The Effects of Different Soil Amendments on Fertility and Productivity in Organic

Farming Systems

A thesis presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Master of Science

Scott E. Fisher

November 2011

This thesis titled

The Effects of Different Soil Amendments on Fertility and Productivity in Organic

Farming Systems

SCOTT E. FISHER

has been approved for

the Program of Environmental Studies

and the College of Arts and Sciences by

Jared L. DeForest

Assistant Professor of Environmental and Plant Biology

Howard Dewald

Interim Dean, College of Arts and Sciences 3

ABSTRACT

FISHER, SCOTT E, M.S., November 2011, Environmental Studies

The Effects of Different Soil Amendments on Fertility and Productivity in Organic

Farming Systems

Director of Thesis: Jared L. DeForest

Productivity and soil fertility are two of the most important factors in farming.

Many organic farmers fertilize their crops with composted plant or animal waste. Some organic farmers who do not have access to large amounts of compost utilize processed fertilizers that are acceptable under certified organic standards. I hypothesized that soils fertilized with composted organic matter would be more fertile and productive than soils fertilized with processed organic fertilizer. To test the hypotheses, I measured nutrient content and availability at three organic farms, each of which uses a different type of fertilizer (animal manure, composted mushroom growing medium, and processed fertilizer). I also grew beans (Phaseolus vulgaris) in soil from each of the farms to measure bean weight as an estimate of productivity. The soil amended with animal manure was the only treatment that resulted in increases in nutrients, nutrient holding capacity, and bean weight. Soils amended with processed fertilizer showed little difference from controls.

Approved: ______

Jared L. DeForest

Assistant Professor of Environmental and Plant Biology 4

ACKNOWLEDGMENTS

I would like to sincerely thank my advisor, Dr. Jared L. DeForest, for providing the guidance I needed to complete this project; the Department of Plant Biology for providing me with funding for the entire duration of my time in graduate school; Green

Edge Gardens, Shade River Organic Farm, and Sassafras Farm, for providing me with valuable information and significant quantities of organic farm soil; Art Trese and Harold

Blazier, who assisted in the design and implementation of the garden experiment; my committee members for their time and input; and my family, for supporting me throughout this process.

TABLE OF CONTENTS

Page

Abstract ...... 3 Acknowledgments...... 4 List of Tables ...... 6 List of Figures ...... 7 Chapter 1: Introduction ...... 8 Chapter 2: Materials and Methods ...... 20 Chapter 3: Results ...... 29 Chapter 4: Discussion ...... 46 Chapter 5: Sustainability and the Organic Philosophy ...... 52 Chapter 6: Future Research ...... 54 Chapter 7: Conclusion...... 55 Works Cited ...... 58

LIST OF TABLES

Page

Table 1: Percent Differences for Bean Measurements ………………………………. 31

Table 2: Raw Means for Bean Measurements ……………………………………….. 33

Table 3: Percent Differences for Soil Fertility Measurements ………………………. 35

Table 4: Raw Means for Soil Fertility Measurements ……………………………….. 36

Table 5: Basic Properties of Native Farm Soils …………………………………….... 40

Table 6: Nutrient Content of Organic Fertilizers …………………………………….. 40

Table 7: Percent Differences for Microbial Measurements ………………………….. 44

Table 8: Raw Means for Microbial Measurements …………………………………... 45

LIST OF FIGURES

Page

Figure 1: Location of Farms ...... 21

Figure 2: Layout of Common Garden Experiment ...... 23

Figure 3: Photograph of Common Garden Experiment ...... 24

Figure 4: Dry Bean Weight ...... 29

Figure 5: Average Number of Beans per Plant ...... 30

Figure 6: Plant Dry Weight ...... 30

Figure 7: Measurements of Bean Growth ...... 32

Figure 8: Total Soil Carbon ...... 34

Figure 9: Nutrient Holding Capacity ...... 34

Figure 10: Nitrogen, Phosphorus, and Potassium Content ...... 37

Figure 11: Calcium, Magnesium, and Sulfur Content ...... 38

Figure 12: pH, Electrical Conductivity, and Carbon/Nitrogen Ratios ...... 39

Figure 13: Bacterial/Fungal Ratios ...... 41

Figure 14: Measurements for Soil Microbes ...... 42

Figure 15: Nitrogen Mineralization and Nitrification ...... 43

CHAPTER 1: INTRODUCTION

Persistent public concern over the potential danger of chemicals in the environment and in the food supply has considerably increased the demand for organically produced commodities over the last decade (USDA, 2010). The implementation of national standards for organic certification in 2002 played a major role in establishing a market for commodities produced without synthetic chemicals. The soaring demand for organic products is evident when examining the recent growth rate of the organic foods market; retail sales have increased from $3.6 billion in 1997 to $21.1 billion in 2008 (USDA, 2010), and the number of certified organic acres has increased from less than one million acres in 1992, to nearly five million in 2008, and yet supply still falls short of demand (USDA, 2010). Accordingly, crop productivity on organic farms is an issue that is important to organic farmers and consumers alike.

Consumers are motivated to choose organically grown commodities over conventional products for a variety of reasons. A 2001 survey showed that the public perceives certified organic produce as safer (containing less pesticide residue) than conventionally grown produce (Williams & Hammitt, 2001). Research conducted by the

USDA indicated that organic produce typically contains significantly fewer pesticides than conventional produce, and is less likely to contain residues from multiple pesticides

(Gold, 2008). Additionally, data collected by the USDA and the Food and Drug

Administration (FDA) from samples of conventional produce confirmed 13 different pesticides on a single fruit or vegetable, an average of two to four different pesticides on 9 a single fruit or vegetable, and a total of 52 different pesticides were detected on all commodities tested, some of which were unapproved by the Environmental Protection

Agency (EWG, 2010).

Another popular assumption is that organically grown crops are more nutritious than crops grown conventionally (Williams & Hammitt, 2001). This is largely based on the basic ideology that organic farming practices are more „natural‟, and therefore produce healthier foods. There are, however, scientific facts that support this theory

(comparisons of nutritional values in this paper are based on concentrations of protein, fiber, vitamins, minerals, or polyphenolic antioxidants; Reganold et al., 2010). Because most OM contains a much broader spectrum of nutrients than most synthetic fertilizers

(which primarily contain N, P, and K), it is reasonable to assume that organically grown crops would contain a wider variety of nutrients than conventional crops. In order to determine scientifically whether organically grown foods are truly more nutritious than crops grown conventionally, numerous experiments have been conducted comparing nutritional values of crops grown in each system. In the past decade, eight of the ten reviews of literature comparing the nutrition of organic and conventional produce found some evidence that organic foods are more nutritious (Reganold et al., 2010). According to a review of the literature by the USDA, organic foods generally have higher trace mineral content, vitamin C, and antioxidants (Gold, 2008). Most recently, Reganold et al. (2010) compared the nutritional content of strawberries grown on pairs of adjacent fields (one organic and one conventional). Similar to previous studies, the results showed that organically grown strawberries were significantly higher in vitamin C, total 10 antioxidant activity, and total phenolics than strawberries that were conventionally grown

(Reganold et al., 2010). While it has been reasonably established that organic produce is more nutritious than conventionally grown crops (for certain parameters), there has been little research comparing the effects of different types of organic amendments on the nutrient content of produce, despite considerable interest in the subject. When asked to prioritize a list of topics according to degree of importance in the Third Biennial National

Organic Farmers‟ Survey, organic farmers ranked, “the relationship between organic growing practices and the nutritional value of food”, third out of thirty-two categories

(Walz, 1999).

