EFFECTS OF ORGANIC VERSUS CONVENTIONAL FARMING METHODS ON PHYSICAL AND CHEMICAL SOIL QUALITY INDICATORS

A Thesis

Presented in Partial Fulfillment of the Requirements for

The Degree Masters of Science in the Graduate

School of the Ohio State University

By

E. Hayden Emery, B.S.

*****

The Ohio State University 2006

Master's Examination Committee Approved by

Professor Rattan Lal, Adviser

Professor Harold Keener Adviser

Dr. Khandakar Rafiq Islam Graduate Program in Soil Science ABSTRACT

There is no universally accepted definition, but in general organic farming is a production system, which avoids or largely excludes the use of synthetically compounded fertilizers, pesticides, growth regulators, and livestock feed additives.

Organic systems emphasize use of renewable resources and conservation of soil and water, enhance environmental quality for future generations. The breadth and quality of soil organic carbon in agroecosystems affects soil’s physical, chemical, and biological properties and therefore influences soil productivity and the sustainability of certain production systems. Soil quality is an integral aspect of soil sustainability and can be used to determine sustainability on a soil to soil level. These two ideas have been linked as “inseparable” and soil quality is considered a “key indicator” of ecosystem sustainability. Recently, with growing concerns over soil degradation and the need for more sustainable soil management practices, there has been a marked emphasis on the value of soil and its properties pertaining to specific ecological and agricultural functions.

The objectives of this study were to identify land use systems and soil/vegetation management practices that lead to an enhanced SOC pool, principally with regards to compost, cover crops, various forms of organic manure, and crop residue. Specific objectives are: to comparatively assess soil quality changes in ii conventional fanning vis-á-vis organic farming practices, quantify the effects of organic farming practices on crop yield, and establish relation between soil quality indicators and crop yield.

This study was broken into two parts, a 6 farm survey and an experimental plot with 6 replications. In this two-year experiment, 3 pairs of farms were sampled for biometric parameters, crop yield and aboveground biomass yield. In each pair there was a certified organic farm and a conventional farm with matching soil types to eliminate yield differences due to exogenous soil variations. The soils sampled were Blount,

Bennington, and Chili silt loams, all planted to corn (Zea mays). On each farm, 3x3m adjacent plots were chosen for core sampling at 0-30cm depth. Overall, the conventionally managed farms did have higher yields across years with an average of

5.3 Mg ha-1, but in 2004 the Chili silt loam organic farm surpassed two of the conventional farms in grain production with 6.4 Mg ha-1 compared to 4.6 and 4.4 Mg ha-1. The Chili silt loam farm has been under organic management for 20 years, the longest period of time compared to the other organic farms. This agrees with other studies that have found organic systems under long-term management often have similar yields to conventionally managed farms.

In this experiment, the 3 pairs of farms were also sampled for a range of soil quality indicators including: pH, mean weight diameter (MWD), water stable aggregation (WSA), bulk density, available water capacity (AWC), cation exchange iii capacity (CEC), and soil organic carbon and nitrogen pool. After analysis, the values for each parameter were assigned a soil quality index rating to compare overall soil quality of each management system. There are many different indices that can be used to measure soil quality but the one implemented here did not reveal a trend according to management system. The Blount silt loam organic farm did have the best soil quality but the two other organic farms had the worst ratings. These findings do not correlate with past studies, which found organic management increased overall soil quality when compared to conventional practices.

In second part of the two-year experiment, a complete random block design was used to test six treatments on various soil quality indicators. These treatments included cover crop, dairy manure, tannin bark compost, fallow, control and Triple 19 fertilizer. The treatments were used to represent common conventional and organic management practices. The synthetic fertilizer and manure yielded the highest amount of corn among the six treatments. According to the soil quality index implemented, organic and conventional farming practices had a similar soil quality index. The synthetic fertilizer and manure treatments also received the highest soil quality ratings while the compost had the lowest yield and worst soil quality rating. These findings expressed a correlation between crop yield and soil quality for this study. This information must be coupled with other long-term studies to more accurately explore the connection between organic agricultural practices and soil quality. iv Dedicated to my parents, Patricia and Gregory Emery,

Dr. Charles J. Stevens,

and my grandmother, Ella Emery

v ACKNOWLEDGMENTS

I would like to thank my adviser, Professor Rattan Lal, for his expertise and knowledgeable advice. I wish to thank Dr. Rafiq Islam for his patient instruction and support, and Professor Harold Keener for his insight. I am grateful to Sindhu

Jagadamma for her endless assistance and dedication in all aspects of the project. Thank you also to Travis Broome, Joyce Tanzosh, Tony Karcher and Jake Elder for their assistance in field work, and Y ogendra Raut, David U ssiri and the staff of the soil physics lab for their technical support. Thanks to Bert Bishop for his help with statistical aspects of the thesis. I would also like to wholeheartedly thank the farmers that were willing to participate in this study for their cooperation: Mr. Jeff Dickenson,

Mr. Dick Jensen, Mr. Ed Snavely, Mr. Otto Smith, Mr. Dennis Shinaberry, and Mr. Bill

Conklin.

Vl VITA

September 20, 1980 ...... Born- Cincinnati, Ohio

2002 ...... B.S. Zoology and

minor in Anthropology,

Miami University of Ohio

2003-present ...... Graduate Teaching

and research Associate,

The Ohio State University

FIELDS OF STUDY

Major Field: Soil Science

Vll TABLE OF CONTENTS

Page

Abstract ...... ii

Dedication ...... v

Acknowledgements ...... vi

Vita ...... vii

Ltst. o fF"tgures ...... xu ..

List of Tables ...... xiii

Chapters:

I. Introduction ...... I

I.I Brief History of Organic Agriculture ...... !

I.2 Sustainability ...... 4

I.2.I Definition ...... 4

I.2.2 Soil Quality ...... 7

I.2.3 Need for Management of Soil Fertility ...... 7

I.2.4 Assessment ...... 8

I.3 Carbon Sequestration ...... I 0

I.4 Objectives ...... I6

List of references ...... I7

Vlll 2. Agronomic sustainability of organic farms ...... 19

Abstract ...... 19

Introduction ...... 20

2.1 Methods and materials ...... 24

2.1.1 Site descriptions ...... 24

2.1.2 Methods ...... 29

2.2 Results and discussion ...... 30

2.2.1 Trends across years ...... 35

2.2.2 The effect of duration under organic management ...... 3 7

Discussion and conclusions ...... 39

List of references ...... 41

3. A soil quality comparison of organic and conventional farms ...... 43

Abstract ...... 43

Introduction ...... 44

3 .1.1 Soil organic matter ...... 44

3.1.2 Strategies for obtaining organic material ...... 45

3.1.3 Cover cropping ...... 49

3.1.4 Manuring ...... 51 IX 3.1.5 Crop residues ...... 52

3.1.6 Soil quality indices ...... 57

3.2 Material and methods ...... 58

3.2.1 Sampling methods ...... 58

3.2.2 Laboratory methods ...... 59

3.2.3 Statistical analysis ...... 60

Results and discussion ...... 61

3.3.1 Results ...... 61

3.3.2 Discussion ...... 76

Conclusions ...... 80

List of references ...... 83

4. Soil quality comparison of six management treatments ...... 87

Abstract ...... 87

Introduction ...... 88

4.1.1 Soil quality ...... 88

4.1.2 Soil indices ...... 89

4.2 Materials and methods ...... 90

4.2.1 Site description ...... 90

4.2.2 Laboratory methods ...... 92

4.2.3 Statistical analysis ...... 94

X 4.3 Results and discussion ...... 95

4.3.1 Soil physical properties ...... 96

4.3.2 Soil chemical properties ...... 97

Conclusions ...... 102

List of references ...... 1 04

5. Conclusions ...... 106

List of references ...... 109

XI LIST OF FIGURES

FIGURE Page

2.1 County Map ...... 28

3.1 Water Stable Aggregation (%) according to soil type and management

system ...... 66

1 3.2 SOC Pool (Mg ha- ) according to soil type and management ...... 67

3.3 pH comparison according to soil type and management system ...... 68

3.4 CEC and WSA correlation among six farms (2004) 0-30cm ...... 69

3.5 SOC and soil pH correlation among six farms (2004) 0-30cm ...... 70

3.6 CEC and soil pH correlation among six farms (2004) 0-30cm ...... 71

3.7 Soil Nand soil pH correlation among six farms (2004) 0-30cm ...... 72

3.8 SON and SOC correlation among six farms (2004) 0-30cm ...... 73

3.9 WSA and SOC correlation among six farms (2004) 0-30cm ...... 74

4.1 Plot and treatment layout for Waterman experimental site ...... 95

Xll LIST OF TABLES

Table Page

2.1 Average leaf height among six conventional and organic farms in 2004 ... 30

2.2 Average Biomass Yield and Grain Yield among six conventional and

organic farms in 2004 ...... 31

2.3 Average harvest Index among six conventional and

organic farms in 2004 ...... 32

2.4 Average leafheight among six conventional and organic farms in 2005 .. .33

2.5 Average Biomass Yield and Grain Yield among six conventional and

organic farms in 2005 ...... 34

2.6 Average Harvest Index among six conventional and organic

farms in 2005 ...... 35

2. 7 Comparison between organic and conventional farms across years ...... 36

2.8 Comparison of systems across years ...... 37

2.9 Comparison of organic farms across years according to establishment ....38

3.1 Soil physical property means according to soil type and management

system ...... 62

3 .2 Soil chemical property means according to soil type and management

system ...... 63 Xlll 3.3 Soil chemical property means according to depth and management

system ...... 64

3.4 Soil physical property means according to depth ...... 64

3.5 Soil physical and chemical comparisons according to management

system ...... 65

3.6 Soil Quality Index for six farms 0-30cm depth (2004) ...... 71

3.7 Soil quality rating versus crop yield (2004-2005) for six farms ...... 76

4.1 Waterman physical property mean comparison for six treatments 0-20cm

(2003-2005) ...... 96

4.2 Waterman soil property mean comparison for all treatments by depth

(2003-2005) ...... 97

4.3 Waterman chemical property mean comparison for six treatments 0-20cm

(2003-2005) ...... 98

4.4 Waterman soil property mean comparison for all treatments according to

year 0-20cm depth ...... 99

4.5 Crop yield and biometric parameters for six treatments (2004-2005) .. 100

XIV 4.6 Soil quality index for Waterman soil parameters according to

treatinent ...... 101

4. 7 Soil quality rating and crop yield (2004-2005) comparison for

Waterman ...... 1 02

XV CHAPTER 1

INTRODUCTION

1.1 Brief History of Organic Agriculture

Until the 1940s most agriculture worldwide could have been considered organic because neither fertilizers nor pesticides were used. It was WWII and the mass production of chemicals that led to pesticide and herbicide development and its dissemination. Since that time three major movements came about which encouraged a more sustainable approach to agriculture, oftentimes drawing on historical local knowledge. Biodynamic agriculture, spearheaded by the research of Rudolph Steiner, grew in Germany and involved a more spiritual connection with the land and natural forces. In 1940s England, the idea of organic farming also blossomed (Duram, 2005).

A British writer named Lord Northbourne described an integrated and sustainable farm as "a dynamic living organic whole" (Scofield, 1986). Albert Howard, with his

Agricultural Testament, and Lady Eve Balfour developed more in-depth theories on the topic. Around the same time a similar movement called biological agriculture began under the tutelage of Hans Peter Rusch and Hans Muller in Switzerland (Le

Guillou and Scharpe, 2001 ).

1 There is no universally accepted definition, but in general organic farming is a production system, which avoids or largely excludes the use of synthetically compounded fertilizers, pesticides, growth regulators, and livestock feed additives.

Organic systems emphasize use of renewable resources and conservation of soil and water, enhance environmental quality for future generations and meat, poultry, eggs, dairy, come from animals with no added antibiotics or growth hormones. Organic crops are produced without conventional pesticides, synthetic fertilizers, or sewage sludge, bioengineering or ionizing radiation. The crops must be government approved and USDA certified. Their systems rely on crop rotations, crop residues, animal manures, legumes, green manures and off-farm organic wastes to build nutrients in the soil. They also use aspects of biological pest control to limit insects, weeds and other pests (www.ers.usda.gov). Until recently, organic foods were certified by independent agencies on a state-by-state basis but that is quickly changing. The U.S. government has been mandated since 1990 to create a standardized definition of the word

"organic", and a set of rules that will determine if products can be labeled as such.

In late 1997 the USDA released their first version of the new proposed rules for public comment. Consumers and the organic industry overwhelmingly rejected it.

The key reasons they did not approve the proposed plan were because it still allowed for the use of organically modified organisms (GMOs), human waste from sewage treatment plants and food-ionizing radiation (irradiation) (Turner, 2000).

Previously organic farmers went by their own set of informal guidelines for what they called "organic". For example, fruits and vegetables must be

2 grown without the use of pesticides, herbicides or preservatives, and livestock must be raised in an open-air environment, without antibiotics or hormones. But farmers began fearing the organic label was becoming overly broad. After the first proposed plan was released farmers were outraged because the standardized rules for organic production were even looser than the informal ones they had been implementing. The most recent proposal of the organic standards was released in April 2000 by the USDA to the

Office of Management and Budget (Turner, 2000). They have been published in the

Federal Register and there was a public response period, followed by a 60-day review

by Congress, just like the first time a proposal was released in 1997. The new

proposed rules can be viewed online at http://www.ams.usda.gov/. This site shows the

allowed and prohibited substances and ingredients in organic production and handling.

As knowledge of the environmental impact of pesticides increases, organic

products have expanded to include non-food items such as paper goods, clothing,

hygiene products and cleaning supplies. Although organic foods are often expensive,

more and more people are buying them. U.S. sales of organic foods have grown by 20

percent annually for the past seven years. Still, only 0.4% of total U.S. cropland was

certified organic as of2003 (www.USDA.gov). The food industry has spent decades

trying to manufacture products as cheaply as possible. Therefore, conventional foods

have the price advantage. But what is the real cost of buying things at a lower price?

Over the long-term, are the environmental ramifications and health concerns worth it?

3 1.2 Sustainability

1.2.1 Definition

No one has yet been able to successfully define a term as broad and interdisciplinary as sustainability. As Donald Worster stated in The Wealth ofNature,

"Sustainability, to begin with, is an idea that has never been really defmed ... Besides giving us no clear time frame, the ideal of sustainability presents us with a bewildering multiplicity of criteria, and we have to sort out which ones we want to emphasize before we can develop any specific program of action"(Worster, 1994). The word conjures up images of self-sufficient farming households with rich dark soil where nutrients are cycled and not drained. Here, farmers' labor and energy inputs should result in relatively equal outputs which can maintain their livelihood for years and years into the future because of more conscientious practices. For instance, the rebuilding of soil through the use of composts and manure, planting a more biodiverse crop and limiting the use oflarge machinery, petroleum and chemicals all lead towards a longer farming life-span which could carry on indefmitely. But this is speaking on a very limited level; sustainability can also be used to measure regions, societies, and even on a global scale. It can be any set of practices that encourage the longest continuation ofthe widest range of ecological life.

Some more specific characteristics of sustainable agriculture, as outlined by

Costanza in "Ecological Economics: The Science and Management ofSustainability," are that human life can continue indefinitely and flourish while its activities remain

4 within bounds so as not to destroy the diversity, complexity and function of the

ecological life support system (Costanza, 1991 ). Robert Netting gives a more

functionalist view in his list of the "attributes of sustainable agroecosystems". First, they have a relatively stable production per unit of land. Their energy inputs are

predictable and also relatively stable (Netting, 1993). The rates of return between

inputs and outputs remain favorable in both energy and monetary terms. Lastly,

returns to labor and energy inputs are sufficient to provide a livelihood to producers.

Miguel Altieri defines sustainability in the article The Agroecosystem:

Determinants, Resources, Processes, and Sustainability as referring to "the ability of

an agroecosystem to maintain production through time, in the face of long-term

ecological constraints and socioeconomic pressures."(Altieri, 1997) Altieri goes on to

list reasons why modern (industrial) agriculture is not stable. It degrades the soil by

salting, waterlogging, compacting and chemical contamination. It also wastes and

overuses water supplies. Agriculture uses two thirds of the world's water supply. It is

the number one source of water pollution. Modern farming is very dependent on

external inputs like petroleum. It leads to the loss of genetic diversity through

monocropping and local governmental control by corporatization and centralization.

