MeredithEyre.MastersThesis.OSU (1)

Characterizing the Effect of Increased Phosphorus and Potassium on Seedling Diseases and Sudden Death Syndrome of Soybean in Ohio

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

By

Meredith Milo Eyre

Graduate Program in Plant Pathology

The Ohio State University

2016

Master's Examination Committee:

Dr. Anne E. Dorrance, Advisor Dr. Steve Culman Dr. Terry Niblack

Dr. Pierce Paul

Copyrighted by

Meredith Milo Eyre

2016

ii

Abstract

Soil fertility may affect the development of soybean diseases, including those

caused by soil borne pathogens. Though increased phosphorus and potassium levels have

the potential to enhance crop productivity and profitability, secondary effects on

pathogens may prove detrimental to overall plant health. Fertility recommendations

serve to define optimum levels and require periodic revision to balance nutrient demands

of modern cultivars and economic yield response with the associated increases in

production costs, environmental considerations, and potential disease development.

Fertility recommendations for soybean in the Tri-State area of Ohio, Michigan, and

Indiana have not been updated in over 20 years, despite dramatic yield increases and

other changes in the industry. As part of a larger collaboration working to re-evaluate

current recommendations, this study assessed the effects of higher than recommended

rates of phosphorus and potassium on seedling disease and sudden death syndrome

disease (SDS) development in soybean through both field and greenhouse trials.

Treatments above the recommended rates in the form of 112 kg/ha diammonium

phosphate (DAP), 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a

nontreated control were applied to 5 field sites with seedling disease history and no

differences in stand nor yield occurred. However, a significantly higher number of plants

affected by damping-off was observed in plots treated with potassium than the other

iii

treatments at one location (p= 0.041). Furthermore, a trend occurred in two intensively

surveyed fields in that higher than recommended rates of phosphorus, potassium, and

phosphorus plus potassium seemed to increase the number of oomycetes, as more isolates

were recovered from plots that had been treated with fertilizer than the nontreated

control. More than 15 different oomycete species were recovered from both fields. In

greenhouse assays, lower root weights occurred in plants which received fertilizer in 2 of

3 greenhouse trials.

When the same treatments were applied to field soils naturally infested

with Fusarium virguliforme, the addition of phosphorus and potassium applied separately

significantly reduced SDS disease index at one of two locations (p= 0.052). The

significant difference detected at this site may be due to lower baseline potassium levels

and higher soybean cyst nematode (SCN) counts. Furthermore, in the presence of SCN

and SDS, phosphorus and phosphorus plus potassium applied at levels higher than

currently recommended enhanced yields, suggesting these additions may decrease disease

pressure or compensate for the biotic stress. Clear trends were not observed in

greenhouse trials with SDS infested soil amended with any of the fertility treatments.

These trends are worth further investigation in continued field trials and

greenhouse trials modified to use inoculated soil with fertility applied incrementally

under consistent conditions. Future field studies which examine the effects of higher

fertility on SDS should prioritize fields with low base levels of potassium and high SCN

counts, as preliminary work suggests applying phosphorus and potassium at rates higher

than currently recommended may enhance yield under these conditions.

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For my loving family

and special Matt

v

Acknowledgments

As with any huge endeavor, this project represents the support of many. I’m honored

to have worked with such a dedicated group of people. I’ve learned more than I could have

imagined from this experience and I’m confident these lessons, both realized and yet-

unknown, will continue to manifest themselves in my career and other pursuits for many

years to come. Most importantly, I thank Dr. Anne Dorrance for her patient guidance,

genuine support, and wise insight. I have always trusted her to simultaneously question and

challenge me in ways that provide the most opportunity for growth, and I can only hope my

future adventures will honor her efforts. I also thank members of the Dorrance lab for

providing a comfortable and supportive work environment. I thank Clifton Martin for his

field help and thoughtful insight on long car rides. I thank Damitha Wickramasinghe for the

time she took to patiently teach me the process of isolate identification and develop my skill

set in the lab. I thank Chrissy Balk for her early support. Even in the midst of her

challenging final weeks here, she was careful to only ever encourage me. I thank Linda,

Delores, Taylor, and Savannah for their help and Cassidy, Jaqueline, and Anna for their

guidance. Beyond their respective help, I thank Kelsey and Jonell for the comic relief and

ridiculous stories that kept me grounded. Amilcar, our rooftop adventures, long talks, and

daily laughs and pranks provided encouragement, perspective, and inspiration. May you earn

the rank of professor someday without accidentally hurting yourself in the process. I thank

Bob James for autoclaving an entire truckload of field soil and the heart-felt encouragement

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when I needed it most. I thank my committee for their advice, direction, and time. Each

models a career rooted in scientific inquiry driven by genuine curiosity. I thank Dr. Steve

Culman for introducing me to the complexity of soil science and including me in his project.

I thank Dr. Pierce Paul for the statistical help and curiosity that has always demanded I think

a bit farther and a bit deeper. I thank Dr. Terry Niblack for her enthusiasm in my first Plant

Pathology course, which can only be described as inspiring. Her genuine support for my

early proposal drafts meant more than she could imagine. I thank The Ohio State University

Plant Pathology Department for providing an excellent academic home. As a third-

generation Buckeye, my loyalty to the school and this department will always run deep. I

thank the Ohio Soybean Council for the support and can only hope I’ve contributed to the

base of knowledge they’ve requested. Finally, I’d like to thank my Wooster community. I

thank the College of Wooster for providing a place of exploration; where the pursuit of

knowledge is only gained through questioning and adventure. I thank Dr. Richard Lehtinen

for the exposure to field ecology and Dr. Charles Kammer for sharing his compassionate

perspective. Both have shaped me profoundly and their respective legacies will last a

lifetime. I thank my Wooster parents, Bob and Bobbie Randall, for sharing their love, home,

and dogs. I thank my Monday night dinner friends for welcoming me into a network of faith,

children, delicious meals, and peace. I thank Carli Moorfield for the conversations, Emily

Oshinksie for being my buddy, and the Wooster Community Band for providing perspective

and peace throughout my time here. Above all, I thank my family and dear Matt Germaine

for everything.

vii

Vita

June 2009……………………………….Westlake High School

May 2013……………………………….B.A. Biology, College of Wooster

August 2016…………………………….M.S. Plant Pathology, The Ohio State University

Publications

Eyre, M. and R.M. Lehtinen. Fitzgerald’s Marsupial Frog (Flectonotus fitzgeraldi). In: Amphibians

and Reptiles of Trinidad and Tobago. Murphy, J.C. (2 ed.) Spring 2013. In Preparation.

Lehtinen, R.M., Steratore, A.F., Eyre, M.M., Cassagnol, E.S., Stern, M.L. and Edgington, H.A., 2016.

Identification of Widespread Hybridization between Two Terrestrial Salamanders Using Morphology,

Coloration, and Molecular Markers. Copeia, 104(1): 132-139.

Eyre M, Dorrance AE, Michel AP, 2015. Damping-off is not always caused by water molds and fungi;

insects can play a role too. C.O.R.N. Newsletter 15.

Eyre M, Martin C, Balk C, Wickramasinghe D, Dorrance AE, 2015. Cold Spring Rains Brought

Perfect Conditions for Pythium in Ohio and a Few More Surprises. Oomycete Molecular Genetics

Network Annual Meeting Monterey, CA.

Eyre M, Martin C, Culman S, Dorrance AE, 2015. Pathogen Response to Altering Levels of Soil

Fertility in Soybean Fields Across Ohio. American Phytopathological Society Annual Meeting

Pasedena, CA.

Eyre M, Culman S, Dorrance AE, 2016. The Effect of Increased Soil Fertility on Seedling Disease

Development of Soybean in Ohio. American Phytopathological Society Annual Meeting Tampa, FL.

Fields of Study Major Field: Plant Pathology

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Table of Contents

Abstract ............................................................................................................................... ii Acknowledgments .............................................................................................................. v

Vita .................................................................................................................................... vii Publications ....................................................................................................................... vii Fields of Study .................................................................................................................. vii Table of Contents ............................................................................................................. viii List of Tables ..................................................................................................................... xi List of Figures ................................................................................................................. xvii Chapter 1: Literature Review ............................................................................................. 1

Significance of Soybean .............................................................................................. 1

Soil Fertility ................................................................................................................. 4

Pathogens of Soybean .................................................................................................. 5

Phosphorus: Significance and Known Disease Response ......................................... 15

Potassium: Significance and Known Disease Response ........................................... 21

Chapter 2: Mini Review: Effects of Fertility on the Development ................................... 26

of Soybean Diseases ......................................................................................................... 26

Abstract ........................................................................................................................ 26

Introduction ................................................................................................................. 26

Influence of Phosphorus and Potassium on Seedling Disease of Soybean ............. 30

Adequate fertility enhances overall plant health and vigor and decreases SDS

incidence .................................................................................................................... 35

Cultivars play a larger role in SDS development than soil fertility........................... 35

ix

Soybean cyst nematode (SCN) may or may not be affected by soil fertility ............ 36

Type of fertilizer may affect SDS development ........................................................ 37

Fertility affects SDS development directly ............................................................... 38

Influence of Soil Fertility on other soybean pathogens ............................................ 39

Conclusion .................................................................................................................... 43

Chapter 3: Effects of Increased Fertility on the Development of ..................................... 44

Seedling Diseases of Soybean .......................................................................................... 44

Introduction ................................................................................................................. 44

Materials and Methods ............................................................................................... 47

Field Experiments ...................................................................................................... 47

Seedling disease survey ............................................................................................. 48

Isolate identification .................................................................................................. 49

Greenhouse experiments ............................................................................................ 51

Statistical analysis...................................................................................................... 52

Results .......................................................................................................................... 55


Survey at VC growth stage ........................................................................................ 56

Greenhouse Experiments ........................................................................................... 56

Discussion ..................................................................................................................... 79

Chapter 4: Effects of Increased Fertility on the Development of ..................................... 84

Sudden Death Syndrome of Soybean ............................................................................... 84

Introduction ................................................................................................................. 84

Materials and Methods ............................................................................................... 88


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Greenhouse experiments ............................................................................................ 89

Statistical analysis...................................................................................................... 91

Results .......................................................................................................................... 93


Greenhouse Experiments ........................................................................................... 93

Discussion ................................................................................................................... 112

References ....................................................................................................................... 116

Appendix A: Soil Regions of Ohio ................................................................................. 137

Appendix B: Media ......................................................................................................... 138

Appendix C: Isolate identification through DNA sequencing ....................................... 141

Appendix D: Digestion and Extraction Buffers .............................................................. 142

Appendix E. Field Notes ................................................................................................ 144

Appendix F: SIUC Method of SDS Scoring ................................................................... 146

Appendix G: Greenhouse Protocols ............................................................................... 147

Appendix H: Greenhouse data collection ....................................................................... 148

Appendix I: Greenhouse Temperatures .......................................................................... 152

Appendix J: 2015 Survey at VC growth stage ................................................................ 154

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List of Tables

Table 1.1. Thirty eight species of Pythium and three species of Phytophthora are known to

infect soybean. Species found in Ohio are noted... ................................................................... 8

Table 1.2. The following species of Fusarium are known to infect soybean. Species

found in Ohio are noted. ................................................................................................... 11

Table 1.3. The addition of phosphorus affects soil borne disease development across a wide

spectrum of hosts (Datnoff et al., 2007). ................................................................................ 18

Table 1.4 In soybean, additional potassium differentially influenced disease development

caused by soil borne pathogens, as summarized from (Datnoff et al., 2007) .................. 23

Table 2.1. Increased fertility levels enhanced seedling disease of soybean caused by

oomycetes in three studies. .............................................................................................. 33

Table 2.2. Previous literature reports several diseases of soybean are affected by soil

fertility. ............................................................................................................................. 40

Table 2.3. Soil fertility affects pathogens of other hosts closely related to those that may

contribute to seedling disease or sudden death syndrome in soybean. ............................ 42

Table 3.1. Soil test resultsa from samples collected prior to planting from Ohio soybean

fields with a known history of seedling disease................................................................ 54

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Table 3.2. P-values from Analysis of Variance (ANOVA) for stand and yield from a

field study that evaluated the addition of phosphorus, potassium, and phosphorus plus

potassiuma at 5 locations in Ohio with a history of seedling disease. ............................. 58

Table 3.3. Mean and standard deviation for stand and yield from a field study that

evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Van

Wert in 2014. ................................................................................................................... 59


evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Van

Wert in 2015. ................................................................................................................... 60


evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at

Defiance in 2014. ............................................................................................................. 62



Defiance in 2015. ............................................................................................................. 63



Wayneb in 2015. ............................................................................................................... 64

Table 3.8. The number of Pythium and Phytophthora isolates recovered from soybean

roots collected at the VC growth stage from Defiance and Van Wert in 2015. .............. 65

Table 3.9. In a field study that evaluated the addition of phosphorus, potassium, and

phosphorus plus potassiuma, isolates were recovered from soybean roots collected at the

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VC growth stage from a survey conducted in Defiance and Van Wert in 2015. Five

symptomatic plants were selected from each plot (chosen arbitrarily if asymptomatic) and

each were plated on both oomycete-selective media (PIBNC) and general growth

promoting potato carrot agar (PCA) to provide 10 opportunities for isolate recovery.

Pythium or Phytophthorab were recovered from the plots in the following frequencies.. 70

Table 3.10. P-values from Analysis of Variance (ANOVA) for stand, root ratings, and

plant weights from a greenhouse study that evaluated the addition phosphorus, potassium,

and phosphorus plus potassiuma to field soil collected from Defiance (Def) and Van Wert

(VW), each with a history of seedling disease. ................................................................ 71

Table 3.11. Means of stand counts from a greenhouse study that evaluated the addition

of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from

two fields with a known history of seedling disease. ....................................................... 72

Table 3.12. Means of root rot ratings from a greenhouse study that evaluated the addition



Table 3.13. Means of root weights from a greenhouse study that evaluated the addition


two fields with a known history of seedling disease. ...................................................... 74

Table 3.14. Means of root weights per planta from a greenhouse study that evaluated the

addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected

from two fields with a known history of seedling disease. .............................................. 75

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Table 3.15. Means of plant weights from a greenhouse study that evaluated the addition



Table 3.16. Means of weight per planta from a greenhouse study that evaluated the

addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected

from two fields with a known history of seedling disease. .............................................. 77

Table 4.1. Soil test resultsa from samples collected prior to planting from Ohio soybean

fields with a known history of sudden death syndrome infested with Fusarium

virguliforme. .................................................................................................................... 92

Table 4.2. P-values from Analysis of Variance (ANOVA) for stand, soybean cyst

nematode Reproductive factor (RF), sudden death syndrome disease index, and yield

from a field study that evaluated the addition of phosphorus, potassium, and phosphorus

plus potassiuma at two locations in Ohio with a history of sudden death syndrome. ...... 95

Table 4.3. Mean and standard deviation for stand, Soybean cyst nematode Reproductive

factor (RF), sudden death syndrome disease index, and yield from a field study that

evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Erie

in 2014. ............................................................................................................................ 96

Table 4.4. Mean and standard deviation for stand, Soybean cyst nematode Reproductive

factor (RF), sudden death syndrome disease index, and yield from a field study that


Wood in 2015. .................................................................................................................. 97

xv

Table 4.5. Mean and standard deviation for Soybean cyst nematode counts and

reproductive factor (RF) from a field study that evaluated the addition of phosphorus,

potassium, and phosphorus plus potassiuma at Erie in 2014. ........................................ 100

Table 4.6. Mean and standard deviation for Soybean cyst nematode counts and

reproductive factor (RF) from a field study that evaluated the addition of phosphorus,

potassium, and phosphorus plus potassiuma at Wood in 2015. ..................................... 101

Table 4.7. P-values from Analysis of Variance (ANOVA) for stand, average height, root

weights, plant weights, and number of plants with diseased roots divided by stand from a

greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus

plus potassiuma to field soil collected from two fields with a history of sudden death

syndrome. ....................................................................................................................... 103

Table 4.8. Mean and standard deviation for stand from a greenhouse study that evaluated

the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil

collected from two fields with a known history of SDS. ............................................... 104

Table 4.9. Mean and standard deviation for plant heights from a greenhouse study that

evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field

soil collected from two fields with a known history of SDS. ........................................ 105

Table 4.10. Mean and standard deviation for root weights from a greenhouse study that



xvi

Table 4.11. Mean and standard deviation for root weights per planta from a greenhouse

study that evaluated the addition of phosphorus, potassium, and phosphorus plus

potassiumb to field soil collected from two fields with a known history of SDS. ......... 107

Table 4.12. Mean and standard deviation for plant weights from a greenhouse study that



Table 4.13. Mean and standard deviation for weights per planta from a greenhouse study

that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiumb to

field soil collected from two fields with a known history of SDS. ................................ 109

Table 4.14. Mean and standard deviation for the number of plants with diseased roots

divided by the number of plants per pot from a greenhouse study that evaluated the

addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected

from two fields with a known history of seedling disease. ............................................ 110

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List of Figures

Figure 2.1. Studies which documented secondary effects of fertility on plant diseases

were often difficult to compare due to variability in experimental designs, base fertility

levels, and environmental conditions. .............................................................................. 29

Figure 3.1. Symptoms of Pythium or Phytophthora infection may include lesions on the

root, stem, or hypocotyls resulting in damping-off or reduced stand. ............................. 45

Figure 3.2. The number of seedlings with damping-off symptoms differed significantly

between additional phosphorus, potassium, phosphorus and potassium, and control

treatments at Van Wert in 2015 (p= 0.041, LSD (0.05)= 27.4). ...................................... 61

Figure 3.3. Pythium and Phytophthora species were recovered from soybean roots

collected at the VC growth stage from Defiance and Van Wert in 2015. Fields were

treated with phosphorus, potassium, and phosphorus plus potassium in a study to

determine the fertility effect on the frequency and diversity of oomycete species

recovered. ......................................................................................................................... 66

Figure 3.4. Pythium and Phytophthora species were recovered from soybean roots

collected at the VC growth stage from Defiance and Van Wert in 2015. Fields were

treated with phosphorus, potassium, and phosphorus plus potassium in a study to

determine the fertility effect on the frequency and diversity of oomycete species

recovered. ......................................................................................................................... 67

xviii

Figure 3.5. In a field study that evaluated the addition of phosphorus, potassium, and

phosphorus plus potassium, isolates were recovered from soybean roots collected at the

VC growth stage from a survey conducted in Defiance Co. in 2015. ............................. 68

Figure 3.6. In a field study that evaluated the addition of phosphorus, potassium, and

phosphorus plus potassium, isolates were recovered from soybean roots collected at the

VC growth stage from a survey conducted in Van Wert Co. in 2015. ............................ 69

Figure 3.7. The first replicate of trial 3 from both locations is pictured above. The

steamed soil control represents plants from one pot. For all other treatments, plants from

both pots for each treatment in the replicate are included. .............................................. 78

Figure 4.1. The first symptoms of the disease appear as small yellow spots between the

veins on the upper leaves of the plant. ............................................................................. 86

Figure 4.2. Crowns of infected plants are usually decayed and discolored, often

becoming necrotic. Characteristic blue-green spores of the fungus are sometimes visible

on the tap root, especially in moist conditions after a rainfall. ........................................ 87

Figure 4.3. Disease index (incidence x severity) differed significantly between

phosphorus, potassium, phosphorus and potassium, and control treatments at Erie in 2014

(p= 0.052, LSD (0.05)= 27.4) but not at Wood in 2015 (p= 0.887, LSD (0.05)= 18.6). .. 98

Figure 4.4. Yield differed significantly at both Fusarium virguliforme infested field sites

between phosphorus, potassium, phosphorus and potassium, and control treatments (Erie:

p= 0.020, LSD at 0.05= 4.0; Wood: p= 0.041, LSD at 0.05= 6.3). ................................. 99

Figure 4.5. Soybean cyst nematode populations were counted before planting and after

harvest at two locations with sudden death syndrome history treated with additional

xix

phosphorus, potassium, and phosphorus plus potassium. An SCN resistant seed was used

(AGI 31R2Y2 3102N). An Analysis of Variance found that treatments did not differ

significantly at either time of year for both locations (Erie Pi p= 0.989; Wood Pi p=

0.807; Erie Pf p= 0.624; Wood Pf p= 0.062). ................................................................ 102

Figure 4.6. Distinct yellow spotting occurred primarily in pots treated with phosphorus

in one of four assays (Wood trial 2). .............................................................................. 111

Figure 4.7. Distinct yellow spotting occurred in one of four assays. Though each

treatment was represented in 12 pots, not all pots germinated. ..................................... 111

1

Chapter 1: Literature Review

Fertility recommendations for soybean in the Tri-State area of Ohio, Michigan,

and Indiana have not been updated in over 20 years (Vitosh et al., 1995). There has been

speculation that high-yielding modern cultivars may require an increased nutrient supply

to satisfy nutrient demand, and current recommendations may not be sufficient.

However, increased levels of phosphorus and potassium may affect the development of

soybean diseases, especially those caused by soil borne pathogens. If increased fertility

is shown to enhance soybean yield in future state or regional surveys, the effects of

increased fertility on the development of soybean disease, specifically seedling disease

and sudden death syndrome, warrants investigation.

Significance of Soybean

Soybean [Glycine max (L.) Merr.] is the leading oilseed crop produced and

consumed in the world today, representing 59% of the world’s oilseed production

(American Soybean Association, 2015). Globally, 11.59 billion bushels were produced

in 2014 (American Soybean Association, 2015). More soybean was produced in the

United States than any other country in 2014 with 3.97 billion bushels (34% of the world

total), followed by Brazil with 3.47 billion bushels (30%) and Argentina with 2.06 billion

bushels (18%) (American Soybean Association, 2015). Of the nearly 4 billion bushels

2

produced valued at 40.3 billion dollars, the United States exported 45% (American

Soybean Association, 2015). Soybean is grown in at least 30 states; in 2014, the leading

states in production were Illinois (548 million bu), Iowa (506 million bu), Indiana (307

million bu), and Minnesota (305 million bu) (American Soybean Association, 2015).

With irrigation, the distribution of soybean in the US extends as far west as the Dakotas,

Nebraska, Kansas, Oklahoma, and Texas (Wilcox, 2004). Soybean represents the

country’s second largest crop in cash sales and most valuable crop export.

In Ohio, the crop was worth $2.64 billion in 2014 (American Soybean

Association, 2015). Soybean was planted on 4.85 million acres in 2014, making it the

leading crop by acreage grown in the state, followed by corn at 3.74 million acres

(National Agricultural Statistics Service, 2014). Though the national average for yield

was 47.8 bu/acre, Ohio harvested 52.5 bu/acre (American Soybean Association, 2015).

This represents a dramatic increase in yield compared with 1986, when farmers in the

United States produced 1.94 billion bushels on 60.4 million acres with a yield of 33.3

bu/acre (National Agricultural Statistics Service, 2014; American Soybean Association,

2015). Though production of soybean in the United States has doubled in the past 30

years, the area dedicated to soybean has increased only 38% while seed yields have

increased by 44%. Growers have come to expect an increase in yield by approximately

1% each year (Wilcox, 2001).

The growth of the soybean industry is a direct result of the increase in popularity

of the soybean itself. The plant is used in a number of ways and can be divided into three

main categories: oil, meal, and hulls. Note that 1 bushel of soybean on average weighs

3

60 lbs and produces 11 lbs of oil and 48 lbs meal (American Soybean Association, 2015).

In 2014, 20.6 billion pounds of oil was produced in the United States. Of this, 70% was

used in human food, 22% was used for biodiesel technology, and the remaining was used

for other industrial purposes (United Soybean Board, 2015). Soybean oil represents 55%

of vegetable oil in the country, followed by canola oil at 16% (American Soybean

Association, 2015). Biodiesel technology has increased from 1.9 million liters in 1999 to

6,615 million liters in 2014 (American Soybean Association, 2015; United Soybean

Board, 2015). The remaining soybean oil is used for industrial purposes. According to

the United Soybean Board, over 800 products have been developed with soy including:

soaps, lotions, paint-strippers, paint, ink, wood adhesives, solvents, surfactants, and

lubricants. Plastic composites from the oil have been used in spray-foam insulation,

hardwood, particle board, boats, cars, and even agricultural equipment. Lecithin is

extracted from soybean oil and can be used for pharmaceuticals, protective coatings,

lubricants, and emulsifiers (American Soybean Association, 2015).

Soybean meal serves as a high source of fiber and includes essential amino acids

for animal feed (United Soybean Board, 2015). In fact, 96.5% of soybean meal

representing 30.5 million short tons was used for animal feed in the US in 2014

(American Soybean Association, 2015). Of this, 55% was fed to poultry, 22% to swine,

11% to beef, 7% to dairy (American Soybean Association, 2015). In addition to meal,

cattle may be fed soybean hulls (crush) (United Soybean Board, 2015).

4

Soil Fertility

Soil fertility is defined as the ability of the soil to provide chemical elements in

quantities and proportions necessary for the growth of specified plants (Havlin et al.,

2005). Though the addition of essential nutrients is crucial for the health and

productivity of the crop, soil fertility represents only one facet of overall soil productivity

and does not solely dictate the yield of the crop. Instead, crop productivity is based on a

number of climatic conditions, crop factors, and soil characteristics (Division of Soil and

Water Conservation, 2005; Rice, 2007) (Appendix A). Climatic conditions include

precipitation, air temperature, humidity, solar radiation, and wind. Crop factors include

genetics, population density, and pests and disease. Soil characteristics also contribute to

overall crop productivity, though the many characteristics form a complex web often

difficult for researchers to tease apart. These characteristics include soil food webs,

organic matter cycling, texture and composition, pH, aggregation, compaction and

drainage, cation exchange capacity, management effects, and soil fertility. Therefore,

soil fertility is only one aspect of a much larger agronomic system. Despite this

perspective, maintaining proper soil fertility is necessary to maximize plant growth and

yield.

Fertilizers typically include nitrogen, phosphorus, and potassium. However,

studies have shown that increasing nitrogen levels has a negligible effect on soybean

yields due to nitrogen fixation by Rhizobium bacteria (Grubinger et al., 1982), so

phosphorus and potassium are the primary inputs. Specific rates of fertilizer application

must be established and updated periodically to balance an increase in crop productivity

5

with environmental and economic losses. Soybean growers in Ohio rely on the Tri-State

Fertilizer Recommendations for application rates (Vitosh et al. 1995). However, these

recommendations are 20 years old. The soybean industry has changed significantly

during this time resulting in relatively dramatic yield increases and many new cultivars,

some of which are considered a high protein variety. Therefore, as part of a larger

collaboration to update these outdated recommendations, the purpose of this study was to

examine the effect of excess phosphorus and potassium on disease development, either

by directly altering pathogen activity or by stressing the plant to favor infection by one or

more pathogens. It should be noted that “excess fertility” indicates fertilizer was applied

at levels higher than recommended by current guidelines.

Pathogens of Soybean

Soybean is affected by a large number of diseases due in part to the diversity of

soybean cultivars and variation in the environmental conditions throughout the crop’s

geographic range. Each pathogen species may be distributed widely or limited

geographically, varying in frequency of occurrence and potential yield loss (Grau et al.,

2004). Though more than 200 pathogens are known to affect soybean around the world,

only 35 are economically important (Hartman, 2015). During the 2009 growing season,

an estimated 484 million bushels were lost to disease in the United States (Bradley et al.,

2015; Koenning and Wrather, 2010). Of these estimated losses, soil borne diseases affect

the crop most dramatically. Soybean cyst nematode, seedling diseases, Phytophthora root

and stem rot, and sudden death syndrome were ranked the top four most influential

6

diseases, respectively, to affect yield in 2006 to 2009 (Bradley et al. 2015; Keonning and

Wrather, 2010). Management has proven difficult for these soil borne diseases, as seed

treatments are limited to managing seedling diseases early in the season, and foliar-

applied fungicides generally do not affect soil borne pathogens.

The most common symptom of seedling disease is reduced stand count (Grau et

al., 2004). Seedlings that have emerged may have lesions on the roots, hypocotyl, or

cotyledons. Often, the stem disintegrates at the base of the newly emerging seedling,

causing damping-off symptoms. Overall root decay with unclear margins may cause the

root to turn pale to deep brown, black, or brick red (Grau et al., 2004).

Several pathogens cause seedling diseases including many species of

Pythium and Fusarium, Rhizoctonia solani, Phytophthora sojae, Ph. sansomeana,

Macrophomina phaseolina, and Mycoleptodiscus terrestrus (Grau et al. 2004; Rizvi and

Yang, 1996; Tachibana et al., 1971, Tachibana, 1971). These pathogens may survive in

the soil for years and infect soybean over a wide range of environmental conditions.

Seedling pathogens may infect individually or in combination (Ellis et al., 2011; Broders

et al., 2007a, Broders et al., 2007b). Studies have shown varying pathogenicity among

the genera. Fields were surveyed in one study and 94% of Pythium isolates, 21% of

Fusarium isolates, and 75% of R. solani isolates were pathogenic (Rizvi and Yang,

1996). In a soil baiting assay which surveyed soil from 3 counties in Ohio, Dorrance et

al. (2004) reported a range of pathogenicity within and between 5 Pythium species.

7

Due to the high pathogenicity of oomycetes, relevant literature addresses oomycete

response to fertility (Canaday and Schmitthenner, 2010; Dirks et al., 1980; Pacumbaba et

al., 1997).

Oomycete pathogens of soybean include Pythium and Phytophthora spp. These

pathogens are favored by cool and wet conditions, though their oospores may survive in

the soil for many years. Infection occurs when zoospores encyst on and germinate into

germinating seeds, seedlings, and young field roots resulting in pre- and post-emergence

damping-off. Soybean pathogenic Phytophthora species include Ph. sojae and Ph.

sansomeana. The Pythium genus includes a much larger number of soybean pathogenic

species. These Pythium species are largely either opportunistic or weakly pathogenic

necrotrophs, and they are often pioneer colonizers. Most Pythium species are considered

generalists due to their wide host range (for example, P. ultimum has 719 documented

hosts) but some species are restricted to certain taxa (for example, P. graminicola and P.

arrhenomaneson are only known to infect Poaceae) (Ellis, 2011; Farr and Rossman,

2012; Schroeder et al., 2013).