Most consumers of organic products also believe that organic farmers employ sustainable methods that conserve soil and water resources (Reganold et al., 1990).

While this may be the case on small organic farms (less than ten acres) that fertilize contained beds, many medium-to-large scale organic farms are unable to acquire sufficient amounts of organic matter to adequately fertilize large open fields. These large organic farms rely on heavy tilling and processed organic fertilizers to increase soil fertility (Walz, 2004). Similar to synthetic fertilizers, processed fertilizers are extremely low in carbon. Consequently, heavy reliance on processed fertilizers will result in low

SOM. Without adequate SOM, organic farms may ultimately experience the same predicament that most conventional farms are now facing, such as infertility, severe erosion, nutrient leaching, poor water-holding capacity, and reduced productivity

(Reganold et al., 1987). Although the public understands that organic farming is generally friendlier to the environment than conventional farming, the distinction 11 between large-scale organic farms and small-scale organic farms, in regards to environmentally sustainability, is unclear. In order for organic farms to become truly sustainable systems, certified organic standards must require farmers to use fertilizers that contribute to soil organic matter. The potential consequences of different amendment strategies for certified organic farming systems will be discussed in terms of soil fertility and sustainability in the paragraphs to follow.

Organic farming is defined as an agricultural system, “…that promotes and enhances biodiversity, biological cycles and soil biological activity…” (USDA, 2007).

One of the primary methods by which organic farmers attempt to achieve these goals is by increasing the amount of organic matter (OM) in the soil. Fresh or composted OM is applied to the soil, decomposed by soil microorganisms, and nutrients are released for plant uptake. Ultimately, OM is transformed into a relatively stable substance known as humus, or soil organic matter (SOM; Wolf & Snyder, 2003). Increasing SOM reduces erosion, buffers soil pH, conserves water, improves soil structure, supports soil microorganisms necessary for important soil processes, provides essential plant nutrients, and increases the availability of plant nutrients (Troeh & Thompson, 2005). In short, soils with higher SOM levels are more fertile than those with low SOM.

According to certified organic standards, the use of synthetic fertilizers is prohibited (USDA, 2007); accordingly, OM is important in organic farming as a source of plant nutrients. Ironically, some of the restrictions imposed by organic standards actually make it more difficult for organic farmers to increase SOM. For example, organic farmers may only purchase cover-crop seed that is certified organic, which is 12 often twice the price of conventionally grown seed. Additionally, fields must be taken out of production for a number of years in order to increase SOM levels with cover-crops

(Fronning et al., 2008), which may be cost prohibitive, especially when it is necessary to supplement cover-cropped fields with additional fertilizer. Animal manure is a cheaper alternative to cover-cropping, and is the primary soil amendment for many organic farmers. However, certified organic regulations mandate specific composting procedures and testing requirements, and restrict the timing of application; consequently, animal manure is not a practical source of OM for some farmers (USDA, 2007).

Increasing SOM is a difficult task (even without restrictions posed by organic standards) because of the large amounts of OM required to produce even small increases in SOM. For example, Wolf and Snyder (2003) estimate that 25 tons/acre of dry matter are required to increase SOM levels by one percent. The reason that SOM levels are so difficult to increase is because 65% of organic C is mineralized to carbon dioxide (CO2), usually within a few months of application (Wolf & Snyder, 2003). After subtracting water weight, one ton (2,000 lbs) of manure will yield approximately 616 lbs of C for dry manure and only 157.5 lbs for wet manure. In soils that are low in OM to begin with, it is especially difficult to increase SOM levels to a point of equilibrium for agricultural systems. For example, soils in Southeastern Ohio usually contain less than 2 % carbon

(NRCS, 2010), which means that a farmer would need to add approximately 75 tons of dry OM per acre to raise the soil carbon level by 3 % (5 % C is considered favorable for agricultural soils; Wolf & Snyder, 2003). 13

Because of the large volume of organic inputs required to build SOM, farmers often amend their soil with whatever is available in large quantities, at minimal cost

(Walz, 2004). However, the composition of OM varies depending on the source; therefore, some forms of OM are more effective for building SOM, increasing N, or stimulating microbial activity (Stark et al., 2006). For example, horse manure usually contains the full spectrum of plant nutrients, and is useful for building SOM levels as well (Simpson, 1986). On average, horse manure contains moderate amounts of plant macronutrients nitrogen (N) and potassium (K), and minimal amounts of phosphorus (P)

(Simpson, 1986). Calcium (Ca), sulfur (S) (Troeh & Thompson, 2005), and micronutrients including manganese (Mn), copper (Cu), boron (B), iron (Fe), zinc (Zn), molybdenum (Mo), and cobalt (Co) are also commonly found in manure (Wolf &

Snyder, 2003). However, one of the major disadvantages of manure is the considerable loss of nutrients through volatilization and leaching if not handled properly (Troeh &

Thompson, 2005). Because all OM is not created equal, the potential for limitations to one or more important soil properties at a farm that applies OM from one primary source

(e.g. animal manure) is great. Accordingly, the productivity and nutritional quality of crops grown in soil amended with different types of OM may vary as well.

Most organic farms are not capable of producing the necessary amounts of compost to increase SOM levels, and therefore must import OM from off the farm.

According to the Third Biennial National Organic Farmers‟ Survey, 65 % of the respondents who fertilized with manure stated that they obtained their manure from sources off the farm; 40 % of the respondents who used compost said they obtained all of 14 their finished compost from off of the farm, with 8% travelling more than 100 miles to get it (Walz, 2004).

Because of the difficulty in acquiring and transporting large quantities of OM, the relatively low nutrient content of OM, and the fact that nutrients are removed with each harvest, it is often impossible to provide adequate plant nutrients with OM alone. For example, 2000 lbs of manure contains roughly the same amounts of N, P, and K as a 50 lb bag of 20-5-20 synthetic mineral fertilizer (Wolf & Snyder, 2003); bear in mind, however, that a bag of synthetic fertilizer contains an insignificant amount of carbon.