In addition it does not facilitate the persistent global inequality and hunger.

Peter Rosset, the executive director for the Institute for Food and Development

Policy explains the scope to which sustainability reaches by stating

"Sustainable agriculture and land use ... has an all-encompassing impact on

communities, environments, and consumers. We must reach a consensus and a

5 common understanding of sustainable land use as an opportunity to improve the

quality of the environment, including its physical (increased soil fertility, better quality

air and water), biological (healthier and more diverse animal, plant, and human populations), and social, economic and institutional (greater social equity, cohesion,

peace/stability, well-being) components" (Rosset, 1997).

In Donald Worster's article The Shaky Ground ofSustainable Development a

quote from Wendel Berry defmes sustainable agriculture simply as an agriculture that

"does not deplete soils or people" (Worster, 1993). He also goes on to say that the

only true sustainable societies have been small-scale agrarian ones; no modem

industrial society could qualifY. Worster describes Berry's notions as "an old

fashioned agrarian way of thinking, steeped in the folk history and local

knowledge ... " Worster goes on to list and state some academic disciplines and

specific research foci and their views or contributions to the idea of sustainability. He

describes economist's interpretation of sustainability as a "measure of productivity in

the economy of nature where we find such commodities as soils, forests, and fisheries,

and a measure of the capacity of that economy to rebound from stresses, avoid

collapse, and maintain output" (Worster, 1993). The basis of economics involves

anything that has an extractable nature and flows through the system but some things

do not and cannot have a prescribed value.

6 1.2.2 Soil Quality

The breadth and quality of soil organic carbon in agroecosystems affects soil's physical, chemical, and biological properties and therefore influences soil productivity and the sustainability of certain production systems (Singh and Lal, 2001 ). Soil quality is an integral aspect of soil sustainability and can be used to determine sustainability on a soil to soil level. Carter (1997) linked these two ideas as "inseparable" and

considered soil quality as a "key indicator" of ecosystem sustainability. Recently, with growing concerns over soil degradation and the need for more sustainable soil management practices, there has been a marked emphasis on the value of soil and its properties pertaining to specific ecological and agricultural functions (Carter et al.,

1997). Some ofthese main functions include a medium for plant and biological

production, a buffer or filter for various pollutants, and general promotion of plant,

animal and human health. One of the most relevant functions to carbon sequestration

is soil's ability to store and cycle nutrients and other elements within the earth's

biosphere (SSSA, 1995). Soil quality can be loosely defined as a specific soil's

capacity to function, within a certain ecosystem, to sustain biological productivity,

store and recycle water, nutrients, and energy and, ultimately, maintain environmental

quality (SSSA, 1995; Doran et al., 1996).

1.2.3 Need for Management of Soil Fertility

Soil quality in agricultural land involves maintaining food and fiber production

for an extended period of time, partitioning water into runoff, storing soil moisture,

7 groundwater recharge, and creating an environmental filter to cleanse air and water

(Ellert et al., 1997). The understanding of soil quality at an ecosystem level is relatively still at its beginning stages. The interactions between plants, microorganisms and soil components continue to be somewhat of a mystery, even to agronomists and

soil scientists. Effective management practices must be created with a thorough understanding of these interactions. Ongoing studies on ecosystem complexity,

biodiversity, stability, and resilience will prove vital to understanding the

sustainability of ecosystems and soil quality (Ellert et al., 1997).

1.2.4 Assessment

There are various approaches to evaluating and quantifying soil quality. All of

them focus mostly on specific soil properties and functions. One such progression of

soil quality evaluation can be functions, processes, attributes or properties, attribute

indicators, and methodology (Carteret al., 1997). Once a desired function is

addressed, the processes that pertain to that function are determined, and then

attributes or measurable properties that influence that function can be defined. When a

property cannot be directly measured an indicator is used to indirectly assess that

attribute. These indicators should be easily quantifiable, verifiable, and sensitive to

soil management practices (Carteret al., 1997). When discussing crop production,

soil's capacity to sustain plant growth is the most important function. With regards to

carbon sequestration, the ability of a soil to store nutrients and carbon would be the

key function.

8 Measuring soil or ecosystem quality must first include a definition of the functions or services expected of the system. Some of these possible services include economic and sustainable production of food, water and gas partitioning, wildlife habitat, waste disposal, biodiversity reservoir, and aesthetic retreat (Ellert et al., 1997).

It is important to evaluate soil health and quality in order to monitor the

sustainability of certain farming methods. One way the sustainability of a land

management system can be ascertained is by assessing if the system is capable of producing or providing adequate organic matter. This can be achieved by measuring the amount of crop residue or organic fertilizer inputs applied to the soil. It is also

important to determine if the farming method is utilizing the organic matter already in

place to the best of its ability (Carteret al., 1997).

Changes in crop yield can be used as an indicator of soil quality, especially on

a short-term basis. Crop yield takes into account the inputs of climatic characteristics

such as solar energy and rainfall, as well as management decisions such as tillage,

fertilizer, pesticide use, and irrigation (Gregorich et al., 1997). Once knowledge of

crop yield flux is acquired, crop management recommendations can be administered,

focusing on increasing yield as well as maintaining soil quality for the long term.

When determining the sustainability of a system, all the major inputs and

outputs of that system must be taken into account. In a study comparing the energy

efficiency between organic and conventional farmers, the organic farm was found to

be approximately eight times more energy efficient with a ratio of3.4 (Loake, 2001).

9 The findings of this study draw attention to the need to include human energy efficiencies when calculating energy budgets of a farming system.

1.3 Carbon Sequestration

"Terrestrial ecosystems contain soil, atmosphere, water, vegetation, and animals. As components of ecosystems, soils function to both regulate biotic processes

(e.g., supplying plants with mineral nutrients and water) and flux of elements (e.g., turnover and storage ofC, N, P, and S)" (Carteret al., 1997). Soil's ability to store carbon has become a very hot topic since the 1990s and will probably continue to be a field of study that will gain attention in the extended future. Because soil accumulates and stores biogenic energy, it is capable of reserving organic matter and moderating the carbon cycle. It serves as a "terrestrial pool" of organic carbon and a source and/or sink for C02 and C~ (Carteret al., 1997).In addition to improving quality of soil and water resources, carbon sequestration is also important for meeting national and worldwide challenges of reversing land degradation trends, resisting desertification,

sustaining productivity and preserving biodiversity (Singh and Lal, 2001).

Many factors affect C sequestration estimates. Some of these are the depth of the soil pool that is being assessed, variations in climate, relief, parent material,

vegetation and previous land use. There is also limited knowledge over the exchange

ofC between soil, atmosphere and biota (Singh and Lal, 2001). Land use conversion

can lead to this transfer of C into the atmosphere through the release of biomass C

during burning or decomposition, mineralization and erosion (Singh and Lal, 2001).

10 Lal et al. (1998) estimates that the U.S. croplands can potentially sequester 75-208 million metric tons of carbon per year. This potential is based on 80% of the land managed under conservation tillage or more sustainable management practices and cropping systems.

The accumulation of soil organic carbon is affected by the formation of soluble complexes, which often results in an increase of total soluble concentration of carbon in the soil solution (Heil and Sposito, 1997). The transport of this carbon through the soil is a result of mass flow and diffusion, which also increases with higher carbon concentration levels. Carbon is added to the soil by the application of organic residues, such as manures, and increased plant residues due to fertilization. Carbon is removed from soil through microbial decomposition, mineralization, and erosion (Gregorich et al., 1997). When a soil is first converted to agricultural production there is a marked decrease in C levels. The rate of this decrease varies according to the type of soil being cultivated.

Singh and Lal (2001) observed in their report "The Potential ofNorwegian

Soils to Sequester Carbon Through Land Use Conversion and Improved Management

Practices," that the adoption of improved management practices, such as erosion control measures, residue management and improved cropping systems can lead to carbon sequestration in soils at a rate higher than the emission of C02 from Norwegian agriculture. Soil is an extremely important sink for carbon. It contains more than three times the C pool of biota and twice what is found in the atmosphere (Lal and Kimble,

1997). Singh and Lal (200 1) reported that a portion of the historic losses of soil

11 organic carbon can be restored if the land is set aside for ecological rehabilitation and

soil quality restoration. Prudent management practices that involve in-depth understanding of nutrient cycles can also lead to heightened C sequestration and increased crop production (Singh and Lal, 2001 ).

When assessing or predicting C sequestration it is important to take into account all major inputs and outputs. Different farming practices use varying amounts

of diesel and mechanically powered devices. If certain methods use large amounts of fossil fuels to cultivate fields, then this should be taken into account when deciding on the most efficient practice for sequestering carbon. In a study on energy accounting for

UK organic and conventional farming systems, Loake (200 1) reported that organic

farmers relied more heavily on human and animal labor than mechanically powered

devices. In the report, the conventional farmer used approximately 10,000 L of diesel in a year, which was calculated to be 478 GJ from fossil fuels a year.

IntensifYing the organic fertilization of cultivated soils results in a more abundant crop that in turn contributes a great volume of residues to the soil, resulting

in higher levels of organic C. Cover cropping and other management practices that

maintain a residue cover also contribute higher organic inputs into the soil and result

in increased soil organic C content (Gregorich et al., 1997). In a comparison of

fertilized and unfertilized soils, Gregorich et al. (1997) observed that the light fraction of the soil accounted for a significant part of the gain in total organic C, and that it was

attributed to recent residue additions. Manure applications also increase light fraction carbon. But macroorganic matter is generally a much larger proportion of soil organic

12 C than the light fraction and can account for well over 10% of the soil C probably due to the higher level of decomposition (Gregorich et al., 1997).

Vesicular-arbuscular mycorrhiza or VA mycorrhiza also plays a crucial role in carbon sequestration. The fungi improve the health and development of their host by enhancing plant nutrition and resistance to disease and stress; the more vigorous plant is a better source ofC to the soil, which encourages the activity ofthe soil biota; the products of microbial metabolism enhance soil aggregation; and better soil structure increases the soil's ability to store that carbon (Gregorich et al., 1997). Mycorrhizal fungi also affect two other important soil functions: crop production and soil quality.

Carbon mineralization is a good estimate of labile organic matter because it provides a direct measure of organic matter turnover. The contribution of C02 to the atmosphere, due to soil organic matter, and the decomposition or accumulation of organic wastes and crop residue can be estimated by the rate of carbon mineralization.

During soil incubation the metabolic activity of heterotrophic soil organisms creates a flux of C02 from the soil. Carbon mineralization is measured by accounting for this gross flux (Gregorich et al., 1997). When organic matter mineralization is being tested in a laboratory, many condition s come into play. The quantities of mineralizable C depend on temperature, moisture content, aeration porosity, and the duration and measurement interval of the incubation (Gregorich, 1997). Carbon mineralization in the field is strongly related to the length of time that the land is left to fallow during cropping rotations. A build-up of crop residue under no-till management is found to

13 have higher amounts of mineralizable C (Gregorich, 1997). Biederbeck et al. (1997) measured the response of labile fractions of organic matter to green manure application and found that the initial rates ofN and C mineralization were more sensitive than biomass C and light fraction soil organic matter. This sensitivity makes mineralization rate a better measure of SOM accumulation in soil.

As much as 5-25% of the total carbon content in soil is due to carbohydrates created from microbial and plant sources (Gregorich et al., 1997). Carbohydrates serve the important function of binding aggregates in soils. This increases soil structure and aids in water infiltration, as well as providing a labile source of carbon. Cover cropping with perennial grasses has been shown to increase carbohydrates in soils

(Chantigny et al., 1997).

In a study conducted by Rasmussen et al. (1998), major factors influencing changes in SOC and N were identified as the frequency of summer fallow period and the amount of C input in the crop residue. Although decreasing tillage intensity is proven to reduce SOM loss, in this study the effect was not as intense as eliminating summer-fallow. Dick et al. (1998) found that the removal of crop residues and use of cover crops were of lesser importance when sequestering C compared to annual organic C input and the tillage intensity. Overall, the biggest changes in C sequestration tended to occur in the first five years after a new management practice was imposed.

There are various problems associated with assessing carbon sequestration in a system. Rasmussen et al. (1998) identify two of these deficiencies with long term C

14 sequestration studies: soil C loss can be partitioned between erosion and biological oxidation only by estimation and C changes occurring below 30cm in grassland soils often cannot be quantified because samples were not collected from this level. Few long-term studies have measured erosion because of the dangers of physical damage caused by measuring instruments on small plots. Soil C loss through biological oxidation needs to also be assessed in relation to toil erosion. This oxidized C may be emitted as C02 into the atmosphere or eroded away and buried in the soil, where decomposition and turnover is much slower (Rasmussen et al., 1998). As a result of

Rasmussen et al. 's findings, biological oxidation is considered the dominant pathway for C loss because most of the C losses could not be accounted for with erosion rates.

Secondly, changes in C below 30cm, even though rarely sampled, could be a significant source of C02 emission and should be measured when modeling C­ sequestration.

The short term and site-specific nature of most field experiments poses another hindrance to assessing the impact of management practices on C sequestration (Dick et al., 1998). The relative impacts of various agricultural management practices on

sequestration oftentimes are not noticeable until after the typical three-year

experiment. Many times the spatial scale is too small to accurately evaluate SOC

dynamics. For example, a study concerning C accumulation and loss in the

Appalachian Piedmont of Georgia showed no observable change in total C content at

the end of the third year, but at the end of 16 years there were declines of 40% and

18% after intense cultivation (Hendrix et al., 1998). After 20 years, the no-till plot

15 1 1 accumulated a mean rate of29 Mg C ha" yr- • This study also encompassed a large spatial scale, the southern Appalachian Piedmont of Georgia, which resulted in C content ranging from 14 to 48 Mg C/ha. This was due to the wide variety of soil types, topographic positions and management histories. Hendrix et al. (1998) claim that it is not possible to estimate a single regional equilibrium level for soil C because it would be highly dependent on these varying soil textures and management systems.

1.4. Objectives

Identify land use systems and soil/vegetation management practices that lead to an enhanced SOC pool, principally with regards to compost, cover crops, various forms of organic manure, and crop residue. Specific objectives are: to comparatively assess soil quality changes in conventional farming vis-a-vis organic farming practices, quantify the effects of organic farming practices on crop yield, and establish relation between soil quality indicators and crop yield.

The hypotheses are that soil quality will increases under organic farming methods, crop yield will be greater with conventional than with organic farming, and that crop yield is positively correlated with soil quality on a long term basis.

16 LIST OF REFERENCES

Altieri, M., "The agroecosystem: determinants, resources, processes, and sustainability," in Agroecology: the science ofsustainable agriculture ( 1997) 41-68.

Biederbeck, V.O., C.A. Campbell, and H.J. Hunter. "Tillage effects on soil microbial and biochemical characteristics in a fallow-whet rotation in a dark brown soil." Canada Journal ofSoil Science 77 (1997) 309-316.

Carter, M.R., E.G. Gregorich, D.W. Anderson, J.W. Doran, H.H. Janzen, and F.J. Pierce. "Concepts of soil quality and their significance," (1997) 1-19. In E.G. Gregorich and M.R. Carter (ed.) Soil Quality for Crop Production and Ecosystem Health. Elsevier, Amsterdam (1997).

Costanza, R., J. Cumberland, H. Daly, R. Goodland, and R. Norgaard, An Introduction to Ecological Economics, St. Lucie Press, Boca Raton, Fl. (1997).

Costanza, Robert. (Ed.) .. Ecological Economics: The Science and Management of Sustainabilitv. New York: New York (1991).

Dick, W.A., R.L. Blevins, W.W. Frye, S.E. Peters, D.R. Christenson, F.J. Pierce and M.L. Vitosh, "Impacts of agricultural management practices on C sequestration in forest-derived soils of the eastern Com Belt," Soil & Tillage Research 47 (1998) 235-244. Duram, Leslie A., Good Growing: Why Organic Farming Works, Lincoln and London: University ofNebraska Press (2005).

Ellert, B.H., M.J. Clapperton and D.W. Anderson.". An Ecosystem Perspective on Soil Quality," In E.G. Gregorich and M.R. Carter (eds.), Soil Quality for Crop Production and Ecosystem Health. Developments in Soil Science and Ecosystem Health, (1997) 25:115-141.

