral content. However, climatic conditions or other environmental factors may have contributed to the variability of the values. Compared to other important green leafy vegetables consumed in the Pacific Island countries, aibika is of good nutritional value and to maximise mineral intake, a combination of aibika and other green leafy vegetables should be included in the diet. Minerals get leached into the cooking water during preparation of aibika and or vegetables so steaming; use of a minimum amount of water as well using the cooking water are amongst the best practices to increase intake.

6.9 Recommendation for future study

To effectively study the variability of minerals in aibika accessions, the accessions should be grown in some standardised controlled conditions. Sampling and analysis needs to be standardised as well and soil studies have to be done so as to know the actual mineral content of the soil the accessions are grown on.

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Chapter 7

General Discussion and Conclusions

This chapter aims to integrate the discussion and conclusions drawn from the micronutrient and genetic work and address one of the main objectives of the study which is to see if genetic diversity does have an effect on micronutrient content of the aibika accessions. The relationship between the morphological and genetic analysis is also compared to see if a specific trait (shape of leaf, or stem colour, etc.) of an accession can be linked to the genetic groups. Since the sequencing work using the chloroplastal regions and ITS did not show any variation among the accessions, the genetic data referred to in this section is elaborated in Chapter 3.

7.1 Relationship between the groups found in this study (see results in Chapter 3, Figure 3.5) and their morphology (photos of the leaves)

Photographs of the leaves of a number of the accessions used in the genetic analysis are as below. These photographs were taken during sampling to show the morphological differences between the accessions. The photographs were examined to see if any similarity in leaf shape could be found within the groups proposed from the genetic analysis. The clustering of the accessions based on presence and absence of bands generated from RAPD and DAMD-PCR for these proposed groups are explained in Figure 3.5.

7.1.1 Group 1: Accessions LAL Am 170, LAL Am 180, LAL Am 200, LAL Am 203, LAL Am 204, LAL Am 206 and LAL Am 220

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Figure 7.0 LAL Am 170

Figure 7.1 LAL Am 200

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Figure 7.2 LAL Am 204

Figure 7.3 LAL Am 206

7.1.2 Group 2: Accessions LAL Am 009, LAL Am 011, LAL Am 030, LAL Am 041, LAL Am 045 and LAL Am 221

Figure 7.4 LAL Am 009

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Figure 7.5 LAL Am 041

Figure 7.6 LAL Am 045

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Figure 7.7 LAL Am 030

Figure 7.8 LAL Am 221

7.1.3 Group 3: Accessions LAL Am 016 and LAL Am 035

Figure 7.9 LAL Am 016

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Figure 7.10 LAL Am 035

7.1.4 Group 4: Accessions LAL Am 134, LAL Am 141 and LAL Am 166

Figure 7.11 LAL Am 134

Figure 7.12 LAL Am 141

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Figure 7.13 LAL Am 166

7.1.5 Group 5: accessions LAL Am 082 and LAL Am 123

Figure 7.14 LAL Am 082

Figure 7.15 LAL Am 123 163

Within Group 1, the leaves of LAL Am 200 and 206 were deeply lobed, with the lobes being so deeply divided that they appear to be almost individual leaflets of a palmately compound leaf. Each of the lobes is spathulate, with the apparent petiolules being narrowly winged (alate). However, the lobes of LAL Am 170 were relatively shallow being less than one third of the lamina length and acute, whilst the lobes of LAL Am 204 were more deeply incised and narrowly triangulate. Within Group 2, the leaves LAL Am 045, 221 and 041 had a reduced number of lobes with 041 having only one lobe and 045 and 221 having only three lobes; the lobes of the latter two accessions were not deeply incised and were mostly obtuse. The other two accessions in this group (LAL Am 009 and 030) had four and five lobes, respectively, and the lobes were deeply incised and narrow lanceolate, the margins being conspicuously undulate. The shape of the leaves of the two accessions within Group 3 were similar having five lobes that were deeply incised but, in contrast to accessions LAL Am 009 and 030, the incision was not present all the way to the base leaving approximately 10–20 mm joined at the junction of the main veins. The leaves of the three accessions in Group 4 had four or seven lobes, and the lobes were only moderately incised with the incision being only one to two thirds of the lamina. Finally, the leaves of the two accessions of Group 5 were dissimilar, with one (LAL Am 082) having multiple lobes that were deeply incised and narrow lanceolate with the incision proceeding almost to the base; the leaf lobes of LAL Am 123 were only moderately incised and were irregular in shape. Thus, whilst there was some similarity between the leaf shapes of the different groups (e.g., two accessions in Group 1 being spathulate and spathulate leaves only occurring in this group and, in Group 3, the leaves of three of the accessions having a reduced number of lobes with the lobes not being deeply incised) there was also substantial overlap in leaf shape among the groups with most groups having accessions with narrow and deeply incised lobes. Therefore, the genetic analysis of the accessions did not correlate well with leaf morphology. The genetic relationships determined from RAPD and DAMD profiles are at the whole genome level whilst the genes governing leaf shape only represent a small fraction of the genome; hence, there need not be a relationship between the profiles and leaf shape.