Wet manure averages only 0.5% N, and therefore must be applied at rates between 4-10 tons/acre to supply enough N for growing crops (Troeh & Thompson, 2005); composted manure contains even less available N (Simpson, 1986). Additionally, only about 30% of the N, 50% of the P (P2O5), and 60% of the K (K2O) is available to crops the first year after application (Simpson, 1986), which means that large amounts of manure need to be applied annually for a number of years before adequate amounts of nutrients are available to plants.

Instead of transporting massive quantities of organic matter to the farm, many organic farmers often supplement OM additions with processed organic fertilizers (POF), such as ReVitaTM Pro 5-4-5, or mined fertilizers, such as rock phosphate, to overcome nutrient deficiencies (Walz, 2004). In instances where it is not logistically feasible to provide any considerable portion of plant nutrients from OM, organic farmers must rely exclusively on POF. The problem with this practice is that using only POF will not increase SOM and can actually accelerate SOM loss (Birkhofer, et al., 2008), resulting in 15 poor soil structure and low nutrient holding capacity. While POF‟s such as ReVitaTM Pro

5-4-5 contain more carbon than synthetic fertilizers, and more nutrients per lb than manure, the amount of ReVitaTM Pro 5-4-5 required to increase carbon levels would be prohibitively expensive. For example, 400 lbs of ReVitaTM Pro 5-4-5 contains roughly the same amount of nutrients as one ton of manure, yet it would take approximately 3080 lbs of ReVitaTM Pro 5-4-5 to get the same amount of carbon contained in one ton of manure. In order to increase SOM levels by 1%, it would require approximately 39 tons of ReVitaTM Pro 5-4-5 per acre, at a cost of $18,095 per acre. This is admittedly a dramatic example which would be extremely excessive in terms of nutrient loads (the recommended application rate for ReVitaTM Pro 5-4-5 is 250-300 lbs per acre); nonetheless, it illustrates the point that adding organic C to the soil with ReVitaTM Pro 5-

4-5 is not feasible. It costs roughly $70 per acre to meet crop nutritional needs using

ReVitaTM Pro 5-4-5 (excluding transportation), which is comparable to what conventional farmers spend on synthetic fertilizer, yet it is acceptable under USDA organic standards.

However, when considering the benefit of adding carbon to the soil when applying OM, and that OM can be obtained for free (plus the cost of transporting), it is clear that the only scenario where it makes sense to rely primarily on POF is when the farmer does not have access to large quantities of OM. Although it may be the only short-term option for some organic farmers, dependence on processed fertilizers is not economically or environmentally sustainable (Wolf & Snyder, 2003).

SOM and nutrient levels are not the only important metrics of soil fertility in farm soils. Microbial activity in the soil drives soil processes such as nutrient cycling and 16 decomposition, and is closely linked to soil fertility (Zelles, 1999). In other words, the potential of OM as an effective soil amendment is dependent on the activity of soil microbes. Mineralization, the conversion of organic N, P, and S into plant-available forms, involves a complex web of interactions between microbes. Put simply, bacteria, fungi, and actinomycetes decompose OM for energy and maintenance, which are then consumed by predatory microbes (e.g. protozoa) and excreted, releasing available N, P, and S (Alexander, 1991). The degree to which a particular form of OM is suitable for microbial growth is largely dependent on the ratio of C to N. Ratios of C to N greater than 32 typically result in slowed decomposition and a reduction of available N (N- immobilization; Troeh & Thompson, 2005). Nitrogen-immobilization happens when the relative increase in C (food for microbes) increases the demand for N, which microbes take from the soil into their bodies to build tissue and produce enzymes. The N consumed by the microbes is then temporarily unavailable for plant uptake. If OM with a large CN ratio is applied and microbes cannot obtain sufficient N from the soil for microbial growth, decomposition is suppressed.

However, N requirements differ among soil organisms. For example, bacteria require relatively large amounts of N in comparison to fungi (Paul & Clark, 1989).

Consequently, quantities of available N, P and S, either immobilized or released, are determined by the nutrient demands of the microbes present, as well as the ratio of these elements to C (Wolf & Snyder, 2003). Conversely, the release of nutrients such as K, Ca, and Mg is essentially dependent on the concentration of these elements in OM (Wolf &

Snyder, 2003), and not on the activity of microbes. Ratios of C to N, P, and S and 17 quantities of K, Ca, Mg, and other nutrients vary significantly depending on the source of

OM (Simpson, 1986).

The functional roles and interrelationships of microbes within the soil ecosystem are poorly understood (Davet, 2004). Determining the effects of various types of OM additions on microbial community composition and nutrient availability may improve the effective use of different sources of OM as fertilizer for agricultural soils. Documenting the differences in ratios of microbial guilds (e.g. fungi/bacteria) and total microbial biomass, found in soils amended with different types of organic fertilizer will contribute to the understanding of soil microbial communities as indicators of soil fertility in agricultural soils. In an effort to better understand the consequences of applying different types of organic fertilizers, the objectives of this project were to:

1) Assess the effects of different soil amendments on crop productivity and

protein content for beans grown in amended and unamended soil from

each farm;

2) Establish the influence of different amendment types on soil quality

using standard metrics of soil fertility, and;

3) Identify differences in microbial community composition and microbial

biomass between three different SOM treatments using PLFA analysis.

I hypothesized that:

1) The soils amended with composted manure or mushroom medium

would produce greater bean weights on average than soils fertilized

with processed fertilizer;

2) The exclusive application of processed organic fertilizer will have little

effect nutrient holding capacity;

3) Beans grown in soils amended with composted OM would have higher

protein content than those grown in soils amended with processed

fertilizer;

4) The soils amended with composted manure or mushroom medium

would have higher soil microbial biomass than soils amended with

processed organic fertilizer (because of larger inputs of OM);

5) Dominant microbial guilds would be different for the compost

treatments when compared to the processed treatment.

To test the hypotheses, bean plants (Phaseolus vulgaris) were grown in soil from each of the farms and weighed to compare plant productivity between the different treatments. Beans were also analyzed for total N, which was converted to protein content for each treatment (Merrill & Watt, 1973). Bean plants were chosen because they are common, can be harvested in a short period of time, and can be grown in a relatively small amount of soil per plant. Standard metrics of soil fertility were measured to determine the effects of the different amendments on soil fertility. Microbial parameters were measured using 1) phospholipid fatty-acid analysis (PLFA), acknowledged as an effective method for determining relative microbial community structure and biomass

(Zelles, 1999) and 2) net N mineralization and nitrification, which are considered to be standard gauges of microbial activity and N availability in agricultural soils (Troeh &

Thompson, 2005).