Gregorich, E.G. and M.R. Carter, (ed.) "Soil Quality for Crop Production and Ecosystem Health" Developments in Soil Science 25 (1997).

Hendrix, P.F., A.J. Franzluebbers and D.V. McCracken, "Management effects on C accumulation and loss in soils of the southern Appalachian Piedmont of Georgia," Soil & Tillage Research 47 (1998) 245-251.

17 Lal, R., J.M. Kimble., R.F. Follett, and C.V. Cole .. The Potential ofU.S. Cropland to Sequester Carbon and Mitigate the Greenhouse Effect.Lewis Publishers, Chelsea, MI.( 1998).

Le Guillou, Gwenaelle and Alberik Scharpe, Organic Farming: Guide to Community Rules, European Commission Directorate, Belgium. (2001).

Loake, C. "Energy accounting and well-being: examining UK organic and conventional farming systems through a human energy perspective," Agricultural Systems 70 (2001) 275-294.

Netting, R.McC., Smallholders, Householders: Farm families and the ecology of intensive, sustainable agriculture, (Stanford Univ. Press, Stanford, 1993).

Rasmussen, P.E., S.L. Albrecht, and R.W. Smiley .. "Soil C and N changes under tillage and cropping systems in semi-arid Pacific Northwest agriculture". Soil and Tillage Research 47: (1998) 197-205.

Rosset, Peter M., and Miguel Altieri, "Agroecology versus Input Substitution: A Fundamental Contradiction of Sustainable Agriculture," Society and Natural Resources. 10 (1997) 283-95.

Scofield, A.M. "Editorial: Organic Farming - the Origin of the Name," Biology. Agriculture. & Horticulture. (1986) 4, 1-5.

Turner, Lisa, "Organic, The Natural Choice," Better Nutrition (April200).

Singh, B.R. and R. Lal, "The potential of Norwegian soils to sequester carbon through land use conversion and improved management practices," (Ohio State University Press, 2001).

USDA. 2006. www.usda.gov.

Worster, D., 'The Shaky Ground of Sustainable Development," in The Wealth ofNature (Oxford University Press, 1993) 142-155.

Worster, D., The Wealth ofNature: Environmental History and the Ecological Imagination, (Oxford University Press, 1994).

18 CHAPTER2

AGRONOMIC SUSTAINABILITY OF ORGANIC FARMS

ABSTRACT

It is common practice for the success of most agricultural systems to be judged by their agronomic productivity, whether the farmer is trying to achieve greater biomass yields or grain yields. This narrow view of agricultural success is now being brought into question. Many farmers are realizing the importance of soil quality as well as crop production. In this two-year experiment, 3 pairs of farms were sampled for biometric parameters, crop yield and aboveground biomass yield. In each pair there was a certified organic farm and a conventional farm with matching soil types to eliminate yield differences due to exogenous soil variations. The soils sampled were

Blount, Bennington, and Chili silt loams, all planted to corn (Zea mays). On each farm, 3x3m adjacent plots were chosen for sampling. Overall, the conventionally managed farms did have higher yields across years, but in 2004 the Chili silt loam organic farm surpassed two of the conventional farms in grain production. The Chili silt loam farm has been under organic management for 20 years, the longest period of time compared to the other organic farms.

19 This agrees with other studies that have found organic systems under long-term management often have similar yields to conventionally managed farms.

INTRODUCTION

The widespread goal of maximizing agronomic productivity is often taken for granted. This perception is now being questioned by a concern over the landscape and the environment, coupled with the growing realization that finite natural resources need to be prudently managed. The ideal of maximizing crop yields has questioned the wisdom of subsidized overproduction in Europe and has brought with it "unendurable financial strain and political embarrassment" (Lampkin, 1990). The same is true of subsidized overproduction in the U.S. Of course, there are benefits to increased productivity such as countrywide food self-sufficiency and subsequent surplus, oftentimes used for export.

A growing number of environmental policy workers consider organic farming a tool for remedying surplus production and the negative impacts of agriculture on international markets (Dabbert et al., 2004). The use of chemical fertilizers, which generally remove nutrient constraints and are imperative to high-yielding varieties of grain created a sharp increase in production in the last half-century. Now this trend of sharply increasing crop production has plateaued and in some cases has begun to decline in major food producing countries such as the United States, Western Europe,

Japan and recently China (Brown, 2004).

20 Since the Industrial Revolution, changes in farming practices have also resulted in a loss of natural habitat and species as well as the environmental pollution of ground and surface waters from agricultural chemicals, to name a few detractors. It is no wonder that increasingly people within and outside the farming community are questioning the desirability ofthis form of agriculture continuing (Lampkin, 1990).

It is important to note that like conventional farming, organic farming may also not be economically viable. Unlike conventional agriculture, however organic farming has not had the support of extensive research and development from the advisory services. Despite this handicap, some organic farms are out-performing the conventional average (Lampkin, 1990). The yield difference between organic and conventional agriculture can range anywhere from 0 to 100 percent. In the U.S., the overall average is usually somewhere between 10 and 30 percent lower yield in organic than conventional agriculture (Blake, 1990). Two major factors that affect these differences are the fact that conventional agriculture receives huge outside inputs to reach these high yields and the nutritional quality of organic produce generally is much larger with a broader range of protein, vitamins and minerals. The excessive concentrations of a few select nutrients on conventional produce causes the fruits or vegetables to take up much more water (Blake, 1990). It is, therefore, reasonable to assume that with even a small portion of the research efforts that have gone into chemical agriculture, organic systems would be much more productive (Lampkin,

1990).

21 In the Haughley Experitment, conducted by Lady Eve Balfour in the 1940s, the efficiency of the organic produce by livestock was approximately 10 percent higher than that by the conventional methods (although the overall organic crop production was lower than the conventional). It took 10 percent less organic food to yield the same amount of milk or eggs. In this case, the lower crop yield was compensated for by the higher nutritional value of the food (Blake, 1990).

Cover crops, especially legumes, also play a vital role in the nutrient cycling of agricultural lands. Crops like hairy vetch ( Vicia Villosa) can supply N for other cash crops that are normally grown in the spring. Other cover crops, such as rye (Secale cere ale L.) can be planted in the fall after a maize crop in order to catch the excess N to prevent nitrate leaching (Lotter et al., 2003).

Research comparing the performance of farming systems incorporating legume based cover crops versus conventional system, which rely on herbicides and pesticides, revealed that in extreme climate years (drought, torrential rains) the legume systems yielded 196% higher than the conventionally cropped system (Lotter et al.,

2003). This was attributed to higher water-holding capacity during drought stages in the legume-based fields.

Application of nutrients through organic manures leads to increased crop yield and, therefore, higher organic matter or biomass return to the soil. The secondary effect can result in an increase in SOC and biological activity in the soil (Singh and

Lal, 2001 ). As a consequence of organic manure application, supplying nutrients and

22 serving as a good source of C cause it to be considered more effective in increasing

SOC than using inorganic fertilizers (Singh and Lal, 2001 ).

In a study conducted by Lotter et al. (2003), a hairy vetch cover crop produced

5425 kglha of dry weight biomass during one winter season. This provided nearly twice the needed N inputs of 150 kg N/ha for the maize (Zea mays) crop. Counting the maize crop that was cultivated, cover crop, and weeds, the legume based treatment for this study supported nearly three times the plant biomass of the conventional farming system. As of 1995, 1.5 Pg of carbon was produced annually in crop residues around the world. This C source has a high turnover rate but it is a substantial enough amount that it should be included in the global C budget. If some of the C from crop residues can be sequestered into the soil as humus, that would have an immense impact on the global C balance (Lal, 1995).

There are many cases where, depending on yearly climate and weather conditions, organic farmers have out-produced some chemically fertilized farms. In one season an organic farm outside of Dayton, Ohio produced 70 bushels of wheat

(Triticum aestivum ) per acre, a record for the county at the time, while the neighboring conventional farmers only yielded approximately 60 bushels per acre that year (Steffan, 1971). Organic farms can exceed conventional systems during water and climate stress situations because these operations tend to have lower long-term yield but higher cropping system stability (Lotter et al., 2003).

In a survey of over 45 sustainable agriculture initiatives in 17 African countries, the results show both crop yields and nutritional levels improved 50 to 100

23 percent in these projects over 20 years (Pretty and Hine, 2001). In North America, organically managed cropping systems have been shown to yield approximately 90 to

95 percent of conventional cropping systems on average (Lotter, 2003).

The rationale for this experiment stems from the need for larger-scale sustainable farms that could try experimental practices over larger areas and convince conventional farmers with superior yields and greater returns. Then more responsible farming methods can be suggested (Steffan, 1971 ). Many past studies have been conducted on small experimental plots of land and it is difficult to imitate the whole systems approach that organic farms implement. Oftentimes, organically managed systems require a more complex approach than conventional farming (Brumfield et al.,

2000). This can include complicated crop rotation systems and weed suppression practices. By sampling from 6 working, full-scale farms, the collected data are more representative of actual yields and conditions. Thus the objectives of this study were to quantify the effects of organic farming practices on crop yield; the hypothesis tested was that crop yield is greater in conventional than organic farms because of the increased amounts of readily available nutrients in synthetic fertilizers.

2.1 METHODS AND MATERIALS

2.1.1 Site Descriptions

A total of six farms in Ohio were sampled for this study. Three of the farms are organic and three conventional (see figure 1.1). Each organically managed farm was

24 paired with a conventional farm from the same county with the same soil type to reduce differences in yield due to soil and climate variances. The three organic farms display a time range of organic conversion. The Licking County farm has been under organic management for over five years, the Delaware County farm, close to 15 years and the Knox County farm, over 20 years of organic production. The six farms were measured for crop yield, ear leaf height and flag leaf height in the fall of2004 and

2005.

The Delaware County organic farm is located at 40°31.815'N,

82°32.009'Wand the conventional farm is located at 40°17.03'N, 83°14.201 'W, and both have a Blount silt loam soil series. The Licking County organic farm is located at

40°12.785'N, 82°35.981 'Wand the conventional at 40°12'58.05"N and

82°35'24.96"W, contain Bennington silt loam series. Lastly, the Knox County organic farm has latitude of 40°15.438'N, and of 82°32.009'W and the conventional with location 40°30.788'N 82°38.021 'W contain the Canfield silt loam soil series.

The Delaware County organic farm has an intricate eight year crop rotation, which includes periods of timothy (Phleum pratense L.), Potomac orchard grass

(Dactylis glomera/a), wheat (Triticum aestivum ), vernal alfalfa (Medicago sativa), oats (Avena sativa), spelt (Triticum spe/ta ), red clover (Trifolium pratense) com (Zea mays ) and fallow. The years that the com was sampled, it came out of a Potomac orchard and vernal alfalfa ley in 2004 and a climax timothy and red clover ley in 2005.

Although the intricate crop rotation is time consuming, it is used to help prevent mining of the soil as well as build green manure biomass and put nitrogen back into

25 the field. These fields are chisel plowed to 30cm in the spring and offset disked to

20cm. The soil is field cultivated to 15cm depth two weeks prior to planting. A rotary hoe is used 1-3 times 1-5 weeks after planting. Lilliston cultivation is used 1-2 times depending on soil conditions and plant height. Bird Hybrids B64 (untreated) com varieties were planted in 2004 and Bird Hybrids B54V (untreated) in 2005. Planting dates were early June for 2004 and late May for 2005. The average temperature for this county, from the autumn of 2003 to the autumn of 2005 was a high of 16. 7°C and a low of 5.6°C (USDA, 2006). The average precipitation for those years was 0.29cm with a total precipitation of208.71cm.

The Licking County organic farm has a much simpler crop rotation in the field that was sampled. This rotation begins with field com, followed by soybeans (Glycine max), wheat, and finally hay. No cover crop was used in this rotation. The field was offset disked to approximately 15cm depth. In 2004 the com was planted May 11th and in 2005 May 25th. Doeblers brand N509 com variety was used and NC+ 3448 was planted in 2004 and 2005. Com is usually harvested with a row combine. The average low temperature for 2003 to 2005 was 7.3°C and a high temperature of 18.2°C. Total precipitation from autumn 2003 to autumn 2005 was 209.9cm with an average of

0.23cm (USDA, 2006).

The Knox County organic farm used a 4-year crop rotation of com, soybean, small grain (oats, wheat or barley) and then clover hay, until recently. They have now switched to a 7-year crop rotation of com, buckwheat, soybean, small grains, cover crop, buckwheat, cover crop, barley or wheat, soybean, small grain and clover hay. 26 Most of the biomass production from the rotation is tilled under and used as a green manure. This farm tills 15cm deep. The field is offset disked in the fall and then tilled again in the spring, 3-4 times until field cultivation. The field has been limed in the past but not for several years. Hog manure, produced on the farm, was applied in 2004 but not in 2005. the field was planted with Doebler's com variety in 2005 and Great

Harvest com variety in 2004.

The Knox County conventional farm only followed a com- soybean rotation but the field was not tilled every other year. Every other year, a Sunflower Soil

Finisher was used to till soil to approximately 8cm to 1Ocm deep in the spring. Pioneer

Hybrid com varieties were planted in early April each year. No cover crop was used in the rotations. A Lexar® (S-metolachlor, atrazine, atrazine related compounds, mesotrione) herbicide was used to combat foxtail (Setaria glauca), fall paniciun, lamb's quarters (Chenopodium album), and giant ragweed (Ambrosia trifida).

Warrior® (active ingredient: lambda-cyhalothrin: [la(S*),3a(Z)]-(±)-cyano-(3- phenoxyphenyl)methyl-3-(2-chloro-3,3,3-trifluoro-1-propenyl)-2,2- dimethylcyclopropanecarboxylate) pesticides were applied only when needed. The com was also harvested using a combine. The average temperature for Knox County from the autumn of2003 to the Autumn of2005 was 8.4°C. The average precipitation was 0.16cm (USDA, 2006).

27

2.1.2 Methods

On each of the six farms, three 3x3m adjacent plots were chosen at the summit landscape position in each field. Dry biomass for each farm was calculated by hand­ harvesting 2 rows 1.5m long from each replication plot. These stalks were weighed in the field and then a sample of two stalks were weighed, carried to the lab and dried at

60°C for 24 hours. With this weight the moisture percentage was calculated (Dry Stalk weight (g) I Wet stalk weight (g)) and then this value multiplied by the field weighed

10 stalk biomass to achieve the dry biomass weight. After the grains were removed, the dried husks were also added to this weight to obtain the total dry biomass weight for each farm, which was then converted to Mg ha -I.

The grains were weighed and then dried at 60°C for 24 hours. This weight was multiplied by 1.14 to account for field moisture and then converted to Mg ha -I . The harvest index was computed, by dividing the calculated grain yield by the biomass and grain yields.

One-way ANOVA tests were conducted using SAS software to compute the

LSD (0.05) values and test the significance of organic and conventional management relationships for flag leaf height (em), ear leaf height (em), grain yield in Mg ha -I, above ground biomass yield in Mg ha -I, and the harvest index (SAS, Inc. 2004). The

SAS software program was also used to generate the means and standard deviations for the six individual farms for the same parameters (SAS, Inc. 2004).

29 RESULTS AND DISCUSSION

2.2 Biometric parameters and grain yield

One-way ANOVA tests showed no significant difference between organic and conventionally managed systems for biometric parameters (flag leaf height em and ear leafheight em) for 2004 (p<0.05). Table 1.1 shows the average flag and leafheights

(em) for the six sampled farms, along with the standard deviation and LSD value

(0.05).

Parameters Flag leaf (em) Ear leaf (em) Organic Chili silt loam 192±10 97±8 Bennington silt loam 126±10 54±4 Blount silt loam 150±5 51±4 Conventional Blount silt loam 159±20 75±12 Bennington silt loam 190±11 84±9 Chili silt loam 253±6 122±5

Flag leaf Ear leaf 2004 height height S!stem Mean{cm} LSD {0.05} Mean {em} LSD {0.05} Conventional 193.5a 87.7a Organic 174.7a 80.5a 46 28.71

Table 2.1: Average leafheight among six conventional and organic farms in 2004 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at 6:=0.05. Values are LSD at 6:=0.05.

30 A one-way ANOVA test revealed a significant difference in grain yield at the p<0.05 level between the organic and conventional farms. The conventional farms had

1 a significantly higher average yield in 2004 of 5. 7 Mg ha· • Table 1.2 shows the average biomass and grain yields for each farm, along with the standard deviations and LSD value (0.05) for 2004. There was no significant difference between management practices for the biomass yield at the p>0.05 level for 2004.