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7.2 Relationship between the genotypes and micronutrient data over the 3 year period

The dendograms discussed in this section were derived using UPGMA to see if there were any similarities in the relationship between the micronutrient and the accessions of aibika in the three year period. The main objective was to see if a specific accession or group of accessions would have consecutively similar levels of certain micronutrient or micronutrients over the three year period that the aibika accessions were collected. The clusters would then be more identifiable. There is one dendogram for each of the three years of sample collections. The data used to construct these dendograms are from the folate values in Table 5.0 in Chapter 5 and the mineral results in Chapter 6 in Tables 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, and 6.7, these micronutrient data were put together with the clustering of accessions presented in Figure 3.5 in Chapter 3.

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Figure 7.16 Clustering determined by UPGMA analysis of accessions from first sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers.

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Figure 7.17 Clustering determined by UPGMA analysis of accessions from the second sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers.

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Figure 7.18 Clustering determined by UPGMA analysis of accessions from the third sample collection determined from the concentrations of all eight minerals and folate. The numbers on the branches denote the accession identification numbers.

Looking at all the three dendograms, it can be seen that there is clearly no similarity between them. Accessions of aibika in year 1 were grouped into four main clusters (Figure 7.16) but, within these main clusters, sub-clusters can also be found. Accessions of aibika in year 2 were grouped into three main clusters with one accession not belonging to any of the main clusters and further away from the others. Sub-clusters can also be seen within these three main clusters. In year 3, the accessions of aibika (Figure 7.18) grouped into two main clusters with two accessions clustering together and distantly from the remainder of the accessions. It can be concluded that based on the micronutrient data, there are no similarities in the accessions forming each cluster in each of the three year’s data (Figures 7.16, 7.17, 7.18), i.e., accessions that clustered together in one year did not necessarily cluster together in the subsequent years. This means that there is no specific accession or groups of accessions that have similar amounts of certain micronutrient or micronutrients which were analysed in this study. Same could be said for the clustering of the accessions according to the genetic data. There were no similarities in the clustering of accessions based on the genetic analysis and that from the micronutrient analysis from any of the three years.

7.3 General conclusions

From the micronutrient and genetic data generated in this study, the following general conclusions can be made:

• Aibika varieties are a good source of folate and mineral micronutrients.

• The twenty three completely different aibika accessions (according to morphological characterisation) were grouped into 5 main groups using the bands generated from the techniques RAPD and DAMD.

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• The micronutrient data for the following nutrients: folate, iron, zinc, calcium, potassium, sodium, magnesium, manganese and copper showed variation in concentrations from one year to the other.

• There seemed to be no significant effect of genotype on the micronutrient content of the aibika accessions.

• There was no significant relationship between the morphology of the leaves and the 5 main groups according to genotype.

• UPGMA clustering of the accessions based on micronutrients showed variation from year to year.

• It is evident from all these data that environmental and other factors seem to play a greater role in influencing the micronutrient data rather than genotype.

7.4 Future work

7.4.1 Micronutrient analysis

Using the data and techniques used in this study, future work should aim at standardising the growing or agricultural practices used in maintaining the accessions on the field. All accessions should be harvested and analysed together in a year so that there is no missing values and the nutrient data of the accessions grown in different seasons as well as in different locations are compared to see the effect of genotype on micronutrient contents.

7.4.2 Genetic analysis

For genetic analysis, future work should take advantage of the DNA extraction methods and PCR conditions optimised in this study to generate more banding patterns to confirm the genetic relationships between and within the aibika accessions in collections in Papua New Guinea.

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APPENDIX A

An oral presentation given at the 9th International Food Data Conference held in Norwich, UK, September 14 – 17th 2010.

Title:

Aibika (Abelmoschus manihot L.) a commonly consumed green leafy vegetable in Papua New Guinea (PNG): Biodiversity and its effect on micronutrients.