Individual fields often contain several different species of Pythium, with varying

levels of virulence on specific hosts. Several species of Pythium are pathogenic to both

corn and soybean, making management difficult (Broders et al., 2009a; Dorrance et al.

2004). Though there are many species known to occur in Ohio, Pythium irregulare is

one of the most widespread species in the state with very high levels of pathogenicity

(Ellis, 2011; Ellis et al. 2012).

8

Table 1.1. Thirty eight species of Pythium and three species of Phytophthora are known to infect soybean. Species found in Ohio are noted. In 2008, Kirk Broders determined the relative pathogenicity for twelve of the most common isolates found in Ohio, and the OSU Soybean Pathology lab is currently working to update this information (Broders, 2008).

Pythium species Susceptible hosta Found in Ohiob

Citation

P. aphanidermatum soybean *Yes Broders, 2008; Rizvi and Yang, 1996 P. arrhenomanes corn and soybean *Yes Lipps and Deep, 1991; Rao et al., 1978; Broders’ excel sheet P. attranthericium corn and soybean *Yes Broders, 2008 P. catenulatum soybean Yes Dorrance et al., 2004 P. conidiophorum soybean? *Yes OSU Soybean Pathology 2015 diagnostic excel sheet P. debaryanum soybean Minnesota Brown and Kennedy, 1965 P. delawarii soybean *Yes Broders et al., 2009b P. dissotocum soybean and corn *Yes Rao et al., 1978; Lipps and Deep, 1991 P. echinulatum corn and soybean Yes Broders, 2008 P. graminicola corn and soybean *Yes Lipps and Deep, 1991; Rao et al., 1978; Broders’ excel sheet P. helicoides soybean *Yes Broders, 2008 P. heterothallicum soybean *Yes Broders’ excel sheet and OSU Soybean Pathology 2015

diagnostic excel sheet P. hypogynum corn and soybean *Yes Broders, 2008 P. inflatum corn and soybean *Yes Broders, 2008 P. irregulare soybean *Yes Dorrance et al., 2004; Rizvi and Yang, 1996 P. longandrum corn and soybean *Yes Broders, 2008 P. middletonii soybean *Yes Broders, 2008 P. myriotylum soybean Iowa McCarter and Littrell, 1970; Rizvi and Yang, 1996 P. nunn soybean *Yes Broders’ excel sheet and OSU Soybean Pathology 2015

diagnostic excel sheet P. oligandrum soybean *Yes Broders, 2008 P. oopapillum soybean *Yes OSU Soybean Pathology 2015 diagnostic excel sheet P. orthogonon soybean *Yes Broders, 2008 P. paroecandrum soybean *Yes Dorrance et al., 2004 P. parvum soybean *Yes Broders, 2008 P. perplexum soybean *Yes Broders, 2008 P. pleroticum soybean *Yes Broders, 2008 P. rostratifingens soybean? *Yes OSU Soybean Pathology 2015 diagnostic excel sheet P. schmitthenneri corn and soybean *Yes Ellis et al., 2012; OSU Soybean Pathology 2015 diagnostic

excel sheet P. selbyi corn and soybean *Yes OSU Soybean Pathology 2015 diagnostic excel sheet P. splendens corn and soybean *Yes Dorrance et al., 2004 P. sylvaticum soybean *Yes Rizvi and Yang, 1996 P. terrestris corn Yes Rao et al., 1978 P. torulosum corn and soybean *Yes Dorrance et al., 2004; Lipps and Deep, 1991; Rao et al., 1978;

Zhang et al., 1998; Zhang and Yang, 2000 P. ultimum corn and soybean *Yes Griffin, 1990; Lipps and Deep, 1991; Rao et al., 1978; Rizvi

and Yang, 1996; Zhang et al., 1998; Zhang and Yang, 2000 P. ultimum var. ultimum

soybean *Yes Rizvi and Yang, 1996

P. ultimum var. sporangiferum

soybean *Yes Rizvi and Yang, 1996

P. vanterpoolii soybean *Yes Broders, 2008 P. vexans soybean *Yes OSU Soybean Pathology 2015 diagnostic excel sheet Phytophthora sojae soybean *Yes Kaufmann and Gerdemann, 1958; Rizvi and Yang, 1996 Ph. medicaginis soybean *Yes Broders’ excel sheet Ph. sansomeana soybean and corn *Yes Dorrance et al., 2004; Zelaya-Molina et al., 2010 aHosts with a question mark indicate isolates were recovered from soybean fields but pathogenicity could not be confirmed. bAn asterisk in the Ohio column indicates the species was found by the OSU Soybean Pathology lab.

9

Traditionally, Pythium species were described morphologically based on sexual

and asexual structures produced in water cultures containing grass blades. Specifically,

the shape of the sporangia, antheridia, and ornamentation of oogonia were considered.

The compilation of Pythium morphological information created by Van der Plaats-

Niterink in 1981 is still considered to be the most complete monograph (Middleton, 1943;

Van der Plaats-Niterink, 1981; Waterhouse, 1968), though many new species have been

added since (Broders et al., 2009b).

The combination of genetic sequence information along with morphological

observation is the recommended approach when identifying Pythium to a species level.

Molecular identification based on amplification and sequencing of the internal

transcribed spacer (ITS) of rDNA. A fairly comprehensive list of primers designed from

this region that are species specific for Pythium species is reported (Schroeder et al.,

2013; White et al., 1990). However, in some species, ITS information alone is not

sufficient due to low divergence between species. Additional loci include the ribosomal

large subunit (LSU) or nuclear encoded β-tubulin of the rDNA (Levesque and De Cock,

2004; Moralejo et al., 2008; Villa et al., 2006) the mitochondrially-encoded cytochrome

oxidase 1 (cox1) or NADH dehydrogenase subunit 1 (nad1) (Martin, 2000; Moralejo et

al., 2008; Villa et al., 2006).

Fusarium species are diverse and widely distributed. Though the genus is

collectively known to infect many hosts, only some species may infect soybean. Of those

species, only a subset is pathogenic. In soybean, pathogenic species cause seed and

seedling disease, Fusarium wilt (F. oxysporum), or sudden death syndrome (F.

10

virguliforme) (Aoki et al., 2003; Armstrong and Armstrong, 1950; Broders et al., 2007b;

Nelson, 1999; Rizvi and Yang, 1996; Schlub et al., 1981) (Table 1.2).

Root rot caused by Fusarium species is common in the United States (Yang and

Feng, 2001). Symptoms of root rot include poor or slow emergence, dark brown lesions

on the root system (especially the lower portion), and decay of the tap root (Arias et al.,

2013b). Root rot is most often caused by F. oxysporum and F. solani (Arias et al., 2013a;

Leslie et al., 1990; Nelson, 1999). Seed and seedling disease is often the result of a

combination of Fusarium species with other soil borne pathogens including oomycetes

(Broders et al., 2007b; Dunleavy, 1961; Schlub et al., 1981). However, some studies

suggest Fusarium species are secondary colonizers (Rizvi & Yang, 1996). Datnoff and

Sinclair (Datnoff & Sinclair, 1988) found F. oxysporum and Rhozoctonia solani were

usually associated in the infection of soybean roots in Illlinois. At least 18 Fusarium

species were isolated from soybean roots (Arias et al., 2013c; Bienapfl et al., 2010;

Bienapfl, 2011; Koning et al., 1995; Leslie et al., 1990; Nelson, 1999; Pioli et al., 2004).

Additional saprophytic Fusarium species often found on plant roots and in soil may

complicate the diagnostic process (Broders et al., 2007b). Broders (2008) found

Fusarium species were isolated from both healthy and diseased plants in approximately

equal frequency (Broders, 2008).

11

Table 1.2. The following species of Fusarium are known to infect soybean. Species found in Ohio are noted.

Fusarium species Susceptible hosta Known to be found in Ohio

Citation

F. acuminatum corn and soybean yes Bienapfl, 2011; Leslie et al., 1990; Rizvi and Yang, 1996

F. anthophilum soybean southern states Leslie et al., 1990 F. armeniacum soybean Arias et al. 2013a F. avenaceum soybean southern states Leslie et al., 1990 F. chlamydosporum soybean? Kansas Leslie et al., 1990 F. compactum soybean? Kansas Leslie et al., 1990 F. equiseti soybean yes Bienapfl, 2011; Leslie et al., 1990; Rizvi and

Yang, 1996 F. graminearum corn and soybean yes Bienapfl, 2011; Leslie et al., 1990 F. merismoides soybean? Kansas Leslie et al., 1990 F. moniliforme corn yes Leslie et al., 1990; Rao et al., 1978 F. nigrum soybean Mississippi Killebrew et al., 1993 F. oxysporum corn and soybean yes Bienapfl, 2011; Griffin, 1990; Leslie et al., 1990;

Rao et al., 1978; Rizvi and Yang, 1996 F. poae soybean Mississippi Killebrew et al., 1993 F. proliferatum corn and soybean yes Arias et al. 2013a; Bienapfl, 2011; Leslie et al.,

1990 F. pseudograminearum soybean Arias et al. 2013a F. redolens soybean Minnesota Arias et al. 2013a; Bienapfl, 2011 F. roseum corn yes Rao et al., 1978 F. semitectum (syn. F. pallidoroseum)

corn and soybean yes Killebrew et al., 1993; Leslie et al., 1990

F. solani corn and soybean yes Bienapfl, 2011; Griffin, 1990; Leslie et al., 1990 F. sporotrichioides soybean Iowa and

Minnesota Arias et al. 2013a; Bienapfl, 2011

F. subglutinans corn yes Bienapfl, 2011; Leslie et al., 1990 F. verticillioides soybean Minnesota Bienapfl, 2011 F. virguliforme soybean yes Gao et al., 2006; Gongora-Canul and Leandro,

2011b; O’Donnell et al., 1998; O’Donnell et al., 2010; Wang et al., 2015

aHosts with a question mark indicate isolates were recovered from soybean fields but pathogenicity could not be confirmed

12

Fusarium graminearum is an especially important seedling pathogen to consider

due to its relatively recent discovery in Ohio as a pathogen of soybean and ability to

produce harmful mycotoxins (Champeil et al., 2004; Pioli et al., 2004; Sella et al., 2014).

This pathogen may cause damping-off, crown rot, or root rot in soybean (Arias et al.,

2013b; Broders et al., 2007b; Pioli et al., 2004).

In contrast to seed and seedling diseases, sudden death syndrome (SDS) is caused

by a single species: Fusarium virguliforme (formerly Fusarium solani f. sp. glycines)

(Aoki et al., 2003). The disease was first reported in Ohio in 1995 and has become

increasingly common in the state ever since (Roy et al., 1997b). SDS poses a significant

threat to soybean yield and though average economic losses are quite significant, disease

severity on a small scale is highly variable. SDS is most likely to occur in fields have

been planted early, exposed to cool temperatures, contain soybean cyst nematode, have

compacted soil, or are heavily irrigated or poorly drained, as these are all factors that

contribute to disease (Roy et al., 1989).

Though infection occurs early in the season, characteristic foliar symptoms are

best seen later in the season, at the R6/R7 growth stage (Navi & Yang, 2008; Njiti et al.,

1997; Roy et al., 1997b). The soil borne pathogen is easily spread through soil

movement and overwinters as chlamydospores; structures that survive in the soil for

years. The pathogen may infect soybean as early as the seedling stage, occurring

approximately two weeks after emergence in the field (Gao et al., 2006). Infection

occurs in the roots and crowns of the seedlings. When the fungus colonizes the roots, a

toxin is produced. This toxin moves up to the leaves through the xylem and results in

13

characteristic foliar symptoms; small yellow interveinal spots on the upper leaves of the

plant that develop into brownish-tan lesions with a yellow halo that expand rapidly

between the veins until the leaflet becomes entirely necrotic (Roy et al., 1997b).

Identification of Fusarium species is similar in methodology to the identification

of oomycete species. Ideally, identification should be based on both morphological

characterizations and molecular sequences. Morphological observations should consider

the macroconidia and microconidia, production of mesoconidia, conidial arrangements,

nature of conidiogenous cells, conidiophore length, formation and arrangement of

chlamydospores, and production and color of sporodochia on carnation leaf agar (Arias et

al., 2013b). Observations should be compared with the system outlined by Leslie and

Summerell (2006) (Leslie et al., 2006). Colony appearance and pigment formation on

potato dextrose agar should also be considered (Arias et al., 2013b).

Molecular identification of Fusarium using conventional PCR is based on the

amplification of several different loci. Arias et al. (2013) amplified and sequenced the

elongation factor 1-α (EF1- α) gene region (Arias et al., 2013b). Primer pairs include

ef1/ef2 and ef1/ef22 (Geiser et al., 2004; O'Donnell et al., 1998). When further analyzing

isolates in the F. oxysporum species complex, Ellis et al. (2014) amplified the translation

elongation (tef1α) gene using the primers EF-1H and EF-2T (O'Donnell et al., 1998; Ellis

et al., 2014). In addition, the mitochondrial small subunit (mtSSU) was amplified using

the primers MS1 and MS2 (White et al., 1990). In order to target F. virguliforme,

Kolander et al. (2012) used the species-specific primers: Fsg1 and Fsg2 (Kolander et al.,

2012; Li & Hartman, 2003; Malvick & Bussey, 2008).

14

Soybean fields with SDS are often associated with soybean cyst nematode (SCN),

Heterodera glycines (Gao et al., 2006; Westphal & Xing, 2011). Though Fusarium

virguliforme can independently infect soybean, the pathogens are often found together.

The relationship between SCN infestation and SDS severity is controversial (Brzostowski

et al., 2014; Gao et al., 2006; Hartman et al., 2015b; Marburger et al., 2014; Roy et al.,

1989). Nematode root feeding weakens the plant and provides wounds for the fungus to

colonize, possibly making the plant more vulnerable (Roy et al., 1989). Fusarium

virguliforme was also found in and on SCN cysts, providing evidence that the pathogens

may travel between locations together (Lawrence et al., 1988).

Soybean cyst nematode has been found in all soybean production areas in Ohio

and may cause substantial yield loss (Niblack 2005). High population densities of SCN

may cause yellowing and stunting, though yield loss may result in asymptomatic fields.

SCN damage is usually most severe in light, sandy soils (Avendano et al., 2004). The

infectious juveniles (second-stage juveniles, or J2) enter the soybean roots and begin to

feed. Though both sexes feed within the roots, the vermiform males leave at the J4 stage

and migrate through the soil to fertilize females. Females develop a feeding site

(syncytium), swell into a white lemon-shaped cyst as eggs develop, and die. Their

melanized bodies continue to protect the developing eggs until environmental conditions

support the hatching of the J2 and subsequent infection (Niblack 2005).

Previous literature documenting the relationship between soil borne disease

development and the alteration of soil fertility levels is complex. However, several

studies have reported changes in incidence and severity of soil borne diseases with

15

increased fertility levels. Specifically, seedling diseases and SDS increased with excess

fertility (Canaday & Schmitthenner, 2010; Pacumbaba et al., 1997; Rupe et al., 2000;

Sanogo & Yang, 2001). Therefore, the effect of soil fertility on soybean pathogens is an

important topic of study.

Phosphorus: Significance and Known Disease Response

After nitrogen, phosphorus is most likely nutrient to limit plant growth (Havlin et

al., 2005). Soybean crops require a relatively large amount of phosphorus, especially as

pods set. The concentration of phosphorus in plants usually ranges from 0.1 to 0.5%

(Havlin et al., 2005). Though it has many roles in the plant, it is primarily associated

with energy transfer and protein metabolism (Datnoff et al., 2007). Specifically,

phosphorus forms phosphate groups that are bound to adenosine diphosphate (ADP) to

form adenosine triphosphate (ATP). The gain or loss of a phosphate group results in an

energy transfer; a process required of all metabolic functions (Havlin et al., 2005).

Phosphorus is also involved in electron transport in oxidation-reduction reactions and

forms the phosphate backbone of DNA and RNA. Phospholipids, coenzymes, and

phosphoproteins also require the element. The nutrient stimulates early plant growth and

hastens maturity (Datnoff et al., 2007). It is necessary for seed production and was found

to increase the number of pods per plant. Phosphorus is also associated with increased

root growth (Datnoff et al., 2007). It is required for nitrogen fixation by B. japonicum,

and application of phosphorus may increase the nitrogen-fixing ability of these bacteria

(Israel, 1987). Additional phosphorus is widely known to increase crop yields, especially

16

in highly weathered acid soils (Fageria & Baligar, 2001; Fageria, 2002). Visual

symptoms of phosphorus deficiency include overall stunting of the plant and slow growth

and some leaf cupping may occur. Because the nutrient is mobile, symptoms will first

appear in older leaves. These leaves will turn purple or bluish-green before becoming

chlorotic. Flowering and maturity may be delayed (Datnoff et al., 2007).

A clear association between balanced and adequate fertility and overall crop

health has been reported (Fageria & Baligar, 1997; Krupinsky et al., 2002). Although

highly specialized pathogens may attack vigorous plants, less specialized pathogens are

often only able to infect weak plants (Prabhu et al., 2007). Therefore, proper fertility

may improve physiological resistance by reducing overall plant stress (Fageria & Baligar,

1997; Krupinsky et al., 2002). Furthermore, higher levels of fungistatic substances

(including phenolic compounds and flavonoids in epidermal cells) are present in plants

with adequate fertility, likely due to overall increased vigor (Prabhu et al., 2007).

Though soilborne pathogens may be inhibited by these modified defense responses, it is

likely the only explanation for the altered disease incidence of airborne diseases (Prabhu

et al., 2007). An increased concentration of phosphorus in leaves was also found to be

associated with accelerated time to maturity, thus decreasing the likelihood of infection

by pathogens that attack young plants (Prabhu et al., 2007).

The effect of phosphorus on disease development is inconclusive and reportedly

complex (Datnoff et al., 2007; Prabhu et al., 2007). Phosphorus-specific research was

performed in both the greenhouse and field, sometimes with contradictory results (Prabhu

et al., 2007). It is important to note the effects of phosphorus are usually only seen in

17

cultivars moderately susceptible to a pathogen, as genetics seem to play a larger role in

susceptibility than phosphorus fertility (Datnoff et al., 2007; Prabhu et al., 2007).

Specific studies documenting the effect of phosphorus on soil borne pathogens for a

number of different hosts is outlined in Table 1.3.

18

Table 1.3. The addition of phosphorus affects soil borne disease development across a wide spectrum of hosts (Datnoff et al., 2007). Host Disease Pathogen P system:

deficient or excessa

Pathogen response to added phosphorusb

Citation

Cabbage Yellows Fusarium oxysporum f. sp. conglutinans

Gradient: .5x to 3x. x= recommended rate of application

Increased Walker and Hooker, 1945

Conifer Damping-off Fusarium oxysporum Excess Increased Sinclair et al. 1975

Cotton Root rot Phymatotrichum omnivorum

Not noted Increased Bell, 1989; McClellan and Stuart, 1947; Prabhu et al., 2007

Cotton Wilt Fusarium oxysporum f. sp. vasinfectum

Not noted Conflicting reports

Bell, 1989; Jones et al. 1989; Prabhu et al., 2007; Vanterpool, 1935

Cucumber Damping-off Rhizoctonia solani Not noted Decreased Prabhu et al., 2007

Geranium Root rot Pythium ultimum Excess Increased Gladstone and Moorman, 1989

Gladiolus Yellows Fusarium oxysporum f. sp. gladioli

Gradient: 8ppm and 39ppm

Decreased McClellan and Stuart, 1947

Lentil Wilt Fusarium oxysporum f. sp. lentis

not noted Increased Kaushal and Sharma, 1998; Prabhu et al., 2007

Linseed Not specified Fusarium oxysporum Not noted Increased Ghorbani et al., 2008; Singh, 1999

Peas Damping-off Rhizoctonia solani Deficient Decreased Prabhu et al., 2007; Srihuttagum and Sivasithamparam, 1991

Potato Late blight Phytophthora infestans

Not noted Conflicting reports

Keinath, 1989; Prabhu et al., 2007

Soybean Root rot Rhizoctonia solani Not noted Decreased Castano and Kerkamp, 1956

Soybean Root rot Phytophthora sojae Gradient: 20 to 317 ppm

No effect Canaday and Schmitthenner, 2010

Soybean Root knot nematode

Melodogyne incognita Not noted Decreased Carling et al., 1989

Continued on next page

19

Table 1.3 continued

Host Disease Pathogen P system: deficient or excessa

Pathogen response to added phosphorusb

Citation

Spring wheat

Root rot Cochliobolus sativus Both: 0 and 15 kg/ha

Increased Goos et al., 1994

Tomato Wilt Fusarium oxysporum f. sp. lycopersici

Deficient and gradient: 8ppm and 39ppm

Conflicting reports

Förster et al., 1998; McClellan and Stuart, 1947; Woltz and Jones, 1973

Tomato Fusarium wilt Fusarium spp. Not noted Increased Woltz and Jones, 1973

Tomato and green peppers

Phytophthora root and crown rot

Phytophthora spp. Deficient Decreased Förster et al., 1998

Wheat Root rot Pythium spp. Not noted Decrease Huber, 1980

Wheat Root rot Helminthosporium sativum

both Conflicting reports exist

Brennan, 1995; Duffy et al., 1997; Goos et al., 1994; Graham and Menge, 1982; Huber, 1989

aThe study may or may not document whether fertilizers were applied to a deficient system or in excess. Levels of fertility were considered excess if they were above the respective recommendation. bIncrease= an increase in either disease incidence or severity; decrease= a decrease in either disease incidence or severity

20

In summary, although the relationship between phosphorus application and plant

disease is well studied, the literature represents the complexity of the topic. For example,

Canaday and Schmitthenner (2010) did not observe any disease response in soybean in

Ohio when phosphorus salts were added to soil naturally infested with Phytophthora

sojae. After phosphate salts were applied, the phosphorus concentration ranged from 0

ppm to 317 ppm, representing both a deficient system and system exposed to excess

phosphorus. Disease response was measured in germination rates, seedling emergence,

damping-off rates, and ratio of surviving seedlings with lesions. This study documented

an increase in disease incidence when potassium was added, which will be explained

further in the potassium section of this review (Canaday & Schmitthenner, 2010). In

contrast, Gladstone and Moorman (1989) reported a significant increase in the mortality

of geraniums infected with Pythium ultimum when ammonium phosphate was added in

excess levels. Dirks et al. (1980) also reported an increase in Phytophthora root rot

severity in soybean in the field due to increased levels of complete fertilizer (Dirks et al.,

1980).

21

Potassium: Significance and Known Disease Response

Potassium is likely to be the third most deficient nutrient after nitrogen and

phosphorus (Havlin et al., 2005). Potassium is absorbed in the largest quantity, after

nitrogen. It is a mobile nutrient in plants and concentrations range from 1 to 5%.

Potassium primarily functions to regulate solution ionic strength in cells. This is vital for

photosynthesis and metabolism, enzyme activation, translocation of assimilates, and

water regulation. Visual symptoms of deficiency include scorching or firing along leaf

margins, stunted growth and poor root system development, and weak stalks or stems.

The effect of potassium alone or in combination with phosphorus and/or nitrogen

has been documented for several pathogen groups in reviews (Datnoff et al., 2007).

Numerous studies reported there may be a greater pathogen response in deficient plants

supplied with adequate potassium than with adequately supplied plants fertilized with

excess potassium (Datnoff et al., 2007; Huber and Arny, 1985). Intuitively, this seems

logical, as stressed plants are generally more susceptible to disease. Unfortunately, fewer

studies have documented disease response to excess potassium. Collectively, these

studies are inconclusive and many have failed to consider the effects of other anion

concentrations and nutrient balance (Prabhu et al., 2007).

Interactions with other nutrients may play a major role in disease development.

For example, diseases caused by Pythium spp. were shown to decrease in severity with

the addition of potassium, but increase when high levels of nitrogen were present

(Warren et al., 1975). The form or type of fertilizer may also play a role, as the addition

of potassium in the form of KCl reduced sudden death syndrome of soybean while

22

KNO3, K2PO4, and K2SO4 increased the severity of the disease (Sanogo & Yang, 2001).

The incidence of soybean root rot caused by Phytophthora sojae increased with the

addition of KCl but decreased with the addition of complete (20-20-20) fertilizer

(Pacumbaba et al., 1997).

23

Table 1.4. In soybean, additional potassium differentially influenced disease development caused by soil borne pathogens, as summarized from (Datnoff et al., 2007). Disease Pathogen Pathogen response to added potassium Citation Phytophthora stem and root rot

Phytophthora sojae

Increased with added K Canaday and Schmitthenner, 2010

Phytophthora stem and root rot

Phytophthora sojae

Increased with added KCl, but decreased if complete N/P/K was added

Pacumbaba et al., 1997

Seedling disease

Increased Canaday and Mengistu, 2008

Soybean cyst nematode

Heterodera glycines

Increased with added K Luedders et al., 1979

Sudden death syndrome

Fusarium virguliforme

Sometimes decreased with added K, depending on when potassium chloride was applied

Nelson et al., 2010



Inconsistent with added K, but apparently more susceptible in high fertility

Rupe et al., 2000



Sometimes decreased with added K: high rates of Cl reduced incidence, severity, and root infection of SDS, but cultivar dependent

Howard et al., 1999



Fertilizer form determined disease response: severity both increased and decreased depending on the form

Sanogo and Yang, 2001

24

Despite the abundance of literature documenting the relationship between

potassium application and disease development, continued research is necessary in the

context of soil borne soybean pathogens. Canaday and Schmitthenner (2010), Gladstone

and Moorman (1989), Pacumbaba et al. (1997), and Dirks et al. (1980) report the

incidence and severity of disease caused by oomycetes increases with the addition of

excess potassium. Because this is consistent with phosphorus response, information

regarding oomycete pathogens and identification of the species will not be repeated;

however, other studies suggest sudden death syndrome caused by Fusarium virguliforme

may also increase in incidence and severity with the addition of potassium (Rupe et al.,

2000; Sanogo & Yang, 2001).

In summary, the purpose of this study was to evaluate disease development in

soybean fertilized with excess levels of phosphorus and potassium growing in naturally

infested soil with high levels of inoculum and disease history. This research is important

for a number of reasons: (1) soil fertility recommendations for soybean have not been

changed in over 20 years, even though the yield has doubled and modern cultivars may

have slightly different nutrient demands that may require increased fertility levels; (2)

soil borne soybean pathogens have the potential to greatly reduce the stand count of

seedlings and year-end yield of the crop; (3) a properly balanced soil fertility

management strategy is essential for plant health and yield potential. However, the

relationship between soil fertility and pathogen response is not well understood. Though

conflicting reports exist regarding the significance and nature of this response, several

25

studies suggest disease incidence and severity will increase in response to excess fertility

(Canaday & Schmitthenner, 2010; Dirks et al., 1980; Gladstone & Moorman, 1989).

26

Chapter 2: Mini Review: Effects of Fertility on the Development of Soybean Diseases

Abstract

Optimum soil fertility can enhance soybean productivity and profitability.

Properly updated recommendations are necessary to balance monetary and environmental

costs with yield response. Though increased fertility levels may increase yield of modern

cultivars, fertilizer may have a secondary impact on disease development. This mini

review will explore literature documenting the effects of low or high levels of phosphorus

and potassium on seedling diseases and the sudden death syndrome/soybean cyst

nematode complex in soybean in the Midwest region of the United States. Higher levels

of soil fertility have been shown to increase seedling disease caused by some oomycete

pathogens as well as to both increase and decrease sudden death syndrome caused by

Fusarium virguliforme. Thus, further research is necessary to clarify inconsistencies in

the literature. This mini review serves to guide future studies of pathogen response to

fertilizer application essential to the re-assessment of soil fertility recommendations.

Introduction

Fertility recommendations for soybean in the Tri-State area of Ohio, Michigan,

and Indiana were last updated in 1995 (Vitosh et al., 1995). Since then, average yields in

Ohio have increased dramatically from 2.6 to 3.4 mt/ha (2.4 to 3.2 mt/ha nationally)

27

(American Soybean Association, 2015; National Agricultural Statistics Service, 2014).

There has been speculation that modern cultivars may require an increased nutrient

supply to satisfy nutrient demands due to higher yields, and current recommendations

may not be sufficient (National Agricultural Statistics Service, 2014). Although most

fertility regimes include nitrogen, phosphorus, and potassium, it should be noted nitrogen

is not typically added to soybean as studies have shown that increasing nitrogen levels

has a negligible effect on soybean yields due to nitrogen fixation by Rhizobium bacteria

(Grubinger et al., 1982). If increased fertility is shown to enhance soybean yield in

future state or regional surveys, several other biological and environmental factors should

also be considered before recommendations are revised. Specifically, the effects of

increased phosphorus and potassium on the development of soybean disease where they

are yield limiting warrants investigation.

Previous research has shown soil fertility may influence disease development in a

variety of crops caused by a variety of pathogens, especially those that are soil borne

(Datnoff et al., 2007). In soybean, soil borne pathogens have significantly reduced plant

health, productivity, and yield on an annual basis (Koenning and Wrather, 2010).

Bradley et al. (2015) reported the five most influential soybean diseases nationally in

2014 were all soil borne: soybean cyst nematode (125,154,024 bu), sudden death

syndrome (61,766,881 bu), seedling diseases (61,335,885 bu), Sclerotinia stem rot

(37,265,435 bu), and Phytophthora stem and root rot (32,224,121 bu). Therefore, a

review of the effect of increased fertility on these pathogens is essential.

28

Comparisons among studies which examined secondary effects of fertility on

plant diseases are often difficult due to variability in experimental designs, base fertility

levels, and environmental conditions. Studies differ in several ways 1) fertility in a

system may be considered deficient, adequate, or applied in excess 2) fertilizer may be

applied in a variety of forms possibly affecting salinity 3) if recorded, base fertility levels

are often in different units and may not be comparable despite unit conversion 4) base

levels (if recorded) rarely differentiate between available and total nutrient availability, as

not all forms are available for the plant to take up and 5) studies may be conducted with

inoculated or naturally infested soil in controlled or field conditions. The diversity of

these studies likely contributes to the diversity of results observed. It should be noted

that “excess fertility” indicates either fertilizer was applied at levels higher than

recommended by the state fertility recommendations or fertilizer was applied at levels

higher than what was considered appropriate by the authors of the respective study.