Biomass Yield Grain Yield 1 1 (Mgha" ) (Mgha- ) Organic Chili silt loam 4.4±0.5 6.4±1.7 Bennington silt loam 4.5±0.6 1.2±0.4 Blount silt loam 5.9±0.9 2.1±0.9 Conventional Blount silt loam 8.2±2.2 4.6±0.4 Bennington silt loam 9.1±3.4 4.4±1.5 Chili silt loam 10.3±1.9 8.6±0.6

2004 Grain yield Biomass yield System (Mgha-1) LSD (0.05) (Mg ha-l) LSD (0.05) Conventional 5.7a 7.3a Organic 3.2b 7.0a 2.49 3.16

Table 2.2: Average Biomass Yield and Grain Yield among six conventional and organic farms in 2004 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05.

Table 1.3 illustrates the outcome of a one-way ANOVA test for the harvest index values between the conventional and organic farms in 2004. At the p<0.05 level,

31 there is no significant difference between the two systems for harvest index. This means the conventional and organically managed systems produce a statistically similar ratio of grain to aboveground biomass. The table also gives the averages for organic and conventional farms as well as the LSD (0.05) value.

Harvest Index 2004 % System Mean LSD (0.05) Conventional 40a Organic 30a 0.22

Table 2.3 Average Harvest Index among six conventional and organic farms in 2004 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at a=0.05. Values are LSD at a=0.05.

Contrary to 2004, the data of 2005 showed significant difference in ear leaf height (em) between the organic and conventional farms at the p<0.05 level. The flag leafheight (em) average still showed no significant difference, results being the same as in the 2004. Table 1.4 expresses these biometric parameters and also gives the LSD

(0.05) values, standard deviations and individual averages of the three replications for each farm.

32 Flag leaf Ear leaf Parameters (em) (em) Organic Chili silt loam 243.2+18.6 92.9±2.6 Bennington silt loam 179.7±24.9 71.1±16.3 Blount silt loam 220.3±10.8 78.9±3.7 Conventional Blount silt loam 206.8±4.8 97.9±0.8 Bennington silt loam 212.9±7.9 93.3±10.2 Chili silt loam 243.4+16.0 105.9+6.7

Flag leaf Ear leaf 2005 height height S~stem (em} LSD (0.05} (em} LSD (0.05} Conventional 22l.Oa 99.0a Organic 214.4a 8l.Ob 27.2 10.5

Table 2.4: Average leaf height among six conventional and organic farms in 2005 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05.

Whereas in 2004 the average grain yield among organic and conventional farms was significantly different at the p<0.05 level, 2005 data showed no significant difference. Rather, in 2005 the mean above ground biomass yield for the conventional

1 farms was significantly higher (7.2 Mg ha- ) than that of the organic farms (4.7 Mg ha-

1 ). Table 1.5 expresses these relationships as well as the individual means for three replications on each farm, standard deviations and the LSD (0.05) values.

33 Biomass Yield Grain Yield Parameters Mgha-• Mg ha-• Organic Chili silt loam 6.4±0.4 2.4±0.74 Bennington silt loam 3.0±0.2 2.9±1.45 Blount silt loam 6.3±0.2 5.4±0.64 Conventional Blount silt loam 4.9±0.7 3.4±1.5 Bennington silt loam 7.0±1.7 5.1±0.9 Chili silt loam 9.7±0.9 7.3±1.5

2005 Biomass yield Grain yield System (Mg ha-l) LSD (0.05) (Mg ha-l) LSD (0.05) Conventional 7.2a 4.8a Organic 4.7b 5.1a 2.2 1.6

Table 2.5: Average BiomassYield and Grain Yield among six conventional and organic farms in 2005 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at a=0.05. Values are LSD at a=0.05.

In 2005 there was a recorded significant difference between average harvest index values for the organic and conventional systems. This contrasts the 2004 findings of no significant difference at the p>0.05 level. The organic farms produced a significantly higher harvest index at 52.0%. The conventional farms had a harvest index mean of 40.0%. This is due to the fact the organic farms had a higher mean grain yield and much lower biomass yield than the conventional farms in 2005.

34 Harvest Index Parameter 0/o Organic Chili silt loam 43±0.05 Bennington silt loam 55±0.06 Blount silt loam 49±0.03 Conventional Blount silt loam 40±0.02 Bennington silt loam 39±0.06 Chili silt loam 43±0.09

2005 Harvest Index System % LSD (0.05) Conventional 40a Organic 52b 0.06

Table 2.6 Average Harvest Index among six conventional and organic farms in 2005 Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at 11=0.05. Values are LSD at 11=0.05.

2.2.1 Trends Across years

The data for 2004 and 2005 were combined because there were no significant differences between years for any parameter except flag leaf height (em). This increased the data pool to achieve a higher confidence level for the comparison between the organic and conventional farms. With the combined data of 2004 and

2005, Table 1. 7 shows the interactions among farms according to mean biometric

1 parameters and grain yield (Mg ha- ). The Chili silt loam organic and conventional farms did not show a significant difference in biometric parameters at the p>0.05 level and neither did the Bennington silt loam conventional farm, Chili silt loam organic or

Blount silt loam organic farm for the average flag leaf height (em). The Chili silt loam

35 organic farm and Blount silt loam organic farm also showed no significant difference between the Bennington and Blount silt loam conventional farms for ear leaf height

(em).

There was also no significant difference in grain yield at the p>0.05 level between the Blount silt loam organic farm and the Blount and Bennington silt loam conventional farms. The organic Bennington silt loam farm was the only one to share no statistical similarity with any of the other farms.

Flag leaf Ear leaf 2004-2005 height height Grain yield System (em) (em) (Mglha) Organic Chili silt loam 217.5ab 94.9ab 4.4b Bennington silt loam 163.3d 68.4c 2.3c Blount silt loam 202.8bc 79.0bc 3.8b Mean 3.95b Conventional Chili silt loam 246.2a 112.7a 6.4a Bennington silt loam 196.5bc 84.8bc 4.7b Blount silt loam 179.0cd 82.5bc 4.0b Mean 6.45a LSD {0.05} 30.49 19.54 1.2

Table 2. 7 Comparison between organic and conventional farms across years Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at <1=0.05. Values are LSD at <1=0.05.

Across years, the organic and conventional farms showed no significant differences at the p>0.05 level for flag leaf height, biomass yield or mean harvest index. The average ear leaf height and grain yield, however, differed significantly

36 among them .. Table 1.8 gives the averages for biometric parameters, yields and harvest indexes in each system across years.

Flag Leaf Ear Leaf Biomass Harvest 2004-2005 height height Grain yield yield Index System (em) (em) (Mglha) (Mglha) 0/o Organic 194.5a 80.8a 4.2a 5.8a 43a Conventional 207.2a 93.4b 5.3b 7.2a 43a

LSD (0.05) 17.6 11.28 0.68 1.72 0.08

Table 2.8 Com.12arison of systems across years Values are mean ±_S.D. Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05.

2.2.2 The effect of duration under organic management

There have been previous studies conducted to determine the phenomena of a transitional period from conventional to organic management practices. This transitional period has been attributed to both physical and management factors.

Organic farms that have recently undergone a transition from conventional practices many times experience a 'learning curve' that can influence their weed and crop management in the initial years. Organic agriculture requires a whole systems approach, which is usually more complicated to develop and increases the implementation time (Bumfield et al., 2000). This time period is typified by lower yields, also referred to as a 'yield drag'. The transitional period usually lasts 3 to 6 years (MacRae et al., 1993). Other studies associate this yield drag with residual chemicals in the soil that may inhibit pertinent biological processes from reaching

37 equilibrium (DeBach, 1990). Although extra work is involved, organic farms report a steadily increasing trend in yields once the soil has been converted (Steffan, 1971).

The three organic farms that were selected for this study have a range of years in which they have been under organic management. These establishment year differences mirror their variances among biometric parameters and yields. Although the experiment was not designed to study this effect, it has revealed itself through the data output. Therefore, through pseudo-replication of three randomly chosen plots for each organic farm, data have been generated through a one-way ANOVA tests to illustrate this trend among the farms. Table 1. 7 shows the mean grain yields for each farm, along with the years under organic management and the LSD (0.05) value. The average grain yield value increases exponentially as the years of organic management increase.

2004-2005 Grain yield Farm Years Established (Mg/ha) Chili silt loam 20 6.4a Bennington silt loam 15 3.8b Blount silt loam 5 2.3c LSD (0.05) 0

Flag leaf Ear leaf 2004-2005 height height Farm Years Established (em) (em) Chili silt loam 20 217.5a 94.9a Bennington silt loam 15 202.8a 79.0ab Blount silt loam 5 163.3b 68.4b LSD (0.05) 37.87 20.19 Table 2.9 Comparison of organic farms across years according to establishment Values are mean+ S.D. Figures followed by same letters in the column are statistically similar at a=0.05. Values are LSD at <1=0.05. 38 DISCUSSION AND CONCLUSIONS

The hypothesis that crop yield would be higher in conventionally managed farms was not disproved in this study. Overall (across years), conventional farms had the highest yields. Although in 2004 an organic farm had higher grain yields than two of the conventional farms, that farm had significantly lower yields the following year, which resulted in the higher overall grain yield average for conventional farms.

In accordance with this experiment, a study comparing the yields of two organic management practices with conventional management shows the average yields of com and soybean from 1985 to 1998 were approximately equal between the three treatments but significantly less in organic soybean (Lotter et al., 2003). Over a

4-year experiment comparing high purchased inputs, organic inputs, and low purchased inputs on a com-soybean rotation and com-soybean-oat/alfalfa-alfalfa rotation, the average com yields were not substantially different. All three treatments were conducted for a 2-year rotation and a 4-year rotation; only the 2-year organic input treatment showed lower yields (Mahoney et al., 2004).

Delate et al. (2003) found, in a study conducted at the Long-Term

Agroecological Research (LTAR) site in Iowa, over a 3 year period that the

1 conventionally manages plots produced an average com yield of8654 kg ha- • This was not significantly higher than the organically managed average com yield of 8340

39 1 kg ha- • Although the feed com yield were comparable between the conventional and

organic systems, the white com yields were significantly lower for the organic system.

They hypothesized this was caused by the lower-yielding hybrid that was grown. The

organic field had a com-soybean-oat/ alfalfa rotation, while the conventional field

consisted of a com-soybean rotation. The other two treatments were an organic com­

soybean-oat/ alfalfa-alfalfa rotation and an organic soybean-winter rye rotation. Over

the three years the study was conducted, the conventional com yields declined after

the first year, while the organic com yields for both the com-soybean-oat and com­

soybean-oat-alfalfa rotations increased from the first year. In every year of the study, the com yields were greatest following 2 years of alfalfa production (Delate et al.,

3003).

These findings contrasted with that of Hanson et al.(l997), where the com

yields were lower in the organic system than that of the conventional system. This

study conducted by the Rodale Institute in Pennsylvania considered three different

organic operations, comparing them to three conventional com-soybean operations.

They found that in the early stages of organic conversion, yields were 29 percent

lower than conventional yields. After the soil rebounded from inorganic fertilizer

treatments, the yields were, on average, only 2 percent lower than conventional

(Hanson et al., 1997). Similarly, in a 3-year study comparing compost, raw dairy

manure and mineral fertilizer treatments, Reider et al. (2000) found yields from

compost-amended com were comparable to raw dairy manure and conventional

treatments by the second year.

40 LIST OF REFERENCES

Blake, F. 1990.0rganic Farming and Growing. Crowood Press, Wiltshire, U.K.

Brown, L.R. 2004. Outgrowing the Earth. Earth Policy Institute. W.W. Norton and Company, Inc. New York, NY.

Brumfield, R.G., A. Rimal and S. Reiners. 2000. Comparative cost analyses of conventional, integrated crop management, and organic methods. HortTechnology 10(4):785-793.

Dabbert, S., A. M. Haring and R. Zanoli. 2004. Organic Farming: Policies and Prospects. Zed Books, New York, NY.

DeBach, P. 1990. Biological Control by Natural Enemies. Cambridge Univ. Press, London.

Delate, K., M. Duffy, C. Chase, A. Holste, H. Friedrich, and N. Wantate. 2003. An economic comparison of organic and conventional grain crops in a long-term agroecological research (L TAR) site in Iowa. American Journal of Alternative Agriculture. Vol. 18 No.2:59-69.

Hanson, J., E. Lichtenberg, and S. Peters. 1997. Organic versus Conventional Grain Production in the Mid-Atlantic: An Economic and Farming System overview. American Journal of Alternative Agriculture.

Lampkin, N. 1990. Organic farming. Farming Press, Ipswich.

Lotter, D. W., R. Seidel and W. Liebhardt. 2003. The performance of organic and conventional cropping systems in an extreme climate year. American Journal of Alternative Agriculture 18(3).

Mahoney, P. R., K. D. Olson, P. M. Porter, D. R. Huggins, C. A. Perillo, and R. K. Crookston. 2004. Profitability of organic cropping systems in southwestern Minnesota. Renewable Agriculture and Food Systems. 19(1 ):35-46.

41 MacRae, R.J., S.B. Hill, G.R. Mehuys, and J. Henning. 1993. Farm-scale agronomic and economic conversion from conventional to sustainable agriculture. Advances in Agronomy. 43:155-198.

OFRF. 2001. Organic Farming Research Foundation Information Bulletin No.10, Summer 2001. Santa Cruz, CA.

Pretty, J. and R. Hine. 2001.Reducing Food Poverty with Sustainable Agriculture: A Summary ofNew Evidence. final report from the SAFE-World proceedings (The Potential of Sustainable Agriculture to Feed the World) Research Project, University of Essex, Colchester, UK.

Reider, C. R., W. R. Herdman, L. E. Drinkwater and R. Janke. 2000.Yields and Nutrient Budgets Under Composts, Raw Dairy Manure and Mineral Fertilizer. Compost Science and Utilization. 8:4, 328-339.

SAS Institute. 2004. SAS Procedures Guide. SAS Institute, Inc., Cary, NC.

Singh, B.R. and R. Lal, "The potential ofNorwegian soils to sequester carbon through land use conversion and improved management practices," (Ohio State University Press, 2001 ).

Steffan, R. ed. 1971. Introduction to Organic Farming Methods and Organic Markets: A Guide to Ecological Farming. Organic Gardening and Farming, Rodale Press, Inc. Emmaus, PA.

USDA. 2006. www.wcc.nrcs.usda.gov

42 CHAPTER3

A SOIL QUALITY COMPARISON OF ORGANIC AND CONVENTIONAL FARMS

ABSTRACT

Soil quality is a specific soil's capacity to function within a certain ecosystem.

The term extends to sustaining biological productivity, nutrient and energy flow, and overall environmental quality. Soil quality is an important indicator of an agricultural management system's overall success. In this two-year experiment, 3 pairs of farms were sampled for a range of soil quality indicators including: pH, mean weight diameter (MWD), water stable aggregation (WSA), bulk density, available water capacity (A WC), cation exchange capacity (CEC), and soil organic carbon and nitrogen pool. In each pair there was an organic farm and a conventional farm with matching soil types to eliminate yield differences due to exogenous soil variations.

The soils sampled were Blount, Bennington, and Chili silt loams, all planted to com

(Zea mays). On each farm, 3x3m adjacent plots were chosen for sampling. Core and bulk samples were taken at three depths, 0-1 Ocm, 10-20cm, and 20-30cm. After analysis, the values for each parameter were assigned a soil quality index rating to compare overall soil quality of each management system. There are many different indices that can be used to measure soil quality but the one implemented here did not reveal a trend according to management system. The Blount silt loam organic farm did

43 have the best soil quality but the two other organic farms had the worst ratings. These findings do not correlate with past studies, which found organic management increased overall soil quality when compared to conventional practices.

INTRODUCTION

3 .1.1 Soil Organic Matter

The biological properties of soil include material derived from living organisms. The residues from these organisms remain in the soil in various states of decomposition. These interact with the chemical elements of a soil, which includes minerals, clays, water, and chemical ions and compounds (Gregorich et al., 1997). The biological attributes of soil quality encompass processes of organic matter cycling.