Abstract: (Your abstract must use Normal style and must fit into the box. Do not enter author details)

Rationale and objectives. Green leafy vegetables are known to be good sources of iron, folate and other micronutrients. Aibika is the most popular and commonly-consumed indigenous green leafy vegetable in PNG. Despite this, micro-nutrient deficiencies especially anaemia are major nutritional problems in PNG. The PNG National Agricultural Research Institute (NARI) is playing a key role in the collection, preservation, morphological characterization and preliminary assessment of aibika accessions. To date the genetic makeup of aibika is unknown. The main objectives of this study are to analyze over thirty different varieties of aibika for micronutrients including folate, minerals and beta-carotene; and to trace the variability of nutrients between the varieties using genetic fingerprinting. The selected micronutrient profile for the varieties would then be documented and the most promising nutrient-rich varieties promoted for consumption in the community. This will also help NARI put in place an effective conservation management system for the aibika germplasm.

Materials and methods. Over 30 accessions grown under similar conditions at NARI were vacuum packed and frozen at -20oC for atleast 3 days to satisfy Australian Quarantine requirements before they were freighted packed in ice to Sydney. Genetic variation was determined using random amplified polymorphic DNA (RAPD) and chloroplast DNA gene sequencing. Mineral analysis was performed using ICPOES whilst for the folate, the extract was tri-enzyme treated and analysed using the Vitafast® folic acid kit.

Results. Initial results for folate ranged from 170 – 300 (µg/100g fresh weight), the mineral contents (mg/100g) were in the following ranges; iron, 5 - 14; zinc, 2 – 14; potassium, 2381 - 3902; calcium,1595 - 2736; magnesium, 570 - 1030; manganese, 2 - 6; sodium, 8 - 87. Preliminary genotyping showed no variation between the accessions in the chloroplast trnL(UAA) 5’ exon and trnF(GAA) region, however, variation was detected in the psbM-trnDGUC, and using RAPD and further studies are in progress.

Abelmoschus manihot L., Aibika, micronutrient, DNA sequence, RAPD

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APPENDIX B

A poster presented at the 10th International Food Data Conference held in Granada, Spain, September 12-14th 2013.

AIBIKA (ABELMOSCHUS MANIHOT L.) A COMMONLY CONSUMED GREEN LEAFY VEGETABLE IN PAPUA NEW GUINEA: BIODIVERSITY AND ITS EFFECT ON MICRONUTRIENTS

Rubiang-Yalambing1 L; Greenfield H2; Holford P3; Arcot J1

1 School of Chemical Engineering, University of New South Wales, Australia 2 University of Sydney, Sydney, Australia School of Science and Health, University of Western Sydney (Hawkesbury Campus)

Presenting author’s contact details: Email: [email protected] or [email protected] Postal Address: Department of Applied Sciences, PNG University of Technology, PMB, Unitech, Lae, Papua New Guinea Phone: (+675 4734551)

Rationale and objectives: Aibika is the most popular and commonly-consumed indigenous green leafy vegetable in PNG. Despite this, micro-nutrient deficiencies especially anaemia are major nutritional problems in PNG. The main objectives of this study were to analyze over twenty different varieties of aibika for micronutrients including folate, and minerals over a period of three years and study the variability between varieties and between seasons. Materials and methods: Over 20 accessions grown at the National Agricultural Research Institute (NARI) were collected for three years in 10 replicates each, vacuum packed and frozen at -20oC before analysis. Mineral analysis was performed on composite samples of each variety using ICPOES and tri-enzyme extraction using the Vitafast® folic acid kit for total folate. Results: Total folate contents ranged from 34 – 132 µg/100 g on a fresh weight basis over two years indicating a wide range and a significant difference (p<0.05) between the two years. The mineral contents (mg/100g fresh weight) were in the following ranges for the 3 year period; iron, 0.8 –8.7; zinc, 0.32 – 2.31; calcium, 197 – 635; potassium, 265 – 630; sodium, 1.0 – 41; magnesium, 79-264; manganese, 0.42 – 2.09 and copper, 0.13 – 1.7. A significant (p<0.05) variation in the mineral contents was observed reflecting on variations in growing conditions between the collectons.

Key words: Abelmoschus manihot L., Aibika, micronutrients

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APPENDIX C

An oral presentation given at the 10th International Food Data Conference held in Granada, Spain, September 12 – 14th 2013.

AIBIKA (ABELMOSCHUS MANIHOT L.) GENETIC VARIATION AND RELATIONSHIP TO MICRONUTRIENT COMPOSITION

Rubiang-Yalambing1 L; Arcot J1; Greenfield H2; Holford P3

1 School of Chemical Engineering, University of New South Wales, Australia 2 University of Sydney, Sydney, Australia 3 School of Science and Health, University of Western Sydney (Hawkesbury Campus)

Background and objectives: Aibika is a perennial shrub in the family Malvaceae that is a commonly consumed indigenous green leafy vegetable in PNG. The taxonomy of Abelmoschus and the species A. mannihot is very complex and possesses very variable leaf characteristics. This study was performed in order to make a preliminary screen of the accessions currently held at the National Agricultural Research Institution (NARI) in PNG with the objective of determining the extent of genetic diversity which would aid effective management of the aibika germplasm.