29

Figure 2.1. Studies which documented secondary effects of fertility on plant diseases were often difficult to compare due to variability in experimental designs, base fertility levels, and environmental conditions.

30

This mini review serves to compile, interpret, and synthesize previous literature

relevant to predicting the effect of soil fertility on soybean disease development.

Specifically, the review will focus on those studies which examined the effects of fertility

on the development of seedling disease and sudden death syndrome.

Influence of Phosphorus and Potassium on Seedling Disease of Soybean

Seedling disease incidence or severity was influenced by the addition of

phosphorus and potassium in several studies (Table 2.1). Collectively, these report

increased fertility levels in soybean fields affect and often enhance the development of

seedling diseases caused by oomycetes.

In a field study in Alabama where base fertility levels were considered adequate

in potassium and deficient in phosphorus, excess potassium treatments and both adequate

and excess phosphorus treatments were applied (Pacumbaba et al., 1997). Phosphorus

applied at excess levels in the form of superphosphate (0-46-0: CaH4P2O8) slightly

increased the incidence of Phytophthora from 7.4 to 9.4%. However, the addition of

potassium applied at excess levels in the form of muriate of potash (0-0-60: K2O)

increased the incidence of Phytophthora sojae significantly from 7.4 to 12.7%. Both

phosphorus and potassium applications, each at half rate of excess, decreased yield

significantly as compared with the application of complete fertilizer (20-20-20) (p<0.05).

Incidence of seedling disease increased with the application of excess potassium

in the form of KCl (Canaday & Schmitthenner, 2010). Field soil, naturally infested with

P. sojae, with adequate base levels of phosphorus and potassium was used in a growth

31

chamber study. Excess fertility was applied in the form of potassium salts (KCl, KNO2,

KNO3, K2SO4, KNO3, K2HPO4, KHCO3), potassium sulfate (K2SO4), and phosphorus

salts (Ca(H2PO4)2, K2HPO4, K2HPO4), each time without an effect on disease

development. However, when potassium chloride was added, the incidence of P. sojae

increased significantly (disease index of control= 12.5%; disease index of both rates of

KCl= 31.2%, 26.5%; p<0.05). The addition of chloride salts (NaCl, MgCl2, CaCl2,

AlCl3, FeCl2, FeCl3, SrCl2) consistently increased disease development while potassium

applied in other forms did not affect incidence. The authors proposed three confounding

factors: salinity stress, electrical conductivity, and calcium concentration.

In another study conducted in a soybean field in Canada, soil fertility applied at

excessive levels also increased seedling disease caused by P. sojae (Dirks et al., 1980).

Though base fertility levels were not noted, one type of complete fertilizer (8-32-16

NPK) was applied at the recommended rate for the area, and in excess levels (2 and 3

times the recommended rate). The incidence of root rot increased significantly as fertility

rates increased (p= 0.052). Plots with treatments of 0, 224, 448, and 672 kg/ha fertilizer

averaged 3.2, 23.0, 32.3, and 41.3% diseased plants respectively. The study also

evaluated disease incidence at varying distances from drainage and reported disease

incidence increased in poorly-drained areas. Within each fertility treatment, disease

incidence increased progressively as distance from drainage increased, but not

significantly at 672 kg/ha suggesting a drain distance x fertilizer interaction. Though

poorly drained soils increased disease incidence caused by P. sojae, disease levels in

plots with highly excessive fertility levels were too high to note any drainage response.

32

Although proper drainage reduces disease, proper fertility rates also play a major role in

disease development.

In contrast, (Sugimoto et al., 2007) found the application of 2.47 to 24.7 mM

potassium nitrate (KNO3) in combination with 0.1 to 10.2 mM calcium chloride (CaCl2)

significantly inhibited P. sojae infection in vitro. A previous study by the same authors

found the release of P. sojae zoospores was significantly decreased with the addition of 4

to 30 mM CaCl2, though a subsequent study found a concentration of 20 to 30 mM KNO3

decreased disease incidence without the application of calcium (Sugimoto et al., 2005;

Sugimoto et al., 2009). An external calcium source also played a role in P. sojae

development, specifically by stimulating direct germination of zoospores while in the

developing sporangia (Xu and Morris, 1998).

33

Table 2.1. Increased fertility levels enhanced seedling disease of soybean caused by oomycetes in three studies.

Study Pacumbaba et al. 1997 Canaday and Schmitthenner 2010 Dirks et al 1980 Base level phosphorus

25 ppm (measured before fertilizers were applied only during the first year)

Vickery: 74 kg/ha Hoytville: 76 kg/ha Van Wert: 75 kg/ha

not noted

Base level potassium

122 ppm (measured before fertilizers were applied only during the first year)

Vickery: 482 kg/ha Hoytville: 473 kg/ha Van Wert: 306 kg/ha

not noted

Soil chemistry

Decatur silty clay loam (Rhodic paleudult), base level of nitrogen (only measured first year): 45 ppm.

-Fulton silty clay (fine, illitic, mesic Aeric Ochraqualf) from Vickery, OH. Organic matter: 2.7%, pH 6.7, CEC 0.20 meq/g -Hoytville silty clay (fine, illitic, mesic, Mollic Ochraqualf) from Hotyville, OH. Organic matter: 5.1%, pH 6.9, CEC 0.21 meq/g – Blount silt loam (fine, illitic, mesic, Aeric Ochraqulf) from Van Wert, OH. Organic matter: 3.5%, pH 6.6, CEC 0.15 meq/g

not noted

Fertility treatments: rate and form

Five rates for each of four fertilizers: Fertilizers: complete (20-20-20), ammonium nitrate (34-0-0), superphosphate (0-46-0), muriate of potash (0-0-60) Rates: 0 kg/ha, 50 kg/ha, 100 kg/ha, 150 kg/ha, 200 kg/ha

-potassium salts applied at 150 to 400 µg of K/g soil -phosphorus salts at 20 to 317 µg P/g soil -A variety of sulfate salts, chloride salts, and ammonium salts at multiple rates

One fertilizer (8-32-16 NPK) applied at 3 rates: 224, 448, and 672 kg/ha

Base levels represented a deficient or adequate system before treatmenta

Deficient in phosphorus, adequate in potassium (Auburn University Soil Testing Laboratory recommended application of 101 kg/ha N, 67 kg/ha P, and 0 kg/ha K)

Vickery: adequate P, excess K Hoytville: adequate P, excess K Van Wert: adequate P and K

Unknown base levels, but complete fertilizer was applied at the recommended rate for the area (224 kg/ha), double the recommended rate (448 kg/ha), and triple the recommended rate (672 kg/ha)

Inoculated or natural

Natural Natural with P. sojae

Natural with P. sojae

Field or controlled conditions

Field (Alabama) Growth chamber Field (Ontario, Canada)


34

Table 2.1 continued Study Pacumbaba et al. 1997 Canaday and Schmitthenner 2010 Dirks et al 1980 Disease response to fertilityb

-Plants fertilized with muriate of potash had higher incidence of PRSR and SMV, followed by plants fertilized with superphosphate. -Complete and superphosphate fertilizers lowered the incidence of SMV at application rates of 0-100kg/ha, then increased up to 200 kg/ha. -BBS incidence and SCN counts were not affected by either type or rate of fertilizer. -Application of any of the treatments reduced SSC incidence.

-Application of KCl at 150-400 µg of K per gram of dry soil increased the incidence of PRSR with Fulton soil. -Other potassium salts at 150 to 400 µg K, phosphorus salts at 20-317 µg P, and sulfate salts of K, Ca, Mg, Na, and Al at 491 µg of sulfate per gram of soil did not affect disease incidence. -Application of chloride salts of K, Na, Mg, Ca, NH4, Al, Fe, and Sr at 250 µg of Cl per gram of soil increased PRSR incidence. Disease was also increased at 304 µg Cl per gram of soil without extra flooding with water. -Application of ammonium salts also increased PRSR incidence.

-The incidence of root rot increased significantly as fertility rates increased (p= 0.0521). Plots with treatments of 0, 224, 448, and 672 kg/ha complete fertilizer (8-32-16 NPK) averaged 3.2, 23.0, 32.3, and 41.3% diseased plants respectively.

Notes -repeated every year for 3 years -fertilizers applied one week before planting -split plot design included two fertilizer application methods: broadcast and hand hoed

-To test salinity effect on plants: the addition of 450 µg Cl per gram of soil applied as NaCl to pasteurized, pathogen-free soil. Increased salinity did not effect germination, emergence, transpiration, height, and dry weight of plants. -The increase of PRSR incidence with the addition of KCl may be due to chloride.

-For all fertility treatments, disease incidence increased progressively as distance from drainage increased, but not significantly at 672 kg/ha. Therefore, there is a drain distance x fertilizer interaction suggesting drainage lowers disease incidence up to twice the recommended fertility rate while fertilizer applied at triple the rate negated drainage response.

aBase levels were considered deficient if they contained less nutrient than recommended by either respective author(s) or Tri-State Fertility Recommendations (Vitosh et al., 1995). If base levels were already within the recommended range, the system was considered adequately supplied and the application of treatments created a system treated with excess fertilizer. bDisease abbreviations include Phytophthora root and stem rot (PRSR), Soybean stem canker (SSC), Bacterial blight of soybean (BBS), Soybean mosaic virus (SMV), and soybean cyst nematode (SCN).

35

Influence of Soil Fertility on Sudden Death Syndrome of Soybean

The development of sudden death syndrome is dependent on cultivar, level of SCN,

and environment, among other factors (Arias et al., 2013a; Gongora-Canul et al., 2012).

Previous literature regarding the effect of soil fertility on SDS is complex and inconsistent,

as both phosphorus and potassium were shown to effect SDS development differently

under a variety of conditions. Several reoccurring themes are described below.

Adequate fertility enhances overall plant health and vigor and decreases SDS incidence

For a number of crops including soybean, a clear association between balanced and

adequate fertility and overall crop health has previously been reported (Fageria & Baligar,

1997; Krupinsky et al., 2002). Higher levels of fungistatic substances (including phenolic

compounds and flavonoids in epidermal cells) are present in plants with adequate fertility,

likely due to increased vigor (Prabhu et al., 2007). Therefore, proper fertility may improve

physiological resistance to a variety of pathogens by reducing overall plant stress (Fageria

& Baligar, 1997; Krupinsky et al., 2002).

In addition to improving overall health, increased fertility levels, specifically

phosphorus, were also shown to accelerate time to maturity (Prabhu et al., 2007). Because

soybean seedlings become less susceptible to infection by F. virguliforme with age

(Gongora-Canul & Leandro, 2011a; Wrather et al., 1995), additional fertility may reduce

disease development.

Cultivars play a larger role in SDS development than soil fertility

36

Cultivar selection played a larger role in SDS susceptibility than fertility treatment

in several studies (Datnoff et al., 2007; Prabhu et al., 2007; Sanogo & Yang, 2001).

Prabhu et al. (2007) reported the effect of phosphorus application (in both adequate and

excess rates) could be measured in moderately susceptible cultivars. Sudden death

syndrome developed inconsistently based on cultivar in multiple studies (Howard et al.,

1999; Rupe et al., 2000), suggesting genetics plays a larger role in susceptibility than soil

fertility (Datnoff et al., 2007; Prabhu et al., 2007). When Howard et al. (1999) used a

highly susceptible variety, significant yield differences occurred between varieties in 2 of 3

years, suggesting fertility affects may be seen differentially based on cultivar. Therefore,

breeding SDS-resistant cultivars remains an important, albeit difficult, management

strategy.

Soybean cyst nematode (SCN) may or may not be affected by soil fertility

Though Fusarium virguliforme can independently infect soybean, SCN and SDS

are often found in combination. The relationship between SCN infestation and SDS

severity is controversial (Brzostowski et al., 2014; Gao et al., 2006; Hartman et al., 2015b;

Marburger et al., 2014; Roy et al., 1989). Despite the status of the potential interaction, the

aforementioned studies all report fields are often infested with both pathogens. Therefore,

the effect of fertility on SCN populations may also influence SDS development and

warrants further investigation (Lawrence et al., 1988; Westphal & Xing, 2011).

Soybean cyst nematode populations decreased significantly (p= 0.01) as potassium

increased in a field study by Luedders et al. (1979). In this study, phosphorus levels were

37

high (over 100 ppm), potassium levels were low (25 to 30 ppm), and potassium was

applied incrementally to reach levels considered excessive (160 ppm) in a system with a

pH of 6.2 and CEC of 7.2. SCN populations were measured as cysts/100 g soil and

cysts/plant and both values decreased significantly as potassium applied in two forms

increased (p= 0.01) (Luedders et al., 1979). In a 7-year field study, Howard et al. (1998)

also reported SCN populations decreased as phosphorus and potassium rates increased

incrementally. In contrast, Rupe et al. (2000) reported an increase in SCN with increasing

KCl levels for some cultivars in a 2-year field study.

In addition to fertility rate, other factors may influence SCN population densities

including but not limited to fertilizer type (Pacumbaba et al., 1997), pH (Pedersen et al.,

2010; Tylka et al., 1998), tillage regime (Howard et al., 1998; Westphal et al., 2009), and

cultivar (Hanson et al., 1988). However, Niblack et al. (2006) stated temperature,

moisture, and host genetics have the greatest impact on SCN population density.

Type of fertilizer may affect SDS development

The type and source of fertilizer may play a major role in SDS development due to

nutrient interactions. Nutrients may be added in a variety of different forms (for example:

potassium chloride, potassium phosphate, potassium sulfate, etc.), and additional elements

within each compound may alter the soil chemistry in a way that effects pH, cation

exchange capacity, or other variables. The role of potassium and phosphorus in SDS

development should be examined in conjunction with other mineral elements.

38

Sanogo and Yang (2001) found fertilizer type affected sudden death syndrome

response in separate growth chamber and lab components. In growth chamber studies with

excess phosphorus and potassium base fertility levels, the addition of KNO3, K2PO4, and

K2SO4 increased SDS severity by 45%, 32%, and 43%, respectively, while the addition of

potassium in the form of KCl decreased the severity by 36% (Sanogo & Yang, 2001). The

dual effects of potassium and phosphorus amendments were studied on F. virguliforme

isolates on media. Mycelial linear growth was enhanced by potassium nitrate (15%),

potassium phosphate (22%), and sodium phosphate (25%), but not with potassium sulfate,

calcium phosphate, or potassium chloride (Sanogo & Yang, 2001). Colony area was

approximately 2.5 times greater in media with a pH of 8.2 than media with a pH of 5.7,

though germination of macroconidia was not affected (Sanogo & Yang, 2001). This study

suggested pH and salinity, in addition to nutrient source, may contribute to SDS disease

development. Howard et al. (1999) also reported a reduction in SDS incidence and

severity when relatively high rates of chloride were applied.

Fertility affects SDS development directly

Studies which evaluated the effect of fertilizer on the pathogen directly were

inconclusive (Datnoff et al., 2007; Hartman et al., 2015b; Howard et al., 1999). A field

study in Iowa showed no association between SDS severity and phosphorus or potassium

application (Scherm et al., 1998). Sudden death syndrome severity was also not

significantly different from the control when pre-plant potassium chloride was applied

(Nelson et al., 2010). Though SDS responded inconsistently to KCl applications in the

39

field, plants appeared more susceptible when potassium chloride was applied at 2240

kg/ha, levels considered excessive (Rupe et al., 2000).

Influence of Soil Fertility on other soybean pathogens

In addition to seedling diseases and sudden death syndrome, previous studies have

shown fertility may affect other diseases of soybean (Table 2.2) or related pathogens of

other hosts (Table 2.3) (Datnoff et al., 2007). Collectively, the literature reported a highly

variable disease response, likely due in part to equally diverse experimental designs.

40

Table 2.2. Previous literature reports several diseases of soybean are affected by soil fertility.

Pathogen Disease Nutrient Base levels represented a deficient or adequate system before treatmenta

Influence on Diseaseb Citation

Cercospora kikuchii

Purple seed stain

Potassium Not noted Decrease Camper and Lutz, 1977

Diaporthe sojae

Pod rot Potassium Not noted No effect Svec et al., 1976

Diaporthe sojae

Pod rot Potassium Varied by study

Decrease Camper and Lutz, 1977; Crittenden and Svec, 1974; Jeffers et al., 1982



Potassium Not noted Sometimes decreased with added K, depended on when KCl was applied. Pre-plant did not reduce disease, application post-planting did

Nelson et al., 2010



Potassium Deficient and adequate

Inconsistent with added K, but appeared more susceptible in high fertility

Rupe et al. 2000




sometimes decreased with added K: high rates of Cl reduced incidence, severity, and root infection of SDS, but cultivar dependent

Howard et al., 1999




Increased or decreased depending on potassium form

Sanogo and Yang, 2001

Heterodera glycines

Soybean cyst nematode

Potassium Adequate P, deficient K

Increased with added K

Luedders et al., 1979

Macrophomina phaseolina

Charcoal rot

Potassium Adequate for both P and K

No effect Canaday and Mengistu, 2007


41

Table 2.2 continued Pathogen Disease Nutrient Base levels

represented a deficient or adequate system before treatmenta

Influence on Diseaseb Citation

Melodogyne incognita

Root knot nematode

Phosphorus Not noted Decreased Carling et al., 1989

Meloidogyne incognita

Root knot nematode

Potassium Not noted Increased Ismail and Saxena, 1977

Phytophthora sojae [sensu P. megasperma var. sojae]

Root rot Potassium Deficient in P, adequate in K

Increased Pacumbaba et al., 1997

Phytophthora sojae

Root rot Phosphorus and potassium

Deficient and adequate

Disease increased with added K, no effect of P

Canaday and Schmitthenner, 2010

Phytophthora sojae

Root rot Phosphorus and potassium

Deficient in P, adequate in K

Increased with added K, but decreased if complete N/P/K was added

Pacumbaba et al., 1997

Rhizoctonia solani

Root rot Phosphorus Not noted Decreased Castano and Kernkamp, 1956

Soybean Mosaic Virus

Soybean Mosaic Virus

Potassium Deficient in P, adequate in K

Increased Pacumbaba et al., 1997

aBase levels were considered deficient if they contained less nutrient than recommended by the respective author(s). If base levels were already within the recommended range, the system was considered adequately supplied and the application of treatments created a system treated with excess fertilizer. bInfluence may be represented in either influence, severity, or disease index (influence x severity).

42

Table 2.3. Soil fertility affects pathogens of other hosts closely related to those that may contribute to seedling disease or sudden death syndrome in soybean.

Host Pathogen Disease Nutrient Base levels represented a deficient or adequate system before treatmenta

Influence on Diseaseb

Citation

Conifer Fusarium oxysporum

Damping-off

Phosphorus Adequate Increased Sinclair et al., 1975

Cucumber Rhizoctonia solani

Damping-off

Phosphorus Not noted Decreased Prabhu et al., 2007

Geranium Pythium ultimum

Root rot Potassium Excess Increased Gladstone and Moorman, 1989

Linseed Fusarium oxysporum

Not specified Potassium Not noted Increased Ghorbani et al., 2008; Sing, 1999

Peas Rhizoctonia solani

Damping-off Phosphorus Deficient Decreased Prabhu et al., 2007; Srihuttagum and Sivasithamparam, 1991

Potato Phytophthora infestans

Late blight Phosphorus Not noted Conflicting reports

Keinath, 1989; Prabhu et al., 2007

Tomato and green peppers

Phytophthora spp.

Phytophthora root and crown rot

Phosphorus Deficient Decreased Förster et al., 1998

Wheat Pythium spp. Root rot Phosphorus Not noted Decreased Huber, 1980 aBase levels were considered deficient if they contained less nutrient than recommended by the respective author(s). If base levels were already within the recommended range, the system was considered adequately supplied and the application of treatments created a system treated with excess fertilizer. bInfluence may be represented in either influence, severity, or disease index (influence x severity).

43

Conclusion

Although the relationship between soil fertility and pathogen response is complex

and not well understood, fertility has been shown through a number of studies to have

secondary effects on soil borne pathogens. This review primarily focuses on work relevant

to soybean diseases, specifically seedling diseases and sudden death syndrome, though it

also introduces several studies of closely related pathogens that may provide additional

valuable insight. The wide diversity of experimental designs likely contributed to the

equally diverse findings. Collectively, these studies suggest soil fertility may significantly

impact disease development in soybean. Specifically, enhanced fertility may enhance

disease, especially for seedling diseases of soybean. However, pathogen response to

fertility is not well understood and warrants future research. In order to compare the

studies more effectively, future research should note base fertility levels, soil chemistry

(including pH, CEC, organic matter %, etc.), whether the fertilizer is applied to deficient or

adequate systems, fertilizer rate and form, and environmental conditions, among other

variables. Ideally, some continuity should exist between future experimental designs and

this review has outlined a structure of factors to consider when designing experiments. The

effect of soil fertility on pathogens causing disease is essential to consider before revising

fertility recommendations for any crop system.

44

Chapter 3: Effects of Increased Fertility on the Development of Seedling Diseases of Soybean

Introduction

Seedling disease has the potential to dramatically reduce soybean stand and is

consistently ranked one of the highest yield-reducing diseases (Bradley et al., 2015;

Koenning and Wrather, 2010). In 2014, seedling disease ranked third most-damaging in

the United States and caused a yield loss of 1,669,317 mt. Only soybean cyst nematode

and sudden death syndrome reduced yield more at 3,406,192 mt and 1,681,047 mt

respectively (Bradley et al., 2015).

Symptoms of seedling disease range from seed rot to damping-off and cause

reduced stand (Grau et al. 2004). If seed rot has not prevented germination entirely,

emerged seedlings may have lesions on the roots, hypocotyl, or cotyledons. Often, the

stem disintegrates at the base of the seedling, causing damping-off symptoms. Overall root

decay may cause the root to turn tan to dark brown, black, or brick red (Grau et al. 2004).

Root necrosis may reduce the number of lateral roots on older seedlings, reducing overall

nutrient and water uptake. Though infected plants may be scattered throughout the field,

infection is most common in areas with poor drainage (Dirks et al., 1980; Grau et al., 2004;

Yang, 1999).

45

Figure 3.1. Symptoms of Pythium or Phytophthora infection may include lesions on the root, stem, or hypocotyls resulting in damping-off or reduced stand.

Seedling disease may be caused by several species, either alone or in combination

(Grau et al., 2004a). It is often caused by a complex of species including Pythium spp.,

Phytophthora sojae, Phytophthora sansomeana, Macrophomina phaseolina, Fusarium

spp., and Rhizoctonia solani, among others (Broders et al., 2007b; Grau et al., 2004b; Rizvi

& Yang, 1996; Schlub et al., 1981; Tachibana, 1971; Tachibana et al., 1971). Though

most Fusarium species are not pathogenic, some are secondary colonizers (Arias et al.,

2013b; Broders et al., 2007a). Pathogenicity varies among genera and a 2-year field survey

in Iowa from over 50 fields each year found 94% of 82 Pythium isolates, 21% of 22

Fusarium isolates, and 75% of 32 Rhizoctonia solani isolates collected were pathogenic

(Rizvi & Yang, 1996). In a soil baiting assay of soil from 3 counties in Ohio, Dorrance et

al. (2004) reported a range of pathogenicity within and between five Pythium species.

Oomycete pathogens including Pythium and Phytophthora species were identified

as the primary cause of seedling disease of soybean in Iowa (Rizvi & Yang, 1996) and

Ohio (Broders et al., 2007a). Over 30 different species of Pythium are known to infect

soybean, some of which are also able to infect corn (Broders et al., 2007a; Broders et al.,

46

2009; Dorrance et al., 2004). A table outlining the oomycete species known to infect

soybean in Ohio is included in Chapter 1 (Table 1.1).

Pythium and Phytophthora overwinter in soil or plant debris as oospores. These

survival structures provide protection from harsh environmental conditions for many years.

Oospores may either germinate directly or produce sporangia that release zoospores that

swim to host tissue and encyst (Grau et al. 2004). Thus, saturated soil conditions favor

infection. The optimal temperature for infection varies by species, albeit cooler

temperatures are often considered more conducive (Mattheisen et al., 2016; Wei et al.,

2010; Yang, 1999).

Several studies have documented an increase in seedling disease incidence or

severity in response to higher than recommended fertility levels. Specifically, the addition

of potash increased the incidence of Phytophthora stem and root rot in soybean in the field

(Pacumbaba et al., 1997), the addition of potassium chloride increased soybean seedling

disease incidence in soil naturally infested with P. sojae (Canaday & Schmitthenner, 2010),

and the addition of complete fertilizer increased Phytophthora root rot significantly in the

field (Dirks et al., 1980). Collectively, this work suggests increased fertility levels may

enhance seedling disease caused by oomycetes. See Chapter 2 for a more thorough review

of this literature.

The objective of this study was to evaluate the effects of higher than recommended

rates of phosphorus and potassium on the development of seedling disease in soybean. Our

study included three approaches (i) stand count and yield data were collected and analyzed

from field studies where fertilizer was added; (ii) diseased seedlings growing in infested

47

fields treated with fertilizer were surveyed at the VC growth stage and pathogens were

isolated from root tissue and identified and; (iii) greenhouse experiments designed to

replicate field studies were conducted with infested field soil.

Materials and Methods

Field Experiments

This study was completed over 2 years from fields in Van Wert (2014 and 2015),

Defiance (2014 and 2015), and Wayne (2015) counties in Ohio for a total of 5 site

locations. All field locations had a history of seedling disease and were poorly drained.

Four fertility treatments were applied to the soil surface at planting, including 112 kg/ha

diammonium phosphate (DAP) (18-46-0: 46% P2O5), 112 kg/ha potash (0-0-60: 60% K2O),

112 kg/ha DAP plus 112 kg/ha potash, and a nontreated control (no fertilizer). It should be

noted these rates are higher than recommended by current recommendations and fertility

levels are thus referred to as being applied in excess. The study was arranged in a

randomized complete block design with 6 replications at Van Wert and Defiance locations

and 4 replications at the Wayne location. One cultivar was used for all field studies, AGI

31R2Y2 3102N (Pond Seed Co., Scott, OH) which has SCN resistance and no seed

treatment. Prior to planting and fertilizer application, soil from each field was submitted to

the Service Testing and Research (STAR) Laboratory (OARDC, The Ohio State

University, Wooster, OH) (Table 3.1).

Stand data were collected at the VC/V1 and R6/R7 growth stage at all fields by

counting the number of plants in the second 9 m row of the 4-row plot. At the Van Wert

48

2015 field site, the number of seedlings with damping-off symptoms were counted for a 1.8

m section of the second 9 m row and multiplied by five to estimate the number of

symptomatic plants per row. At all fields, the second and third row of each plot were

harvested for yield and adjusted for moisture content (standardized at 13.5%).

Seedling disease survey

The Defiance and Van Wert sites were sampled for seedling pathogens in 2015. At

the VC growth stage, five symptomatic plants per plot were selected from the first and

fourth rows. Plants were stored in a cooler for transport back to the lab, and stored at 4˚C

overnight.

Roots were processed within 24 h of collection. Plants were first washed

thoroughly with water and surface sterilized (5% ethanol solution for 15 to 20 seconds, two

rinses of sterile deionized water). Two pieces of root tissue per plant (each approximately

5 mm) were cut from margins of lesions or arbitrarily if asymptomatic. Pieces were plated

onto potato carrot agar (PCA), and an oomycete-selective media, PIBNC (V8-media+

pentachloronitrobenzene, iprodione, benlate, neomycin sulfate, and chloramphenicol) for a

total of 10 plates per plot (Appendix B: Table B.1). A hyphal tip of mycelium from the

colony of the predominant morphology was transferred to PCA after approximately five

days and this was repeated if necessary to purify the colony (Appendix B: Figure B.1).

Cultures were stored long term in PCA vials at 4˚C after incubation at room temperature

for 3 weeks.

49

Isolate identification

Each pure culture was observed under a microscope at 100 to 400x for morphologic

characteristics (Appendix J). Oomycetes were identified through the observation of

coenocytic mycelium, sporangia, or oospores and further identified to species through ITS

sequencing and BLAST analysis (Appendix C). Each isolate was transferred to fresh PCA

and allowed to grow for approximately 5 days in the dark. Approximately 10 plugs (5 mm

diameter) were transferred to V8 liquid broth (approximately 75 mL in 125 mL Erlenmeyer

flask) and grown for approximately five days or until mycelium covered at least two-thirds

of the surface of the broth in the dark. Isolates varied in growth rate; those later identified

as Pythium usually required about 4 days to reach this point whereas Phytophthora isolates

usually required about 7 days. Mycelia were harvested by filtration with a piece of sterile

P5 filter paper (Fisher Scientific) set in a Buchner funnel attached to a flask equipped for

vacuum suction. Mycelia were ground in liquid nitrogen with a mortar and pestle

(CoorsTek, Inc., Golden, CO) and approximately 200 mg was immediately put into a sterile

2 mL eppendorf tube and thoroughly mixed with 800 mL digestion buffer (10 mM

Tris/HCl pH 8.0, 50 mM EDTA, 0.5% SDS, 0.5% Triton X-100, 0.5% Tween 20)

(Appendix D). DNA from each isolate was extracted using the protocol from Zelaya-

Molina et al., (2011). Within the same 2 mL Eppendorf tube, 2 µL of 20mg/mL of

Proteinase K solution (Amresco, Solon, OH) was added. The samples were mixed by

inverting the tubes several times and incubated for 30 min at 55˚C (Isotemp, Fisher

Scientific), mixing gently by inversion every 10 min. After samples were allowed to cool

for several minutes, 800 µL chloroform/isoamyl alcohol (24:1, vol/vol) was added to each

50

sample. Samples were shaken by hand for five minutes until a complete milky-white

emulsion was formed and centrifuged for 10 min at 14,000 rpm using an Eppendorf 5424

centrifuge (Hamburg, Germany). The supernatant was transferred to a new sterile 2 mL

microcentrifuge tube and 1 mL cold isopropanol was added, and the tube was inverted

several times to mix gently. Samples were centrifuged at 14,000 rpm for 10 min. The

supernatant was discarded and the remaining pellets were washed first with 1 mL 70%

(vol/vol) ethanol then with 1 mL absolute ethanol. Once pellets dried completely, they

were resuspended with 100 µL warm EB buffer (Qiagen Sciences, Germantown, MD) and

stored at 4˚C overnight to dissolve. Next, 1 µL of 10 mg/mL Ribonuclease A (Amresco,

Solon, OH) was added to the sample and incubated at 37˚C for 1 h. The quality and

quantity of DNA was evaluated using a NanoDrop ND-1000 spectrophotometer

(NanoDrop Technologies, Wilmington, DE) to measure concentration (ng/µL) and

A260/A280 and A260/A230 ratios. DNA was diluted to 50 ng/µL using nuclease-free sterile

water and stored at -20˚C.