CHAPTER 2: MATERIALS AND METHODS

Study Sites

Study sites are located on three different farms in the unglaciated Allegheny

Plateau of Southeast Ohio (Figure 1). Average annual rainfall for the area is 100.6 cm, mean temperature is 13.3 °C, and the average growing season lasts 150 days (NOAA,

2011). The study sites include three farms that employ three different amendment strategies. Farm A is a small, chemical-free farm located on a ridge top (39°21‟57.48” N,

82°15‟22.35” W). The soil is classified as fine, mixed, mesic Typic Hapludalf , Upshur series (NRCS, 2010). These soils are highly eroded, and are described as having „severe limitations‟ for crop production due to poor soil quality (NRCS, 2010). Composted horse manure is the primary nutrient source, and has been applied to the sampled raised beds of

Farm A for the past 30 years. ReVita Pro 5-4-5TM, a processed organic fertilizer, is applied sparingly approximately every other year to supplement the manure compost.

Farm B (39°14‟54.01” N, 82°01‟12.10” W) is a certified organic farm located on soils classified as silty clay loam, Typic Hapludalf, Upshur series (NRCS, 2010), adjacent to a river. The ten-acre field from which samples were taken has been fertilized annually with four to five tons of ReVita Pro 5-4-5TM, and one to two tons of both Greensand and

Rock Phosphate (or CalphosTM) for 25 years. ReVita Pro 5-4-5TM is a dried, pelletized organic fertilizer which contains composted poultry manure as the primary ingredient, and also contains humate, feathermeal, and kelp. Farm C is also certified organic, and is located in a valley (39°25‟03.42” N, 81°58‟42.15” W), on soil classified as silt loam,

Dystric Fluventic Eutrochrept, Nolin series (NRCS, 2010). Peat moss and pea gravel 21 were incorporated into the soil when the greenhouse beds were first established approximately seven years ago. Compost made from spent mushroom growing medium is applied annually. The mushroom medium consists primarily of cotton seed hulls and oak sawdust; cereal grains, bran, and chalk (CaCO3) are also incorporated. Farm C supplements OM additions with minimal applications of ReVita Pro 5-4-5TM fertilizer.

Figure 1. Location of Farms A (brown manure), B (processed), and C (green manure) in S.E. Ohio.

Soil Samples

Samples were collected from the three farms in early July, before peak soil dryness (Dyer, 2002). Six soil cores, 15 cm deep x 2 cm diameter wide, were collected randomly within each of the six plots on amended and six plots of uncultivated, unamended areas on each farm, and kept in a cooler with ice packs until they were 22 refrigerated. Six bags of amended soil and six bags of unamended soil were collected from each of the three farms for chemical analysis. Six additional cores (three amended and three unamended), 1425 cm3 each, were taken from each farm to measure bulk density.

Three samples of fertilizer (170 cm3 each of manure, composted mushroom growing medium, or ReVita TM) were collected from each farm for chemical analysis as well. Sampled plots on each farm were equivalent in size, and the arrangement of the plots was specific to the unique layout of each farm. All soil (excluding the bulk density samples) was sieved to 2 mm and homogenized before analysis. All values for soil analysis procedures were calculated using oven-dry weight for soil samples. Five grams of soil was taken from each bag for PLFA analysis and frozen on the day of collection.

Common Garden Experiment

Approximately 15 gallons of amended soil and 15 gallons of unamended and uncultivated soil was taken from each of the 3 farms in June and stored at 5°C in sealed

5-gallon buckets until it was used. One and one-half gallon pots were used to grow Blue

Lake 247 (bush-type) bean (Phaseolus vulgaris) plants in replications of 15 for each treatment (amended or unamended farm soil; Figures 2, 3). Soil for each treatment was mixed with medium-grade perlite at a 1:1 ratio to minimize problems of compaction and poor drainage that can result from potting field soil. Pots were elevated from the ground to discourage root growth out of the bottom of the pot, and were watered (uniformly) as needed to maintain adequate moisture levels. Each bean plant was fertilized with a top- 23 dressing of ½ teaspoon ReVita 3-3-3 Compost PlusTM organic fertilizer to simulate field conditions of the sampled farms, and to provide plants with essential nutrients. Once beans matured, they were harvested at once, counted, and weighed. Beans were oven- dried in paper bags at 65°C and weighed again to determine oven-dry weight. Oven- dried beans were ground and analyzed for total nitrogen on a CN analyzer and multiplied by a conversion factor of 6.25 to compare total protein content among the three treatments (Merrill & Watt, 1973). Bean plants were cut at the soil line before senescence, weighed, oven-dried, and weighed again to determine dry weights and plant biomass as a measurement of soil productivity. Plant roots were cleaned, inspected for nodules, oven-dried at 65°C, and weighed. Root/shoot ratios were calculated by dividing root biomass by shoot biomass.

Figure 2. Bean plants were grown in soil from each farm in replicates of 15 to compare productivity between farms. Unfertilized/uncultivated soil was collected from each farm for controls.

Figure 3. Photograph of the common garden experiment taken at the OU greenhouse.

Physico-Chemical Analysis

The six soil cores collected to determine bulk density were oven-dried at 105°C for approximately 48 hours and then weighed. Bulk density (Db) was calculated by dividing the weight of oven-dried soil by the soil core volume (Robertson et al., 1999).

Soil texture (% sand/silt/clay) was calculated using the hydrometer method. First, 20 g of air dried, sieved soil was added to 100 ml of dispersing agent and placed on an orbital shaker overnight. Samples were further homogenized in a blender before hydrometer readings were taken. Hydrometer readings were recorded two more times; 30 minutes after the initial reading, and 24 hours after the initial reading. Blank readings were taken 25 of distilled water with dispersing agent to be subtracted from the initial reading to calculate % sand. Percent clay was calculated using the equation described by Robertson et al. (1999): P2μm = [m x ln(2/X24)] + 24. The sum of % clay and % sand was subtracted from 100 % to calculate % silt.