This includes total organic carbon (C), nitrogen (N), microbial biomass, light fraction, and mineralizable C and N. Soil characteristics like these are appropriate measures of soil quality because they are easily influenced by natural and anthropogenic change

(Gregorich et al., 1997).

The soil organic matter (SOM) performs a major role in maintaining soil quality. Its many functions include preservation of soil tilth, air and water infiltration, water retention, and the reduction of erosion. It is also the primary source and sink for plant nutrients (Gregorich et al, 1997). Many factors affect SOM levels in soils, such as soil moisture, aeration, temperature conditions, and the physical disruption of

"protected" organic matter in deeper soil layers. This is why cover cropping and returning crop residues back into the soil (instead of removing them from the site) enhances SOM concentrations. 44 The SOM and its many forms are a significant source of plant nutrients.

Microorganisms break down this material through decomposition, transforming them into a more readily available state. Two forms of SOM are humus and the light fraction. Humus is highly decomposed and contains reactive adsorption sites to retain base nutrient cations, such as Ca+2, Mg+2, and K+. Therefore, SOM contributes substantially to the cation exchange capacity (CEC) of soils (Carteret al., 1997). The light fraction is a mixture or fresh plant residues, humified SOM, and plant and microbial residues. These elements make it highly enriched with C and other vital nutrients. The short turnover time of the light fraction makes it a key C substrate

(Gregorich et al, 1997).

Some agricultural practices that enhance the light fraction mostly involve increasing the amount of residue inputs into the soil. Cropping with grasses, legumes, and continuous pasture generally have a positive correlation with light fraction SOM levels. The longer a field is left to fallow, the faster the light fraction decomposes and loses its nutritive properties. Animal manure additions also have the same positive effect as crop residues to this type of SOM (Gregorich et al, 1997). The light fraction is also very sensitive to changes in cultivation and cropping practices, which makes it another good indicator of soil quality.

3 .1.2 Strategies for Obtaining Organic Material

Agricultural practices affect soil C pools in various ways. Two main results of sustainable management practices are increasing the rate of biomass decomposition and mineralization, thereby increasing emission of C02 into the atmosphere. Secondly,

45 these practices expose soil organic carbon (SOC) in the soil surface to the climatic elements, which expands the rate of SOM mineralization. Smith et al., (2005) list various management practices affecting green house gas (GHG) emissions from agricultural areas, such as changes between arable and grassland, grassland and forest, cropland management such as tillage, rotations, fertilizer use, use of legumes, the type of fertilizer applied, farm management pattern, ley systems (cut or grazed) and water management. Soil properties and climatic changes also play a role in GHG emission rates (Singh and Lal, 2001). Singh and Lal recommend these practices for sustaining and enhancing SOC sequestration (most of which also build SOM): soil surface management involving tillage methods and residue administration; soil fertility management through application of both inorganic fertilizers and biosolids according to a strategy of integrated nutrient control; crop rotation, selection, and use of cover crops; management and restoration of eroded and degraded lands, and water management. In addition to these factors, the concentration of SOM is mostly related to the climate of the region, soil texture, especially clay content, and soil drainage status (Shepherd et al, 2002).

Pulleman et al. (2003) compared the effects of conventional versus organic arable farming on SOM concentrations. The study was conducted on marine loam soil in the Netherlands. Three different management systems (permanent pasture, organic arable, and conventional arable) were chosen for the study, each of which had been under the same management practices for over 70 years. The study showed that although the permanent pasture system had the highest SOM concentration, nutrient

46 mineralization, earthworm activity and water stable aggregation due to lack of tillage, the organic system had significantly greater levels of these than the conventional system. The total SOM concentration in the organic system resulted in 24g/kg while the conventional system had only 15 g/kg to a 20 em depth. From the study, these results could not be differentiated from the effects of manure inputs or the absence of inorganic fertilizers and pesticides. But these findings do coincide with Christensen and Johnston's (1997) UK study on clayey soils. Their study showed definite increase in soil organic matter content with the long-term application of animal manure.

In order to evaluate SOM changes on a global environmental scale, long-term experiments must be conducted. Small changes in SOM concentration are difficult to measure accurately over short periods because of all the extenuating circumstances affecting year-to-year organic matter inputs. Changes in SOM must also take into account the already existing levels present; for instance, SOM changes occur very slowly in temperate climates. (Powlson et al, 1998). Powlson et al. (1998) outline the characteristics of long-term experiments comprising, "accurate records, archived samples and continuity of treatments, as long as the treatments remain relevant and do not cause soil damage or crop failure." They conclude that the amendment of arable soils with organic manures could lead to an approximate soil C sequestration of 18.33

1 Tg ofCf • This is equivalent to an increase of 4.76% of present C pool in the top

30cm of European soils, over a century. Powlson et al. (1998) argues that the estimates are crude and must be studied further with more precise measures of soil C changes.

47 There are various limitations associated with long-term studies in projecting C­ sequestration. Concerning SOM, trends in change and loss are often studied on gently sloping fertile lands where the erosion rates are less than the surrounding landscape.

When these findings and trends are transferred to lands with soils of low fertility, there is little known about the validity of this data transfer (Rasmussen et al., 1998).

Composting is highly recommended for use in sustainable farming practices. Along with building SOM and aiding in C sequestration, it can be used to control weeds, pests and diseases (Watson et al., 2002). True composting of manures requires aerobic decomposition at temperatures of approximately 60°C. This results in physical and chemical changes such as reducing nutrient availability. Therefore, composting is more beneficial in the long-term building of soil fertility (Watson et al.,

2002).

Organic and biodynamic farming practices are two oftoday's leading methods utilizing compost to increase SOM concentration. Biodynamic management specializes in using eight authorized "preparations" applied to crops, soil, or manure to create fermented composts and compost sprays. There is apparently a consistent report ofhigher SOM% (even with similar fertilizer loadings) in these practices versus organic farming, although the cause of this has not been identified (Shepherd et al.,

2002). In a study conducted by Carpenter-Boggs et al. (2000) they found that organic and biodynamically managed soils had higher microbial status and were more biotically active than soils that didn't receive compost but the levels were not significantly different between the two sustainable practices. Even though their

48 research did not show a difference between the positive effects of biodynamic and organic farming, their literary review revealed that biodynamic compost may result in more organic C, N, and biomass. Carpenter-Boggs et al. (2000) revealed that both of the compost-amended soils had higher levels ofmineralizable C, more soil respiration, and served as a source for labile C when compared with treatments of just inorganic fertilizers or none at all.

Bailey and Lazarovits (2003) revealed another benefit of composting, stating that some composts may be as effective as commercial fungicides for controlling a broad spectrum of fungal diseases but there is a major limitation in recommending compost for disease control. This study serves as an example of the difficulty in replicating experiments with compost. There is such variability in quality and materials comprising compost because up to this point compost cannot be standardized to the extent required for credible scientific research.

3.1.3 Cover Cropping

In long-term studies conducted between 1920 and the present, Rasmussen et al. (1998) reported that eliminating fallow periods from a cropping system had more of an effect on SOM loss than decreasing tillage. High rates of biological oxidation during the summer months were mostly due to the absence of C in the fallow year, rather than erosion. Earlier studies show that soil C and N losses were always more in crop rotations that include fallow periods. The SOM loss in these soils was linearly correlated with the amount initially present in the soil. It is extremely difficult to prevent C loss in soils with high SOM concentration if they are fallow. The research

49 also revealed that loss of C due to biological oxidation exceeded the input of C from cereal roots and residue management. Since there was a steady state of C under grassland, this implies that cover cropping is even more effective than crop residue inputs that include fallowing.

Most of these long-term studies were conducted on semi-arid soils in the

Pacific Northwest. A study beginning in 1881 showed that about 35% ofC concentration was lost in the top 30cm in the first 50 years the land was farmed. After returning to pasture in 1931, there has been a substantial increase of soil C and N concentrations. Summer-fallow systems produce no residue during the fallow year and biological oxidation is more than in cropped soils. This is probably more detrimental to soils in the Pacific Northwest because the land receives low summer rainfall and soils are usually dry for more than 90 days, whereas weed-free fallow periods allow soil to remain moist, creating ideal conditions for biological oxidation (Rasmussen et al., 1998).

Some of the most common legume cover crops in sustainable and organic farming systems include legume-based leys and clover leys. In mixed systems white clover-grass and red clover (with or without grass) are the most popular. These can also be used for fodder or green manure. Other types of clover, lucerne, vetches, lupins and trefoils may be used depending on the soil and climate characteristics of the region (Watson et al., 2002). Using crops with different rooting depths during rotation also aids in varying the sward structures above and below ground. This method can considerably increase theN use efficiency (Watson et al., 2002). The cover crops

50 immobilize theN, which can be leached over winter periods if left to fallow. Then, during spring planting, this N can be incorporated through mineralization.

3 .1.4 Manuring

One of the most common amendments applied to agricultural soils are animal manures. For a sustainable farming system they are extremely important for recycling the nutrients back into the soil. Organic manures are traditionally applied to silage and root crops, but it may prove more beneficial to use them for cash crops (Watson et al.,

2002). The quantity and type of nutrients found in manures vary greatly with the animal, feed composition, quality and amount of bedding material incorporated and the length and condition of storage. The common chemical makeup of farmyard manure will contain 159kg ofN, 35 kg ofP, and 140kg ofK with a 25 Mg ha·1 application rate (Shepherd et al., 1999).

Powlson et al. (1998) observed that long term experiments tracking rates of

SOM suggest that amending arable soils with 10 Mg ha- 1 of organic manure could lead to an increase in current total European soil C pool to 30 em by approximately 4.8% over 90 years.

There are two main types of manure: green and animal. Green manure assists in the horizontal shift of nutrients through a system. A horizontal shift means nutrients are produced or taken from one area of a farm, are recycled through livestock or a compost heap, and then moved to another area of the farm (Blake, 1990). Green manures include forms of stock feed, straw, or other plant by-products. The United

States produces approximately 1 billion Mg of organic and inorganic agricultural

51 recyclable by-products a year. 50 million Mg of cattle manure, 30 million Mg of poultry and swine manure, and 150 million Mg of municipal solid wastes (Edwards and Someshwar, 2000).

Rasmussen et al ( 1998) reported that the addition of manure decreased C and N losses from the soil. This effect intensified with continuous cropping. Manure even had a greater effect than N fertilization on increasing SOC concentration at all the tested locations, but this is attributed to manure's ability to increase total C input by

30-80%. Dick et al. ( 1998) observed similar results during a long-term study conducted in some soils of Kentucky, Michigan, Ohio, and Pennsylvania. After 20 annual applications of manure, SOC concentrations were much higher throughout the top 25cm ofthe soil layer in the manured than in the conventionally farmed sites. This is due to higher C input levels and, once the manure applications ceased, C concentrations rapidly declined.

The drawback to using animal manures involves rapid mineralization and volatilization. The release of nutrients from organic manure is often not synchronized with crop uptake. If mineralization takes place when no crops are present, high levels of nitrate (N0-3) leaching results (Biao et al., 2002). This problem can sometimes be remedied by the use of catch crops to absorb the extra nutrients before leaching takes place.

3.1.5 Crop Residues

Lal (1995) affirmed the importance of crop residues in obtaining SOM by asserting, "The return of crop residues is essential to maintain an acceptable level of

52 soil organic matter." Crop residues contain about 40% C and are a major resource with various uses like fodder, fuel, and industrial raw material, including the restoration of

SOC when returned to the soil. Belowground crop or weed root biomass efficiently enhances SOC in the soil through its contribution of organic materials. The amount of this material due to residue is dependent on the quantity and quality of the residue applied, soil properties, and the management practices followed (Singh and Lal, 2001).

The U.S. produces approximately 400 million tons of crop residue a year

(Edwards and Someshwar, 2000). Crop residues generally refer to fibrous plant tissue left on the field after harvest and include stems, leaves, roots, chaffs and other plant parts. Some well-known sources of crop residue are listed below, of these, the grain crops contribute the most to world residue production: barley (Hordeum vulgare), com

(Zea mays), millet (Pennisetum americanum), oats (Avena satica), rice (Oryza sativa), rye (Secale cereale), sorghum (Sorghum bicolor), sugarcane (Saccharum o.fficinarum), wheat (Triticum aestivum), legumes such as (Viciafaba), chickpeas (Cicer arietinum), cowpeas (Vigna unguiculata), lentils (Lens esculenta), peas (Pisum sativum), pulses, soybeans (Glycine max), and root crops like cassava (Manihot esculenta), colocassia

(Xanthomona spp.), potato (Solanum tuberosum), sugarbeet (Beta vulgaris), sweet potato (Ipomea batatas), taro (Colocasia esculenta), and yams (Dioscorea sp.). Lastly, oil seeds that contribute to crop residues include linseed (Linum usitatissimum), rapeseed (Brassica campestris), safflower (Carthamus tinctorius), sesame (Sesamum indicum), and sunflower (Helianthus annus) (Lal, 1995).

53 In "The Role of Residues Management in Sustainable Agricultural Systems"

Lal (1995) stated that crop residues returned to the soil play a significant role in the maintenance of and increase in SOC concentration as well as adding to plant nutrients and decreasing the need for inorganic fertilizers. Residues contain large amounts ofN,

P and K. The positive effects of supplying residues back into agricultural areas include adding the aforementioned nutrients to the soil, increasing SOM concentration, enhancing soil structure, and influencing soil moisture and temperature regimes. This occurs as a result of increased water stored in the root zone, and aiding in the balance of gaseous and energy fluxes from the soil (Lal, 1995).

Indirect consequences of crop residues input include reducing volatilization and leaching losses, increasing root-soil interaction with nutrients, and increasing

SOM concentration, which in turn improves intensity and capacity of water and nutrients in the soil. Crop residues sequester C and reduce emissions of GHGs into the atmosphere, thereby affecting gaseous and volatilization fluxes. Residue mulch changes the intensity and capacity of soil moisture by decreasing runoff and evaporation rate. The mulch is only effective in the first and second stages of evaporation at conserving soil moisture. Percent of precipitation stored and depth of water penetration are at their greatest when crop residue straw is left on the soil surface as mulch (Lal, 1995).

In a study comparing conventional and organic farming systems, Gunapala et al. (1998) observed that microbial activity and abundance, which aids in SOM decomposition, was high with the addition of a vetch (Vicia villosa) residue. Another

54 study revealed that there were no significant structural differences between organically and conventionally farmed soils (when the organic system had not received any manure for six weeks) until the ley cover was plowed under. Plowing under of organic soil's ley improved soil structure (Shepherd et al., 2002). The conclusion was that young organic matter is especially important for improving structural stability through fungal hyphae, which physically bind aggregates and extracellular polysaccharides

(soluble carbohydrates). Shepherd et al. (2002) postulated that it is probably not the farming system, per se, that is important but the amount and quality of organic matter that is returned to the soil.

Replacing nutrients removed by crops with residues is equally if not more important in low-productivity subsistence farming, even if the nutrients harvested are fewer than in commercial agriculture (Lal, 1995). Energy produced in crop residues can be greater than that used in crop production. Efficiently utilizing this energy through innovative agricultural systems is the challenge to farmers and soil scientists alike. Farming systems must produce huge quantities of biomass that can be used for residue mulch, fodder, fuel, and construction materials (especially in developing countries). Some methods to achieve this quantity of production include introducing high-yielding cultivars that are especially adapted to soils that may have less than ideal conditions such as acidic, droughty, shallow rooting depth, high soil temperature, and eroded and degraded soils(Lal, 1995). Another method incorporates efficient and aggressive cover crops during fallow periods to increase soil fertility while contributing to biomass that can later be mulched on the soil surface. The final step

55 and often most difficult is developing tillage methods with economic and efficient weed control so that the residues can be left on the soil surface without the accumulation of pests and diseases. These practices often involve large amounts of pesticide and herbicide use, sometimes more than conventional tillage. There are currently studies being conducted that attempt to develop no-till methods in a more sustainable fashion.

Crop residues also carry additional benefits to soil quality. Many studies have been conducted concerning crop residue management and its effects on suppressing soil-borne diseases. Bailey and Lazarovits (2002) assert that soil management practices influence the release of biologically active substances from crop residues and soil microorganisms that aid in preventing common diseases such as root rot in cereals.