The internal transcribed spacer (ITS) region was then amplified and sequenced

(White et al., 1990). A 50 µL PCR reaction mix contained 24.5 µL sterile nuclease-free

water, 10.0 µL PCR buffer (Promega Corp., Madison, WI), 3.0 µL of 25 mM MgCl2

(Promega Corp., Madison, WI), 2.0 µL of dNTPs (Promega Corp., Madison, WI), 0.5 µL

Taq polymerase (Promega Corp., Madison, WI), 2.0 µL ITS1 primer

(TCCGTAGGTGAACCTGCG), 2.0 µL ITS4 primer (TCCTCCGCTTATTGATATGC),

and 6.0 µL sample DNA (at 50 ng/µL). For amplification of the ITS region, the primers

ITS1 and ITS4 were used (White et al., 1990). The Fisher Biotech large horizontal gel

51

system was used when visualizing bands with the GelRed Nucleic Acid Stain and 1 kb

DNA ladder (New England Biolabs). Next, 10 µL of PCR product was purified with 4 µL

of ExoSAP-IT (Affymetrix, Cleveland, OH) and this mixture was incubated in the

thermocycler at 37˚C for 15 min immediately followed by 15 min of incubation at 80˚C.

The purified PCR amplicons were sent to the Molecular and Cellular Imaging

Center at the Ohio Agricultural Research and Development Center for sequencing with the

ThermoFisher Scientific ABI Prism 3100x1 Genetic Analyzer. Raw sequences were edited

and contigs were assembled from both the forward and reverse sequences with CodonCode

version 5.1.3. Each contig sequence was submitted to a BLAST search of the National

Center for Biotechnology Information database (http://ncbi.nlm.nih.gov) for species

identification.

Greenhouse experiments

Soil was collected from Van Wert and Defiance sites on 26 September 2015, from

the same locations used for field studies. Soil was collected from twelve points divided

between two areas of the field separated by approximately 30 m and at a uniform depth of

15 to 20 cm. The soil from each area was used in independent greenhouse studies

representing the first and second trial. The third trial used the remaining soil from both

areas of the field which was thoroughly mixed together. Soil was stored in 10 gallon

plastic bins and allowed to partially dry for 1 week, after which the bins were covered and

stored at room temperature. A soil grinder (Iler Improved, The Fen Machine Co.,

Cleveland, OH) was used to grind clay clumps.

52

Five treatments consisted of fertility regimes calculated to match the rate applied in

the field, including 112 kg/ha DAP (18-46-0: 46% P2O5), 112 kg/ha potash (0-0-60: 60%

K2O), 112 kg/ha DAP plus 112 kg/ha potash, a control (no fertilizer), and a steamed soil

control (no fertilizer) as a check for seed viability and general greenhouse conditions.

Coffee filters were placed in the bottoms of 15 cm pots and then filled with approximately

1.4 kg soil per pot, 2 pots per treatment and 6 replicates. Pots were placed in a tub with

deionized water for 24 h and drained until the moist soil formed cracks when the pot was

squeezed slightly and decompressed (24 to 48 h), at which point they were incubated in

plastic bags at room temperature (18 to 21˚C) for 2 weeks. Fifteen seeds of a susceptible

cultivar (Sloan 2014) were planted in each pot. For the first trial, pots were experimentally

flooded after 3 days for 24 hours. Plants were watered twice daily with deionized water

and although greenhouse temperatures were set to remain between 14 to 18˚C, greenhouse

renovations complicated temperature regulation. Temperatures generally ranged from 20

to 24˚C in trial 1, 17 to 23˚C in trial 2, and 17 to 18˚C in trial 3 (Appendix I: Table I.1).

Treatments were arranged in a randomized complete block design. The experiment

was performed three times for both Defiance and Van Wert, occurring in November 2015,

February 2016, and March 2016.

Data for stand were collected at 7 and 14 days after planting. When seedlings

reached the VC growth stage, final stand was recorded and roots were washed with water

and rated (Appendix H: Figure H.1). Fresh root and plant weights were also collected.

Statistical analysis

53

All data were analyzed with Statistical Analysis Software (SAS, version 9.4).

Homogeneity of variance existed for all parameters investigated and analyses of variance

(ANOVA) were carried out for each field or greenhouse trial separately. Residual plots of

the data sets showed major assumptions were satisfied and thus ANOVA could be used

without prior transformations. Treatments were compared with the Fisher’s protected least

significant difference (LSD) test at p ≤ 0.05. For greenhouse trials, the steamed soil control

was removed from the analysis.

54

Table 3.1. Soil test resultsa from samples collected prior to planting from Ohio soybean fields with a known history of seedling disease.

Soil Characteristics Van Wert (2014)

Van Wert (2015)

Defiance (2014)

Defiance (2015)

Wayne (2015)

Paulding clay

Paulding clay

Latty silty clay

Latty silty clay

Canfield silt loam

Soil pH 5.8 6.0 5.9 6.4 6.4 Buffer pH 6.5 6.7 6.6 6.7 6.9 Organic Matter (%) 2.9 2.5 3.1 2.8 1.5 Phosphorus (m3-ppm) 41 15.9 32 61.8 79.8 Potassium (m3-ppm) 248 207.8 282 282.3 144.5 CEC 21.1 18.9 21 20.8 7.3 K Saturation (%) 2.5 2.4 2.9 3.0 4.3 Bray P1 (lbs/A) 30.6 na 23.3 na na Bray P1 (ppm) 15.3 na 11.65 na na aSoil was tested in the Service Testing and Research (STAR) Laboratory through The Ohio State University.

55

Results

Field Experiments

The 2014 season brought widespread damping-off throughout Ohio. Cool

temperatures (4 to 10˚C) and excess rainfall (over 5 cm) within a week of planting provided

conditions conducive to seedling disease development (Eyre et al., 2015b). Record

precipitation levels in 2015 created suboptimal conditions at all field sites and standing

water was documented at the Van Wert location (Appendix E: Figure E.1). Defiance and

Van Wert locations received 21.6 and 37.4 cm of rain in June, respectively. June 2015

represented the wettest month on record since records began in 1893 for Van Wert and the

wettest June on record since records began in 1998 for Defiance (National Weather

Service, 2015). A seedcorn maggot infestation at the 2015 Wayne Co. site prevented the

field from ultimately being included in the survey, despite initial sampling at the VC stage

(Eyre et al., 2015a) (Appendix E: Figure E.2; Appendix J).

No significant differences were found between fertility treatments for early stand,

final stand, or yield at the five field sites, with the exception of a slightly significant final

stand increase for plots treated with potassium at Wayne in 2015 (p=0.078) (Table 3.2). At

the Van Wert and Defiance sites, the addition of fertility did not improve yields either year.

At Van Wert in 2015, a significantly higher number of seedlings were affected by

damping-off in plots treated with potassium compared with the nontreated control,

phosphorus, or phosphorus and potassium (p= 0.041) (Figure 3.2).

56

Survey at VC growth stage

There were more than 700 isolates recovered from seedlings collected from

Defiance, Van Wert, Wayne, and Wood sites (Appendix J). After all isolates were initially

cleaned and morphologically observed, those taken from Wayne were not identified further

because seedling disease symptoms at this field were likely confounded by the seedcorn

maggot infestation. The Wood isolates were also removed from the analysis due to the

high proportion of Fusarium species. Between Defiance and Van Wert samples, oospores

were observed in 140 of the isolates collected from all treatments (71 isolates from

Defiance and 69 isolates from Van Wert) (Table 3.8). Although species identification

through ITS sequencing was attempted for all 140 isolates, only 69 were identified as

Pythium or Phytophthora. Thirty three isolates representing 12 species and 36 isolates

representing 13 species were recovered from seedlings collected at Defiance and Van Wert,

respectively. Collectively, oomycetes were recovered from all fertility treatments.

Greenhouse Experiments

In greenhouse assays with a steamed soil control and comparable fertility treatments

on field soil, dramatically lower stands and weights consistently occurred in infested field

soil compared with the steamed soil. Of the 15 seeds planted in each pot, stand ranged

from 10.1 to 13.8 plants in the steamed soil control. However, final stand counts in the

treated field soil was dramatically lower and treatment means for Defiance trials were 8.60,

2.23, and 1.96 while Van Wert trials were 8.40, 0.44, and 0.94 (Table 3.11). High

emergence in the steamed soil controls indicated greenhouse conditions were conducive,

57

albeit not ideal, for plant growth. High disease pressure in the field soil likely contributed

to the lack of clear or consistent trends (Table 3.10).

Oomycetes were re-isolated from seedlings grown in every treatment from both

fields during trial 2. Oospores were observed at 100 to 400x in the roots of seedlings

grown in every treatment for both fields in trial 3 confirming the presence of oomycetes

(Appendix H: Figure H.2).

Treatment means for stand were slightly significant in three assays (p= 0.111, p=

0.054, p= 0.069) suggesting a possible trend in which excess fertility may contribute to a

decrease in stand (Table 3.11). Treatment means for root disease severity ratings were

significant in one (p= 0.045) and slightly significant in two assays (p= 0.092, p= 0.111)

suggesting fertility may also increase root rot, as the nontreated control had less disease

than at least one fertilizer treatment (Table 3.12). Treatment means for root weights were

significantly lower in pots treated with fertility in two assays (p= 0.028, p= 0.002) and

slightly significant in three assays (p= 0.120, p= 0.100, p= 0.112), though treatment means

varied (Table 3.13). When root weights were divided by stand, treatment means were only

significant in one assay (p= 0.050) (Table 3.14). Treatment means for plant weights were

significantly different in two assays (p= 0.056, p= 0.002) and slightly significant in two

assays (p= 0.124, p= 0.110) suggesting excess fertility may decrease plant weights (Table

3.15). When plant weights were divided by stand, treatment means were only significant in

one assay (p= 0.019) (Table 3.16).

58

Table 3.2. P-values from Analysis of Variance (ANOVA) for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at 5 locations in Ohio with a history of seedling disease. P-values <0.05 were considered statistically significant, and values <0.15 were considered slightly significant. Van Wert

(2014) Van Wert (2015)

Defiance (2014)

Defiance (2015)

Wayne (2015)

Early stand emergencebc 0.876 0.236 0.930 0.357 0.229 Final stand emergencecd 0.559 0.772 0.189 0.634 0.078 Yield 0.486 0.679 0.183 0.967 0.680 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bEarly stand counts were taken at the VC growth stage by counting the number of plants per 9 m row. Emergence was calculated by dividing stand count by seeds planted per row multiplied by 100 (seeding rate for all fields except Wayne: 26.2 seeds/m or 346,000 seeds/ha; Wayne seeding rate: 27.9 seeds/m or 368,000 seeds/ha). cP-values for percent emergence are equivalent to p-values for respective stand counts dFinal stand counts were taken at the R8 growth stage by counting the number of plants per 9 m row.

59

Table 3.3. Mean and standard deviation for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Van Wert in 2014.

Treatment Early stand (plants/row)b

Early % emergencec

Final stand (plants/row)d

Final % emergencec

Yield (mt/ha)

Overall 156.8 65.3 155.1 64.6 3.60 (53.6 bu/A) P 158.8 ± 11.7 66.2 ± 4.9 158.0 ± 12.6 65.9 ± 5.3 3.56 ± 0.30 K 152.8 ± 6.5 63.7 ± 2.7 152.2 ± 8.3 63.4 ± 3.4 3.48 ± 0.27 P/K 158.2 ± 9.4 65.9 ± 3.9 160.0 ± 9.4 66.7 ± 3.9 3.71 ± 0.24 None 157.4 ± 17.1 65.6 ± 7.1 150.0 ± 14.3 62.5 ± 6.0 3.64 ± 0.33 P-value 0.876 0.876 0.559 0.559 0.486 LSD (0.05) ns ns ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bEarly stand counts were taken at the VC growth stage by counting the number of plants per 9 m row. cEmergence was calculated by dividing stand count by seeds planted per row multiplied by 100. The seeding rate was approximately 26.2 seeds/m or 346,000 seeds/ha. dFinal stand counts were taken at the R8 growth stage by counting the number of plants per 9 m row.

60

Table 3.4. Mean and standard deviation for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Van Wert in 2015.


Early % emergencec

Plants with damping- off (plants/row)d

Final stand (plants/ row)e

Final % emergencec

Yield (mt/ha)

Overall 84.3 35.1 47.9 84.6 35.2 1.07 (16.0bu/A) P 89.3 ± 21.8 37.2 ± 9.1 40.0 b ± 26.8 90.0 ± 27.9 37.5 ± 11.6 1.09 ± 0.31 K 87.8 ± 25.2 36.6 ± 10.5 73.3 a ± 55.0 88.3 ± 28.8 36.8 ± 12.0 0.95 ± 0.24 P/K 76.7 ± 9.9 31.9 ± 4.1 41.7 b ± 38.7 78.3 ± 18.1 32.6 ± 7.5 1.09 ± 0.37 None 83.5 ± 17.5 34.8 ± 7.3 36.7 b ± 32.0 81.7 ± 26.8 34.0 ± 11.2 1.15 ± 0.24 P-value 0.236 0.236 0.041 0.772 0.772 0.679 LSD (0.05) ns ns 27.4 ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bEarly stand counts were taken at the VC growth stage by counting the number of plants per 9 m row. The seeding rate was approximately 346,000 seeds/ha. cEmergence was calculated by dividing stand count by seeds planted per row multiplied by 100. The seeding rate was approximately 26.2 seeds/m or 346,000 seeds/ha. dAt the VC stage, the number of seedlings affected by damping-off were counted for a 1.8 m section of the 9 m row and multiplied by 5 to estimate the number of plants per row. eFinal stand counts were taken at the R8 growth stage by counting the number of plants per 9 m row.

61

Figure 3.2. The number of seedlings with damping-off symptoms differed significantly among additional phosphorus, potassium, phosphorus and potassium, and control treatments at Van Wert in 2015 (p= 0.041, LSD (0.05)= 27.4). Error bars represent standard deviation for each treatment.

b

a

b

b

0

20

40

60

80

100

120

140

P K PK none

Plan

ts a

with

dam

ping

-off

sym

ptom

s(p

lant

s/30

' row

)

Number of Seedlings with Damping-off Symptoms at Van Wert in 2015

62

Table 3.5. Mean and standard deviation for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Defiance in 2014.


Early % emergencec


Final % emergencec

Yield (mt/ha)


63

Table 3.6. Mean and standard deviation for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Defiance in 2015. Treatment Early stand

(plants/row)b Early % emergencec


Final % emergencec

Yield (mt/ha)


64

Table 3.7. Mean and standard deviation for stand and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Wayneb in 2015.

Treatment Early stand (plants/row)c

Early % emergenced

Final stand (plants/row)e

Final % emergenced

Yield (mt/ha)

Overall 53.6 52.3 47.8 46.6 2.52 (37.5 bu/A) P 50.0 ± 8.9 48.9 ± 8.7 43.1 ± 6.6 42.1 ± 6.4 2.34 ± 0.48 K 67.5 ± 15.1 65.9 ± 14.8 63.7 ± 16.4 62.2 ± 16.0 2.63 ± 0.60 P/K 50.6 ± 20.8 49.4 ± 20.2 41.3 ± 13.3 40.2 ± 13.0 2.39 ± 0.09 None 46.3 ± 6.3 45.1 ± 6.1 43.1 ± 5.5 42.1 ± 5.4 2.70 ± 0.32 P-value 0.229 0.229 0.078 0.078 0.680 LSD (0.05) ns ns ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bThe 2015 Wayne Co. site was heavily infested with seedcorn maggot. cEarly stand counts were taken at the VC growth stage by counting the number of plants per 4.5 m row. dEmergence was calculated by dividing stand count by seeds planted per row multiplied by 100. The seeding rate was approximately 27.9 seeds/m or 368,000 seeds/ha. eFinal stand counts were taken at the R8 growth stage by counting the number of plants per 4.5 m row.

65

Table 3.8. The number of Pythium and Phytophthora isolates recovered from soybean roots collected at the VC growth stage from Defiance and Van Wert in 2015. Fields were treated with phosphorus, potassium, and phosphorus plus potassiuma in a study to determine fertility effect on the frequency and diversity of oomycete species recovered.

Defiance Van Wert P K P/K None P K P/K None

Total oomycetes 11 24 17 19 19 18 20 12 Species Pythium acanthicum 1 P. attranthericium 1 1 P. diclinum 1 P. dissotocum 4 1 1 1 1 1 P. helicoides 1 1 1 P. heterothallicum 1 1 P. inflatum 1 1 2 3 2 P. longandrum 1 P. lutarium 2 P. middletonii 3 2 1 P. oopapillum 2 2 1 P. pleroticum 1 P. torulosum 1 1 3 1 2 P. ultimum var. ult. 2 2 Ph. sansomeana 2 2 1 3 3 1 Ph. sojae 1 1 1 Total P. and Ph. isolates 6 10 9 8 11 7 12 6 Number of species 2 7 7 5 8 4 7 5 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control.

66

Figure 3.3. Pythium and Phytophthora species were recovered from soybean roots collected at the VC growth stage from Defiance and Van Wert in 2015. Fields were treated with phosphorus, potassium, and phosphorus plus potassium in a study to determine the fertility effect on the frequency and diversity of oomycete species recovered.

0

2

4

6

8

10

12

14

Num

ber o

f sol

ates

col

lect

ed

Pythium and Phytophthora SpeciesRecovered by Field

Defiance

Van Wert

67

Figure 3.4. Pythium and Phytophthora species were recovered from soybean roots collected at the VC growth stage from Defiance and Van Wert in 2015. Fields were treated with phosphorus, potassium, and phosphorus plus potassium in a study to determine the fertility effect on the frequency and diversity of oomycete species recovered.

0

2

4

6

8

10

12

14

Num

ber o

f iso

late

s co

llect

ed

Pythium and Phytophthora Species Recovered by Treatment

none

PK

K

P

68

Figure 3.5. In a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassium, isolates were recovered from soybean roots collected at the VC growth stage from a survey conducted in Defiance Co. in 2015. All recovered isolates were observed at 100 to 400x and samples containing oospores were characterized as oomycetes. Although identification through BLAST analysis of the ITS region was attempted for all oomycetes, only a subset were successfully sequenced and subsequently identified as Pythium or Phytophthora. The number of Pythium and Phytophthora species recovered from each treatment is also included.

0

5

10

15

20

25

30

P K P/K None

Num

ber o

f iso

late

s

Oomycete Isolates Recovered from Defiance

Oomycetes

Pythium and Phytophthoraisolates

Number of species

69

Figure 3.6. In a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassium, isolates were recovered from soybean roots collected at the VC growth stage from a survey conducted in Van Wert Co. in 2015. All recovered isolates were observed at 100 to 400x and samples containing oospores were characterized as oomycetes. Although identification through BLAST analysis of the ITS region was attempted for all oomycetes, only a subset were successfully sequenced and subsequently identified as Pythium or Phytophthora. The number of Pythium and Phytophthora species recovered from each treatment is also included.

0

5

10

15

20

25

P K P/K None

Num

ber o

f Iso

late

s

Oomycete Isolates Recovered from Van Wert

Oomycetes

Pythium and Phytophthoraisolates

Number of species

70

Table 3.9. In a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma, isolates were recovered from soybean roots collected at the VC growth stage from a survey conducted in Defiance and Van Wert in 2015. Five symptomatic plants were selected from each plot (chosen arbitrarily if asymptomatic) and each were plated on both oomycete-selective media (PIBNC) and general growth promoting potato carrot agar (PCA) to provide 10 opportunities for isolate recovery. Pythium or Phytophthorab were recovered from the plots in the following frequencies.

Plot

Replicate

Treatment

Defiance Van Wert # of Pythium or Phytophthora

isolates recovered from

each plot

# of species

recovered from each

plot

# of Pythium or Phytophthora

isolates recovered from

each plot

# of species

recovered from

each plot 1 1 P 1/10 1 4/10 3 2 1 K 4/10 4 2/10 1 3 1 P/K 1/10 1 2/10 2 4 1 none 3/10 3 0/10 0 5 2 P/K 1/10 1 5/10 5 6 2 none 2/10 2 2/10 2 7 2 P 0/10 0 3/10 2 8 2 K 1/10 1 0/10 0 9 3 P 0/10 0 0/10 0 10 3 none 1/10 1 2/10 2 11 3 K 1/10 1 0/10 0 12 3 P/K 0/10 0 3/10 3 13 4 P 0/10 0 2/10 2 14 4 K 0/10 0 1/10 1 15 4 none 2/10 1 0/10 0 16 4 P/K 0/10 0 1/10 1 17 5 none 0/10 0 1/10 1 18 5 P/K 4/10 4 1/10 1 19 5 P 1/10 1 0/10 0 20 5 K 3/10 2 1/10 1 21 6 P 4/10 2 2/10 2 22 6 P/K 3/10 2 0/10 0 23 6 K 1/10 1 2/10 2 24 6 none 0/10 0 1/10 1 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSpecies were identified through BLAST analysis of the ITS region using the primers ITS1 (TCCGTAGGTGAACCTGCGG) and ITS4 (TCCTCCGCTTATTGATATGC) (White et al., 1990).

71

Table 3.10. P-values from Analysis of Variance (ANOVA) for stand, root ratings, and plant weights from a greenhouse study that evaluated the addition phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from Defiance (Def) and Van Wert (VW), each with a history of seedling disease. Three trials were conducted with soil from each field. P-values <0.05 were considered statistically significant, and values <0.15 were considered slightly significant. Variable VW 1 VW 2 VW 3 Def 1 Def 2 Def 3 Stand 0.111 0.054 0.791 0.625 0.254 0.069 Root rot rating 0.092 0.045 0.778 0.403 0.111 0.320 Root weight 0.120 0.028 0.703 0.100 0.112 0.002 Root weight/stand 0.578 0.625 0.193 0.014 0.219 0.779 Plant weight 0.124 0.056 0.466 0.362 0.110 0.002 Plant weight/stand 0.571 0.371 0.376 0.019 0.361 0.363 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control.

72

Table 3.11. Treatment means for stand from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of seedling disease. Fifteen seeds were planted in each 15 cm pot. Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlb

13.83 13.25 10.08 12.00 13.8 10.6

Overallc 8.40 0.44 0.94 8.60 2.23 1.96 P 6.92 0.42 ab 1.17 9.50 1.75 1.83 K 8.33 0.17 b 0.75 8.50 2.08 2.67 PK 9.83 0.25 b 0.83 8.25 3.17 0.83 none 8.5 0.91 a 1.00 8.17 1.92 2.50 p-value 0.111 0.054 0.791 0.625 0.254 0.069 LSD (0.05) ns 0.577 ns ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

73

Table 3.12. Treatment means for root rot ratings from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of seedling disease. Root rot was rated on a 1 to 5 scale where: 1= healthy roots with no symptoms on any part of root system; 2= 1-20% of root system had lesions on lateral roots; 3= 21-75% of roots had symptoms, some lesions on tap root; 4= 76-100% of roots had symptoms on lateral and tap roots; and 5= complete root rot, no germination of seed (Appendix H: Figure H.1).

Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlb

1.2 1.0 1.7 1.4 1.0 1.0

Overallc 2.0 3.7 3.6 1.9 3.5 3.7 P 2.7 4.1 a 3.8 1.9 3.8 3.5 K 2.0 3.5 ab 3.5 1.8 3.3 3.7 PK 2.0 4.1 a 3.6 2.1 2.9 3.8 none 1.9 3.2 b 3.5 1.8 3.8 3.9 p-value 0.092 0.045 0.778 0.403 0.111 0.320 LSD (0.05) ns 0.758 ns ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

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Table 3.13. Treatment means for root weights from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of seedling disease. Roots were cut at the crown and weights include all roots in the pot, regardless of stand. Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlb

6.53 g 12.36 g 4.66 g 4.48 g 10.8 g 6.32 g

Overallc 1.82 0.24 0.18 2.12 0.42 0.37 P 1.40 0.14 b 0.21 2.48 0.25 0.26 bc K 1.82 0.25 ab 0.16 2.15 0.45 0.45 ab PK 2.18 0.16 b 0.20 1.61 0.66 0.16 c none 1.90 0.43 a 0.14 2.23 0.33 0.67 a p-value 0.120 0.028 0.703 0.100 0.112 0.002 LSD (0.05) ns 0.203 ns ns ns 0.243 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

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Table 3.14. Treatment means for root weights per planta from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected from two fields with a known history of seedling disease. Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlc

0.471 0.941 0.445 0.377 0.773 0.597

Overalld 0.211 0.339 0.115 0.242 0.186 0.143 P 0.197 0.213 0.119 0.251 a 0.130 0.136 K 0.212 0.400 0.138 0.255 a 0.220 0.149 PK 0.221 0.233 0.105 0.192 b 0.207 0.138 none 0.217 0.438 0.096 0.271 a 0.169 0.154 p-value 0.578 0.625 0.193 0.014 0.219 0.779 LSD (0.05) ns ns ns 0.050 ns ns aRoots were cut at the crown and root weight per plant (g/plant) was calculated as the sum weight of roots in a pot divided by the final plant stand. bFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. cSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. dOverall means represent the average of treatments (P, K, PK, none) from the field soil.

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Table 3.15. Treatment means for plant weights from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of seedling disease. Plant weight included the entirety of the plant, regardless of stand. Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlb

26.76 g 42.06 g 14.6 g 19.4 g 33.4 g 18.3 g

Overallc 11.09 1.47 1.27 11.8 2.30 2.50 P 9.00 0.80 b 1.46 13.2 1.43 1.75 bc K 11.02 1.42 ab 0.94 11.3 2.28 3.21 ab PK 13.23 1.13 b 1.90 10.1 3.62 1.04 c none 11.10 2.52 a 1.01 12.5 1.89 4.33 a p-value 0.124 0.056 0.466 0.362 0.110 0.002 LSD (0.05) ns 1.28 ns ns ns 1.51 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

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Table 3.16. Treatment means for weight per planta from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected from two fields with a known history of seedling disease. Van Wert Defiance Treatment Trial 1 Trial 2 Trial 3 Trial 1 Trial 2 Trial 3 Steamed controlc

1.93 3.20 1.40 1.62 2.41 1.72

Overalld 1.29 1.99 0.796 1.35 0.976 0.930 P 1.26 1.24 0.769 1.34 ab 0.754 0.887 K 1.27 1.70 0.819 1.33 ab 1.01 0.981 PK 1.35 2.07 1.02 1.20 b 1.10 0.825 none 1.28 2.47 0.660 1.51 a 0.988 1.04 p-value 0.571 0.371 0.376 0.019 0.361 0.363 LSD (0.05) ns ns ns 0.190 ns ns aWeight per plant was calculated as the sum weight of whole plants in a pot divided by the final plant stand (g/plant). bFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. cSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. dOverall means represent the average of treatments (P, K, PK, none) from the field soil.

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Figure 3.7. The first replicate of trial 3 from both locations is pictured above. The steamed soil control represents plants from one pot. For all other treatments, plants from both pots for each treatment in the replicate are included.

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Discussion

Seedling disease was observed in all field trials in 2014 and 2015. However,

excessive rains in 2015 caused severe flooding, especially at Van Wert, where standing

water was observed. This weather created exceptionally conducive field conditions for

pathogenic oomycetes and likely enhanced seedling disease. Fertility treatments did not

affect stand or yield at any the field sites, though flooding may have confounded results.

However, a significantly higher number of plants affected by damping-off were observed

with excess levels of potassium compared with the remaining treatments at one of the five

locations (Figure 3.2). It may be possible that excessive levels of potash lessens seedcorn

maggot infection, as a slightly significant trend occurred in which final stand for potassium

treated plots was higher than all other treatments (p= 0.078) (Table 3.7). Because seedcorn

maggot infection was underway during the initial stand count collection, it seems likely the

full effect of the decimation would best be seen in the final stand count. Barring the

exception of a serious seedcorn maggot infestation, these field studies did not provide

evidence that increased fertility levels enhanced yields (Table 3.2).

Sixteen Pythium and Phytophthora species were recovered from all treatments in a

field survey, confirming previous observations that a large number of Pythium and

Phytophthora species, rather than a few predominant species, are contributing to seedling

disease by causing seed rot and damping-off (Broders et al., 2007a; Dorrance et al., 2004;

Schmitthenner, 1970). Future field surveys should consider the differing methodology

between the soil baiting method used by Broders (2007a) and the VC growth stage root

80

isolation used in this study. More Ohio fields should be surveyed at the VC stage to better

understand which oomycete species are most relevant after emergence.

Though synergistic effects between species were documented by Mao et al. (1998),

this study did not investigate potential synergistic interactions. Instead, the survey

recorded species presence in each plot, occasionally recovering several oomycete species

from a single plot (Table 3.9). In addition to the oomycetes, several distinct morphological

groups were recovered from seedlings at both sites, including a high number of Fusarium

species (Appendix J).

When the study was repeated in the greenhouse with naturally infested soil

collected from both fields treated with the same fertility treatments, there were not any

clear and consistent differences among the treatments for stand, root rot ratings, or plant

weights (Table 3.10). However, the disease pressure in the infested soil and greenhouse

conditions may have been too severe to adequately measure these effects (Table 3.11).

Emergence was rarely over 50% and a high proportion of roots were observed to have

lesions in every trial. Because the soil was taken from the same fields used in the field

component of this study, a diverse population of oomycetes was already documented

(Figure 3.3). The high clay content likely contributed to low emergence as the fine

particles would create a very hard top layer for seedlings to penetrate. Pots were watered

twice daily and often a third time to prevent caking. Although soil composition may have

contributed to low emergence, the high number of root lesions suggested the primary cause

was disease pressure.