To measure soil pH, a pH meter was inserted into a slurry consisting of a 1:2 ratio of soil and deionized water. Standard buffer solutions (pH 4, pH 5, and pH 7) were used to calibrate the pH meter. Conductivity was also measured at this time using an electrical conductivity meter. To determine base cations and cation exchange capacity

(CEC), soil samples were extracted with Mehlich III (Robertson et al., 1999) and analyzed on a Thermo Scientific X Series 2© ICPMS (Inductively Coupled Plasma Mass

Spectrometer) to measure concentrations of calcium (Ca), potassium (K), magnesium

(Mg) and sodium (Na). Samples of OM and ReVita were combusted at 600°C prior to extraction to release organically-bound nutrients. CEC was calculated as the sum of base cation charge. Available phosphorus (P) and sulfur (S) were also measured on the

ICPMS (Mehlic III extracted). Total C and N were measured on an Elementar Vario EL©

CN analyzer. Total C measurements indicate organic matter content, which is correlated with CEC. Total N is measured to compare pools of organic and inorganic nitrogen among treatments. To prepare the samples, 10 g of oven-dried soil was pulverized for one minute using an 8000M ball mill. The pulverized soil was encapsulated, weighed to approximately 35 mg (or 4 mg of OM or ReVita), and analyzed. Six samples of beans were randomly selected from each treatment for CN analysis. Within each sample, only beans that were of marketable size (longer than 3 inches/seeds not mature) were selected, 26 to decrease the effect of extremely mature (or immature) beans skewing the CN ratio.

Selected beans were dried, ground, weighed to approximately 4 mg, and encapsulated before analysis.

+ Ammonium (NH4 ) was measured by adding 75 µl sodium salicylate solution and

75 µl bleach solution to 50 µl soil solution consisting of 10 g of soil (or OM or ReVita) extracted with 20 ml 1 M KCl (or added to 50 µl standard solution) in a 96-wellplate and incubated for 50 minutes at 37° C (Miranda et al., 2001). Samples were analyzed on a

- Biotek synergy© with absorbency read at 650 nm. For nitrate (NO3 ) analysis, 10 g field- fresh soil was extracted with 1 M KCl and placed on the shaker for one hour. The soil solution was filtered and transferred into a 96-well plate. 100 µl of a reagent mixture consisting of 2 parts vanadium solution (VCl3), 1 part 2.0 % (w/v) sulfanilamide solution, and 1 part 0.1% (w/v) NEDD solution was combined with 100 µl soil solution

(or standard), incubated for one hour at 37°C, and analyzed on a Biotek synergy© with

+ absorbency read at 540 nm (Miranda et al., 2001). To determine N mineralization, NH4

- and NO3 were measured on soil samples incubated at room temperature for 14 days.

+ - + The NH4 and NO3 data from the refrigerated soil samples were subtracted from NH4

- and NO3 measured on incubated samples to calculate net N mineralization. Net

- nitrification was calculated by subtracting concentrations of NO3 measured in the

- refrigerated soil samples from the concentration of NO3 found in incubated samples

(Miranda et al., 2001).

Biological Analysis

PLFA analysis was conducted in three phases, according to methods described by

DeForest and Scott (2010). In phase one, five grams of freeze-dried soil was extracted using 10 ml methanol, 5 ml chloroform, and 4 ml of phosphate buffer. An internal standard was added at this point to calculate percent recovery after running the samples.

Samples were evaporated in a nitrogen evaporator (N-EVAP) at 37°C for approximately

30 minutes and stored at -20°C. In phase 2, polar lipids were separated from non-polar lipids using silicic acid chromatography (DeForest et al., 2004). The solvent containing polar lipids was evaporated on an N-EVAP for approximately two hours. Finally, in phase 3, polar lipids were methylated using 0.2 M methanolic KOH, yielding fatty-acid methyl esters (FAMEs; Zelles, 1999). The solvent was then placed on an N-EVAP for approximately 15 minutes before running on an HP 6890 GC® (gas chromatograph) for analysis of FAMEs. Peaks were compared to a standard FAME mix to identify PLFA biomarkers. Specific fatty-acid chains were identified according to the magnitude of the peaks. Various fatty-acids indicative of bacteria and fungi were used to calculate the ratio of bacteria to fungi (Frostegård & Bååth, 1996). Microbial biomass was expressed as nmol PLFA C/gram of soil, and calculated by converting the area under each peak to micrograms C using regression analysis, dividing this by the weight of the soil sample, and then adding up the values for each of the biomarkers. The biomass of arbuscular mycorrhizal fungi was calculated as the total nanomoles of 16:1ω5 PLFA C/gram of soil

(Olsson et al., 1999). PLFA was not conducted on OM or ReVita samples.

Statistical Analysis

The Shapiro-Wilk normality test was used to assess whether data were normal.

Non-normal data were transformed logarithmically to help meet assumptions of normality and homogeneous variances. To account for differences in soil types and cultivation practices at the three different farms, a mixed-effects model ANOVA, with soil variables as a function of treatment, was used to find significant differences between treatments and controls for each variable (P = 0.01). All statistics were calculated using

R software.

CHAPTER 3: RESULTS

Bean Productivity

Dry bean weight was significantly higher for the brown treatment (P < 0.01), and lower (but not significant) for the green (P = 0.07) and processed treatments (P = 0.22)

(Figure 4). Plant dry weight was significantly higher for the brown (P < 0.01) and green treatments (P < 0.05), but not for the processed treatment (Figure 6). Both compost treatments showed significant increases in the average number of beans per plant (Figure

5), fresh bean weight per plant, and fresh plant weight (shoot only; P < 0.01; Table 1;

Figure 7). Dry root weight was significantly higher for both compost treatments and significantly lower for the processed treatment (P < 0.01). Nodules were present on all roots, and all roots had approximately the same proportion of nodules. Protein content was not significantly different for any treatment (brown: P = 0.19; green: P = 0.73; processed: P =0.36).

Figure 4. Dry bean weight was significantly higher than controls for the brown treatment (P < 0.01), but not for the other two treatments.

Figure 5. The average number of beans per plant was significantly higher than controls for compost-amended soils (P < 0.01), but not for soils amended with processed fertilizer.

Figure 6. Plant dry weight was significantly higher than controls for the brown (P < 0.01) and green treatments (P < 0.05), but not for the processed treatment.

Table 1

Difference (%) Between Beans Grown In Amended Vs. Unamended/Uncultivated Soil for Each Farm (Figures Are In Bold Where the Difference of Least Squares Means P-values for That Variable Are Significant At P < 0.01; Figures Are In Bold Italics Where P < 0.1)

Brown Green Processed (%) (%) (%) Variable Difference Difference Difference Dry bean weight (g) 45 -14 -14

Fresh bean weight (g) 106 47 11

Number of beans 157 48 -12

Plant dry weight 165 14 3

Plant fresh weight (g) 190 29 -10

Root dry weight (g) 157 44 -34

Shoot/root ratio -4 -10 38

Protein (%) 10 1 -6

% C 0 -1 1

% N 7 2 -5

C/N -7 -3 6

Figure 7. Measurements for (a) bean fresh weight, (b) plant fresh weight, (c) root dry weight, (d) bean protein, and (e) bean carbon for each treatment compared to controls.