Residue management methods can lower the pathogen's inoculum density in the soil, reduce it's ability to survive, deprive the pathogen of a host, and create conditions favorable to microorganisms at the expense of the pathogen (Bailey and

Lazarovits, 2003). The quality and quantity of crop residue greatly influence pathogen growth and survival. Bailey and Lazarovits stated that C released from crop residues contribute to increasing soil microbial activity, therefore increasing the likelihood of displacing a pathogen from its preferred niche through competition. These organic amendments may be slower-acting than chemical fungicides but can last longer with cumulative effects.

56 The use of crop residues can be even more important to C sequestration than manuring. A long-term study revealed the removal of com residues decreases SOC concentrations even during years when manure is applied (Dick et al., 1998).

C sequestration by crop residue application is affected by many factors. The rates of decomposition of certain residues affect nutrient levels in the soil. Residues such as wheat straw decompose more slowly than plants like sorghum. In a ten year study conducted in Texas, a continuous wheat rotation resulted in greater SOC compared to sorghum and com (Potter et al., 1998). The decomposition rate was slower over the long term, which is probably due to the variance in N concentration in the residues.

The study also revealed that temperature plays a key role in C sequestration with residues. Studies conducted in cooler climates, like the northern U.S., report much greater increases in SOC concentration than those in the warmer southwest.

In review of previously published estimates of yearly per-area mitigation potentials for carbon sequestration in European soils, Smith et al. (2005), found that organic farming was the only management practice that had increased from

1990-2000 that held large-scale C-enhancing potential for European soils. They not however, that although organic farming might increase SOC in practiced areas, a simple redistribution of organic resources would not result in a net gain in SOC at the country level (Smith et al., 2005).

3.1.6 Soil Quality Indices

Lal (1994) separates key soil quality indicators into several smaller sub­ catgories, these include: soil strength and structure, soil mechanical properties,

57 porosity and A WC, water transmission, chemical indicators, and organic carbon concentration. Each of these categories directly pertain to soil sustainability and productivity. Ifthese indicators are at extreme limitations in the soil, the productivity in the soil is in jeopardy (Lal, 1994).

By sampling from 6 working, full-scale farms, the collected data are more representative of actual soil conditions. Thus the objectives of this study were to assess soil quality changes in conventional farming vis-a-vis organic management practices and establish a relationship between soil quality indicators and crop yield.

The hypothesis tested was that soil quality will increase under organic farming methods and that crop yield will have a positive correlation with the soil quality index rating.

3.2 MATERIALS AND METHODS

3 .2.1 Sampling methods

Six farms were sampled for the present study and are the same farms as those described in chapter II. Details of the sites, soils, and management practices are described in chapter II. The sampling was performed in Delaware, Knox and Licking

Counties. A conventionally and an organically managed farm with corresponding soil types was sampled from each. As a result of three different soil types for the replications, pseudoreplication was used on-site (Hurlbert, 1984). Three 3x3m adjacent plots were chosen at the summit landscape position in each field. Soil cores

3 (diameter=5.5cm, height=6cm, volume=142.5cm ) and bulk samples (approximately

58 500g) were taken from three depths (0-1 Ocm, 10-20cm, 20-30cm) in each plot. Bulk samples were taken with a hand trowel, stored in an airtight bag and then placed in refrigeration pending analysis. Soil cores were wrapped in cellophane and secured with rubber bands to create an airtight environment, then also stored in refrigeration

3.2.2 Laboratory methods

Bulk density (pb) was determined by the core method with stones (> 2 mm) removed (Blake and Hartge, 1986). Volumetric moisture retention was measured at different matric potentials using a tension table for -0.003 and -0.006 Mpa suctions. A pressure plate apparatus was used to determine soil moisture retention at -0.03, -0.3 and -1.5 Mpa suctions (Klute, 1986). . After determining the wet Pb of the core samples at the field moisture stage, gravimetric soil moisture content ( m) was determined by oven drying at 105 °C. Dry Pb was calculated from the values of wet Pb and m.

After the bulk sample was air-dried and ground, it was sieved through 5 and 2 mm sieves to obtain aggregates for wet-sieving. The other portion was ground with a mortar and pestle and passed through a 0.25mm sieve to be used in C and N analyses.

Percent water stable aggregation (WSA) was established by the wet sieving procedure.

Five nested sieves with mesh sizes of 4. 75, 2.0, 1.0, 0.5 and 0.25mm were used for wet sieving analyses (Yoder, 1936). The nest of sieves was oscillated in water for 30 minutes. The mean weight diameter (MWD) of the water stable aggregates (WSA) was determined according to Kemper and Rosenau (1986). 59 One g of the <0.25mm soil was analyzed for C and N concentration by the dry combustion method (Nelson and Sommer, 1982) in a NC 2100 soil analyzer

(ThermoQuest CE Instruments, Milan, Italy). For soil samples with pH< 8.5, total soil

C was assumed to be SOC (Bohn and McNeal, 1985). No soil sample in this study had a pH of>8.0 soC and N values obtained by the dry combustion method were assumed to be SOC and SON, respectively. Pools of SOC and SON were calculated with the product of SOC and SON concentrations, and Ph using Eq. [1] (Lal et al.,

1998). The CEC was measured using an ammonium acetate extraction followed by emission spectrometry. Soil pH was determined using a 1: 1 ratio of soil to water and a pH meter.

1 3 4 2 1 Mg C (N) ha- =[% C (N) x corrected Ph (Mg m- ) x d (m) x 10 m ha- ]/ 100

[Eq. 1]

3.2.3 Statistical Analysis

To determine statistical differences and interactions among systems, depths and soil types for each soil parameter, analysis of variance (ANOVA) tests were conducted. Data arranged in a factorial form were analyzed by using the ANOVA procedure ofSAS software (SAS Institute, 2001). Significant differences in means and interactions were separated based on F-protected LSD tests at the p:S 0.05 level.

Duncan's multiple range test was used to separate the mean values (Adesodun et al.,

2001; 2005). Unless otherwise noted, results are for soils combined for the 0-30cm sampling depth. For certain parameters, these depths were combined because of a lack of significant difference.

60 RESULTS AND DISCUSSION

3.3 .1 Results

Soil physical and chemical properties are grouped according to significant interactions. Only C:N ratio, SOC and SON pools, bulk density and WSA% had a significant interaction at the p:S 0.05 level for system and depth. Tables 3.3 and 3.4 express the means for these parameters. These, as well as the other parameters expressed a significant interaction for soil type and system at the p:S 0.05 level.

The MWD was significantly higher at the p:S 0.05 level for the organic management system in Blount and Bennington silt loams than in other soils. The Chili silt loam soil had the lowest MWD among all farms, across management practices.

The organically managed Blount silt loam and conventionally managed Bennington silt loam had the highest WSA% among all the sampled farms. The MWD values were similar across management systems and soil types. The organically managed Chili silt

3 loam had significantly lower WSA% than all the other farms. Bulk density (Mg m- ) was statistically similar for both Blount silt loam farms, the conventional Bennington silt loam and the organic Chili silt loam farms. Organic Bennington and conventional

Chili silt loam soils had significantly lower bulk density than other farms. Bulk density was not significantly different across management systems and was statistically similar for all farms at the 10-20cm and 20-30cm depths. Soil bulk density was lower only in the 0-1 0 em depth for all farms, regardless of management system.

61 Table 3.1 shows the means and significance for MWD, WSA and bulk density for all the farms according to soil type and management system. Figure 3.1 illustrates the comparison of WSA% across farms.

Soil T~~e S~stem MWD WSA% Bulk Density !mm) (Mglm3) Blount silt loam Organic 3.2a 75.8ab 1.5a Blount silt loam Conventional 2.3bc 71.1b 1.6a Bennington silt loam Organic 2.5ab 64.4c 1.4b Bennington silt loam Conventional 1.7cd 76.4a 1.5a Chili silt loam Organic 0.6e 46.8d 1.5a Chili silt loam Conventional 1.2de 71.5b 1.3b LSD 0.7 4.7 0.1

Table 3.1 Soil physical property means according to soil type and management system Figures followed by same letters in the column are statistically similar at a=0.05. Values are LSD at <1=0.05.

Soil chemical properties for each soil type and management system are shown in Table 3.2, with means and significance at the p~0.05 level. The pH varied greatly with soil type and management system. The organically managed soils tended to have a lower pH across soil types compared to the conventionally managed farms. This is most likely due to the increase in liming practices among the conventional farms. The organically managed Chili silt loam had a significantly more acid pH than the other farms. The Blount silt loam soil tended to have a higher pH in general, but the organic farm still had lower pH than the conventional farm. The data on soil pH are shown in

Fig. 3.3.

1 SOC pool and SON pool (Mg ha" ) were significantly different for every farm at the p~0.05level. The conventionally managed farms had significantly higher SOC 62 and SON pools, across soil type, than did the organic farms. The Bennington

1 conventional farm had a much higher SOC pool of26.2 Mg ha- • The Blount silt loam farms had almost the same SOC pools despite management practice but the Chili and

Bennington silt loam farms showed a wide disparity in values across systems. Figure

3.2 illustrates this comparison. The C:N ratios for all conventional farms were higher than that of organic but the organic Blount silt loam and conventional Chili silt loam farm had statistically similar values. Table 3.2 expresses the means for the aforementioned comparisons.

The CEC (cmol+c/kg) levels for conventional farms were higher than those of the organic farms, across soil types. The conventional Blount silt loam farm had a significantly higher CEC than all the others and the organic Chili silt loam had the lowest CEC value.

Soil Tn~e S!stem ~H SOC Pool SON Pool C:N CEC (Mglha) (Mglha) (cmol+clkg) Blount silt loam Organic 7.4b 18.2d 1.9c 9.6b 19.5c Blount silt loam Conventional 8.0a 18.5c 1.8d 10.3a 38.la Bennington silt loam Organic 5.4e 13.8f 1.4f 9.7b lO.ld Bennington silt loam Conventional 7.1c 26.2a 2.5a 10.7a 22.6b Chili silt loam Organic 5.3f 14.8e 1.6e 8.8c 8.3e Chili silt loam Conventional 6.0d 21.9b 2.3b 9.7b 20.5c LSD 0 0 0 0.4 5.6

Table 3.2 Soil chemical property means according to soil type and management system Figures followed by same letters in the column are statistically similar at 0.=0.05. Values are LSD at 0.=0.05.

63 Table 3.3 expresses the C:N, SOC and SON pools across depth with their significances at the p:::_0.05 level. The C:N ratio for the 0-10cm depth in conventional farms was significantly higher than the rest. The 1-20cm range for organic farms was statistically similar to the 20-30cm range in conventional systems. For both managements C:N, SOC and SON were highest in the 0-IOcm depth and lowest in the

20-30cm depth.

SOC SON Organic Depth C:N Pool Pool (em) (Mglha) (Mglha) 0-10 9.7bc 18.3d 1.9d 10-20 9.5c 17.le 1.8e 20-30 8.9d 11.4f 1.3f Conventional 0-10 10.7a 24.4a 2.3a 10-20 IO.lb 23.3b 2.3b 20-30 9.8bc 18.7c 1.9c LSD (0.05) 0.4 0 0 Table 3.3 Soil chemical property means according to depth and management system Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05.

Bulk Depth WSA% Density Organic (MglmJ) 0-lOcm 71.8b 1.3c 10-20cm 62.7c 1.5a 20-30cm 52.5d 1.5ab Conventional 0-lOcm 67.8b 1.4bc 10-20cm 79.la 1.5ab 20-30cm 72.2b 1.5a LSD (0.05) 4.5 0.1 Table 3.4 Soil physical property means according to depth Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05. 64 soc SON S;rstem ~H MWD WSA% Bulk Density C:N Pool Pool (mm) (Mgtml) (Mglha) (Mglha) Organic 6.0b 2.0a 61.9b 1.5a 9.4b 15.6b 1.7b

Conventional 7.0a 1.7a 73.0a 1.5a 10.2a 22.2a 2.2a

LSD 0 0.4 2.6 0.06 0.2

Table 3.5 Soil physical and chemical comparisons according to management system Figures followed by same letters in the column are statistically similar at 6.=0.05. Values are LSD at 6.=0.05.

65

90

80

~ -I C) 70 0 0 ~ 60 * C) * Organic c(- Conventional 50 • ~ * 40 ~=0.84**

30 10 20 30 40 CEC (cmol+c kg-1)

2 Equation for graph 3.4 (y =a+ bx-cx ) Fig. 3.4 CEC and WSA correlation among six farms (2004) 0-30cm

Figure 3.4 shows the correlation ofWSA to CEC with an r2 value of0.84** between the organic and conventional sampled farms. Overall, the conventional farms had higher CEC and WSA values than the measured organic farms. The CEC values show a strong correlation with WSA for the sampled farms. WSA aggregation begins to decline after increased CEC in the soil because the influx of K+ can increase dispersion at heightened levels (Islam and Weil, 2000).

69 30

25 •

~ -•ca 20 .c: * • 15 r Organic - * * Conventional 10 • ~ .-2=0.73* 5

0 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 Soil pH

2 Equation for graph 3.5 (y =a+ bx-cx ) Fig. 3.5 SOC and soil pH correlation among six farms (2004) 0-30cm

Soil pH is compared to SOC, CEC and SON in figures 3.5-3.3.7. The strongest correlation among the 6 farms was between the SOC and soil pH with an i value of 0. 73 *. SOC was highest for the conventional farm at a pH of 7 .1. As the pH value increased or decreased from 7.0, the SOC value also decreased. Conventional farms consistently had higher SOC, CEC and SON values than the organic farms, except the organic farm with a lower pH than the conventional farm in figure 3.7. The organic farm with a lower pH of7.4 had a higher SON value than the conventional farm with a higher pH of 8.0.

70 50

Organic "t- 40 * -I Conventional C) • • ~ (J ,.Z:0.80* ..t 30 0 E (J 20 • * -0 w 0 10

0 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 Soil pH

2 Equation for graph 3.6 (y =a+ bx+cx ) Fig. 3.6 CEC and soil pH correlation among six farms (2004) 0-30cm

Figure 3.6 shows a positive correlation between soil pH and CEC for the six farms sampled. Once the pH reaches 7.0, the CEC value increases more quickly.

Figure 3.7 illustrates the effect of soil pH on SON. The ideal range for SON lies between pH 6.0 and pH 7.5. After pH 7.5 N fixation decreases because of an alkaline effect that hinders biomass production (Buckman et al., 2001)

71 3.0

2.5 • ..... • -I 2.0 CIS .s::. * C) • ::E 1.5 * * Organic -z * • Conventional -·o 1.0 2 en r =0.76*

0.5

0.0 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 Soil pH

2 Equation for graph 3.7 (y =a+ bx-cx ) Fig. 3.7 Soil Nand soil pH correlation among six farms (2004) 0-30cm

Figure 3.8 shows the relationship between SON and SOC in the 6 sampled farms. SON levels increase as SOC increases because C and N are stoichiometrically linked in the soil.

72 2.6 ..------,

2.4 ~=0.97*** • .;:-- 2.2 I ca .c 2.0 C) :IE -z 1.8 • 0 U) 1.6 * Organic * • Conventional

1.4

1.2 +--.----,--,----.----.--.....--.----l 12 14 16 18 20 22 24 26 28 SOC (Mg ha-1)

2 Equation for graph 3.8 (y =a+ bx-cx ) Fig 3.8 SON and SOC correlation among six farms (2004) 0-30cm

73 100 .------,

80

-I -CJ) 0 60 0 * Organic -CJ) * Conventional 40 * • -c( U) 3: ~=0.53* 20

0+----r----,---~---~ 10 15 20 25 30 SOC (Mg ha-1)

2 Equation for graph 3.9 (y =a+ bx-cx ) Fig. 3.9 WSA and SOC correlation among six farms (2004) 0-30cm

Table 3.6 shows the soil quality index rating for each farm. According to Lal's

( 1994) soil quality index, the higher the value, the more at risk the soil. The lowest ratings indicate the best soil quality for that system. The suggested critical levels of the measured key soil and water indicators are outlined in A rating of 1 means there is no limitation on agronomic production as a result of the specific soil parameter at that level. A rating of2 means a slight limitation on productivity, 3 is a moderate limitation, 4 is severe, and 5 is extremely severe. The Blount silt loam organic farm had the best soul quality rating and the Chili silt loam organic farm had the worst.

74 This table of soil quality shows no trend across management system. The two conventional farms, Bennington and Chili silt loam, had the next best soil quality rating to the Blount organic farm.