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Naturally infested soil was rarely used in previous studies presumably to avoid

unpredictable disease pressure and interactions between species. However, Canaday and

Schmitthenner (2010) used field soil naturally infested with P. sojae in a study that

evaluated the effect of several types of fertilizers and salts. The study controlled for the

effect of salinity on seedlings by comparing treatment effect on seedlings with and without

disease pressure. Disease was suppressed in two independent trials with thorough steaming

of the infested soil and planting seed treated with metalaxyl. This design provided some

evidence that salinity may contribute to disease development. Future greenhouse assays

should consider similar designs to begin to tease apart other factors affecting soil chemistry

including, but not limited to, CEC, pH, and organic matter. Future work should also

consider using variable rates of fertilizer to better assess seedling disease response to

increasing rates of fertility.

Differences between greenhouse trials may be attributed to several factors including

greenhouse temperatures, time of year, and water regime. Greenhouse temperatures were

highly variable in trial 1 (19 to 27˚C) and trial 2 (13 to 36˚C) due to Selby greenhouse

repairs that were in progress throughout the course of this study (Appendix I: Table I.1).

Consequently, the third trial was carried out at the Williams greenhouse where

temperatures remained more consistent (17 to 18˚C). In addition to greenhouse conditions,

seasonal differences may have affected temperature ranges, as trial 1 was conducted in the

fall under relatively warmer temperatures while trials 2 and 3 were conducted in the winter

and early spring under relatively cooler temperatures. Trial 1 was also flooded 3 days after

planting. Mean values for all variables were roughly comparable between trials 2 and 3.

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Cooler temperatures seemed to increase disease pressure more than flooding as lower

stand, more root rot, and lower root and plant weights were observed in trial 2 and 3 as

compared to trial 1. Between fields, soil from Defiance seemed to support slightly higher

plant weights and stand count than soil from Van Wert. Although greenhouse assays

provided some evidence that excessive levels of fertilizer may increase seedling disease by

reducing root weights, greenhouse conditions were too variable and disease pressure was

too severe to observe clear and consistent results.

This study provided some evidence of increased seedling disease when phosphorus,

potassium, or phosphorus and potassium were applied to the soil at 112 kg/ha DAP and 112

kg/ha potash, levels above what is recommended by the Tri-State Fertility

Recommendations at these two locations (Vitosh et al., 1995). Although excess fertility

affected neither stand nor yield at any of the five field sites (Table 3.2), a higher number of

seedlings affected by damping-off occurred in plots treated with excess potassium at Van

Wert (Figure 3.2). Furthermore, in both fields, excess fertility seemed to increase the

number of oomycetes, as more oomycete isolates were recovered from plots that had been

treated with fertilizer than in the nontreated control, supporting previous studies in which

seedling disease incidence and severity was enhanced by the addition of fertilizers

(Canaday & Schmitthenner, 2010; Dirks et al., 1980; Pacumbaba et al., 1997) (Figures 3.5

and 3.6), albeit conditions were highly favorable for seedling disease to occur with less

than 50% overall emergence.

In greenhouse assays there was a trend toward lower root weights in 2 of 3

experiments with the addition of excess fertility. Although this trend is worth continued

83

exploration, future work may be more productive if the focus is shifted from observing

differences in oomycete frequency among treatments to identifying all components of this

complex community, even those that are individually nonpathogenic, and working to better

understand how the complex as a whole responds to excess fertilizer (Broders et al., 2007a;

Castano & Kernkamp, 1956). Future investigation of oomycete response specifically

should involve inoculated steamed soil or vermiculite in greenhouse studies with more

consistent greenhouse temperature regulation. This study did not find any evidence of

enhanced yield response with increased fertility.

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Chapter 4: Effects of Increased Fertility on the Development of Sudden Death Syndrome of Soybean

Introduction

Sudden death syndrome (SDS) poses a significant threat to soybean yield in many

areas of the Midwest. This disease is caused by the fungus Fusarium virguliforme

(formerly Fusarium solani f. sp. glycines) (Roy, 1997). Although its distribution is still

limited in Ohio, this soil borne fungus has continued to spread across the state since its first

detection in 1995 (Roy et al., 1997b). Yield loss associated with SDS may be severe

depending on initial levels of inoculum, timing of infection, subsequent weather conditions,

timing of defoliation, and level of soybean cyst nematode (SCN) in the field. In 2014, SDS

was estimated to cause a yield loss of 1,681,047 mt nationwide, second only to soybean

cyst nematode estimated to cause a 3,406,192 mt loss (Bradley et al., 2015).

Fusarium virguliforme is soil borne and may spread easily through movement of

soil. It overwinters as chlamydospores; structures that survive in the soil for years

(Kolander et al., 2012; Roy, 1997). The pathogen may infect soybean as early as the

seedling stage in the roots and crowns, occurring approximately 2 weeks after emergence

in the field (Gao et al., 2006). When the fungus colonizes the roots, toxins are produced

(Abeysekara & Bhattacharyya, 2014; Hartman et al., 2015b). This toxin moves through the

xylem up to the leaves and results in the characteristic foliar symptoms typically seen in the

middle pod-fill stages (Figure). If infected as a seedling, plants may exhibit foliar

symptoms as early as the V1 growth stage, but fade as the plant matures, only to reappear

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later in the reproductive growth stages. Pod abortion may result and significantly decrease

yield (Roy et al., 1997b).

In addition to soybean, this pathogen can infect a number of other hosts. Fusarium

virguliforme may also cause root necrosis in alfalfa, pinto and navy beans, white and red

clover, pea, and Canadian milk vetch, and foliar symptoms in alfalfa and red clover

(Kolander et al., 2012). A significant reduction in biomass occurred when sugar beet and

canola were infected with the pathogen (Kolander et al., 2012). Asymptomatic hosts

include corn, wheat, rye grass, pigweed, and lambsquarters (Kolander et al., 2012). An

asymptomatic host supports fungal colonization, reproduction, and growth of survival

structures, without either visible symptoms or impact on yield.

Although soybean fields with SDS are often associated with soybean cyst nematode

(SCN), the relationship between SCN infestation and SDS severity is controversial

(Brzostowski et al., 2014; Gao et al., 2006; Hartman et al., 2015b; Marburger et al., 2014;

Roy et al., 1989). Fusarium virguliforme independently infects soybean; however,

nematode root feeding may make the plant more vulnerable, providing wounds for the

fungus to colonize (Roy et al., 1989). Fusarium virguliforme was found in and on SCN

cysts, providing evidence that the fungus may travel with the nematode between locations

(Lawrence et al., 1988), though Gao et al. (2006) found interactions were seldom

statistically significant.

SDS is most likely to occur in fields that have been planted into poorly drained or

compacted cool soils (<60 F) that contain SCN. Management practices include the use of

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SDS and SCN resistant varieties, drainage improvement, the reduction of soil compaction,

later planting dates with fast germination, and proper SCN management.

Figure 4.1. The first symptoms of the disease appear as small yellow spots between the veins on the upper leaves of the plant. Spots merge as they increase in size, and develop into brownish-tan lesions with a bright yellow halo. These lesions continue to expand rapidly between the veins until the leaflet becomes entirely necrotic and leaflets drop, leaving the petiole still attached to the stem. A confident field diagnosis depends on the observation of all three symptoms: foliar symptoms, a white pith, and blue spores on the roots or crown.

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Figure 4.2. Crowns of infected plants are usually decayed and discolored, often becoming necrotic. Characteristic blue-green spores of the fungus are sometimes visible on the tap root, especially in moist conditions after a rainfall.

The effect of fertility on SDS development is inconclusive, complex, and

contradictory (Datnoff et al., 2007). Some field studies suggest SDS severity may be

increased when exposed to high levels of potassium (Rupe et al., 2000). Other studies

suggest adequate fertility may enhance overall plant health and decrease incidence of SDS

(Fageria & Baligar, 1997; Huber & Arny, 1985; Krupinsky et al., 2002), cultivars may play

a larger role in SDS development than soil fertility (Howard et al., 1999; Prabhu et al.,

2007; Rupe et al., 2000; Sanogo & Yang, 2001), SCN may or may not be affected by

fertility (Luedders et al., 1979; Pacumbaba et al., 1997; Rupe et al., 2000), and the type of

fertilizer may affect SDS development (Howard et al., 1999; Sanogo & Yang, 2001). For a

more thorough review of these studies, see Chapter 2.

OSU Soybean Pathology Lab

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The objective of this study was to evaluate the effects of higher than recommended

rates of phosphorus and potassium on the development of sudden death syndrome of

soybean. Our study included two approaches (i) stand and yield data were collected and

analyzed from Fusarium virguliforme infested fields where fertilizer was added and; (ii)

greenhouse experiments designed to replicate field studies were conducted with infested

field soil and identical fertility treatments.

Materials and Methods

Field Experiments

Two field sites located in Erie and Wood Counties, Ohio with a known history of

SDS and SCN were used in this study during 2014 and 2015, respectively. Four fertility

treatments were applied to the soil surface at planting, including 112 kg/ha diammonium

phosphate (DAP) (18-46-0: 46% P2O5), 112 kg/ha potash (0-0-60: 60% K2O), 112 kg/ha

DAP plus 112 kg/ha potash, and a nontreated control (no fertilizer). It should be noted

these rates are higher than recommended by current recommendations and fertility levels

are thus referred to as being applied in excess. The study was arranged in a randomized

complete block design with 6 replications at each location. One cultivar was used for all

field studies, AGI 31R2Y2 3102N (Pond Seed Co., Scott, OH) which has SCN resistance

and no seed treatment. Prior to planting and fertilizer application, soil was collected from

each field and submitted to the Service Testing and Research (STAR) Laboratory

(OARDC, The Ohio State University, Wooster, OH) (Table 4.1). Soybean cyst nematode

populations were counted from pre and post-season soil sampling. Cysts were extracted

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from 100 cm3 soil samples with a semiautomatic elutriator (Byrd et al., 1976) and ground

with a motorized pestle to release eggs which were counted under a dissecting microscope

(Faghihi and Ferris, 2000).

Stand data were collected at the VC/V1 and R6/R7 growth stage at all fields by

counting the number of plants in the second 9 m row of the 4-row plot. At the R5/6 stage,

foliar SDS symptoms were rated with the Southern Illinois University Carbondale (SIUC)

SDS scoring method (Schmidt, 2007) (Appendix F). The second and third row of each plot

were harvested for yield and adjusted for moisture content (standardized at 13.5%).

Greenhouse experiments

Soil was collected from Erie and Wood site on 4 November and 16 October 2015,

respectively, from the same locations used for field studies. Soil was collected from twelve

points divided between two areas of the field separated by approximately 30 m and at a

uniform depth of 15 to 20 cm. The soil from each area was used in independent

greenhouse studies representing trial 1 and trial 2. Soil was stored in 10 gallon plastic bins

and allowed to partially dry for 1 week, after which the bins were covered and stored at

room temperature. A soil grinder (Iler Improved, The Fen Machine Co., Cleveland, OH)

was used to grind clay clumps. Two soybean cyst nematode counts were measured and

averaged for each trial (Byrd et al., 1976; Niblack et al., 1993). Population densities for

the Erie trials were 437 and 287 eggs/100 cm3 soil respectively and 60 and 187 eggs/100

cm3 soil for Wood.

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Five treatments consisted of fertility regimes calculated to match the rate applied in

the field, including 112 kg/ha DAP (18-46-0: 46% P2O5), 112 kg/ha potash (0-0-60: 60%

K2O), 112 kg/ha DAP plus 112 kg/ha potash, a control (no fertilizer), and a steamed

greenhouse soil mix (no fertilizer) as a check for seed viability and general greenhouse

conditions. Coffee filters were placed in the bottoms of 15 cm pots and then filled with

approximately 1.4 kg soil per pot, 2 pots per treatment and 6 replicates. The same cultivar

used in both field and greenhouse studies (AGI 31R2Y2 3102N). Twelve seeds were

planted in each pot and watered twice daily with deionized water. Greenhouse

temperatures were set to favor F. viruguliforme infection and disease development at 14 to

18˚C the first week followed by 20 to 22˚C; however, greenhouse renovations complicated

temperature regulation. Temperatures ranged from 18 to 32˚C in trial 1 and 15 to 41˚C

(Appendix I: Table I.2).

Treatments were arranged in a randomized complete block design. The

experiment was performed twice for both Erie and Wood, in November/December 2015

and February/March 2016.

Data were collected for 7 and 14 day stand and final stand at the V5 growth stage.

The heights of up to five plants were measured at the V4 stage and averaged (Appendix H:

Figure H.4). The plants were removed from the pots at the V5 growth stage, and the roots

gently washed under running tap water. The number of plants with symptomatic roots

were counted. Roots were considered symptomatic if dark brown lesions were visible on

the taproot after washing (Appendix H: Figure H.3). Fresh root and plant weights were

also collected.

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Statistical analysis

All data were analyzed with Statistical Analysis Software (SAS, version 9.4).

Homogeneity of variance existed for all parameters investigated and analyses of variance

(ANOVA) were carried out for each field or greenhouse trial separately. Residual plots of

the data sets showed major assumptions were satisfied and thus ANOVA could be used

without prior transformations. Treatments were compared with the Fisher’s protected least

significant difference (LSD) test at p ≤ 0.05. For greenhouse trials, the steamed soil control

was removed from the analysis.

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Table 4.1. Soil test resultsa from samples collected prior to planting from Ohio soybean fields with a known history of sudden death syndrome infested with Fusarium virguliforme. Soybean cyst nematode counts were taken pre-planting and post-harvest.

Soil Characteristics Erie (2014) Wood (2015) Colwood loam and

Bixler loamy fine sand Colwood fine sandy

loam Soil pH 7.1 6.4 Buffer pH 0 7.1 Organic Matter (%) 2.7 1.4 Phosphorus (m3-ppm) 83 37.2 Potassium (m3-ppm) 171 223.4 CEC 6.9 7.1 K Saturation (%) 5.3 6.9 Bray P1 (lbs/A) 71.2 na Bray P1 (ppm) 35.6 na Spring SCN counts (eggs/100cm3) 1696 205 Fall SCN counts (eggs/100cm3) 625 44 SCN Reproduction factor (RF)b 0.37 0.21 aSoil was tested in the Service Testing and Research (STAR) Laboratory through The Ohio State University. bSCN Reproductive factor (RF) was calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting.

93

Results

Field Experiments

Sudden death syndrome developed at both field locations with similar indices

(incidence x severity). The treatment averages of the disease index for Erie and Wood

were 23.7 and 23.1 respectively. Though no treatment differences at Wood occurred, there

were significant differences at Erie (p= 0.052) (Figure 4.3). At Erie, the addition of

phosphorus (112 kg/ha DAP) and potassium (112 kg/ha potash) applied separately reduced

disease index for SDS significantly (p= 0.052) and phosphorus plus potassium decreased

the final stand count (p=0.051) (Table 4.3). At both fields, phosphorus increased yield

significantly (Erie: p=0.020; Wood: p=0.041) (Figure 4.4).

Soybean cyst nematode population counts averaged across treatments were

dramatically higher for both initial and final counts in Erie than Wood (Erie: Pi= 1696 eggs

and juveniles per 100 cm3 soil, Pf= 625, Wood Pi= 205, Wood Pf= 44) but not significantly

different among treatments (Tables 4.5 and 4.6). Although the SCN reproductive factor

was higher at Erie (0.506) than Wood (0.287), populations in both fields decreased with the

use of SCN resistant seed (Tables 4.5 and 4.6).

Greenhouse Experiments

In greenhouse assays with a steamed soil control and comparable fertility treatments

on field soil, lower stands and weights consistently occurred in the field soil compared with

the steamed soil control. Of the 12 seeds planted in each pot, stand in the steamed soil

control ranged from 6.4 to 11.0 while field soil treatment means were 3.2 and 1.5 for Erie

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and 6.8 and 1.2 for Wood (Table 4.8). Although inconsistent greenhouse temperatures

were not ideal, high emergence in the steamed soil controls indicated conditions were

conducive for plant growth.

Distinct yellow spotting occurred in one of four greenhouse assays and was

primarily observed in pots treated with phosphorus (Figure 4.6). Root sections from all

treatments from the second trial of both Erie and Wood were plated on APDA-SA media

(acidified potato-dextrose agar amended with 100 mg/L streptomycin B sulfate and 2 mg/L

aureomycin) according to the method outlined in Roy et al., (1997a). Purple colonies were

observed on several plates indicating F. virguliforme isolates were recovered from the

plants in the greenhouse trials.

Treatment means for stand were significant in two assays (p= 0.014, p= 0.03854, p=

0.069) suggesting a possible trend in that phosphorus and potassium applied together may

decrease stand in soils naturally infested with F. virguliforme (Table 4.8). This trend was

supported by significantly shorter plants in pots treated with phosphorus plus potassium in

one of four assays (p= 0.017) (Table 4.9). Treatment means for corrected root weights

(root weight per plant) were significantly higher than nonamended controls in greenhouse

studies where phosphorus (Erie trial 2: p= 0.018), potassium (Wood trial 2: p= 0.022), and

phosphorus plus potassium (Wood trial 1: p= 0.0002) were added (Table 4.11). There was

not a consistent trend for plant weight and fertility application (Table 4.7).

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Table 4.2. P-values from Analysis of Variance (ANOVA) for stand, soybean cyst nematode reproductive factor (RF), sudden death syndrome disease index, and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at two locations in Ohio with a history of sudden death syndrome. Erie (2014) Wood (2015) Early % emergencebc 0.086 0.968 Final % emergencecd 0.051 0.390 SCN RFe 0.203 0.169 SDS disease indexf 0.052 0.887 Yield 0.020 0.041 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bEarly stand counts were taken at the VC growth stage by counting the number of plants per 9 m row. Emergence was calculated by dividing stand count by seeds planted per row multiplied by 100. The seeding rate was approximately 26.2 seeds/m or 346,000 seeds/ha. cP-values for percent emergence are equivalent to p-values for respective stand counts dFinal stand counts were taken at the R8 growth stage. eRF indicates reproductive factor which is calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting (Byrd et al., 1976; Niblack et al., 1993). fSDS disease index was calculated by multiplying incidence by severity using the SIUC SDS Scoring Method (Schmidt, 2007).

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Table 4.3. Mean and standard deviation for stand, soybean cyst nematode reproductive factor (RF), sudden death syndrome disease index, and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Erie in 2014.

Treatment Early stand (plants/row)bc

Final stand (plants/row)cd

SCN RF (Pf /Pi)e

SDS disease indexf

Yield (mt/ha)

Overall 159.3 164.0 0.506 23.7 3.34 (49.8 bu/A) P 164.8 ± 7.3 170.8 a ± 9.5 0.778 ± 0.80 10.5 b ± 15.1 3.60 a ± 0.61 K 151.2 ± 8.2 162.8 ab ± 5.1 0.478 ± 0.46 13.3 b ± 15.1 3.17 b ± 0.76 P/K 162.5 ± 11.8 156.0 b ± 12.2 0.192 ± 0.12 23.3 ab ± 16.3 3.35 ab ± 0.60 None 160.8 ± 9.3 166.4 a ± 6.3 0.576 ± 0.55 47.5 a ± 36.4 3.25 b ± 0.64 P-value 0.086c 0.051c 0.203 0.052 0.020 LSD (0.05) ns 10.4 ns 28.1 0.27 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bEarly stand counts were taken at the VC growth stage by counting the number of plants per 9 m row. cP-values for percent emergence are equivalent to p-values for respective stand counts. Emergence was calculated by dividing stand count by seeds planted per row multiplied by 100. The seeding rate was approximately 26.2 seeds/m or 346,000 seeds/ha. dFinal stand counts were taken at the R8 growth stage. eRF indicates reproductive factor which is calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting (Byrd et al., 1976; Niblack et al., 1993). fSDS disease index was calculated by multiplying incidence by severity using the SIUC SDS Scoring Method (Schmidt, 2007).

97

Table 4.4. Mean and standard deviation for stand, soybean cyst nematode reproductive factor (RF), sudden death syndrome disease index, and yield from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Wood in 2015.

Treatment Early stand (plants/row)bc

Final stand (plants/row)cd

SCN RF (Pf /Pi)e

SDS disease indexf

Yield (mt/ha)

Overall 163.5 184.8 0.287 23.1 3.56 (53.1 bu/A) P 165.2 ± 10.4 185.8 ± 16.6 0.152 ± 0.26 19.2 ± 8.0 3.89 a ± 0.23 K 163.4 ± 7.2 195.8 ± 23.5 0.168 ± 0.19 24.2 ± 19.6 3.38 b ± 0.28 P/K 161.8 ± 16.7 185.8 ± 16.6 0.646 ± 0.72 25.8 ± 18.6 3.65 ab ± 0.55 None 163.6 ± 5.3 171.7 ± 41.7 0.161 ± 0.21 23.3 ± 10.3 3.31 b ± 0.28 P-value 0.968c 0.390c 0.169 0.887 0.041 LSD (0.05) ns ns ns ns 0.42 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. aRF indicates Reproductive factor which is calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting (Byrd et al., 1976; Niblack et al., 1993). bDisease index (incidence x severity) was calculated at the R6/R7 growth stage from ratings taken using the SIUC SDS Scoring Method (Schmidt, 2007). cP-values for stand are equivalent to respective p-values for percent emergence.

98

Figure 4.3. Disease index (incidence x severity) differed significantly among phosphorus, potassium, phosphorus and potassium, and control treatments at Erie in 2014 (p= 0.052, LSD (0.05)= 27.4) but not at Wood in 2015 (p= 0.887, LSD (0.05)= 18.6). Ratings were taken at the R6/R7 growth stage according to the SIUC SDS Scoring Method (Schmidt, 2007). Error bars represent standard deviation for each treatment within each location.

99

Figure 4.4. Yield differed significantly at both Fusarium virguliforme infested field sites among phosphorus, potassium, phosphorus and potassium, and control treatments (Erie: p= 0.020, LSD at 0.05= 4.0; Wood: p= 0.041, LSD at 0.05= 6.3). Error bars represent standard deviation for each treatment within each location.

100

Table 4.5. Mean and standard deviation for soybean cyst nematode counts and reproductive factor (RF) from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Erie in 2014. An SCN-resistant seed variety was used (AGI 31R2Y2 3102N). Treatment Initial population (Pi)

(# eggs and juveniles per 100 cm3 soil )

Final population (Pf) (# eggs and juveniles

per 100 cm3 soil )

SCN RF (Pf /Pi)b

Overall 1696 625 0.506 P 1693 ± 1220 847 ± 741 0.778 ± 0.803 K 1777 ± 1380 607 ± 624 0.478 ± 0.461 P/K 1727 ± 925 360 ± 341 0.192 ± 0.120 None 1587 ± 1040 687 ± 635 0.576 ± 0.547 P-value 0.989 0.624 0.203 LSD (0.05) ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bRF indicates reproductive factor which is calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting (Byrd et al., 1976; Niblack et al., 1993).

101

Table 4.6. Mean and standard deviation for soybean cyst nematode counts and reproductive factor (RF) from a field study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma at Wood in 2015. An SCN resistant seed variety was used (AGI 31R2Y2 3102N).

Treatment Initial population (Pi) (# eggs and juveniles

per 100 cm3 soil )

Final population (Pf) (# eggs and juveniles

per 100 cm3 soil )

SCN RF (Pf /Pi)b

Overall 205 43.9 0.287 P 273 ± 297 15.6 ± 17.7 0.152 ± 0.261 K 167 ± 85 44.4 ± 45.1 0.168 ± 0.192 P/K 187 ± 131 93.3 ± 88.8 0.646 ± 0.715 None 193 ± 211 22.2 ± 32.3 0.161 ± 0.211 P-value 0.807 0.062 0.169 LSD (0.05) ns ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bRF indicates reproductive factor which is calculated using the formula: RF = Pf/Pi, where Pf = number of eggs and juveniles per 100 cm3 soil at harvest and Pi = number of eggs and juveniles per 100 cm3 soil at planting (Byrd et al., 1976; Niblack et al., 1993).

102

Figure 4.5. Soybean cyst nematode population densities were counted before planting and after harvest at two locations with sudden death syndrome history and treated with additional phosphorus, potassium, and phosphorus plus potassium. An SCN resistant seed was used (AGI 31R2Y2 3102N). An Analysis of Variance revealed that treatments did not differ significantly at either time of year for both locations (Erie Pi p= 0.989; Wood Pi p= 0.807; Erie Pf p= 0.624; Wood Pf p= 0.062). The reproductive factor (Pf/Pi) was not significantly affected by fertility at either location (Erie p= 0.203; Wood p= 0.169). Error bars represent standard deviation for each treatment.

0

500

1000

1500

2000

2500

3000

3500

P K PK none

SCN

cou

nts

(# o

f egg

s and

juve

nile

s/10

0 cm

3so

il)

Treatment

Soybean Cyst Nematode Populations at Erie and Wood

Erie: Initial population (Pi)

Erie: Final population (Pf)

Wood: Initial population (Pi)

Wood: Final population (Pf)

103

Table 4.7. P-values from Analysis of Variance (ANOVA) for stand, average height, root weights, plant weights, and number of plants with diseased roots divided by stand from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a history of sudden death syndrome. P-values <0.05 were considered statistically significant, and values <0.15 were considered slightly significant. Erie Wood

Trial 1 Trial 2 Trial 1 Trial 2 Stand (plants/row) 0.259 0.014 0.856 0.038 Average height (5 plants) 0.141 0.017 0.836 0.184 Root weight 0.483 0.368 0.0006 0.028 Root weight/stand 0.824 0.018 0.0002 0.022 Plant weight 0.160 0.679 0.087 0.005 Plant weight/stand 0.532 0.0009 0.0002 0.017 Number of plants with diseased roots/stand

0.652 0.502 0.284 0.006

aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control.

104

Table 4.8. Mean and standard deviation for stand from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of sudden death syndrome. Twelve seeds were planted in each 15 cm pot.

Erie Wood Treatment Trial 1 Trial 2 Trial 1 Trial 2 Steamed controlb

8.92 9.57 11.00 6.36

Overallc 3.23 1.48 6.77 1.17 P 2.92 ± 1.31 1.58 a ± 0.79 6.58 ± 2.19 2.17 a ± 1.99 K 3.17 ± 1.64 1.92 a ± 1.24 7.25 ± 2.67 0.67 b ± 0.78 PK 4.00 ± 1.65 0.67 b ± 0.78 6.75 ± 2.45 0.75 b ± 0.87 none 2.83 ± 1.47 1.80 a ± 1.69 6.50 ± 2.35 1.10 ab ± 1.52 p-value 0.259 0.014 0.856 0.038 LSD (0.05) ns 0.882 ns 1.16 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

105

Table 4.9. Mean and standard deviation for plant heights from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of sudden death syndrome. Heights were determined by averaging five plants. If fewer than five plants emerged, heights of all plants were averaged.


9.12 cm 10.68 cm 12.59 cm 11.82 cm

Overallc 7.68 7.57 9.21 9.83 P 7.04 ± 2.48 9.10 a ± 3.20 8.84 ± 1.44 11.30 ± 1.62 K 8.33 ± 1.57 8.23 a ± 2.69 9.19 ± 1.88 9.76 ± 3.00 PK 8.09 ± 1.10 4.57 b ± 4.84 9.58 ± 2.19 9.66 ± 2.50 none 7.27 ± 1.39 8.53 a ± 4.72 9.23 ± 2.08 8.13 ± 3.35 p-value 0.141 0.017 0.836 0.184 LSD (0.05) ns 3.05 ns ns aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

106

Table 4.10. Mean and standard deviation for fresh root weights from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of sudden death syndrome. Roots were cut at the crown and weights include all roots in the pot, regardless of stand. Erie Wood Treatment Trial 1 Trial 2 Trial 1 Trial 2 Steamed controlb

26.0 g 32.4 g 50.2 g 21.1 g

Overallc 3.70 5.23 5.63 5.11 P 3.40 ± 1.25 6.14 ± 2.30 4.63 b ± 1.68 7.41 a ± 1.50 K 3.51 ± 1.90 5.15 ± 2.41 5.55 b ± 1.63 5.42 ab ± 1.74 PK 4.38 ± 1.96 3.67 ± 1.37 7.39 a ± 1.97 3.81 b ± 2.82 none 3.46 ± 2.09 5.29 ± 2.85 4.93 b ± 1.37 3.23 b ± 2.90 p-value 0.483 0.368 0.0006 0.028 LSD (0.05) ns ns 1.32 2.86 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

107

Table 4.11. Mean and standard deviation for fresh root weights per planta from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected from two fields with a known history of sudden death syndrome.

Erie Wood Treatment Trial 1 Trial 2 Trial 1 Trial 2 Steamed controlc

3.03 3.07 4.53 3.14

Overalld 1.13 2.96 0.884 2.91 P 1.10 ± 0.41 3.72 a ± 0.96 0.718 b ± 0.211 2.68 ab ± 1.19 K 1.21 ± 0.24 2.65 b ± 0.76 0.824 b ± 0.276 4.25 a ± 1.35 PK 1.15 ± 0.43 2.83 ab ± 0.88 1.190 a ± 0.350 3.04 ab ± 2.10 none 1.07 ± 0.68 2.45 b ± 1.05 0.805 b ± 0.212 1.75 b ± 0.92 p-value 0.824 0.018 0.0002 0.022 LSD (0.05) ns 0.909 0.202 1.68 aRoots were cut at the crown and root weight per plant (g/plant) was calculated as the sum weight of roots in a pot divided by the final plant stand. bFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. cSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. dOverall means represent the average of treatments (P, K, PK, none) from the field soil.