Table 2

Raw Means for Common Garden Experiment

Brown Green Processed Variable Control Amended Control Amended Control Amended Bean dry weight (g) 2.72 3.94 5.70 4.88 3.61 3.12

Bean fresh weight (g) 25.42 52.47 36.27 53.21 30.48 33.80

No. of beans 4.20 10.80 6.73 9.93 6.47 5.67

Plant dry weight (g) 4.53 12.00 9.81 11.20 7.14 7.36

Plant fresh weight (g) 17.95 52.08 38.49 49.60 30.83 27.77

Root weight (g) 0.67 1.72 1.02 1.47 1.49 0.99

Shoot/Root ratio 6.88 6.62 8.50 7.66 4.98 6.88

% C 40.51 40.68 40.83 40.08 40.21 40.94

% N 2.64 2.90 2.73 2.75 2.74 2.57

C/N 15.55 14.13 15.18 14.70 14.82 16.12

Protein (%) 16.50 18.10 17.08 17.21 17.11 16.07

Soil and Fertilizer Chemistry

Several of the parameters measured as indicators of soil fertility were significantly higher than the control for both brown and green compost, but not for processed fertilizer (P < 0.01; Table 3). Total C (Figure 8), CEC (Figure 9), total N,

+ - available NH4 , NO3 , Ca, and S were all significantly higher than controls in compost- 34 amended soils (P < 0.01). Soil pH and K increased significantly only in the brown compost treatment (P < 0.01), while Mg increased significantly only in the green and processed treatments (P < 0.01). Total P was significantly higher than the control for all soils (P < 0.01).

Figure 8. Total carbon was significantly (P < 0.01) higher in compost-amended plots, while soils amended with processed fertilizer had significantly lower total carbon.

Figure 9. CEC was significantly (P < 0.01) higher in compost-amended soils, but not in soils amended with processed fertilizer.

Table 3

Difference (%) Between Amended and Unamended/Uncultivated Soil for Each Farm (Figures Are In Bold Where the Difference of Least Squares Means P-values for That Variable Are Significant At P < 0.01; Figures Are In Bold Italics Where P < 0.1)

Brown Green Processed % % % Variable Difference Difference Difference pH 10 4 2

Total Carbon 244 73 -28

Total Nitrogen 129 44 -5

C:N Ratio 43 20 -22

Ammonium 38 37 -31

Nitrate 103 95 -29

Net N Mineralization 16 6 -1

Nitrification 203 -41 206

Calcium 285 65 -2

Magnesium 57 51 43

Potassium 420 -9 -22

Phosphorus 6818 235 110

Sulfur 386 130 1

CEC 379 68 6

Table 4

Raw Means for Measured Soil Parameters

Brown Green Processed Variable Control Amended Control Amended Control Amended pH 6.74 7.40 7.23 7.49 7.46 7.59

% Carbon 1.57 5.40 3.04 5.27 2.78 2.01

% Nitrogen 0.18 0.41 0.29 0.42 0.20 0.19

CN Ratio 9.15 13.12 10.54 12.70 13.71 10.68

Phosphorus (g/m2) 1.25 86.48 34.50 115.70 46.12 96.98

Potassium (g/m2) 22.27 115.80 42.77 38.77 65.30 50.70

Calcium (g/m2) 169.80 653.60 1000.00 1652.00 1025.00 1005.00

Magnesium (g/m2) 41.22 64.57 89.77 135.30 85.97 123.00

CEC (cmolc/kg) 7.92 37.92 34.93 58.65 31.97 33.98

Sulfur (g/m2) 1.22 5.93 5.82 13.40 6.23 6.32

NH4 (mg NX/kg) 4.71 6.52 5.02 6.86 5.00 3.46

NO3 (mg NX/kg) 123.60 250.50 124.90 243.40 147.00 104.30

Figure 10. Measurements of (a) nitrogen, (b) phosphorus, and (c) potassium for each treatment compared to controls.

Figure 11. Measurements for (a) calcium, (b) magnesium, and (c) sulfur for each treatment compared to controls.

Figure 12. Measurements for (a) pH, (b) EC, and (c) CN ratio for each treatment compared to controls.

Table 5

Basic Properties of Native Soil for Each Farm

Bulk Density (g/cm3) % Sand % Clay pH % Carbon Brown 1.05 13.41 43.64 6.7 1.6

Green 1.11 30.11 48.14 7.2 3

Processed 1.25 52.6 27.23 7.5 2.8

Table 6

Approximate Nutrient Contents Of Each Fertilizer; Brown Compost (Manure), Green Compost (Mushroom Medium), and Processed Fertilizer

Variable (%) Brown Green Processed Nitrogen (N) 1.4 1.7 -

Phosphorus (P) 0.4 0.9 -

Potassium (K) 1.4 0.7 -

Carbon (C) 15.6 20.6 20.6

Calcium (Ca) 3.0 5.3 9.3

Magnesium (Mg) 0.4 0.7 0.7

Sulfur (S) 0.4 0.6 0.8

Soil Biology

Bacteria/fungal ratios were significantly higher (P = 0.01) for the manure treatment only (Figure 13). Net N mineralization was significantly higher for both 41 compost treatments (P < 0.01), but not for the processed fertilizer treatment (Table 7)

(Figure 15a). Nitrification, however, was significantly higher than control only in the brown and processed treatments (P < 0.01), and not for green. Biomass measurements for bacteria, fungi, and arbuscular mycorrhizae did not significantly differ from the control for any treatment. However, the brown treatment did significantly (P = 0.09) increase AM biomass by eight percent, while the other two treatments resulted in decreases in AM biomass (Figure 14a). No significant difference from controls was found for total microbial biomass, although it is worth noting that the brown treatment

(manure) showed an increase in total biomass when compared to the control, while green and processed both showed decreases.

Figure 13. Bacterial/Fungal ratio was significantly higher (P < 0.01) than controls for the brown treatment but not for the other two treatments. 42

Figure 14. Measurements for (a) arbuscular mycorrhizal biomass, (b) total biomass, (c) bacterial biomass, and (d) fungal biomass. 43

Figure 15. Measurements for (a) net N-mineralization and (b) net nitrification for each treatment compared to controls.