Treatment MWD WSA %Bulk Density AWC ~H soc CEC Total Organic mm Mglm3 em % %of Blount silt loam I I 3 3 2 3 2 I5 Bennington silt loam 2 2 3 4 3 3 3 20 Chili silt loam 4 3 3 3 4 3 4 24 Conventional Blount silt loam 2 2 4 4 4 3 I 20 Bennington silt loam 3 I 3 4 2 3 I I7 Chili silt loam 3 2 2 3 2 3 2 I7 Ratings are derived from soil quality index Lal (I994) Table 3.6 Soil Oualitv Index for six farms 0-30cm de12th (2004)

According to table 3. 7, there does not appear to be a strong correlation between the soil quality rating and the average crop yield over years for the 6 sampled farms.

The organic Blount silt loam farm had the best soil quality rating but a lower crop yield than the conventional farms with the second best soil quality ratings. The organic

Chili silt loam farm had the worst soil quality rating among all the farms but a relatively high crop yield. On average, the conventional farms did have a better soil quality rating and higher average crop yield than the organic farms according the to

Lal (I994) soil quality index.

75 Treatment Grain Yield SQI Rating

Organic Mglha

Blount 3.8 15

Bennington 2.3 20

Chili 4.4 24

Conventional

Blount 4.0 20

Bennington 4.7 17

Chili 6.4 17

Table 3.7 Soil gualitv rating versus crop yield (2004-2005) for six farms Ratings are derived from soil quality index Lal (1994)

3 .3 .2 Discussion

The majority of the findings from this study differ from many previous studies. For the most part, previous experiments have revealed an increase in soil

76 quality under organic management and alternative fertilizer inputs. This is especially true in reference to SOC and SON levels, WSA% and CEC.

The pH of organically managed soils is generally lower in the early stages of management than conventional farms but after years of organic practices the pH increases. Bulluck et al., (2002) observed that soil with alternative fertility amendments initially had a lower soil pH than that treated with synthetic fertilizers but over time the pH levels increased to higher than those observed in conventionally amended plots. The pH levels of the organic farms in the present study were lower than those under conventional farms but the years of management had no direct effect on soil pH.

In a study conducted at the Rodale Institute Farming Systems Trial in

Kutztown, P A, between 1981 and 2002, SOC and SOM levels were significantly higher in the organically managed treatments compared to the conventionally managed plots. Even though the annual net aboveground C input was the same for the organic legume based treatment and the conventional treatment, the organic system retained more of its soil carbon. From 1981 to 2002, SOC concentration 27.9%,

15.1%, and 8.6% in the organic manure, organic legume, and conventional plots, respectively (Pimentel et al., 2005). Soil N levels were measured in 1981, at the start of the study and 2002 for all three treatments. Across treatments, N levels were not significantly different in 1981 but in 2001 the conventional system did not increase soil N levels but the organic manure system and organic legume system increased N from 0.31% to 0.35% and 0.33%, respectively (Pimentel et al., 2005).

77 Total SOC tended to be higher in macroaggregates of permanent pasture and organic farms compared to conventional farms in the (Pulleman et al., 2005).

However, much smaller amounts of particulate organic matter (POM) was found in the microaggregates of conventional and organic arable land than permanent pasture. The study demonstrated that farming practices that lead to larger earthworm populations and activity are very important to microaggregate formation and an important aspect of sustainable farming methods. The addition of green and dairy manures were found to correlate with increased earthworm population and an increase in organic C contents of earthworm-made macroaggregates (Pulleman et al., 2005).

Bulluck et al. (2002) compared the use of organic and synthetic fertility amendments on physical and chemical properties on organic and conventional farms, respectively. The study showed an increase in SOM, total C and CEC, as well as a decrease in bulk density for soil amended with alternative (organic) fertilizers compared to conventional inputs. Therefore, it was concluded that soil quality on conventional farms was significantly improved over a 2-year period with organic amendments as compared with synthetic fertilizers. The alternative inputs included

2 composted cotton-gin trash, composted yard waste and cattle manure. Calcium (Ca+ ) concentrations increased two-fold over a 2-year period in soils treated with the alternative fertilizers, whereas the soils treated with synthetic fertilizers experienced no significant increase in Ca+Z concentrations.

78 Soil concentration ofMg +2 also doubled with alternative inputs while conventional fertilizers only produced slight increases and K+ increased by a factor of 3 when it decreased in concentration with use of synthetic fertilizers (Bulluck et al., 2002).

Over a 9 year study, Zaller and Kopke (2004) reported that the application of farmyard manure (FYM), whether composted or biodynamically composted, significantly increased pH and nutrient levels (specifically P and K) in agricultural soils. The study also revealed that composted manure had a significantly positive effect on soil C:N ratio and crop yields. They concluded that organic farming systems using composted FYM as fertilizer can stimulate biological soil activity and therefore support soil quality and fertility (Zaller and Kopke, 2004).

Wu et al. (2003), found that organic amendments and changes in management practice did not significantly change the mechanical resistance, oxygen diffusion rates, hydraulic conductivity or non-limiting water range between soil amended with dairy manure, biosolids and green waste, conventional or organic treatments. But the soil under the organic farming system had a narrow non-limiting water range because less water was retained at field capacity. This indicated that the soil surface under this management practice had more macro-pores (Wu et al., 2003). Soil water content is generally higher in the organic systems than the conventional systems (Pimentel et al.,

2005). The high levels of SOM conserve soil and water resources, especially during the drought years (Pimentel et al., 2005).

Martini et al. (2004) compared organic, conventional and transitional (from organic to conventional) plots. Martini and colleagues observed that a lack of

79 differences in crop growth and yield between transitional and organic plots indicated that there was no overall improvement in soil quality associated with the organic management. This lack of yield difference between management systems was thought to be a reflection of balance between improvements in some aspects of soil quality and a worsening of others (Martini et al., 2004). There were no significant differences observed in % WSA between systems but there were some differences in other soil properties. The organically managed plot (5 years) had lower pH, significantly higher

N, P, K, and C concentrations than the transitional plot. These properties however, showed no clear connection with crop yields (Martini et al., 2004).

CONCLUSIONS

The hypothesis that soil quality would increase under organic farming practices compared to conventional farming practices was not proven. Although an organic farm had the best soil quality rating the other two had the worst quality ratings. There seemed to be no trend across management practices as far as soil quality is concerned. The second hypothesis, that crop yield would carry a strong correlation with soil quality was also not proven. There was some relationship observed with the crop yield data from Chapter 2 and the soil quality index rating for each farm, but this trend did not extend across the board. Two of the conventional farms that had the highest yields also had good soil quality ratings and the two organic farms with the worst yields showed low soil quality.

80 The exception to this trend was the Blount silt loam organic farm, which had mid- range crop yields compared to the other farms, but the best soil quality rating.

Soil quality, according to the parameters measured, was similar for organic and conventional farms. The observed increase in these parameters for organic fanning in other studies was not reflected in this experiment. The lower levels of SOC, SON pool and CEC may be due to increased tillage in the organic farms tested. Organic farming uses both tillage and cover crop rotations to suppress weeds. These farms may be tilling their soils more often than the conventional farms that usually till once a year.

This increased tillage can result in mineralization and ultimate loss of nutrients form the soil, especially C. The Blount silt loam organic farm had very similar levels of

SOC and SON to the conventional farm on the same soil type. This organic farm also was the only farm to have higher WSA% than the conventional farm counterpart. /

From the background information, it is revealed that this farm relies on a very intricate crop rotation and green manure application (as outlined in chapter 2). Perhaps, the use of complex crop rotations instead of heavy reliance on tillage to suppress weeds in organic fanning, could improve soil quality, especially with nutrient levels. More study would need to be conducted in order to investigate the relationship of crop rotation versus tillage weed suppression in organic farms with soil quality.

Two major problems often found in organic agriculture are N deficiency and weed competition. The Rodale experiments have overcome these challenges through legume cover crop management. Organic farms are limited to mechanical and biological weed control, whereas conventional farms can implement mechanical,

81 biological or chemical control. Mechanical control is oftentimes more effective in dry conditions than chemical control but the reverse is true in wet conditions (Pimentel et al., 2005). Testing the plant available N and the C:N ratios of all the inputs added to the 6 farms would give a clearer representation of soil quality. After these parameters were tested, a stronger correlation between soil quality and crop yield could be derived.

Organic amendments can provide advantages beyond the benefits of increased

SOM on soil physical and chemical properties because these fertilizers contain numerous other nutrients that conventional farmers rarely apply, such as manganese, zinc and sulfur. These added nutrients create insurance against potential yield limitations and unlike commercial fertilizers, the organic amendments permit nutrient to accrue in the soil (Bulluck et al., 2002).

82 LIST OF REFERENCES

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86 CHAPTER4

SOIL QUALITY COMPARISON OF SIX MANAGEMENT TREATMENTS

ABSTRACT

Soil quality plays an integral part in the sustainability of any agricultural system. Soil quality indexes are useful tools in deciphering best management practices to build soil quality. In this two-year experiment, a complete random block design was used to test six treatments on various soil quality indicators. These treatments included cover crop, dairy manure, tannin bark compost, fallow, control and Triple 19 fertilizer.

The treatments were used to represent common conventional and organic management practices. The synthetic fertilizer and manure yielded the highest amount of corn among the six treatments. According to the soil quality index implemented, organic and conventional farming practices had a similar soil quality index. The synthetic fertilizer and manure treatments also received the highest soil quality ratings while the compost had the lowest yield and worst soil quality rating. These findings expressed a correlation between crop yield and soil quality for this study. This information must be coupled with other long-term studies to more accurately explore the connection between organic agricultural practices and soil quality.

87 INTRODUCTION

4.1.1 Soil Quality

Soil quality is defined as a specific soil's capacity to function, within a certain ecosystem, to sustain biological productivity, store and recycle water, nutrients, and energy and, ultimately, maintain environmental quality (Doran et al.,

1996). The breadth and quality of soil organic carbon in agroecosystems affects soil's physical, chemical, and biological properties and therefore influences soil productivity and the sustainability of certain production systems (Singh and Lal, 2001 ). Soil quality is an integral aspect of soil sustainability and can be used to determine sustainability on a soil to soil level. Carter (1997) linked these two ideas as "inseparable" and considered soil quality as a "key indicator" of ecosystem sustainability.

With growing concerns over soil degradation and the need for more sustainable soil management practices at the onset of the 21st century, there has been a marked emphasis on the value of soil and its properties pertaining to specific ecological and agricultural functions (Carter et al., 1997). Some of these main functions include a medium for plant and biological production, a buffer or filter for various pollutants, and general promotion of plant, animal and human health. One of

88 the most relevant functions to carbon sequestration is soil's ability to store and cycle nutrients and other elements within the earth's biosphere (SSSA, 1995).

4.1.2 Soil Indices

In practice, a farmer who is attempting to optimize his or her management practices is likely to view soil quality as the condition of the existing soil in relation to the potential function of that soil (Islam and Weil, 2000).

Doran et al. (1996) stated that soil quality indicators should be sensitive enough to detect the effects of differing management practices but should not be so sensitive that they are affected by short-term changes, such as weather patterns. Islam and Weil (2000) used three classifications of soil quality indicators: ephemeral, intermediate, and permanent. The ephemeral parameters include water content, pH, bulk density, available K and P and soil respiration. These are factors that are very sensitive to management changes but also weather and other exogenous factors that cause them not to be strong indicators for assessing a soil's quality. The permanent indicators are so immutable and take such a long time to be affected by management practices, that they are also not considered the best for assessing quality. These include such features as soil depth, slope, texture and mineralogy. The intermediate soil characteristics are therefore the most ideal for assessing soil quality. Intermediate features refers to aggregation (dry and wet), organic matter content, active C and soil biological properties (Islam and Weil, 2000)

89 Lal (1994) separates key soil quality indicators into several smaller sub­ catgories, these include: soil strength and structure, soil mechanical properties, porosity and A WC, water transmission, chemical indicators, and organic carbon concentration. Each of these categories directly pertain to soil sustainability and productivity. If these indicators are at extreme limitations in the soil, the productivity in the soil is injeopardy (Lal, 1994).

The objectives of this study were to assess soil quality changes in conventional farming vis-a-vis organic management practices and establish a relationship between soil quality indicators and crop yield. The hypothesis tested was that soil quality will increase under organic farming methods and crop yield will have a positive correlation with soil quality index

4.2 Materials and Methods

4.2.1 Site Description:

A field experiment was initiated in Sept. 2003 at the Waterman Farm, The

Ohio State University in Columbus, Ohio. The experimental site is located at

40°02'00" N latitude and 83°02'30" W longitude, and situated in Franklin county,

Ohio. The soil of this site belongs to the Crosby soil series, and is classified as a fine, mixed, mesic, Aerie Ochraqualf. The average low temperature for 2003 to 2005 was

7.3°C and a high temperature of 18.2°C. The total precipitation was 209.9cm from autumn 2003 to autumn 2005 with a yearly average of0.23cm (USDA, 2006). Until the autumn of2003, the site was disked and roto-tilled but left fallow. From2001-

90 2002, the site was planted to soybean (Glycine max), tilled and chisel plowed. No fertilizer was used that year but Roundup TM [ (2-(phosphonomethylamino)acetic acid) isopropylamine salt of glyphosate (active ingredient), water, ethoxylated tallowamine surfactant, related organic acids of glyphosate, isopropylamine, polyoxyethylene alkylamine; molecular formula: C3HsNOsP] was sprayed to combat weeds. In 2000, the field was planted to com (Zea mays) and in 1999 it was planted in soybean.

The design of the sample site was a complete random block totaling 30x30m.

This square was broken down into 4 subplots (blocks) and subdivided with six 5x3m replications of each treatment. The treatments included dairy manure, tannin bark compost, Austrian winter pea (Pisum sativum), Triple 19 fertilizer, fallow and control.

The control and Triple 19 plots, also received Roundup ™ herbicide to mimic conventional practices. Each replication was spaced 1.5m apart vertically and 2m apart horizontally, with a larger 3m alley between the blocks, see fig. 4.1. Fertilizers were applied based on their N and C content. The tannin bark compost contained 1.54%N :

38.14%C, the dairy manure contained 1.35%N : 22.92%C and the Triple 19 Fertilizer held 19%N : 19%P: 19%K. The site was left untilled for the length of the experiment and all crop residue was left on-site. The site was planted to Roundup ™ ready field com and fertilized according to The Ohio State University Extension Agronomy

Guide 13th edition (1995).

Soil samples were taken in the fall of2003, before treatments were applied and again in the fall of2005, after two years of treatment. Crop yield and biometric measurements were taken in the fall of 2004 and 2005. The Soil cores

91 3 (diameter=5.5cm, height=6cm, volume=142.5cm ) and bulk samples (approximately

500g) were taken from 2 depths (0-1 Ocm, 10-20cm) in each plot. Bulk samples were taken with a hand trowel, placed in an airtight bag and then placed in a refrigerator pending analyses. Soil cores were wrapped in cellophane and secured with rubber bands to create an airtight environment and also stored in a refrigerator.

Dry biomass for each farm was calculated by hand-harvesting 2 rows 1.5m long from each replication plot. These stalks were weighed in the field and then a sample of two stalks was weighed, taken back to the lab and dried at 60°C for 24 hours. With this weight the moisture percentage was calculated (Dry Stalk weight (g) I

Wet stalk weight (g)) and then this value multiplied by the field weighed 10 stalk biomass to achieve the dry biomass weight. After the grains were removed, the dried husks were also added to this weight to gain the total dry biomass weight for each

1 farm, which was then converted to Mg ha - •

The grains were weighed and then dried at 60°C for 24 hours. This weight was multiplied by 1.14 to account for field moisture at 14% and then converted

1 to Mg ha - • The harvest index was computed, by dividing the calculated grain yield by the biomass yield and grain yield.

4.2.2 Laboratory methods

Bulk density (Pb) was determined by the core method with stones (> 2 mm) removed (Blake and Hartge, 1986). Volumetric moisture content was measured at different matric potentials using a tension table for --0.003 and --0.006 Mpa suctions. A pressure plate apparatus was used to determine soil moisture content at --0.03, -0.3 and 92 -1.5 Mpa suctions (Klute, 1986). . After determining the wet Pb of the core samples at the field moisture stage, gravimetric soil moisture content ( m) was determined by oven drying at 105 °C. Dry Pb was calculated from the values of wet Pb and ro.