108

Table 4.12. Mean and standard deviation for plant weights from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of sudden death syndrome. Plant weight included the entirety of the plant, regardless of stand. Erie Wood Treatment Trial 1 Trial 2 Trial 1 Trial 2 Steamed controlb

62.5 g 75.4 g 109.3 g 53.6 g

Overallc 10.6 11.8 20.4 16.2 P 10.2 ± 2.9 13.5 ± 4.8 17.9 b ± 5.9 24.9 a ± 3.3 K 9.3 ± 5.3 11.6 ± 5.2 21.3 ab ± 5.9 15.5 b ± 5.2 PK 13.2 ± 5.3 9.8 ± 3.3 23.6 a ± 7.1 13.2 b ± 9.2 none 9.3 ± 5.1 11.0 ± 6.4 18.7 b ± 5.6 8.8 b ± 7.5 p-value 0.160 0.679 0.087 0.005 LSD (0.05) ns ns 4.9 8.4 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

109

Table 4.13. Mean and standard deviation for weights per planta from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiumb to field soil collected from two fields with a known history of sudden death syndrome. Erie Wood Treatment Trial 1 Trial 2 Trial 1 Trial 2 Steamed controlc

7.21 7.15 9.89 7.99

Overalld 3.10 6.68 3.10 9.14 P 3.27 ± 0.72 8.18 a ± 1.86 2.75 b ± 0.40 8.89 ab ± 3.30 K 2.96 ± 1.24 5.96 bc ± 1.59 3.06 b ± 0.49 12.07 a ± 3.47 PK 3.37 ± 0.73 7.53 ab ± 1.77 3.64 a ± 0.55 10.56 a ± 6.70 none 2.84 ± 1.44 4.97 c ± 1.55 2.96 b ± 0.42 4.88 b ± 2.46 p-value 0.532 0.0009 0.0002 0.017 LSD (0.05) ns 1.69 0.377 4.96 aWeight per plant was calculated as the sum weight of whole plants in a pot divided by the final plant stand (g/plant). bFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. cSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. dOverall means represent the average of treatments (P, K, PK, none) from the field soil.

110

Table 4.14. Mean and standard deviation for the number of plants with diseased roots divided by the number of plants per pot from a greenhouse study that evaluated the addition of phosphorus, potassium, and phosphorus plus potassiuma to field soil collected from two fields with a known history of sudden death syndrome. Within each pot, the number of plants with diseased roots was counted and divided by stand. Roots were considered diseased if they appeared darker in color than the steamed soil control for the respective replicate (Appendix H: Figure H.3).


0.0 0.47 0.0 0.625

Overallc 0.97 2.79 0.926 0.317 P 1.00 ± 0.01 1.87 ± 0.83 0.951 ± 0.08 0.298 b ± 0.045 K 0.94 ± 0.20 2.16 ± 1.13 0.872 ± 0.15 0.350 a ± 0.036 PK 0.98 ± 0.06 2.79 ± 1.00 0.956 ± 0.10 0.278 b ± 0.060 none 0.95 ± 0.15 4.93 ± 8.34 0.925 ± 0.11 0.354 a ± 0.041 p-value 0.652 0.502 0.284 0.006 LSD (0.05) ns ns ns 0.048 aFertilizers were applied at planting at levels higher than recommended by the Tri-State Fertility Recommendations (Vitosh et al., 1995) in the form of 112 kg/ha DAP, 112 kg/ha potash, 112 kg/ha DAP and 112 kg/ha potash, and a nontreated control. bSteamed soil control was used to check seed viability and greenhouse conditions. This treatment was not included in ANOVA analysis. cOverall means represent the average of treatments (P, K, PK, none) from the field soil.

111

Figure 4.6. Distinct yellow spotting occurred primarily in pots treated with phosphorus in one of four assays (Wood trial 2).

Figure 4.7. Distinct yellow spotting occurred in one of four assays. Though each treatment was represented in 12 pots, not all pots germinated.

0

2

4

6

8

10

12

Steamed soil Field control P K PK

Pots

Treatment

Foliar Symptoms Occured in Some Treatments in Wood Trial 2

Asymptomatic

Foliar symptoms

112

Discussion

The addition of phosphorus and potassium applied separately significantly reduced

disease index for sudden death syndrome at Erie in 2014 (p= 0.052), but this trend was not

repeated the following year at Wood (p= 0.887). Although the average disease index for all

treatments was remarkably similar between fields (Erie= 23.7, Wood= 23.1), several

factors may have contributed to the significance detected only at Erie.

First, the base fertility levels were different. Base fertility levels were considered

adequate at both fields before fertility treatments were applied (Vitosh et al., 1995), but the

Erie site had a lower base level of potassium (measured in both m3-ppm and percent

saturation) than the Wood site (Table 4.1). This may have contributed to the significant

reduction of SDS observed when potassium was added to the Erie field. Several studies

suggested there may be a greater pathogen response in deficient plants supplied with

adequate fertility than adequately supplied plants exposed to fertility applied at levels

higher than recommended (Fageria & Baligar, 1997; Huber & Arny, 1985; Krupinsky et

al., 2002).

A more thorough exploration of pathogen response to specific variables such as soil

pH, buffer pH, organic matter %, and CEC may provide additional insight necessary to

understand interactions between the pathogens and their environment on a deeper level.

Though soil chemistry renders the environment complex, facets of the system might

become clearer with further study, as Canaday and Schmitthenner (2010) did to tease apart

salinity effect. Ultimately, this information may be used to update management strategies.

113

In addition to differences in base fertility levels between fields, SCN population

densities also differed. Population densities were higher, with a higher reproductive factor,

at Erie compared with Wood (RF at Erie: 0.506, RF at Wood: 0.287). This may have

contributed to the disease pressure of F. virguliforme at Erie. SCN and SDS are often

found together (Roy et al., 1989), though Gao et al. (2006) found interaction between the

pathogens was rarely significant. There were no significant differences in initial population

densities, final population densities, and reproduction factor between fertility treatments at

both field sites, suggesting excess fertility did not affect SCN population, supporting

research by Pacumbaba et al., (1997) but contradicting the study by Luedders et al., (1979)

reporting that SCN levels decreased as potassium increased. The effects of high and low

SCN on SDS development in fields treated with excess fertilizer should be investigated

further. Base levels of F. viguliforme were not recorded thus SDS/SCN interactions can

only be speculated so far. Future field studies might consider quantifying SDS infection by

F. virguliforme DNA extraction from roots (Weems et al., 2015), to better understand how

much is present in the fields, as this plays a role in determining the severity of the disease

and possible interactions with SCN.

In the presence of SCN and SDS, phosphorus and phosphorus plus potassium

applied at excess levels enhanced yield. However, these results should be kept in

perspective. A larger survey of more than two fields throughout the state over several

years is necessary to assess the consequences of excess fertility on yields at fields with a

history of SDS/SCN. Future work investigating SDS response to fertility should prioritize

114

fields with high SCN populations and investigate the potential for phosphorus to mitigate

some yield loss.

Greenhouse studies did not clearly nor consistently support field results. However,

corrected fresh root weights (root weight per plant) were significantly higher than

nonfertilized controls when phosphorus (Erie trial 2: p= 0.018), potassium (Wood trial 2:

p= 0.022), and phosphorus plus potassium (Wood trial 1: p= 0.0002) were added (Table

4.11). The first trial for each field was conducted in Nov/Dec in greenhouses set to remain

between 18 to 19˚C, though their actual temperatures generally ranged from 20 to 26˚C

(Appendix I: Table I.2). Because no foliar symptoms were observed in this first trial, the

second trial was moved to a warmer greenhouse after 1 week, as previous studies generally

associate foliar symptoms with warmer temperatures, though actual infection is known to

occur at cool temperatures shortly after germination (Gongora-Canul & Leandro, 2011b;

Gongora-Canul et al., 2012). The second trial of each field was conducted in Feb/March,

and greenhouse temperatures generally ranged from 18 to 24˚C during the first week and

19 to 28˚C for the remainder of the experiment. Higher stand counts in the first trial may

have been linked to the warmer temperature range within the first week after planting.

Plants needed an extra week to reach the desired growth stage (V5) in the second trial,

possibly due to the cooler temperatures experienced during this first week. This extra time

may have contributed to the larger heights, higher root weights, and higher plant weights

observed in the second trial.

Distinct yellow spotting occurred in one of four assays and was primarily observed

in pots treated with phosphorus (Figure 4.6). Isolates recovered from these roots appeared

115

purplish-blue on APDA-SA, suggesting the presence of F. virguliforme. However, similar

isolates were also recovered from asymptomatic plants. Plants in all other trials were

asymptomatic. Isolates recovered from a 2015 survey of seedlings at the VC stage also

suggested F. virguliforme was present at the Wood site, known to have SDS history and

later used in the greenhouse assays. Single spore colonies of a subset of Fusarium isolates

collected in this survey were identified through sequencing of the ITS region and F.

oxysporum was confirmed. Although only a subset was identified to species, morphologic

and pigment variation suggested a complex community was present (Appendix J). It is

likely that the presence of other root pathogens may have contributed to the high disease

pressure. In order to assess the effect of soil fertility on SDS specifically, future

greenhouse studies should involve inoculated, rather than previously infested, soil.

Fertility treatments should also be applied incrementally as disease development is

monitored.

In summary, the field data suggest a potential effect of potassium and phosphorus

on SDS severity and final impact on yield in the presence of SCN. The significant

differences in disease index observed at Erie may be due to lower baseline potassium levels

and higher SCN counts. However, these studies should be repeated at more locations with

varying levels of fertility as well as greenhouse assays using inoculated steamed soil or

vermiculite. Future field studies should prioritize fields with low base levels of potassium

and high SCN counts.

116

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Appendix A: Soil Regions of Ohio

Figure A.1. Soil regions are characterized by the names of the soil series that are most common in each region (Division of Soil and Water Conservation, 2005).

138

Appendix B: Media

Table B.1. Several types of media were used in this study. Though each type of media may be used in a variety of ways, the primary function for its use in this study is listed below. Media Purpose Potato Carrot Agar (PCA)

General growth promoter for oomycetes and fungi

PIBNC Oomycete-selecting media. Sample from plant or previous plate should be placed under this media using sterile technique. Bacteria, fungi, etc. is limited to growth below the media and oomycetes will grow through the agar to the surface.

Water Agar (WA) Nutrient-poor media. Used when obtaining single spore colonies of Fusarium.

Carnation Leaf Agar (CLA)

This is the standard media used when observing morphologic characteristics of Fusarium spores. Place dried, sterile piece of carnation leaf on water agar at the time colonies are transferred.

Acidified Potato Dextrose Agar (APDA)

Used to promote mycelial growth while limiting bacterial contamination. When this media is inoculated with Fusarium and placed under fluorescent lights, the fungi may become pigmented. This color may be used to aide diagnostic purposes.

Amended APDA (APDA-SA)

Media used when isolating Fusarium virguliforme (the cause of sudden Death Syndrome in soybean) from the plant. Place under fluorescent lights and plates containing F. virguliforme will appear blue/purple after 2 weeks (Roy et al., 1997a).

NASH Fusarium-selecting media (Arias et al., 2013b). V8 broth Nutrient broth used when growing oomycetes for identification.

Approximately 5 days after inoculation with an oomycete isolate, the mycelium is vacuumed and ground with liquid nitrogen for DNA extraction.

Potato Dextrose Broth (PDB)

Fusarium may be stored long term in 1 mL PDB at 4˚C (Arias et al., 2013b).

Fusarium nutrient broth

Nutrient broth used when growing Fusarium for identification. Approximately 5 days after inoculation with a Fusarium isolate, the mycelium is vacuumed and ground with liquid nitrogen for DNA extraction (Ellis et al., 2014).

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Sampling for Oomycetes

Figure B.1. Though this chart may be used to guide oomycete recovery, alternative methodology may also be successful.

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Sampling for Fusarium

Figure B.2. Though this chart may be used to guide Fusarium recovery, alternative methodology may also be successful.

141

Appendix C: Isolate identification through DNA sequencing

Overview of process:

1. Obtain clean isolates approximately 5 days old.

2. Transfer approximately ten 5 mm plugs to V8 broth and grow for several days until mycelium covers about two-thirds of the surface (isolates later identified as Pythium may reach desired size around 4-5 days while Phytophthora isolates may require about 7).

3. Vacuum mycelium, grind in liquid nitrogen, and add extraction buffer.

4. Extract DNA.

5. Run a 1.5% gel to visualize bands, ensuring DNA was successfully extracted.

6. Nanodrop extracted DNA and dilute to 50 ng/µL.

7. Run PCR under program titled “ITS_DNA”

8. Run a 2% gel to visualize bands, ensuring PCR worked.

9. Clean PCR products with Exozap.

10. Nanodrop (no more than 1.5 µL because there should only be 14 µL product). Dilute to 50 ng/µL. (Though the MCIC directions call for a concentration of 5 ng/µL, Damitha always recommended 50 ng/µL. On occasion, sequences failed and adding an even higher concentration of product has solved the issue in the past.)

11. Prepare for sequencing by adding 3 µL of primer (concentration: 1 µM) to 6 µL of post enzyme cleanup product. Each sample will be submitted twice: once with the forward primer and once with the reverse. Submit to MCIC and include email attachment.

12. Prepare sequence output from MCIC by assembling contigs in CodonCode. Perform BLAST analysis through the NCBI database.

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Appendix D: Digestion and Extraction Buffers

Pythium/Phytophthora/Fusarium Digestion Buffer: (from Zelaya-Molina et al. 2011 and Ellis et al. 2014) Buffer: 10 mM Tris/HCl pH 8.0, 50 mM EDTA, 0.5% SDS, 0.5% Triton X-100, 0.5% Tween 20 (Procedure for making stock solutions of the following components is described below.) 25 mL of 1 M EDTA (or 50 mL of 0.5 M EDTA) 5 mL of 1 M Tris-HCl 2.5 mL of 100% Triton X-100 (Stored on top chemical shelf in lab 116 above water bath to left of sink) 2.5 mL of 100% Tween 20 (Stored on top chemical shelf in lab 116 above water bath to left of sink) 25 mL of 10% SDS solution Mix above components in sterile d. water and bring up to 500 mL by adding additional sterile d. water. Do NOT autoclave. Preparing stock solutions for this buffer: 1 M Tris-HCl [pH=8]:

1. Dissolve 12.11 g Tris in approximately 30 mL d. water (Note: Tris is stored in bucket below counter under pH meter in lab 116)

2. Titrate solution with 1 M HCl until pH=8 3. Bring to volume of 100 mL by adding d. water 4. Autoclave to sterilize 5. Store at 4˚C

1 M EDTA: 1. Dissolve 29.22 g in 100 mL d. water and stir vigorously. (Note: EDTA is found on

chemical shelf in lab 116 near Dextrose. EDTA is also known as “Ethylenediaminetetraacetic acid 99%”). May need to adjust pH to dissolve.

2. Autoclave to sterilize 3. Store at room temperature

Note: Probably best to make 0.5 M so it will dissolve easier.

(Continued on next page)

143

10% SDS: 1. Add 10g SDS to 80 mL sterile distilled water, bring up to 100 mL in volumetric

flask by adding sterile d. water. (Note: SDS is stored on top chemical shelf in lab 116 above water bath to left of sink)

2. Do NOT autoclave. 3. Store at room temperature

Fusarium Elution Buffer: (from Ellis et al. 2014)

(Note: stock solution preparation for the following components is described in the Fusarium Digestion Buffer procedure) Add 100 µL of 1 M Tris-HCl [pH=8] and 20 µL of 0.5 M EDTA into sterile 10 mL volumetric flask and raise to 10 mL by adding sterile d. water.

144

Appendix E. Field Notes

A

B Photographs for Soybean Pathology (OSU)

Figure E.1. Standing water was recorded at the Van Wert field site. A) Picture taken 12 June, 2015 after approximately 1.7 in. of rain in 30 min. B) Picture taken 26 June, 2015.

145

Figure E.2. A) Seedcorn maggot causes characteristic tunnels as it burrows through plant material above the soil line. B) The maggots are small, yellowish-white, and legless. C) Pupae resemble brown rice in appearance and size. D) Maggots may cause mild to severe damage to the cotyledons (Eyre et al., 2015a).

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Appendix F: SIUC Method of SDS Scoring

147

Appendix G: Greenhouse Protocols

For seedling disease assay:

1. Grind and thoroughly mix soil. 2. Add 12 pots worth of soil into clean plastic bin (approximately 1.4 kg/pot). Add

2.4 g of DAP, 2.4 g potash, or 2.4 g DAP plus 2.4 g potash, depending on the treatment. Thoroughly mix.

3. Put coffee filter in bottom of pot, add treated soil to approximately 3 cm below rim. Add stakes to label.

4. Put pots in large white tray and flood with deionized water overnight. 5. Drain pots for approximately 24-36 hours or until the moist soil formed cracks

when a pot was squeezed slightly and decompressed. 6. Put in plastic bags and incubate at room temperature for 2 weeks. 7. Plant 15 seeds 3 cm into the soil. (Sloan 2014 was used.) 8. Flood after 3 days for 24 hours. (Note: this step was ONLY done for the first trial.) 9. Record stand counts at 7 and 10 days. 10. Record remaining data when plants have reached the VC growth stage

(approximately 2 weeks in the fall and 3 weeks in the winter/early spring). For sudden death syndrome assay:

1. Grind and thoroughly mix soil. 2. Add 12 pots worth of soil into clean plastic bin (approximately 1.4 kg/pot). Add

2.4 g of DAP, 2.4 g potash, or 2.4 g DAP plus 2.4 g potash, depending on the treatment. Thoroughly mix.

3. Put coffee filter in bottom of pot, add treated soil to approximately 3 cm below rim. Add stakes to label.

4. Plant 12 SDS-susceptible seeds 3 cm into the soil. (untreated AGI 31R2Y2 3102N from Pond Seed Co. was used.)

5. Record stand counts at 7 and 10 days. 6. Record heights when plants have reached V4 growth stage. 7. Record remaining data when plants have reached the V5 growth stage

(approximately 5 weeks in the fall and 6 weeks in the winter/early spring).

148

Appendix H: Greenhouse data collection

Figure H.1. Root rot was rated on a 1 to 5 scale where (left to right) 1= healthy roots with no symptoms on any part of root system; 2= 1-20% of root system had lesions on lateral roots; 3= 21-75% of roots had symptoms, some lesions on tap root; 4= 76-100% of roots had symptoms on lateral and tap roots; and (not pictured) 5= complete root rot, no germination of seed.

Photo from Christine Balk

149

Figure H.2. Sporangia and oospores provide evidence of oomycete infection.

150

Figure H.3. In greenhouse assays with Fusarium virguliforme infested soil, the number of plants with diseased roots were counted and divided by the stand. Roots were considered diseased if dark brown lesions were visible on the taproot after a thorough washing. A) Asymptomatic roots B) The plant on the left was considered asymptomatic and the plant on the right was considered symptomatic. Thus, the pot was rated ½, or 0.5 C) Arrows indicate symptomatic roots and the pot was rated 5/7, or 0.71.

A B

C

151

Figure H.4. In sudden death syndrome disease greenhouse assays, plants were measured from the soil to the base of the V2 petiole at the V4 growth stage. Up to five plants were measured and averaged.

152

Appendix I: Greenhouse Temperatures Table I.1. For seedling disease greenhouse assays conducted with soil from Defiance and Van Wert, temperatures were set to remain between 17 to 18˚C (62 to 64˚F). However, greenhouse renovations in Selby complicated temperature regulation and temperatures fluctuated outside the ideal range frequently. Greenhouse conditions for each trial were recorded. The maximum and minimum temperature was recorded every weekday and some weekends for each greenhouse. The maximum and minimum temperature each trial was exposed to is recorded below, in addition to the average range. This range was calculated by separately averaging the available maximum and minimum values.

Van Wert Trial 1 Trial 2 Trial 3

Dates and Greenhouse

11/9-11/23 in Selby G008 2/5-3/2 in Selby G005 3/21-4/14 in Williams 060

Max. temp. 27˚C (82˚F) 36˚C (96˚F) 18˚C (64˚F) Min. temp. 19˚C (66˚F) 13˚C (56˚F) 17˚C (62˚F) Avg. range 20-24˚C (68-75˚F) 17-23˚C (62-74˚F) 17-18˚C (62-

64˚F) Notes -Watered with chlorinated water

for 6 days (11/10-11/16) -Only natural light before 11/18 when greenhouse lights were installed -Flooded for 24 hours three days after planting

Defiance Trial 1 Trial 2 Trial 3


11/16-11/30 in Selby G008 2/19-3/10 in Selby G005 3/21-4/14 in Williams 060

Max. temp. 28˚C (82˚F) 36˚C (96˚F) 18˚C (64˚F) Min. temp. 19˚C (66˚F) 13˚C (56˚F) 17˚C (62˚F) Avg. range 20-24˚C (68-76˚F) 17-24˚C (62-75˚F) 17-18˚C (62-

64˚F) Notes -Only natural light before 11/18

when greenhouse lights were installed -Flooded for 24 hours three days after planting -Vermiculite used to cover seed

-Moved to growth chamber on 3/7 for better temperature regulation. Growth chamber set to remain at 17-18 ˚C (62-64˚F).

153

Table I.2. For sudden death syndrome greenhouse assays with soil from Erie and Wood, temperatures were set to remain between 17-18˚C (62-64˚F) for the entirety of the first trial and the first week of the second trial. After 7 days, these second trials were moved to a warmer greenhouse set to remain at 20-21˚C (68-70˚F) in the effort to induce foliar symptoms of sudden death syndrome. However, greenhouse renovations in Selby complicated temperature regulation and temperatures fluctuated outside the ideal range frequently. The maximum and minimum temperature was recorded every weekday and some weekends for each greenhouse. The maximum and minimum temperature each trial was exposed to is recorded below, in addition to the average range. This range was calculated by separately averaging the available maximum and minimum values.

Erie Trial 1 Trial 2


11/10-12/16 in G008 2/2-2/9 in G005 set at 17-18˚C (62-64˚F) 2/10-3/20 in G025 set at 20-21˚C (68-70˚F)

Max. temp. 32˚C (89˚F) First week: 26˚C (79˚F) After first week: 41˚C (106˚F)

Min. temp. 11˚C (52˚F) First week: 16˚C (60˚F) After first week: 18˚C (64˚F)

Avg. range 19-24˚C (67-76˚F) First week: 16-22˚C (61-71˚F) After first week: 18-27˚C (65-81˚F)

Notes -Watered with chlorinated water for 6 days (11/10-11/16) -only natural light from 11/10-11/18, when greenhouse lights were installed

Wood Trial 1 Trial 2 Dates and Greenhouse

10/26-11/10 in Selby G003 11/10-12/2 in Selby G008

2/22-2/29 in G005 set at 17-18˚C (62-64˚F) 3/1-4/14 in G025 set at 20-21˚C (68-70˚F)

Max. temp. 32˚C (89˚F) First week: 32˚C (91˚F) After first week: 33˚C (92˚F)

Min. temp. 18˚C (65˚F) First week: 15˚C (59˚F) After first week: 18˚C (65˚F)

Avg. range 21-27˚C (69-80˚F) First week: 18-27˚C (64-81˚F) After first week: 21-29˚C (69-84˚F)

Notes -Watered with chlorinated water for 6 days (11/10-11/16) -only natural light from 11/10-11/18, when greenhouse lights were installed

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Appendix J: 2015 Survey at VC growth stage

# Sample code Field Plot Trt Plant Media Preliminary ID 1 MWa1.1a Wood 1 P 1 PCA Fusarium sp. 2 MWa1.1b Wood 1 P 1 PBNC lost 3 MWa1.1c Wood 1 P 1 PDA Fusarium sp. 4 MWa1.2a Wood 1 P 2 PCA Fusarium sp. 5 MWa1.2b Wood 1 P 2 PBNC lost 6 MWa1.2c Wood 1 P 2 PDA Fusarium sp. 7 MWa1.3a Wood 1 P 3 PCA Fusarium sp. 8 MWa1.3b Wood 1 P 3 PBNC lost 9 MWa1.3c Wood 1 P 3 PDA Fusarium sp.

10 MWa1.4a Wood 1 P 4 PCA Fusarium sp. 11 MWa1.4b Wood 1 P 4 PBNC lost 12 MWa1.4c Wood 1 P 4 PDA black 13 MWa1.5a Wood 1 P 5 PCA double oospore 14 MWa1.5b Wood 1 P 5 PBNC lost 15 MWa1.5c Wood 1 P 5 PDA Fusarium sp. 16 MWa2.1a Wood 2 K 1 PCA Fusarium sp. 17 MWa2.1b Wood 2 K 1 PBNC lost 18 MWa2.1c Wood 2 K 1 PDA Unknown 19 MWa2.2a Wood 2 K 2 PCA Unknown 20 MWa2.2b Wood 2 K 2 PBNC lost 21 MWa2.2c Wood 2 K 2 PDA Macrophomina phaseolina 22 MWa2.3a1 Wood 2 K 3 PCA Fusarium sp. 23 MWa2.3b Wood 2 K 3 PBNC lost 24 MWa2.3c Wood 2 K 3 PDA Fusarium sp. 25 MWa2.4a Wood 2 K 4 PCA Fusarium sp. 26 MWa2.4b Wood 2 K 4 PBNC lost 27 MWa2.4c Wood 2 K 4 PDA Fusarium sp. 28 MWa2.5a Wood 2 K 5 PCA Unknown 29 MWa2.5b Wood 2 K 5 PBNC lost 30 MWa2.5c Wood 2 K 5 PDA large white sclerotia 31 MWa3.1a Wood 3 PK 1 PCA Fusarium sp. 32 MWa3.1b Wood 3 PK 1 PBNC lost 33 MWa3.1c Wood 3 PK 1 PDA likely Trichoderma or Gliocadium 34 MWa3.2a Wood 3 PK 2 PCA lost 35 MWa3.2b Wood 3 PK 2 PBNC lost 36 MWa3.2c Wood 3 PK 2 PDA likely Trichoderma or Gliocadium 37 MWa3.3a Wood 3 PK 3 PCA Fusarium sp. 38 MWa3.3b Wood 3 PK 3 PBNC lost 39 MWa3.3c Wood 3 PK 3 PDA Fusarium sp. 40 MWa3.4a Wood 3 PK 4 PCA Fusarium sp. 41 MWa3.4b Wood 3 PK 4 PBNC lost 42 MWa3.4c Wood 3 PK 4 PDA Fusarium sp. 43 MWa3.5a Wood 3 PK 5 PCA Fusarium sp. 44 MWa3.5b Wood 3 PK 5 PBNC lost 45 MWa3.5c Wood 3 PK 5 PDA likely Trichoderma or Gliocadium 46 MWa4.1a1 Wood 4 None 1 PCA Fusarium sp.