Table 7

Difference Between Amended and Unamended/Uncultivated Soil for Microbial Communities at Each Farm (Figures Are In Bold Where the Difference of Least Squares Means P-values for Variables That Are Significant At P < 0.01; Figures Are In Bold Italics Where P < 0.1)

Brown Green Processed % % % Variable Difference Difference Difference Total Biomass 17 -8 -15

Fungal Biomass -3 -1 1

Bacterial Biomass 1 2 -4

Bacterial/Fungal Ratio 10 -5 -2

AM Fungi Biomass 8 -7 -5

Table 8

Raw Means for Soil Microbial Data

Brown Green Processed Variable Control Amended Control Amended Control Amended

Bacteria/Fungi (ratio) 1.84 2.02 2.04 1.94 1.99 1.95

AM Fungi (nmol PLFA C/g) 3.26 3.52 3.63 3.37 3.40 3.22

Fungal Biomass (nmol PLFA C/g) 3.98 3.85 4.03 3.99 3.63 3.65

Bacterial Biomass (nmol PLFA C/g) 5.12 5.16 5.12 5.21 5.12 4.89

Total Biomass (nmol PLFA C/g) 313.00 366.30 397.00 365.40 297.00 251.80

Net N Mineralization (mg NX/kg/d) 4.75 5.53 5.29 5.60 5.08 5.01

Nitrification (mg NX/kg/d) -0.63 0.65 1.83 1.08 0.47 1.44

CHAPTER 4: DISCUSSION

Bean Productivity

Significant increases in dry bean weight (45 %) and dry plant weight (165 %) were observed for the brown compost treatment only (P <0.01). This is likely a result of the significantly increased nutrient holding capacity (CEC; P < 0.01) and soil carbon (P <

0.01) in the brown treatments as compared to control (Bauer & Black, 1994). Although there were significant increases in CEC for the green treatment also (P <0.01), there were no significant increases in dry bean weight or dry plant weight. Additionally, the CEC of the brown treatment was 379 % higher than controls, while CEC for the green treatment was only 68 % higher than controls. Increases in nutrient holding capacity can most likely be attributed to the significant increases in SOM (total C) in the compost treatments in comparison to controls (P < 0.01; Brady & Weil, 2008). The significant increase in bean dry weight in the brown treatment is probably a result of the greater increases in CEC and nutrient content observed for the brown treatment in comparison to the green treatment. For example, percent differences between amended and controls for the major plant nutrients N, P, and K in the brown manure treatment were 129 %, 6818

%, and 420 %, while percent differences for N, P, and K in the green treatment were much smaller at 44 %, 235 %, and -9 % (all values represent significant differences at P

< 0.01 except for -9, which was insignificant at P = 0.75). From the standpoint of the consumer, beans from the brown treatment have the highest value since they contain the greatest carbohydrate and nutrient concentration per weight (the green treatment only increased the water content of the beans). And although one could argue that farmers 47 could profit from produce priced by weight regardless of the ratio of carbonaceous material to water, it is highly possible that the increase in water weight seen in the green treatment would not even be observed under normal farm conditions (soils in the garden experiment were kept consistently moist).

It is worth noting that Farm B (processed fertilizer) applies nearly four times the recommended amount of ReVitaTM per acre, and yet the fertilized fields were not significantly higher than controls for any nutrients (with the exception Mg and P). In fact, the fertilized soils at Farm B were lower than the unfertilized soils (controls) for total N, available N (ammonium and nitrate), Ca, and K. These results suggest that most of the nutrients applied as processed fertilizer at Farm B are either taken up by plants or leached from the soil (Brady & Weil, 2008). The data also suggests that some of the nitrogen applied as fertilizer is being leached from the processed soil before it is taken up by plants, as the N content of beans grown in the processed treatment was not significantly higher than the control (P =0.36; Ca and K were not measured in the beans;

Tessier & Raynal, 2003). As previously discussed, increasing SOM results in increased nutrient holding capacity (CEC) and decreased runoff/nutrient leaching. Total soil carbon

(SOM) was significantly lower than controls in the processed soils (P < 0.01), yet it was significantly higher for both compost treatments (P < 0.01); this suggests that the amount of C in the processed fertilizer is not enough to increase SOM levels. Furthermore, significantly higher productivity for the compost treatments in comparison to the control

(P < 0.01), suggests that the beans grown in the processed fertilizer treatment were nutrient limited, despite the large amounts of nutrients applied to the soil; nutrient 48 limitation is likely due to relatively low CEC (Tiessen et al., 1999). Finally, in farming systems with low soil carbon, microbes can become unresponsive (Peacock, et al., 2000); this could eventually exacerbate nutrient limitations for crops grown with processed organic fertilizer, as the organically bound nutrients in processed fertilizer may not be mineralized quickly enough for healthy plant growth. In ReVitaTM, half of the N is bound in organic molecules, and the other half is mineral N. Mineral N is immediately available to plants for uptake, but it can also be easily leached from soils with low CEC if crops are not actively taking up large quantities of N at the time of fertilization, or if the microbial community is not actively cycling it (Brady & Weil, 2008).

Microbial Community

Microbial community structure may have also played a role in the increased productivity for the brown treatment. High levels of soluble C from manure are known to cause changes in microbial community structure (Peacock, et al., 2000) which result in more efficient nutrient cycling and increases in microbe-plant interactions, both of which enhance nutrient uptake by plants (Smith et al., 2003). Brown compost (manure) was the only treatment that was different than controls for microbial parameters. The bacterial/fungal ratio of the brown treatment was significantly higher than controls (P <

0.01), and arbuscular mycorrhizal (AM) biomass was higher than controls as well (P =

0.09). The significant increase in bacterial/fungal ratios in the brown treatment is consistent with previous studies showing higher bacterial/fungal ratios in farm soils with more OM (Marschner et al., 2003). In farm soils, higher bacterial/fungal ratios could 49 equal less N loss through leaching, as well as a more consistent supply of available N for crops, provided that there is adequate N in the soil to preclude competition between plants and microbes. This is because bacteria have a lower CN ratio than fungi, and therefore cycle more N (Marschner et al., 2003). The increase in AM fungal biomass in the brown treatment (and not the processed treatment) is consistent with previous studies where AM fungal biomass was found to be higher in organic soils than conventional soil

(Douds et al., 1993). It is worth noting that AM fungi play an important role in farm soils because of the positive effect they have on soil aggregation and plant uptake of P and other scarce nutrients (Smith et al., 2003). It is unclear why neither the bacterial/fungal ratio nor the AM fungal biomass measurements were significantly higher than controls for the green treatment; however, it is likely that arbuscular mycorrhizal growth in the processed treatment was negatively affected due to more frequent tillage (Jasper et al.,

1989; Evans et al., 1988).

Absolute values for nitrification in amended soils were highest in processed fertilizer soil, which is probably due to the fact there is a flush of excess ammonium-N when the processed fertilizer is initially spread, stimulating rapid oxidation (nitrification) of ammonium by autotrophic bacteria (Brady & Weil, 2008). Research on conventional farms has shown increases in ammonia oxidizing bacteria (AOB) populations (nitrifiers) as a result of high N application (Hermansson & Lindgren, 2000) and/or frequent tillage

(Cavagnaro et al., 2008), both of which are factors for the processed treatment.