After the bulk sample was air-dried the soil was passed through sieves to acquire a portion of aggregates >2.0 mm and <5.0mm for wet sieving. The other portion was ground with a mortar and pestle and passed through a 0.25mm sieve to be used inC and N analyses. Percent water stable aggregation (WSA) was established by the wet sieving procedure. Five nested sieves with mesh sizes of 4.75, 2.0, 1.0, 0.5 and

0.25mm were used for wet sieving analyses (Yoder, 1936). Sieves were agitated for 30 minutes. The mean weight diameter (MWD) of the water stable aggregates was determined according to Kemper and Rosenau (1986).

One g of the <0.25mm soil was analyzed for C and N contents by the dry combustion method (Nelson and Sommer, 1982) in a NC 2100 soil analyzer

(ThermoQuest CE Instruments, Milan, Italy). For soil samples with pH< 8.5, total soil

C was assumed to be SOC (Bohn and McNeal, 1985). No soil sample in this study had a pH of>8.0 soC and N values obtained by the dry combustion method were assumed to be SOC and SON concentrations, respectively. Pools of SOC and SON were calculated with the product of SOC and SON concentrations, and Pb using Eq.

[1] (Lal et al., 1998). The cation exchange capacity (CEC) was measured using an ammonium acetate extraction followed by emission spectrometry.

Soil pH was determined using a 1:1 ratio of soil to water and a pH meter. 93 1 3 4 2 1 Mg C (N) ha" =[% C (N) x corrected Pb (Mg m- ) x d (m) x 10 m ha- ]/ 100

[Eq. 1]

4.2.3 Statistical Analysis

To determine statistical differences and interactions among systems, depths and soil types for each soil parameter, analysis of variance (ANOVA) tests were conducted. Data arranged in a factorial form were analyzed by using the ANOVA procedure of SAS software (SAS Institute, 2001 ). Significant differences in means and interactions were separated based on F-protected LSD tests at the p:::; 0.05 level.

Duncan's multiple range test was used to separate the mean values (Adesodun et al.,

2001, 2005). Unless otherwise noted, results are for soils combined for the 0-20cm sampling depth. For certain parameters, these depths were combined because of a lack of significant difference.

One-way ANOVA tests were conducted using SAS software to produce the

LSD (0.05) values and test the significance of organic and conventional management treatments for flag leafheight (em), ear leafheight (em), grain yield Mg ha -I, above ground biomass yield Mg ha -I, and the harvest index (SAS, Inc. 2004).

94

4.3.1 Soil Physical Properties

The means according to treatment for the physical parameters MWD, WSA, bulk density, and A WC are all shown in Table 4.1. For MWD, the conventional treatments, control and fertilizer, were significantly higher at the p_:s 0.05 level than the organic treatments, including manure, compost and cover crop. Fallow was also significantly similar to the conventional treatments. The WSA was significantly higher for compost and fallow treatments than the other organic amended plots. They were also statistically similar to the conventional treatments. There were no significant differences in bulk density at the p.:S 0.05 level across years and across treatments.

Available water content (A WC) was significantly higher for the control and manure plots, compost held the least water and fertilizer, fallow and cover cropped plots were all statistically similar.

Physical Treatment MWD WSA 0/o Bulk Density AWC mm (Mglm3) em Control 1.61a 66.5ab 1.3a 10.5a Fertilizer 1.29ab 64.7ab 1.3a 8.8b Fallow 1.72a 71.7a 1.3a 8.5b Cover Crop 0.82b 55.5b 1.3a 9.1ab Manure 1.49ab 67.7ab 1.3a 10.0a Compost 1.5ab 73.5a 1.3a 7.3c LSD 0.7 12.2 0.1 0.6

Table 4.1 Waterman physical property mean comparison for six treatments 0-20cm 2003-2005 Figures followed by same letters in the column are statistically similar at a=0.05. Values for LSD at a=0.05.

96 There were only three parameters, of those tested, which expressed a significant difference according to depth. This was not however, significantly related to treatment or year effect. MWD, WSA and bulk density were all significantly lower at the p<0.05 level in the 0-1 Ocm soil compared to the 10-20cm soil. WSA was much higher in the 10-20cm soil, with a difference of21.2%.

Bulk Del!th MWD WSA% Densitv mm (Mglm3) 0-10cm 1.02b 56.03b 1.2b 10-20cm 1.78a 77.25a 1.3a LSD 0.4 7.0 0.1

Table 4.2 Waterman soil property mean comparison for all treatments by depth 2003- 2005 Figures followed by same letters in the column are statistically similar at 6.=0.05. Values for LSD at 6.=0.05.

4.3.2 Soil Chemical Properties

Chemical parameters are expressed in Table 4.3, along with the means for each treatment and LSD values at the 6.=0.05 level. The pH was lowest across years and depths for fertilizer and manure amended plots. The control plot had the highest pH and fallow, cover crop and compost were statistically similar. Table 4.4 shows the significant drop in pH from 2003 to 2005 after treatments were applied. The SOC concentration was the highest for the cover crop treatment; except for control, the rest of the treatments were statistically similar. The SON concentration was highest for fallow, cover cropped and compost amended plots. Except for the cover crop treatment, all other treatments were statistically similar at the p,:S 0.05 level. The C:N

97 ratio was not significantly different for any of the treatments at the p:S0.05 level, across years and depths. Lastly, the CEC was highest for the fallow, cover crop and compost treatments. The other treatments were statistically similar except for the fertilized plots, which had the lowest CEC.

Chemical Treatment pH SOC Pool SON Pool C:N CEC Mglha Mglha cmol+clkg Control 7.3a 26.5b 2.6b 11.4a 27.3ab Fertilizer 6.6c 29.6ab 2.6b 11.3a 24.8b Fallow 7.0ab 32.1a 2.8ab 11.3a 29.2a Cover Crop 7.0ab 33.8a 3.0a 11.5a 28.7a Manure 6.9bc 29.9ab 2.6b 11.4a 26.5ab Compost 7.2ab 32.0a 2.8ab 11.4a 29.3a LSD 0.3 4.2 0.3 0.3 3.1

Table 4.3 Waterman chemical property mean comparison for six treatments 0-20cm 2003-2005 Figures followed by same letters in the column are statistically similar at 6:=0.05. Values for LSD at 6:=0.05.

SOC, C:N, CEC and pH, were significantly different among years (Table

4.4)._None of these parameters had a significant relationship between management type and year, except for the SOC. Before any treatments were applied, the plots where organic amendments would be spread had a significantly higher level of SOC than the plots where conventional amendments would be applied. But after two years of treatments, the organic plots actually lost SOC and the conventional plots significantly increased at the p:S0.05 level for 0-20cm. C:N significantly increased across plots and depths over the two years but CEC and pH significantly declined after treatments. 98 System pH SOC Pool C:N CEC Mg/ha cmol+clkg 2003 7.3a 11.2b 29.3a Organic 31.2a Conventional 28.0b 2005 6.8b 11.6a 26.0b Organic 30.7b Conventional 32.6a LSD 0.17 0.18 0.18 0.18

Table 4.4 Waterman soil property mean comparison for all treatments according to year {0-20cm depth) Figures followed by same letters in the column are statistically similar at 6.=0.05. Values for LSD at 6.=0.05.

Table 4.5 shows the synthetic fertilizer plots had the highest biomass yield and grain yield compared to all other treatments for 2004 and 2005. The control plots had the second highest biomass yield, due to the fact they were also treated with

Roundup™ and were not threatened by increased weed populations but the manure plots had the second highest grain yield, even with no herbicide treatment. Overall, the manure plots had the highest harvest index % among all the treatments. The fertilizer and manure plots also had the comparatively tallest plants.

99 Bio Gr. Treatment Flag Ear Yield Yield HI em em Mg/ha Mglha % Control 118.5b 39.5b 4.0b 3.6b 47ab Fertilizer 139.9a 51.5a 6.7a 5.9a 46b Cover Crop 100.2c 37.9b 2.9b 3.5b 50ab Manure 120.9b 53.0a 3.1b 3.7b 52a Com~ost 100.6c 36.5b 3.3b 3.1b 48ab LSD 14.5 10.8 1.5 1.4 0.05

Table 4.5 Crop yield and biometric parameters for six treatments (2004-2005) Figures followed by same letters in the column are statistically similar at 11=0.05. Values for LSD at 11=0.05.

The soil quality index shown in Table 4.6 is based on the rating scale used in

R. Lal, (1994). This index assigns a soil quality rating for different levels of each parameter. These are based on the critical levels, informed by the potentials and constraints of each resource, the available data base for the soil being tested, and the intended land use (Lal, 1994). The higher the rating for each treatment, the lower the quality of the soil. The critical levels range from 1 to 5, from no limitation to extreme limitation expressed in the soil. If best management techniques are not adopted at the critical level 1, soil degradation will proceed until crop production and sustainability ofthe system is affected (Lal, 1994).

Table 4.6 gives the soil quality ratings for each of the treatments over 2 years and from a 0-20cm depth. The fallow and the compost treatments received the highest rating, almost twice that of the manure and fertilizer plots. This means they are the most susceptible to soil degradation or production limitations. The fallow plot received no amendments for the two years and although the compost plot received tannin bark treatment for both years, it still has the same rating. The fertilizer and 100 manure plots have the lowest rating, which means they have comparatively higher soil quality than the rest of the treatments. The control and cover crop plots are just slightly higher on the rating scale than the manure and fertilizer treatments.

Soil Quality Index Treatment MWD WSA% Bulk Density AWC pH soc CEC Total em % %of Control 3 2 2 3 2 3 2 17 Fertilizer 3 2 2 3 1 3 2 16 Fallow 3 2 2 3 1 3 2 16 Cover Crop 4 2 2 3 1 3 2 17 Manure 3 2 2 3 1 3 2 16 Com~ost 3 2 2 4 2 3 2 18

Table 4.6 Soil quality index for Waterman soil parameters according to treatment Values for each parameter are assigned according to R. Lal ( 1994). The larger the values, the lower soil quality.

Table 4. 7 shows a correlation between grain yield and soil quality rating among the six treatments. Over the two years of the experiment the fertilizer and manure treatments had the highest grain yields and also received the best soil quality ratings compared to the other treatments. The tannin bark compost treatment had the lowest grain yield and the worst soil quality rating among treatments.

101 Treatment Grain SQI Plot Yield rating Control 3.6 17 Fertilizer 5.9 16 Cover Crop 3.5 17 Manure 3.7 16 Com~ost 3.1 18

Table 4.7 Soil quality rating and crop yield (2004-2005) comparison for Waterman Values for each parameter are assigned according toR. Lal (1994). The larger the values, the lower soil quality.

CONCLUSIONS

During a two year study of soil quality under various management treatments, only ephemeral and some intermediate soil quality indicators can be examined.

Especially when concerning organic treatments, which often experience a "lag period" or "learning curve", more time is needed to measure the full effect of these treatments on soil quality (Brumfield et al., 2000, MacRae et al., 1993, DeBach, 1990 ). Organic and conventional management treatments were similar in their effect on the soil quality indicators measured, therefore the hypothesis that soil quality would increase under organic methods was not proven. There did seem to be a correlation between crop yield over the two years sampled, and soil quality rating. Conventional fertilizer and manure had the best soil quality ratings and also the highest crop yields, while the compost treatment had the worst soil quality and also lowest crop yield among the treatments. These correlations were not statistically significant, however.

Conventional fertilizer and dairy manure had the best soil quality ratings according to the index used (Lal, 1994). Min et al. (2003) also reported similar results 102 with the application of dairy manure. Over a long-term study of conventional fertilizer and dairy manure application on an alfalfa orchard grass system, dairy manure enhanced soil quality in the form of SOC, aggregate stability, and microbial biomass.

Although, the conventional treatment did not build soil quality and actually decreased

WSA and SOC pool. This contradicts the results of this experiment but the Min et al. study was conducted over a long period of time, as opposed to this two-year time span.

Shepherd et al. (2002) conducted a study of over 90 fields, comparing farm systems and conventional and organic management practices. Their data supported the hypothesis that organic systems tended to increase SOM in the soil and therefore had a greater potential for structural improvements in soil than conventional systems.

Those findings contradict the similarity found in this study between organic and conventional methods pertaining to soil structure.

Overall, the data from this study can be coupled with findings from long-term experiments to better understand the connection between organic management practices and soil quality. Soil quality indexes are a useful and integral tool for assessing these relationships.

103 LIST OF REFERENCES

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Adesodun, J.K., J.S.C. Mbagwu and N. Oti. 2005. Distribution of carbon, nitrogen and phosphorous in water stable aggregates of an organic waste amended Ultisol in southern Nigeria. Biosource Tech. 96: 509-516.

Beuerlein, J., J. Johnson, M. Loux, J. Street, M. Sulc and P. Thomison. 1995 The Ohio State University Extension Agronomy Guide 13th edition. Ohio State University. Columbus, OH.

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105 CHAPTERS

CONCLUSIONS

Soil quality is defined as a specific soil's capacity to function, within a certain ecosystem, to sustain biological productivity, store and recycle water, nutrients, and energy and, ultimately, maintain environmental quality. Although organic crops are produced without conventional pesticides and synthetic fertilizers, and their systems rely on crop rotations, crop residues, manures, and legumes, to build nutrients in the soil, this study did not find a significant difference in soil quality of organic compared to conventional farming methods.

The hypothesis that crop yield would be higher in conventionally managed farms was proven in this study. Overall (across years), conventional farms produced the highest yields. These findings agree with the results of many previous studies. In

2004, the oldest organic farm had higher grain yields than two of the conventional farms, but that farm produced significantly lower yields the following year, which resulted in the higher overall grain yield average for conventional farms.

The hypothesis that soil quality would increase under organic farming practices compared to conventional farming practices was not proven. Although one organic farm had the best soil quality rating the other two had the worst quality

106 ratings. There seemed to be no trend across management practices as far as soil quality is concerned. The second hypothesis, that crop yield would be strongly correlated with soil quality was also not proven. Crop yield was weakly correlated with the soil quality index rating for each farm, but this trend did not extend across the board. Two of the conventional farms that had the highest yields also had good soil quality ratings and the two organic farms with the worst yields showed low soil quality rating. The exception to this trend was the Blount silt loam organic farm, which had mid-range crop yields compared to the other farms, but the best soil quality rating.

Soil quality, according to the parameters measured, was similar for organic and conventional farms. The observed increase in these parameters for organic farming in other studies was not reflected in this experiment. The lower levels of SOC, SON pool and CEC in organic farms may be due to increased tillage used for weed control.

Organic farming uses both tillage and cover crop rotations to suppress weeds. These farms may be tilling their soils more often than the conventional farms that usually till once a year. This increased tillage can result in mineralization of organic matter and ultimate loss of nutrients form the soil, especially C. The Blount silt loam organic farm had very similar levels of SOC and SON concentrations to the conventional farm on the same soil type. This organic farm also was the only farm to have higher WSA% than the conventional farm counterpart. From the background information, it is revealed that this farm relies on a very intricate crop rotation and green manure application (as outlined in chapter 2). Perhaps, the use of complex crop rotations instead of heavy reliance on tillage to suppress weeds in organic farming, could

107 improve soil quality, especially with nutrient levels. More study would need to be conducted in order to investigate the relationship of crop rotation versus tillage weed suppression in organic farms with soil quality.

In the Waterman study, organic and conventional management treatments were similar in their effect on the soil quality indicators measured, therefore the hypothesis that soil quality would increase under organic methods was not proven. There was a weak correlation between crop yield over the two years sampled, and soil quality rating. Conventional fertilizer and manure had the best soil quality ratings and also the highest crop yields, while the compost treatment had the worst soil quality and also lowest crop yield among the treatments. These correlations were not statistically significant, however.

The soil quality index used for this study was originally designed for tropical soils. This farm survey was conducted on temperate soils and, therefore, the index used could have been better adapted to the specific soils studied. This difference could have had an impact on the overall findings of the study. Also, the organic and synthetic inputs for the 6 sampled farms were not tested for C:N or other nutrients.

With this background, stronger correlations between soil quality and the specific measured parameters may occur. However, only a select number of soil quality indicators were tested for this study but there are many more that could have been assessed. One important parameter that could be measured in future studies is plant available N. If tested, a stronger correlation may be observed between soil quality and management systems.

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