155

# Sample code Field Plot Trt Plant Media Preliminary ID 47 MWa4.1b Wood 4 None 1 PBNC lost 48 MWa4.1c Wood 4 None 1 PDA Fusarium sp. 49 MWa4.2a Wood 4 None 2 PCA Fusarium sp. 50 MWa4.2b Wood 4 None 2 PBNC lost 51 MWa4.2c Wood 4 None 2 PDA likely Trichoderma or Gliocadium 52 MWa4.3a Wood 4 None 3 PCA Fusarium sp. 53 MWa4.3b Wood 4 None 3 PBNC lost 54 MWa4.3c Wood 4 None 3 PDA likely Trichoderma or Gliocadium 55 MWa4.4a Wood 4 None 4 PCA likely Trichoderma or Gliocadium 56 MWa4.4b Wood 4 None 4 PBNC lost 57 MWa4.4c Wood 4 None 4 PDA large white sclerotia 58 MWa4.5a1 Wood 4 None 5 PCA Fusarium sp. 59 MWa4.5b Wood 4 None 5 PBNC lost 60 MWa4.5c Wood 4 None 5 PDA Fusarium sp. 61 MWa5.1a Wood 5 PK 1 PCA Unknown 62 MWa5.1b Wood 5 PK 1 PBNC Unknown 63 MWa5.1c Wood 5 PK 1 PDA likely Trichoderma or Gliocadium 64 MWa5.2a Wood 5 PK 2 PCA lost 65 MWa5.2b Wood 5 PK 2 PBNC lost 66 MWa5.2c Wood 5 PK 2 PDA likely Trichoderma or Gliocadium 67 MWa5.3a Wood 5 PK 3 PCA Fusarium sp. 68 MWa5.3b Wood 5 PK 3 PBNC lost 69 MWa5.3c Wood 5 PK 3 PDA Fusarium sp. 70 MWa5.4a Wood 5 PK 4 PCA double oospore 71 MWa5.4b Wood 5 PK 4 PBNC lost 72 MWa5.4c1 Wood 5 PK 4 PDA black 73 MWa5.5a Wood 5 PK 5 PCA Fusarium sp. 74 MWa5.5b Wood 5 PK 5 PBNC lost 75 MWa5.5c Wood 5 PK 5 PDA likely Trichoderma or Gliocadium 76 MWa6.1a Wood 6 None 1 PCA Fusarium sp. 77 MWa6.1b Wood 6 None 1 PBNC lost 78 MWa6.1c Wood 6 None 1 PDA likely Trichoderma or Gliocadium 79 MWa6.2a Wood 6 None 2 PCA Fusarium sp. 80 MWa6.2b Wood 6 None 2 PBNC lost 81 MWa6.2c Wood 6 None 2 PDA Fusarium sp. 82 MWa6.3a Wood 6 None 3 PCA Fusarium sp. 83 MWa6.3b Wood 6 None 3 PBNC lost 84 MWa6.3c Wood 6 None 3 PDA Macrophomina phaseolina 85 MWa6.4a1 Wood 6 None 4 PCA Fusarium sp. 86 MWa6.4b Wood 6 None 4 PBNC lost 87 MWa6.4c Wood 6 None 4 PDA Fusarium graminearum 88 MWa6.5a Wood 6 None 5 PCA oomycete 89 MWa6.5b Wood 6 None 5 PBNC lost 90 MWa6.5c Wood 6 None 5 PDA Fusarium sp. 91 MWa7.1a Wood 7 P 1 PCA Fusarium graminearum 92 MWa7.1b Wood 7 P 1 PBNC lost 93 MWa7.1c Wood 7 P 1 PDA likely Trichoderma or Gliocadium 94 MWa7.2a Wood 7 P 2 PCA Fusarium sp. 95 MWa7.2b Wood 7 P 2 PBNC lost 96 MWa7.2c Wood 7 P 2 PDA Fusarium sp. 97 MWa7.3a Wood 7 P 3 PCA Fusarium sp. 98 MWa7.3b Wood 7 P 3 PBNC lost 99 MWa7.3c Wood 7 P 3 PDA likely Trichoderma or Gliocadium

100 MWa7.4a Wood 7 P 4 PCA Macrophomina phaseolina 101 MWa7.4b Wood 7 P 4 PBNC lost


156

# Sample code Field Plot Trt Plant Media Preliminary ID 102 MWa7.4c Wood 7 P 4 PDA likely Trichoderma or Gliocadium 103 MWa7.5a Wood 7 P 5 PCA Fusarium sp. 104 MWa7.5b Wood 7 P 5 PBNC lost 105 MWa7.5c Wood 7 P 5 PDA Fusarium sp. 106 MWa8.1a1 Wood 8 K 1 PCA Fusarium sp. 107 MWa8.1b Wood 8 K 1 PBNC lost 108 MWa8.1c Wood 8 K 1 PDA lost 109 MWa8.2a Wood 8 K 2 PCA Fusarium graminearum 110 MWa8.2b Wood 8 K 2 PBNC lost 111 MWa8.2c Wood 8 K 2 PDA likely Trichoderma or Gliocadium 112 MWa8.3a Wood 8 K 3 PCA Fusarium sp. 113 MWa8.3b Wood 8 K 3 PBNC lost 114 MWa8.3c Wood 8 K 3 PDA Fusarium sp. 115 MWa8.4a Wood 8 K 4 PCA Fusarium sp. 116 MWa8.4b Wood 8 K 4 PBNC double oospore 117 MWa8.4c Wood 8 K 4 PDA Fusarium sp. 118 MWa8.5a1 Wood 8 K 5 PCA Fusarium sp. 119 MWa8.5b Wood 8 K 5 PBNC lost 120 MWa8.5c Wood 8 K 5 PDA likely Trichoderma or Gliocadium 121 MWa9.1a1 Wood 9 P 1 PCA oomycete 122 MWa9.1b Wood 9 P 1 PBNC Unknown 123 MWa9.1c Wood 9 P 1 PDA Fusarium graminearum 124 MWa9.2a Wood 9 P 2 PCA Fusarium sp. 125 MWa9.2b Wood 9 P 2 PBNC lost 126 MWa9.2c Wood 9 P 2 PDA Unknown 127 MWa9.3a Wood 9 P 3 PCA Fusarium sp. 128 MWa9.3b Wood 9 P 3 PBNC lost 129 MWa9.3c Wood 9 P 3 PDA Unknown 130 MWa9.4a Wood 9 P 4 PCA Fusarium sp. 131 MWa9.4b Wood 9 P 4 PBNC double oospore 132 MWa9.4c Wood 9 P 4 PDA Unknown 133 MWa9.5a2 Wood 9 P 5 PCA Fusarium oxysporum 134 MWa9.5b Wood 9 P 5 PBNC Unknown 135 MWa9.5c Wood 9 P 5 PDA lost 136 MWa10.1a Wood 10 None 1 PCA Fusarium sp. 137 MWa10.1b Wood 10 None 1 PBNC lost 138 MWa10.1c Wood 10 None 1 PDA Fusarium graminearum 139 MWa10.2a Wood 10 None 2 PCA Fusarium graminearum 140 MWa10.2b Wood 10 None 2 PBNC lost 141 MWa10.2c Wood 10 None 2 PDA Fusarium sp. 142 MWa10.3a1 Wood 10 None 3 PCA Fusarium graminearum 143 MWa10.3b Wood 10 None 3 PBNC lost 144 MWa10.3c1 Wood 10 None 3 PDA Fusarium sp. 145 MWa10.4a Wood 10 None 4 PCA Fusarium graminearum 146 MWa10.4b Wood 10 None 4 PBNC lost 147 MWa10.4c Wood 10 None 4 PDA Fusarium graminearum 148 MWa10.5a Wood 10 None 5 PCA Fusarium graminearum 149 MWa10.5b Wood 10 None 5 PBNC lost 150 MWa10.5c Wood 10 None 5 PDA black 151 MWa11.1a Wood 11 K 1 PCA Fusarium sp. 152 MWa11.1b Wood 11 K 1 PBNC lost 153 MWa11.1c Wood 11 K 1 PDA likely Trichoderma or Gliocadium 154 MWa11.2a Wood 11 K 2 PCA Fusarium sp. 155 MWa11.2b Wood 11 K 2 PBNC lost


157

# Sample code Field Plot Trt Plant Media Preliminary ID 156 MWa11.2c Wood 11 K 2 PDA likely Trichoderma or Gliocadium 157 MWa11.3a Wood 11 K 3 PCA Unknown 158 MWa11.3b Wood 11 K 3 PBNC lost 159 MWa11.3c Wood 11 K 3 PDA lost 160 MWa11.4a Wood 11 K 4 PCA Fusarium oxysporum 161 MWa11.4b Wood 11 K 4 PBNC lost 162 MWa11.4c Wood 11 K 4 PDA likely Trichoderma or Gliocadium 163 MWa11.5a Wood 11 K 5 PCA Fusarium sp. 164 MWa11.5b Wood 11 K 5 PBNC lost 165 MWa11.5c Wood 11 K 5 PDA Fusarium sp. 166 MWa12.1a Wood 12 PK 1 PCA oomycete 167 MWa12.1b Wood 12 PK 1 PBNC Unknown 168 MWa12.1c Wood 12 PK 1 PDA Fusarium oxysporum 169 MWa12.2a Wood 12 PK 2 PCA Fusarium graminearum 170 MWa12.2b Wood 12 PK 2 PBNC Unknown 171 MWa12.2c Wood 12 PK 2 PDA Fusarium graminearum 172 MWa12.3a Wood 12 PK 3 PCA Fusarium graminearum 173 MWa12.3b Wood 12 PK 3 PBNC lost 174 MWa12.3c Wood 12 PK 3 PDA Fusarium sp. 175 MWa12.4a Wood 12 PK 4 PCA Fusarium oxysporum 176 MWa12.4b Wood 12 PK 4 PBNC lost 177 MWa12.4c Wood 12 PK 4 PDA Fusarium sp. 178 MWa12.5a Wood 12 PK 5 PCA black 179 MWa12.5b Wood 12 PK 5 PBNC lost 180 MWa12.5c Wood 12 PK 5 PDA black 181 MWa13.1a Wood 13 P 1 PCA oomycete 182 MWa13.1b Wood 13 P 1 PBNC lost 183 MWa13.1c Wood 13 P 1 PDA Fusarium graminearum 184 MWa13.2a Wood 13 P 2 PCA Unknown 185 MWa13.2b Wood 13 P 2 PBNC lost 186 MWa13.2c Wood 13 P 2 PDA Fusarium graminearum 187 MWa13.3a Wood 13 P 3 PCA Unknown 188 MWa13.3b Wood 13 P 3 PBNC lost 189 MWa13.3c Wood 13 P 3 PDA Unknown 190 MWa13.4a Wood 13 P 4 PCA Fusarium sp. 191 MWa13.4b Wood 13 P 4 PBNC lost 192 MWa13.4c Wood 13 P 4 PDA Fusarium sp. 193 MWa13.5a Wood 13 P 5 PCA Fusarium oxysporum 194 MWa13.5b Wood 13 P 5 PBNC lost 195 MWa13.5c Wood 13 P 5 PDA likely Trichoderma or Gliocadium 196 MWa14.1a Wood 14 K 1 PCA lost 197 MWa14.1b Wood 14 K 1 PBNC lost 198 MWa14.1c Wood 14 K 1 PDA lost 199 MWa14.2a Wood 14 K 2 PCA Fusarium sp. 200 MWa14.2b Wood 14 K 2 PBNC lost 201 MWa14.2c Wood 14 K 2 PDA likely Trichoderma or Gliocadium 202 MWa14.3a Wood 14 K 3 PCA Macrophomina phaseolina 203 MWa14.3b Wood 14 K 3 PBNC lost 204 MWa14.3c Wood 14 K 3 PDA lost 205 MWa14.4a Wood 14 K 4 PCA Fusarium oxysporum 206 MWa14.4b Wood 14 K 4 PBNC lost 207 MWa14.4c Wood 14 K 4 PDA black 208 MWa14.5a Wood 14 K 5 PCA Fusarium sp. 209 MWa14.5b Wood 14 K 5 PBNC lost


158

# Sample code Field Plot Trt Plant Media Preliminary ID 210 MWa14.5c Wood 14 K 5 PDA Fusarium sp. 211 MWa15.1a Wood 15 None 1 PCA Unknown 212 MWa15.1b Wood 15 None 1 PBNC lost 213 MWa15.1c Wood 15 None 1 PDA likely Trichoderma or Gliocadium 214 MWa15.2a Wood 15 None 2 PCA Fusarium sp. 215 MWa15.2b Wood 15 None 2 PBNC Unknown 216 MWa15.2c Wood 15 None 2 PDA Unknown 217 MWa15.3a Wood 15 None 3 PCA Fusarium sp. 218 MWa15.3b Wood 15 None 3 PBNC double oospore 219 MWa15.3c Wood 15 None 3 PDA Fusarium sp. 220 MWa15.4a Wood 15 None 4 PCA Fusarium sp. 221 MWa15.4b Wood 15 None 4 PBNC double oospore 222 MWa15.4c Wood 15 None 4 PDA Fusarium graminearum 223 MWa15.5a Wood 15 None 5 PCA Unknown 224 MWa15.5b Wood 15 None 5 PBNC lost 225 MWa15.5c Wood 15 None 5 PDA Fusarium sp. 226 MWa16.1a Wood 16 PK 1 PCA Fusarium sp. 227 MWa16.1b Wood 16 PK 1 PBNC lost 228 MWa16.1c Wood 16 PK 1 PDA likely Trichoderma or Gliocadium 229 MWa16.2a Wood 16 PK 2 PCA Fusarium sp. 230 MWa16.2b Wood 16 PK 2 PBNC Unknown 231 MWa16.2c Wood 16 PK 2 PDA Fusarium sp. 232 MWa16.3a Wood 16 PK 3 PCA lost 233 MWa16.3b Wood 16 PK 3 PBNC lost 234 MWa16.3c Wood 16 PK 3 PDA Unknown 235 MWa16.4a Wood 16 PK 4 PCA Fusarium sp. 236 MWa16.4b Wood 16 PK 4 PBNC lost 237 MWa16.4c Wood 16 PK 4 PDA Fusarium sp. 238 MWa16.5a Wood 16 PK 5 PCA Fusarium sp. 239 MWa16.5b Wood 16 PK 5 PBNC lost 240 MWa16.5c Wood 16 PK 5 PDA Fusarium sp. 241 MWa17.1a Wood 17 None 1 PCA black 242 MWa17.1b Wood 17 None 1 PBNC lost 243 MWa17.1c Wood 17 None 1 PDA Fusarium sp. 244 MWa17.2a Wood 17 None 2 PCA Fusarium sp. 245 MWa17.2b Wood 17 None 2 PBNC lost 246 MWa17.2c Wood 17 None 2 PDA Fusarium sp. 247 MWa17.3a Wood 17 None 3 PCA black 248 MWa17.3b Wood 17 None 3 PBNC lost 249 MWa17.3c Wood 17 None 3 PDA Fusarium sp. 250 MWa17.4a Wood 17 None 4 PCA likely Trichoderma or Gliocadium 251 MWa17.4b Wood 17 None 4 PBNC lost 252 MWa17.4c Wood 17 None 4 PDA likely Trichoderma or Gliocadium 253 MWa17.5a Wood 17 None 5 PCA lost 254 MWa17.5b Wood 17 None 5 PBNC lost 255 MWa17.5c Wood 17 None 5 PDA likely Trichoderma or Gliocadium 256 MWa18.1a Wood 18 PK 1 PCA Fusarium graminearum 257 MWa18.1b Wood 18 PK 1 PBNC Unknown 258 MWa18.1c Wood 18 PK 1 PDA lost 259 MWa18.2a Wood 18 PK 2 PCA likely Trichoderma or Gliocadium 260 MWa18.2b Wood 18 PK 2 PBNC lost 261 MWa18.2c Wood 18 PK 2 PDA likely Trichoderma or Gliocadium 262 MWa18.3a Wood 18 PK 3 PCA Fusarium sp. 263 MWa18.3b Wood 18 PK 3 PBNC lost 264 MWa18.3c Wood 18 PK 3 PDA Fusarium sp. 265 MWa18.4a Wood 18 PK 4 PCA black


159

# Sample code Field Plot Trt Plant Media Preliminary ID 266 MWa18.4b Wood 18 PK 4 PBNC lost 267 MWa18.4c Wood 18 PK 4 PDA large white sclerotia 268 MWa18.5a Wood 18 PK 5 PCA Fusarium sp. 269 MWa18.5b Wood 18 PK 5 PBNC lost 270 MWa18.5c Wood 18 PK 5 PDA Fusarium sp. 271 MWa19.1a Wood 19 P 1 PCA Fusarium sp. 272 MWa19.1b Wood 19 P 1 PBNC lost 273 MWa19.1c Wood 19 P 1 PDA likely Trichoderma or Gliocadium 274 MWa19.2a Wood 19 P 2 PCA Fusarium sp. 275 MWa19.2b Wood 19 P 2 PBNC lost 276 MWa19.2c Wood 19 P 2 PDA likely Trichoderma or Gliocadium 277 MWa19.3a Wood 19 P 3 PCA Unknown 278 MWa19.3b Wood 19 P 3 PBNC lost 279 MWa19.3c Wood 19 P 3 PDA lost 280 MWa19.4a Wood 19 P 4 PCA Fusarium sp. 281 MWa19.4b Wood 19 P 4 PBNC lost 282 MWa19.4c Wood 19 P 4 PDA Fusarium sp. 283 MWa19.5a Wood 19 P 5 PCA Fusarium sp. 284 MWa19.5b Wood 19 P 5 PBNC lost 285 MWa19.5c Wood 19 P 5 PDA likely Trichoderma or Gliocadium 286 MWa20.1a Wood 20 K 1 PCA Fusarium sp. 287 MWa20.1b Wood 20 K 1 PBNC lost 288 MWa20.1c Wood 20 K 1 PDA Fusarium sp. 289 MWa20.2a Wood 20 K 2 PCA likely Trichoderma or Gliocadium 290 MWa20.2b Wood 20 K 2 PBNC lost 291 MWa20.2c Wood 20 K 2 PDA likely Trichoderma or Gliocadium 292 MWa20.3a Wood 20 K 3 PCA small black fuzzy sclerotia 293 MWa20.3b Wood 20 K 3 PBNC lost 294 MWa20.3c Wood 20 K 3 PDA lost 295 MWa20.4a Wood 20 K 4 PCA lost 296 MWa20.4b Wood 20 K 4 PBNC Unknown with septa 297 MWa20.4c Wood 20 K 4 PDA lost 298 MWa20.5a Wood 20 K 5 PCA Fusarium sp. 299 MWa20.5b Wood 20 K 5 PBNC lost 300 MWa20.5c Wood 20 K 5 PDA likely Trichoderma or Gliocadium 301 MWa21.1a Wood 21 P 1 PCA Fusarium sp. 302 MWa21.1b Wood 21 P 1 PBNC lost 303 MWa21.1c Wood 21 P 1 PDA Fusarium sp. 304 MWa21.2a Wood 21 P 2 PCA Unknown with septa 305 MWa21.2b Wood 21 P 2 PBNC lost 306 MWa21.2c Wood 21 P 2 PDA Unknown 307 MWa21.3a Wood 21 P 3 PCA Fusarium graminearum 308 MWa21.3b Wood 21 P 3 PBNC lost 309 MWa21.3c Wood 21 P 3 PDA likely Trichoderma or Gliocadium 310 MWa21.4a Wood 21 P 4 PCA Fusarium sp. 311 MWa21.4b Wood 21 P 4 PBNC lost 312 MWa21.4c Wood 21 P 4 PDA likely Trichoderma or Gliocadium 313 MWa21.5a Wood 21 P 5 PCA Fusarium graminearum 314 MWa21.5b Wood 21 P 5 PBNC lost 315 MWa21.5c Wood 21 P 5 PDA Fusarium sp. 316 MWa22.1a Wood 22 PK 1 PCA Fusarium sp. 317 MWa22.1b Wood 22 PK 1 PBNC lost 318 MWa22.1c Wood 22 PK 1 PDA Fusarium sp. 319 MWa22.2a Wood 22 PK 2 PCA Fusarium sp. 320 MWa22.2b Wood 22 PK 2 PBNC lost 321 MWa22.2c Wood 22 PK 2 PDA large white sclerotia


160

# Sample code Field Plot Trt Plant Media Preliminary ID 322 MWa22.3a1 Wood 22 PK 3 PCA Fusarium sp. 323 MWa22.3b Wood 22 PK 3 PBNC lost 324 MWa22.3c Wood 22 PK 3 PDA likely Trichoderma or Gliocadium 325 MWa22.4a Wood 22 PK 4 PCA Fusarium sp. 326 MWa22.4b Wood 22 PK 4 PBNC lost 327 MWa22.4c Wood 22 PK 4 PDA lost 328 MWa22.5a Wood 22 PK 5 PCA lost 329 MWa22.5b Wood 22 PK 5 PBNC lost 330 MWa22.5c Wood 22 PK 5 PDA Unknown with septa 331 MWa23.1a Wood 23 K 1 PCA Fusarium sp. 332 MWa23.1b Wood 23 K 1 PBNC lost 333 MWa23.1c Wood 23 K 1 PDA Fusarium sp. 334 MWa23.2a Wood 23 K 2 PCA Fusarium sp. 335 MWa23.2b Wood 23 K 2 PBNC lost 336 MWa23.2c Wood 23 K 2 PDA likely Trichoderma or Gliocadium 337 MWa23.3a Wood 23 K 3 PCA black 338 MWa23.3b Wood 23 K 3 PBNC lost 339 MWa23.3c Wood 23 K 3 PDA likely Trichoderma or Gliocadium 340 MWa23.4a Wood 23 K 4 PCA lost 341 MWa23.4b Wood 23 K 4 PBNC lost 342 MWa23.4c Wood 23 K 4 PDA likely Trichoderma or Gliocadium 343 MWa23.5a Wood 23 K 5 PCA Fusarium sp. 344 MWa23.5b Wood 23 K 5 PBNC lost 345 MWa23.5c Wood 23 K 5 PDA Fusarium sp. 346 MWa24.1a Wood 24 None 1 PCA likely Trichoderma or Gliocadium 347 MWa24.1b Wood 24 None 1 PBNC lost 348 MWa24.1c Wood 24 None 1 PDA likely Trichoderma or Gliocadium 349 MWa24.2a Wood 24 None 2 PCA likely Trichoderma or Gliocadium 350 MWa24.2b Wood 24 None 2 PBNC lost 351 MWa24.2c Wood 24 None 2 PDA likely Trichoderma or Gliocadium 352 MWa24.3a1 Wood 24 None 3 PCA black 353 MWa24.3b Wood 24 None 3 PBNC lost 354 MWa24.3c Wood 24 None 3 PDA Fusarium graminearum 355 MWa24.4a Wood 24 None 4 PCA black 356 MWa24.4b Wood 24 None 4 PBNC lost 357 MWa24.4c Wood 24 None 4 PDA likely Trichoderma or Gliocadium 358 MWa24.5a Wood 24 None 5 PCA Fusarium sp. 359 MWa24.5b Wood 24 None 5 PBNC lost 360 MWa24.5c Wood 24 None 5 PDA large white sclerotia 361 MVa1.1a VW 1 P 1 PCA Fusarium graminearum 362 MVa1.1b VW 1 P 1 PBNC oomycete 363 MVa1.2a VW 1 P 2 PCA oomycete 364 MVa1.2b VW 1 P 2 PBNC oomycete 365 MVa1.3a VW 1 P 3 PCA Fusarium graminearum 366 MVa1.3b VW 1 P 3 PBNC Unknown 367 MVa1.4a VW 1 P 4 PCA oomycete 368 MVa1.4b VW 1 P 4 PBNC oomycete 369 MVa1.5a VW 1 P 5 PCA Unknown 370 MVa1.5b VW 1 P 5 PBNC Unknown 371 MVa2.1a VW 2 K 1 PCA Fusarium graminearum 372 MVa2.1b VW 2 K 1 PBNC Unknown 373 MVa2.2a VW 2 K 2 PCA Fusarium sp. 374 MVa2.2b VW 2 K 2 PBNC oomycete 375 MVa2.3a VW 2 K 3 PCA Fusarium sp. 376 MVa2.3b VW 2 K 3 PBNC Unknown 377 MVa2.4a VW 2 K 4 PCA oomycete


161

# Sample code Field Plot Trt Plant Media Preliminary ID 378 MVa2.4b VW 2 K 4 PBNC oomycete 379 MVa2.5a VW 2 K 5 PCA Fusarium sp. 380 MVa2.5b VW 2 K 5 PBNC oomycete 381 MVa3.1a VW 3 PK 1 PCA Fusarium sp. 382 MVa3.1b VW 3 PK 1 PBNC oomycete 383 MVa3.2a VW 3 PK 2 PCA Fusarium sp. 384 MVa3.2b VW 3 PK 2 PBNC Unknown 385 MVa3.3a VW 3 PK 3 PCA oomycete 386 MVa3.3b VW 3 PK 3 PBNC oomycete 387 MVa3.4a VW 3 PK 4 PCA Fusarium sp. 388 MVa3.4b VW 3 PK 4 PBNC oomycete 389 MVa3.5a VW 3 PK 5 PCA oomycete 390 MVa3.5b VW 3 PK 5 PBNC oomycete 391 MVa4.1a VW 4 None 1 PCA Unknown 392 MVa4.1b VW 4 None 1 PBNC Unknown 393 MVa4.2a VW 4 None 2 PCA Fusarium sp. 394 MVa4.2b VW 4 None 2 PBNC Unknown 395 MVa4.3a VW 4 None 3 PCA Fusarium sp. 396 MVa4.3b VW 4 None 3 PBNC Unknown 397 MVa4.4a VW 4 None 4 PCA lost 398 MVa4.4b VW 4 None 4 PBNC Unknown 399 MVa4.5a VW 4 None 5 PCA Unknown 400 MVa4.5b VW 4 None 5 PBNC Unknown 401 MVa5.1a VW 5 PK 1 PCA oomycete 402 MVa5.1b VW 5 PK 1 PBNC oomycete 403 MVa5.2a VW 5 PK 2 PCA Fusarium graminearum 404 MVa5.2b VW 5 PK 2 PBNC oomycete 405 MVa5.3a VW 5 PK 3 PCA Fusarium sp. 406 MVa5.3b VW 5 PK 3 PBNC oomycete 407 MVa5.4a VW 5 PK 4 PCA oomycete 408 MVa5.4b VW 5 PK 4 PBNC oomycete 409 MVa5.5a VW 5 PK 5 PCA oomycete 410 MVa5.5b VW 5 PK 5 PBNC oomycete 411 MVa6.1a VW 6 None 1 PCA Unknown 412 MVa6.1b VW 6 None 1 PBNC lost 413 MVa6.2a VW 6 None 2 PCA Unknown 414 MVa6.2b VW 6 None 2 PBNC Unknown 415 MVa6.3a VW 6 None 3 PCA Fusarium sp. 416 MVa6.3b VW 6 None 3 PBNC oomycete 417 MVa6.4a VW 6 None 4 PCA oomycete 418 MVa6.4b VW 6 None 4 PBNC oomycete 419 MVa6.5a VW 6 None 5 PCA Fusarium sp. 420 MVa6.5b VW 6 None 5 PBNC oomycete 421 MVa7.1a VW 7 P 1 PCA oomycete 422 MVa7.1b VW 7 P 1 PBNC Unknown 423 MVa7.2a VW 7 P 2 PCA oomycete 424 MVa7.2b VW 7 P 2 PBNC oomycete 425 MVa7.3a VW 7 P 3 PCA Fusarium graminearum 426 MVa7.3b VW 7 P 3 PBNC oomycete 427 MVa7.4a VW 7 P 4 PCA oomycete 428 MVa7.4b VW 7 P 4 PBNC oomycete 429 MVa7.5a VW 7 P 5 PCA Fusarium graminearum 430 MVa7.5b VW 7 P 5 PBNC oomycete 431 MVa8.1a VW 8 K 1 PCA Unknown 432 MVa8.1b VW 8 K 1 PBNC oomycete 433 MVa8.2a VW 8 K 2 PCA Fusarium graminearum


162

# Sample code Field Plot Trt Plant Media Preliminary ID 434 MVa8.2b VW 8 K 2 PBNC Unknown 435 MVa8.3a VW 8 K 3 PCA Fusarium sp. 436 MVa8.3b VW 8 K 3 PBNC Unknown 437 MVa8.4a VW 8 K 4 PCA Unknown 438 MVa8.4b VW 8 K 4 PBNC oomycete 439 MVa8.5a VW 8 K 5 PCA Fusarium graminearum 440 MVa8.5b VW 8 K 5 PBNC Unknown 441 MVa9.1a VW 9 P 1 PCA lost 442 MVa9.1b VW 9 P 1 PBNC lost 443 MVa9.2a VW 9 P 2 PCA Fusarium sp. 444 MVa9.2b VW 9 P 2 PBNC Unknown 445 MVa9.3a VW 9 P 3 PCA Unknown 446 MVa9.3b VW 9 P 3 PBNC Unknown 447 MVa9.4a VW 9 P 4 PCA Fusarium graminearum 448 MVa9.4b VW 9 P 4 PBNC Unknown 449 MVa9.5a VW 9 P 5 PCA Unknown 450 MVa9.5b VW 9 P 5 PBNC Unknown 451 MVa10.1a VW 10 None 1 PCA Fusarium graminearum 452 MVa10.1b VW 10 None 1 PBNC lost 453 MVa10.2a VW 10 None 2 PCA Fusarium sp. 454 MVa10.2b VW 10 None 2 PBNC oomycete 455 MVa10.3a VW 10 None 3 PCA Fusarium sp. 456 MVa10.3b VW 10 None 3 PBNC oomycete 457 MVa10.4a VW 10 None 4 PCA Unknown 458 MVa10.4b VW 10 None 4 PBNC oomycete 459 MVa10.5a VW 10 None 5 PCA lost 460 MVa10.5b VW 10 None 5 PBNC Unknown 461 MVa11.1a VW 11 K 1 PCA Fusarium graminearum 462 MVa11.1b VW 11 K 1 PBNC Unknown 463 MVa11.2a VW 11 K 2 PCA Unknown 464 MVa11.2b VW 11 K 2 PBNC Unknown 465 MVa11.3a VW 11 K 3 PCA Fusarium sp. 466 MVa11.3b VW 11 K 3 PBNC oomycete 467 MVa11.4a VW 11 K 4 PCA Fusarium sp. 468 MVa11.4b VW 11 K 4 PBNC Unknown 469 MVa11.5a VW 11 K 5 PCA Unknown 470 MVa11.5b VW 11 K 5 PBNC Unknown 471 MVa12.1a VW 12 PK 1 PCA Fusarium sp. 472 MVa12.1b VW 12 PK 1 PBNC Unknown 473 MVa12.2a VW 12 PK 2 PCA Fusarium sp. 474 MVa12.2b VW 12 PK 2 PBNC Unknown 475 MVa12.3a VW 12 PK 3 PCA oomycete 476 MVa12.3b VW 12 PK 3 PBNC oomycete 477 MVa12.4a VW 12 PK 4 PCA Fusarium sp. 478 MVa12.4b VW 12 PK 4 PBNC Unknown 479 MVa12.5a VW 12 PK 5 PCA Fusarium sp. 480 MVa12.5b VW 12 PK 5 PBNC oomycete 481 MVa13.1a VW 13 P 1 PCA Fusarium sp. 482 MVa13.1b VW 13 P 1 PBNC Unknown 483 MVa13.2a VW 13 P 2 PCA Fusarium sp. 484 MVa13.2b VW 13 P 2 PBNC Unknown 485 MVa13.3a VW 13 P 3 PCA Fusarium sp. 486 MVa13.3b VW 13 P 3 PBNC oomycete 487 MVa13.4a VW 13 P 4 PCA Fusarium sp. 488 MVa13.4b VW 13 P 4 PBNC Unknown 489 MVa13.5a VW 13 P 5 PCA oomycete


163

# Sample code Field Plot Trt Plant Media Preliminary ID 490 MVa13.5b VW 13 P 5 PBNC oomycete 491 MVa14.1a VW 14 K 1 PCA lost 492 MVa14.1b VW 14 K 1 PBNC Unknown 493 MVa14.2a VW 14 K 2 PCA Fusarium graminearum 494 MVa14.2b VW 14 K 2 PBNC Unknown 495 MVa14.3a VW 14 K 3 PCA Fusarium graminearum 496 MVa14.3b VW 14 K 3 PBNC Unknown 497 MVa14.4a VW 14 K 4 PCA Fusarium sp. 498 MVa14.4b VW 14 K 4 PBNC oomycete 499 MVa14.5a VW 14 K 5 PCA Fusarium sp. 500 MVa14.5b VW 14 K 5 PBNC Unknown 501 MVa15.1a VW 15 None 1 PCA Unknown 502 MVa15.1b VW 15 None 1 PBNC Unknown 503 MVa15.2a VW 15 None 2 PCA Fusarium graminearum 504 MVa15.2b VW 15 None 2 PBNC lost 505 MVa15.3a VW 15 None 3 PCA Fusarium graminearum 506 MVa15.3b VW 15 None 3 PBNC Unknown 507 MVa15.4a VW 15 None 4 PCA lost 508 MVa15.4b VW 15 None 4 PBNC Unknown 509 MVa15.5a VW 15 None 5 PCA Fusarium graminearum 510 MVa15.5b VW 15 None 5 PBNC Unknown 511 MVa16.1a VW 16 PK 1 PCA lost 512 MVa16.1b VW 16 PK 1 PBNC Fusarium sp. 513 MVa16.2a VW 16 PK 2 PCA oomycete 514 MVa16.2b VW 16 PK 2 PBNC Fusarium graminearum 515 MV16.3a VW 16 PK 3 PCA Fusarium sp. 516 MVa16.3b VW 16 PK 3 PBNC Fusarium sp. 517 MVa16.4a VW 16 PK 4 PCA lost 518 MVa16.4b VW 16 PK 4 PBNC Fusarium sp. 519 MVa16.5a VW 16 PK 5 PCA Unknown 520 MVa16.5b VW 16 PK 5 PBNC Fusarium sp. 521 MVa17.1a VW 17 None 1 PCA Unknown 522 MVa17.1b VW 17 None 1 PBNC Fusarium sp. 523 MVa17.2a VW 17 None 2 PCA oomycete 524 MVa17.2b VW 17 None 2 PBNC Fusarium graminearum 525 MVa17.3a VW 17 None 3 PCA oomycete 526 MVa17.3b VW 17 None 3 PBNC Fusarium sp. 527 MVa17.4a VW 17 None 4 PCA oomycete 528 MVa17.4b VW 17 None 4 PBNC Fusarium graminearum 529 MVa17.5a VW 17 None 5 PCA oomycete 530 MVa17.5b VW 17 None 5 PBNC Fusarium graminearum 531 MVa18.1a VW 18 PK 1 PCA Fusarium graminearum 532 MVa18.1b VW 18 PK 1 PBNC lost 533 MVa18.2a VW 18 PK 2 PCA Fusarium graminearum 534 MVa18.2b VW 18 PK 2 PBNC Unknown 535 MVa18.3a VW 18 PK 3 PCA Fusarium graminearum 536 MVa18.3b VW 18 PK 3 PBNC oomycete 537 MVa18.4a VW 18 PK 4 PCA Unknown 538 MVa18.4b VW 18 PK 4 PBNC Unknown 539 MVa18.5a VW 18 PK 5 PCA lost 540 MVa18.5b VW 18 PK 5 PBNC oomycete 541 MVa19.1a VW 19 P 1 PCA lost 542 MVa19.1b VW 19 P 1 PBNC Fusarium graminearum 543 MVa19.2a VW 19 P 2 PCA Unknown 544 MVa19.2b VW 19 P 2 PBNC Fusarium graminearum 545 MVa19.3a VW 19 P 3 PCA Unknown