Microbial Biomass

Microbial biomass was 17 % higher, although not significant, in the brown treatment, but lower for the green or processed fertilizer treatments (P = 0.24, 0.73, and

0.16 for brown, green, and processed). Because microbial biomass is typically higher in soils that receive OM amendments compared to those that receive only mineral fertilizer

(Peacock, et al., 2000), it was hypothesized that the processed fertilizer treatment would support lower microbial biomass than the compost-amended treatments. However, because there was no significant difference found between any of the treatments and controls for microbial biomass, one must consider if microbial biomass alone is an adequate measure of soil fertility for organic farm soils. Current research indicates responsiveness and metabolic activity of soil microbes as an important indicator of healthy microbial communities in organic farm soils (Peacock et al., 2000; Stark, et al.,

2006); future agricultural research may benefit from measuring these parameters, in addition to determining microbial biomass and microbial community structure.

There are number of limitations that may have affected the results of this study which must be acknowledged: 1) the results for bean growth may not be representative of results that would be obtained for beans grown in actual field conditions, as plants grown in pots face different advantages and disadvantages than those grown in field soil; 2) allowing the beans to fully mature and dry on the plants before measuring protein content would have ensured that all the beans were at the same stage of development, and may have produced a more accurate measurement of protein content; 3) because the soil samples for physical and chemical analyses were collected from three different farms, it 51 is likely that confounding variables such as native soil type may have affected the results

(e.g., the native field soils (controls) for the manure treatment are exceptionally low in nutrients and soil organic matter, which makes it difficult to compare the percent differences between controls and treatments to the other treatments.)

CHAPTER 5: SUSTAINABILITY AND THE ORGANIC PHILOSOPHY

The terms “organic farming” and “sustainable agriculture” are often used interchangeably, and although there are distinctions between these terms, the overarching goal of both ideologies is to produce food in a manner that is environmentally sustainable. According to the organic philosophy, one of the most important factors in sustainable food production is maintaining long-term soil health by increasing the organic matter content of the soil (USDA, 2007). However, in reality, not all organic farming practices accomplish this. As the results of this study show, amending the soil with processed fertilizers alone may result in a loss of soil organic matter in agricultural soils, which will ultimately increase susceptibility to drought, erosion, and loss of soil fertility

(Wolf & Snyder, 2003).

Another major component of the organic philosophy for sustainable food production is to reduce the use of off-farm inputs (USDA, 2007). For example, fertilizing with manure produced on the farm (or from nearby farms) is considered to be much more sustainable than purchasing processed fertilizer from a remote source. A growing movement of consumers, known as locavores, support sustainable food production by choosing to purchase foods from local organic/sustainable farmers.

Locavores strive not only to reduce the environmental impacts (soil degradation from the loss of soil organic matter, air pollution from fossil fuels, and water contamination by synthetic fertilizers and pesticides) caused by the production of foods on large, centralized, conventional farms, but also aim to increase the sustainability of the local economy by supporting small, local farmers. That being said, it is important to 53 acknowledge the fact that not all farmers have access to local, abundant sources of organic matter. As stated in the introduction, some farmers travel more than 100 miles to obtain compost (Walz, 2004). While this type of commitment to building fertile, sustainable soil is admirable, trucking large amounts of manure long distances may be less sustainable in terms of fossil fuel consumption than using processed fertilizers. In this case, a more balanced approach of adding the proper quality and quantity of organic matter to maintain soil organic matter levels, while supplementing with processed fertilizers to ensure adequate plant nutrients, might be the best approach. However, further research is necessary to determine the appropriate qualities and quantities of organic matter necessary for this approach to be effective.

CHAPTER 6: FUTURE RESEARCH

Measuring soil fertility on samples taken from authentic functioning farms adds a certain degree of real world applicability to this project. However, as previously discussed, there are also a number of limitations that come along with this design. A long-term, controlled study where fertility and productivity are measured on adjacent plots, each receiving different amendments (e.g., manure, mushroom medium, processed fertilizer, and combined treatments), would be an excellent compliment to this project, and could supply extremely valuable data to local farmers. By measuring the productivity of crops grown in actual field soil instead of pots, and analyzing the effects that different amendments have on fertility for identical soil types, it would be possible to make more concrete distinctions between different organic fertilizers in terms of their value to farmers.

CHAPTER 7: CONCLUSION

Generally speaking, the data from this study support my hypotheses that the compost treatments would result in greater increases in soil fertility and productivity than processed fertilizer. However, some of my more specific hypotheses were not supported by the data. For this study, I hypothesized that:

1) The compost treatments would result in greater bean weight than the

processed treatment. Both compost treatments produced increases in fresh

weight while the processed treatment did not, although only the manure

treatment resulted in greater bean weight for both dry and fresh weights;

2) The processed treatment would have a minimal effect on nutrient

holding capacity. This was also supported by the results of this study, as

both of the compost treatments showed increases in nutrient holding

capacity, while the processed treatment did not;

3) Bean protein content would be higher for beans grown in soils

amended with compost than soils amended with processed organic

fertilizer. The data show no compelling difference between treatments for

this variable;

4) The soils amended with composted manure or mushroom medium

would have higher soil microbial biomass than soils amended with

processed organic fertilizer (because of larger inputs of OM). Microbial

biomass was not significantly (P = 0.01) higher for any treatment.

5) Dominant microbial guilds would be different for the compost

treatments when compared to the processed treatment. There were no

similarities between the compost treatments. Only the manure treatment

resulted in microbial community composition that differed from the

control.

The general increase in soil fertility in the compost treatments was not a big surprise, as the benefits of increasing SOM levels are well documented (Bauer & Black,

1994). However, the fact that the compost treatments resulted in higher productivity than the processed treatment is particularly noteworthy, as SOM levels and crop productivity are not necessarily correlated. For example, because conventional farm soils are typically more productive than organic farm soils amended with compost, despite the fact that conventional soils are generally lower in SOM (Offermann & Nieburg, 2002), it would be reasonable to assume that organic farms using processed fertilizer could be more productive than organic farms that fertilize with compost. However, the data from this study show a clear distinction between the compost treatments and the processed 57 treatment, supporting my hypotheses that the compost treatments would result in both greater productivity and greater fertility than the processed treatment.

The most important implications of this study are that the soils amended with animal manure appear to support more productive bean growth and greater fertility than soils fertilized with either composted mushroom medium or processed fertilizer. The manure treatment also stood out from the other two treatments as the only amendment that produced changes in microbial community structure that could benefit plant growth.

Considering the large increases in CEC, nutrient content, total soil C, and bean dry weight for the soils amended with manure, the brown (manure) treatment appears to be superior to the other two. Alternatively, the shortcomings in terms of productivity, nutrient content, and organic C levels of soils amended with processed fertilizers, compared to either compost treatment, imply that this type of organic fertilizer is an inadequate and unsustainable substitute for composted organic matter.

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