Materials and methods: Over 20 accessions grown at NARI were collected and mineral and total folate analysis was performed using ICPOES and the Vitafast® folic acid kit. The techniques of random amplification of polymorphic DNA and directed amplification of minisatellite region DNA were used to study the genetic variation between the accessions. The data matrix (dendograms) was generated from the RAPD and DAMD band patterns using the DendroUPGMA software.

Results: UPGMA analysis revealed five distinct genetic groups within the accessions studied. The clusters of accessions of aibika according to concentrations of all minerals and total folate in the accessions revealed differences. It was concluded that environmental and other factors seem to have a greater impact on the micronutrient data compared to the genotype.

Key words: Abelmoschus manihot L., Aibika, micronutrients

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APPENDIX D

Three (3) separate gene sequences from this research was submitted directly to the GenBank. The following are the descriptions and the accession numbers allocated to the each of them.

GenBank flat file:

LOCUS KC488171 519 bp DNA linear PLN 18-APR-2013 DEFINITION Abelmoschus manihot psbM-trnD intergenic spacer, partial sequence; chloroplast. ACCESSION KC488171 VERSION KC488171 KEYWORDS . SOURCE chloroplast Abelmoschus manihot ORGANISM Abelmoschus manihot Eukaryota; Viridiplantae; Streptophyta; Embryophyta; Tracheophyta; Spermatophyta; Magnoliophyta; eudicotyledons; core eudicotyledons; rosids; malvids; Malvales; Malvaceae; Malvoideae; Abelmoschus. REFERENCE 1 (bases 1 to 519) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Analysis of accessions of Abelmoschus manihot from the collection at the National Agricultural Research Institute, Papua New Guinea JOURNAL Unpublished REFERENCE 2 (bases 1 to 519) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Direct Submission JOURNAL Submitted (15-JAN-2013) School of Science and Health, University of Western Sydney, Bourke Street, Richmond, NSW 2753, Australia

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LOCUS KC488172 988 bp DNA linear PLN 18-APR-2013 DEFINITION Abelmoschus manihot tRNA-Leu (trnL) gene and trnL-trnF intergenic spacer, partial sequence; chloroplast.

ACCESSION KC488172 VERSION KC488172 KEYWORDS . SOURCE chloroplast Abelmoschus manihot ORGANISM Abelmoschus manihot Eukaryota; Viridiplantae; Streptophyta; Embryophyta; Tracheophyta; Spermatophyta; Magnoliophyta; eudicotyledons; core eudicotyledons; rosids; malvids; Malvales; Malvaceae; Malvoideae; Abelmoschus. REFERENCE 1 (bases 1 to 988) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Analysis of accessions of Abelmoschus manihot from the collection at the National Agricultural Research Institute, Papua New Guinea JOURNAL Unpublished REFERENCE 2 (bases 1 to 988) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Direct Submission JOURNAL Submitted (15-JAN-2013) School of Science and Health, University of Western Sydney, Bourke Street, Richmond, NSW 2753, Australia

LOCUS KC488173 685 bp DNA linear PLN 18-APR-2013 DEFINITION Abelmoschus manihot internal transcribed spacer 1, partial sequence; 5.8S ribosomal RNA gene and internal transcribed spacer 2, complete sequence; and 28S ribosomal RNA gene, partial sequence.

ACCESSION KC488173 VERSION KC488173 174

KEYWORDS . SOURCE Abelmoschus manihot ORGANISM Abelmoschus manihot Eukaryota; Viridiplantae; Streptophyta; Embryophyta; Tracheophyta; Spermatophyta; Magnoliophyta; eudicotyledons; core eudicotyledons; rosids; malvids; Malvales; Malvaceae; Malvoideae; Abelmoschus. REFERENCE 1 (bases 1 to 685) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Analysis of accessions of Abelmoschus manihot from the collection at the National Agricultural Research Institute, Papua New Guinea JOURNAL Unpublished REFERENCE 2 (bases 1 to 685) AUTHORS Rubiang-Yalambing,L. and Holford,P. TITLE Direct Submission JOURNAL Submitted (15-JAN-2013) School of Science and Health, University of Western Sydney, Bourke Street, Richmond, NSW 2753, Australia

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