164

# Sample code Field Plot Trt Plant Media Preliminary ID 546 MVa19.3b VW 19 P 3 PBNC Fusarium graminearum 547 MVa19.4a VW 19 P 4 PCA lost 548 MVa19.4b VW 19 P 4 PBNC oomycete 549 MVa19.5a VW 19 P 5 PCA lost 550 MVa19.5b VW 19 P 5 PBNC Fusarium sp. 551 MVa20.1a VW 20 K 1 PCA oomycete 552 MVa20.1b VW 20 K 1 PBNC oomycete 553 MVa20.2a VW 20 K 2 PCA Macrophomina phaseolina 554 MVa20.2b VW 20 K 2 PBNC Unknown 555 MVa20.3a VW 20 K 3 PCA Fusarium graminearum 556 MVa20.3b VW 20 K 3 PBNC oomycete 557 MVa20.4a VW 20 K 4 PCA oomycete 558 MVa20.4b VW 20 K 4 PBNC oomycete 559 MVa20.5a VW 20 K 5 PCA Fusarium graminearum 560 MVa20.5b VW 20 K 5 PBNC oomycete 561 MVa21.1a VW 21 P 1 PCA Fusarium graminearum 562 MVa21.1b VW 21 P 1 PBNC oomycete 563 MVa21.2a VW 21 P 2 PCA Fusarium graminearum 564 MVa21.2b VW 21 P 2 PBNC Unknown 565 MVa21.3a VW 21 P 3 PCA Fusarium sp. 566 MVa21.3b VW 21 P 3 PBNC Unknown 567 MVa21.4a VW 21 P 4 PCA Unknown 568 MVa21.4b VW 21 P 4 PBNC oomycete 569 MVa21.5a VW 21 P 5 PCA lost 570 MVa21.5b VW 21 P 5 PBNC oomycete 571 MVa22.1a VW 22 PK 1 PCA Fusarium graminearum 572 MVa22.1b VW 22 PK 1 PBNC Fusarium graminearum 573 MVa22.2a1 VW 22 PK 2 PCA Macrophomina phaseolina 574 MVa22.2b VW 22 PK 2 PBNC Unknown 575 MVa22.3a VW 22 PK 3 PCA oomycete 576 MVa22.3b VW 22 PK 3 PBNC Unknown 577 MVa22.4a VW 22 PK 4 PCA Unknown 578 MVa22.4b VW 22 PK 4 PBNC Unknown 579 MVa22.5a VW 22 PK 5 PCA lost 580 MVa22.5b VW 22 PK 5 PBNC Unknown 581 MVa23.1a1 VW 23 K 1 PCA Fusarium sp. 582 MVa23.1b VW 23 K 1 PBNC Unknown 583 MVa23.2a VW 23 K 2 PCA Fusarium graminearum 584 MVa23.2b VW 23 K 2 PBNC Unknown 585 MVa23.3a VW 23 K 3 PCA Unknown 586 MVa23.3b VW 23 K 3 PBNC oomycete 587 MVa23.4a VW 23 K 4 PCA oomycete 588 MVa23.4b VW 23 K 4 PBNC Unknown 589 MVa23.5a VW 23 K 5 PCA oomycete 590 MVa23.5b VW 23 K 5 PBNC oomycete 591 MVa24.1a VW 24 None 1 PCA lost 592 MVa24.1b VW 24 None 1 PBNC oomycete 593 MVa24.2a VW 24 None 2 PCA Unknown 594 MVa24.2b VW 24 None 2 PBNC Unknown 595 MVa24.3a VW 24 None 3 PCA Fusarium sp. 596 MVa24.3b VW 24 None 3 PBNC Unknown 597 MVa24.4a VW 24 None 4 PCA Fusarium sp. 598 MVa24.4b VW 24 None 4 PBNC Unknown 599 MVa24.5a VW 24 None 5 PCA Unknown 600 MVa24.5b VW 24 None 5 PBNC Unknown 601 MDa1.1a Defiance 1 P 1 PCA Fusarium graminearum


165

# Sample code Field Plot Trt Plant Media Preliminary ID 602 MDa1.1b Defiance 1 P 1 PBNC Fusarium sp. 603 MDa1.2a Defiance 1 P 2 PCA Macrophomina phaseolina 604 MDa1.2b Defiance 1 P 2 PBNC Unknown 605 MDa1.3a Defiance 1 P 3 PCA oomycete 606 MDa1.3b Defiance 1 P 3 PBNC Unknown 607 MDa1.4a Defiance 1 P 4 PCA Unknown with septa 608 MDa1.4b Defiance 1 P 4 PBNC oomycete 609 MDa1.5a Defiance 1 P 5 PCA oomycete 610 MDa1.5b Defiance 1 P 5 PBNC oomycete 611 MDa2.1a Defiance 2 K 1 PCA oomycete 612 MDa2.1b Defiance 2 K 1 PBNC Unknown 613 MDa2.2a Defiance 2 K 2 PCA Fusarium sp. 614 MDa2.2b Defiance 2 K 2 PBNC Unknown 615 MDa2.3a Defiance 2 K 3 PCA oomycete 616 MDa2.3b Defiance 2 K 3 PBNC oomycete 617 MDa2.4a Defiance 2 K 4 PCA Fusarium graminearum 618 MDa2.4b Defiance 2 K 4 PBNC oomycete 619 MDa2.5a Defiance 2 K 5 PCA Unknown 620 MDa2.5b Defiance 2 K 5 PBNC lost 621 MDa3.1a Defiance 3 PK 1 PCA Fusarium sp. 622 MDa3.1b Defiance 3 PK 1 PBNC Unknown 623 MDa3.2a Defiance 3 PK 2 PCA Fusarium graminearum 624 MDa3.2b Defiance 3 PK 2 PBNC lost 625 MDa3.3a Defiance 3 PK 3 PCA Fusarium sp. 626 MDa3.3b Defiance 3 PK 3 PBNC lost 627 MDa3.4a Defiance 3 PK 4 PCA Unknown with septa 628 MDa3.4b Defiance 3 PK 4 PBNC lost 629 MDa3.5a1 Defiance 3 PK 5 PCA Unknown 630 MDa3.5b Defiance 3 PK 5 PBNC oomycete 631 MDa4.1a Defiance 4 None 1 PCA oomycete 632 MDa4.1b Defiance 4 None 1 PBNC oomycete 633 MDa4.2a Defiance 4 None 2 PCA Unknown 634 MDa4.2b Defiance 4 None 2 PBNC oomycete 635 MDa4.3a Defiance 4 None 3 PCA Fusarium sp. 636 MDa4.3b Defiance 4 None 3 PBNC oomycete 637 MDa4.4a1 Defiance 4 None 4 PCA Fusarium sp. 638 MDa4.4b Defiance 4 None 4 PBNC oomycete 639 MDa4.5a Defiance 4 None 5 PCA Unknown 640 MDa4.5b Defiance 4 None 5 PBNC lost 641 MDa5.1a Defiance 5 PK 1 PCA Fusarium sp. 642 MDa5.1b Defiance 5 PK 1 PBNC Fusarium sp. 643 MDa5.2a Defiance 5 PK 2 PCA oomycete 644 MDa5.2b Defiance 5 PK 2 PBNC oomycete 645 MDa5.3a Defiance 5 PK 3 PCA Fusarium graminearum 646 MDa5.3b Defiance 5 PK 3 PBNC Unknown 647 MDa5.4a Defiance 5 PK 4 PCA Fusarium sp. 648 MDa5.4b Defiance 5 PK 4 PBNC oomycete 649 MDa5.5a Defiance 5 PK 5 PCA Fusarium sp. 650 MDa5.5b Defiance 5 PK 5 PBNC Unknown 651 MDa6.1a Defiance 6 None 1 PCA Fusarium sp. 652 MDa6.1b Defiance 6 None 1 PBNC oomycete 653 MDa6.2a Defiance 6 None 2 PCA Fusarium sp. 654 MDa6.2b Defiance 6 None 2 PBNC Unknown 655 MDa6.3a1 Defiance 6 None 3 PCA Fusarium sp. 656 MDa6.3b Defiance 6 None 3 PBNC lost 657 MDa6.4a Defiance 6 None 4 PCA oomycete


166

# Sample code Field Plot Trt Plant Media Preliminary ID 658 MDa6.4b Defiance 6 None 4 PBNC oomycete 659 MDa6.5a Defiance 6 None 5 PCA Unknown 660 MDa6.5b Defiance 6 None 5 PBNC oomycete 661 MDa7.1a Defiance 7 P 1 PCA Unknown 662 MDa7.1b Defiance 7 P 1 PBNC lost 663 MDa7.2a Defiance 7 P 2 PCA Fusarium sp. 664 MDa7.2b Defiance 7 P 2 PBNC lost 665 MDa7.3a Defiance 7 P 3 PCA Fusarium sp. 666 MDa7.3b Defiance 7 P 3 PBNC lost 667 MDa7.4a Defiance 7 P 4 PCA Fusarium sp. 668 MDa7.4b Defiance 7 P 4 PBNC lost 669 MDa7.5a Defiance 7 P 5 PCA lost 670 MDa7.5b Defiance 7 P 5 PBNC lost 671 MDa8.1a Defiance 8 K 1 PCA Fusarium sp. 672 MDa8.1b Defiance 8 K 1 PBNC lost 673 MDa8.2a Defiance 8 K 2 PCA oomycete 674 MDa8.2b Defiance 8 K 2 PBNC oomycete 675 MDa8.3a Defiance 8 K 3 PCA Fusarium sp. 676 MDa8.3b Defiance 8 K 3 PBNC Unknown 677 MDa8.4a Defiance 8 K 4 PCA oomycete 678 MDa8.4b Defiance 8 K 4 PBNC oomycete 679 MDa8.5a Defiance 8 K 5 PCA Fusarium sp. 680 MDa8.5b Defiance 8 K 5 PBNC oomycete 681 MDa9.1a Defiance 9 P 1 PCA lost 682 MDa9.1b Defiance 9 P 1 PBNC lost 683 MDa9.2a Defiance 9 P 2 PCA Fusarium sp. 684 MDa9.2b Defiance 9 P 2 PBNC lost 685 MDa9.3a Defiance 9 P 3 PCA Fusarium sp. 686 MDa9.3b Defiance 9 P 3 PBNC lost 687 MDa9.4a Defiance 9 P 4 PCA Fusarium graminearum 688 MDa9.4b Defiance 9 P 4 PBNC lost 689 MDa9.5a Defiance 9 P 5 PCA lost 690 MDa9.5b Defiance 9 P 5 PBNC lost 691 MDa10.1a Defiance 10 None 1 PCA Unknown with septa 692 MDa10.1b Defiance 10 None 1 PBNC Unknown 693 MDa10.2a Defiance 10 None 2 PCA Fusarium sp. 694 MDa10.2b Defiance 10 None 2 PBNC lost 695 MDa10.3a Defiance 10 None 3 PCA Unknown 696 MDa10.3b Defiance 10 None 3 PBNC lost 697 MDa10.4a Defiance 10 None 4 PCA Fusarium sp. 698 MDa10.4b Defiance 10 None 4 PBNC Fusarium sp. 699 MDa10.5a Defiance 10 None 5 PCA Unknown 700 MDa10.5b Defiance 10 None 5 PBNC oomycete 701 MDa11.1a Defiance 11 K 1 PCA lost 702 MDa11.1b Defiance 11 K 1 PBNC lost 703 MDa11.2a Defiance 11 K 2 PCA oomycete 704 MDa11.2b Defiance 11 K 2 PBNC Unknown 705 MDa11.3a Defiance 11 K 3 PCA Fusarium sp. 706 MDa11.3b Defiance 11 K 3 PBNC oomycete 707 MD1.4a Defiance 11 K 4 PCA Unknown 708 MDa11.4b Defiance 11 K 4 PBNC lost 709 MDa11.5a Defiance 11 K 5 PCA Fusarium sp. 710 MDa11.5b Defiance 11 K 5 PBNC oomycete 711 MDa12.1a Defiance 12 PK 1 PCA Fusarium sp. 712 MDa12.1b1 Defiance 12 PK 1 PBNC oomycete 713 MDa12.2a Defiance 12 PK 2 PCA Fusarium sp.


167

# Sample code Field Plot Trt Plant Media Preliminary ID 714 MDa12.2b Defiance 12 PK 2 PBNC oomycete 715 MDa12.3a Defiance 12 PK 3 PCA Unknown 716 MDa12.3b Defiance 12 PK 3 PBNC lost 717 MDa12.4a Defiance 12 PK 4 PCA Fusarium sp. 718 MDa12.4b Defiance 12 PK 4 PBNC lost 719 MDa12.5a Defiance 12 PK 5 PCA Unknown 720 MDa12.5b Defiance 12 PK 5 PBNC oomycete 721 MDa13.1a Defiance 13 P 1 PCA lost 722 MDa13.1b Defiance 13 P 1 PBNC lost 723 MDa13.2a Defiance 13 P 2 PCA lost 724 MDa13.2b Defiance 13 P 2 PBNC lost 725 MDa13.3a Defiance 13 P 3 PCA lost 726 MDa13.3b Defiance 13 P 3 PBNC lost 727 MDa13.4a Defiance 13 P 4 PCA lost 728 MDa13.4b Defiance 13 P 4 PBNC lost 729 MDa13.5a Defiance 13 P 5 PCA Fusarium graminearum 730 MDa13.5b Defiance 13 P 5 PBNC lost 731 MDa14.1a Defiance 14 K 1 PCA Unknown 732 MDa14.1b Defiance 14 K 1 PBNC lost 733 MDa14.2a Defiance 14 K 2 PCA Unknown 734 MDa14.2b Defiance 14 K 2 PBNC Unknown 735 MDa14.3a Defiance 14 K 3 PCA Fusarium sp. 736 MDa14.3b Defiance 14 K 3 PBNC lost 737 MDa14.4a Defiance 14 K 4 PCA Fusarium sp. 738 MDa14.4b Defiance 14 K 4 PBNC lost 739 MDa14.5a Defiance 14 K 5 PCA Fusarium sp. 740 MDa14.5b Defiance 14 K 5 PBNC lost 741 MDa15.1a Defiance 15 None 1 PCA Fusarium sp. 742 MDa15.1b Defiance 15 None 1 PBNC lost 743 MDa15.2a Defiance 15 None 2 PCA Fusarium sp. 744 MDa15.2b Defiance 15 None 2 PBNC Unknown 745 MDa15.3a Defiance 15 None 3 PCA Unknown 746 MDa15.3b Defiance 15 None 3 PBNC Unknown 747 MDa15.4a Defiance 15 None 4 PCA Fusarium sp. 748 MDa15.4b Defiance 15 None 4 PBNC lost 749 MDa15.5a Defiance 15 None 5 PCA oomycete 750 MDa15.5b Defiance 15 None 5 PBNC oomycete 751 MDa16.1a Defiance 16 PK 1 PCA oomycete 752 MDa16.1b Defiance 16 PK 1 PBNC Unknown 753 MDa16.2a Defiance 16 PK 2 PCA Fusarium sp. 754 MDa16.2b Defiance 16 PK 2 PBNC lost 755 MD16.3a Defiance 16 PK 3 PCA Fusarium sp. 756 MDa16.3b Defiance 16 PK 3 PBNC Unknown 757 MDa16.4a Defiance 16 PK 4 PCA Fusarium sp. 758 MDa16.4b Defiance 16 PK 4 PBNC lost 759 MDa16.5a Defiance 16 PK 5 PCA Unknown 760 MDa16.5b Defiance 16 PK 5 PBNC lost 761 MDa17.1a Defiance 17 None 1 PCA oomycete 762 MDa17.1b Defiance 17 None 1 PBNC oomycete 763 MDa17.2a Defiance 17 None 2 PCA Fusarium sp. 764 MDa17.2b Defiance 17 None 2 PBNC Unknown 765 MDa17.3a Defiance 17 None 3 PCA Fusarium sp. 766 MDa17.3b Defiance 17 None 3 PBNC lost 767 MDa17.4a Defiance 17 None 4 PCA Fusarium sp. 768 MDa17.4b Defiance 17 None 4 PBNC Unknown 769 MDa17.5a Defiance 17 None 5 PCA Fusarium sp.


168

# Sample code Field Plot Trt Plant Media Preliminary ID 770 MDa17.5b Defiance 17 None 5 PBNC oomycete 771 MDa18.1a Defiance 18 PK 1 PCA oomycete 772 MDa18.1b Defiance 18 PK 1 PBNC oomycete 773 MDa18.2a Defiance 18 PK 2 PCA Fusarium graminearum 774 MDa18.2b Defiance 18 PK 2 PBNC Fusarium sp. 775 MDa18.3a Defiance 18 PK 3 PCA Fusarium sp. 776 MDa18.3b Defiance 18 PK 3 PBNC oomycete 777 MDa18.4a Defiance 18 PK 4 PCA Fusarium sp. 778 MDa18.4b Defiance 18 PK 4 PBNC lost 779 MDa18.5a Defiance 18 PK 5 PCA Fusarium sp. 780 MDa18.5b Defiance 18 PK 5 PBNC oomycete 781 MDa19.1a Defiance 19 P 1 PCA oomycete 782 MDa19.1b Defiance 19 P 1 PBNC Unknown 783 MDa19.2a Defiance 19 P 2 PCA Fusarium sp. 784 MDa19.2b Defiance 19 P 2 PBNC lost 785 MDa19.3a1 Defiance 19 P 3 PCA Macrophomina phaseolina 786 MDa19.3b Defiance 19 P 3 PBNC Unknown 787 MDa19.4a Defiance 19 P 4 PCA Fusarium sp. 788 MDa19.4b Defiance 19 P 4 PBNC lost 789 MDa19.5a Defiance 19 P 5 PCA Fusarium sp. 790 MDa19.5b Defiance 19 P 5 PBNC oomycete 791 MDa20.1a Defiance 20 K 1 PCA oomycete 792 MDa20.1b Defiance 20 K 1 PBNC oomycete 793 MDa20.2a Defiance 20 K 2 PCA oomycete 794 MDa20.2b Defiance 20 K 2 PBNC oomycete 795 MDa20.3a Defiance 20 K 3 PCA Fusarium sp. 796 MDa20.3b Defiance 20 K 3 PBNC oomycete 797 MDa20.4a Defiance 20 K 4 PCA oomycete 798 MDa20.4b Defiance 20 K 4 PBNC oomycete 799 MDa20.5a Defiance 20 K 5 PCA oomycete 800 MDa20.5b Defiance 20 K 5 PBNC oomycete 801 MDa21.1a Defiance 21 P 1 PCA Fusarium sp. 802 MDa21.1b Defiance 21 P 1 PBNC lost 803 MDa21.2a Defiance 21 P 2 PCA oomycete 804 MDa21.2b Defiance 21 P 2 PBNC oomycete 805 MDa21.3a Defiance 21 P 3 PCA Fusarium sp. 806 MDa21.3b Defiance 21 P 3 PBNC oomycete 807 MDa21.4a Defiance 21 P 4 PCA Fusarium sp. 808 MDa21.4b Defiance 21 P 4 PBNC oomycete 809 MDa21.5a Defiance 21 P 5 PCA Fusarium sp. 810 MDa21.5b Defiance 21 P 5 PBNC oomycete 811 MDa22.1a Defiance 22 PK 1 PCA oomycete 812 MDa22.1b Defiance 22 PK 1 PBNC oomycete 813 MDa22.2a Defiance 22 PK 2 PCA Fusarium sp. 814 MDa22.2b Defiance 22 PK 2 PBNC oomycete 815 MDa22.3a Defiance 22 PK 3 PCA Fusarium sp. 816 MDa22.3b Defiance 22 PK 3 PBNC oomycete 817 MDa22.4a Defiance 22 PK 4 PCA Fusarium sp. 818 MDa22.4b Defiance 22 PK 4 PBNC oomycete 819 MDa22.5a Defiance 22 PK 5 PCA Fusarium graminearum 820 MDa22.5b Defiance 22 PK 5 PBNC Unknown 821 MDa23.1a Defiance 23 K 1 PCA Fusarium graminearum 822 MDa23.1b Defiance 23 K 1 PBNC Unknown 823 MDa23.2a Defiance 23 K 2 PCA oomycete 824 MDa23.2b Defiance 23 K 2 PBNC oomycete 825 MDa23.3a Defiance 23 K 3 PCA Fusarium sp.


169

# Sample code Field Plot Trt Plant Media Preliminary ID 826 MDa23.3b Defiance 23 K 3 PBNC Unknown 827 MDa23.4a Defiance 23 K 4 PCA Unknown 828 MDa23.4b Defiance 23 K 4 PBNC Unknown 829 MDa23.5a Defiance 23 K 5 PCA lost 830 MDa23.5b Defiance 23 K 5 PBNC oomycete 831 MDa24.1a Defiance 24 None 1 PCA Fusarium sp. 832 MDa24.1b Defiance 24 None 1 PBNC lost 833 MDa24.2a Defiance 24 None 2 PCA Fusarium sp. 834 MDa24.2b Defiance 24 None 2 PBNC oomycete 835 MDa24.3a Defiance 24 None 3 PCA oomycete 836 MDa24.3b Defiance 24 None 3 PBNC oomycete 837 MDa24.4a Defiance 24 None 4 PCA Fusarium sp. 838 MDa24.4b Defiance 24 None 4 PBNC Unknown 839 MDa24.5a Defiance 24 None 5 PCA oomycete 840 MDa24.5b Defiance 24 None 5 PBNC Unknown 841 MSa1.1a Snyder 1 P 1 PCA lost 842 MSa1.1b Snyder 1 P 1 PBNC lost 843 MSa1.2a Snyder 1 P 2 PCA Unknown A 844 MSa1.2b Snyder 1 P 2 PBNC Rhizopus contamination 845 MSa1.3a Snyder 1 P 3 PCA Unknown A 846 MSa1.3b Snyder 1 P 3 PBNC lost 847 MSa1.4a Snyder 1 P 4 PCA Fusarium sp. 848 MSa1.4b Snyder 1 P 4 PBNC lost 849 MSa1.5a Snyder 1 P 5 PCA oomycete 850 MSa1.5b Snyder 1 P 5 PBNC lost 851 MSa2.1a Snyder 2 K 1 PCA Rhizopus contamination 852 MSa2.1b Snyder 2 K 1 PBNC lost 853 MSa2.2a Snyder 2 K 2 PCA oomycete 854 MSa2.2b Snyder 2 K 2 PBNC Fusarium sp. 855 MSa2.3a Snyder 2 K 3 PCA Fusarium graminearum 856 MSa2.3b Snyder 2 K 3 PBNC Unknown 857 MSa2.4a Snyder 2 K 4 PCA Unknown 858 MSa2.4b Snyder 2 K 4 PBNC oomycete 859 MSa2.5a Snyder 2 K 5 PCA Fusarium graminearum 860 MSa2.5b Snyder 2 K 5 PBNC Rhizopus contamination 861 MSa3.1a Snyder 3 PK 1 PCA lost 862 MSa3.1b Snyder 3 PK 1 PBNC lost 863 MSa3.2a Snyder 3 PK 2 PCA Unknown with septa 864 MSa3.2b Snyder 3 PK 2 PBNC Unknown 865 MSa3.3a Snyder 3 PK 3 PCA Rhizopus contamination 866 MSa3.3b Snyder 3 PK 3 PBNC oomycete 867 MSa3.4a Snyder 3 PK 4 PCA Unknown with septa 868 MSa3.4b Snyder 3 PK 4 PBNC lost 869 MSa3.5a Snyder 3 PK 5 PCA Unknown with septa 870 MSa3.5b Snyder 3 PK 5 PBNC Unknown 871 MSa4.1a Snyder 4 None 1 PCA Macrophomina phaseolina 872 MSa4.1b Snyder 4 None 1 PBNC lost 873 MSa4.2a1 Snyder 4 None 2 PCA Fusarium sp. 874 MSa4.2b Snyder 4 None 2 PBNC lost 875 MSa4.3a Snyder 4 None 3 PCA Macrophomina phaseolina 876 MSa4.3b Snyder 4 None 3 PBNC lost 877 MSa4.4a Snyder 4 None 4 PCA Fusarium sp. 878 MSa4.4b Snyder 4 None 4 PBNC lost 879 MSa4.5a Snyder 4 None 5 PCA Unknown A 880 MSa4.5b Snyder 4 None 5 PBNC lost 881 MSa5.1a Snyder 5 PK 1 PCA Fusarium graminearum


170

# Sample code Field Plot Trt Plant Media Preliminary ID 882 MSa5.1b Snyder 5 PK 1 PBNC Rhizopus contamination 883 MSa5.2a Snyder 5 PK 2 PCA Unknown with septa 884 MSa5.2b Snyder 5 PK 2 PBNC lost 885 MSa5.3a Snyder 5 PK 3 PCA Fusarium sp. 886 MSa5.3b Snyder 5 PK 3 PBNC oomycete 887 MSa5.4a Snyder 5 PK 4 PCA oomycete 888 MSa5.4b Snyder 5 PK 4 PBNC oomycete 889 MSa5.5a Snyder 5 PK 5 PCA Fusarium sp. 890 MSa5.5b Snyder 5 PK 5 PBNC oomycete 891 MSa6.1a Snyder 6 None 1 PCA Fusarium sp. 892 MSa6.1b Snyder 6 None 1 PBNC lost 893 MSa6.2a Snyder 6 None 2 PCA Unknown with septa 894 MSa6.2b Snyder 6 None 2 PBNC Unknown 895 MSa6.3a Snyder 6 None 3 PCA Unknown 896 MSa6.3b Snyder 6 None 3 PBNC lost 897 MSa6.4a Snyder 6 None 4 PCA Macrophomina phaseolina 898 MSa6.4b Snyder 6 None 4 PBNC lost 899 MSa6.5a Snyder 6 None 5 PCA Fusarium sp. 900 MSa6.5b Snyder 6 None 5 PBNC lost 901 MSa7.1a Snyder 7 P 1 PCA Unknown 902 MSa7.1b Snyder 7 P 1 PBNC lost 903 MSa7.2a1 Snyder 7 P 2 PCA Fusarium graminearum 904 MSa7.2b Snyder 7 P 2 PBNC Rhizopus contamination 905 MSa7.3a Snyder 7 P 3 PCA lost 906 MSa7.3b Snyder 7 P 3 PBNC lost 907 MSa7.4a Snyder 7 P 4 PCA Fusarium graminearum 908 MSa7.4b Snyder 7 P 4 PBNC lost 909 MSa7.5a1 Snyder 7 P 5 PCA Fusarium sp. 910 MSa7.5b Snyder 7 P 5 PBNC Unknown 911 MSa8.1a Snyder 8 K 1 PCA Rhizopus contamination 912 MSa8.1b Snyder 8 K 1 PBNC lost 913 MSa8.2a Snyder 8 K 2 PCA oomycete 914 MSa8.2b Snyder 8 K 2 PBNC lost 915 MSa8.3a Snyder 8 K 3 PCA Fusarium graminearum 916 MSa8.3b Snyder 8 K 3 PBNC Rhizopus contamination 917 MSa8.4a Snyder 8 K 4 PCA oomycete 918 MSa8.4b Snyder 8 K 4 PBNC lost 919 MSa8.5a Snyder 8 K 5 PCA Unknown 920 MSa8.5b Snyder 8 K 5 PBNC lost 921 MSa9.1a Snyder 9 P 1 PCA Fusarium sp. 922 MSa9.1b Snyder 9 P 1 PBNC lost 923 MSa9.2a Snyder 9 P 2 PCA Fusarium sp. 924 MSa9.2b Snyder 9 P 2 PBNC lost 925 MSa9.3a1 Snyder 9 P 3 PCA Unknown with septa 926 MSa9.3b Snyder 9 P 3 PBNC Unknown 927 MSa9.4a Snyder 9 P 4 PCA Unknown with septa 928 MSa9.4b Snyder 9 P 4 PBNC oomycete 929 MSa9.5a Snyder 9 P 5 PCA lost 930 MSa9.5b Snyder 9 P 5 PBNC Unknown 931 MSa10.1a1 Snyder 10 None 1 PCA Rhizopus contamination 932 MSa10.1b Snyder 10 None 1 PBNC Unknown 933 MSa10.2a Snyder 10 None 2 PCA Fusarium sp. 934 MSa10.2b Snyder 10 None 2 PBNC oomycete 935 MSa10.3a1 Snyder 10 None 3 PCA Fusarium sp. 936 MSa10.3b Snyder 10 None 3 PBNC lost 937 MSa10.4a Snyder 10 None 4 PCA Rhizopus contamination


171

# Sample code Field Plot Trt Plant Media Preliminary ID 938 MSa10.4b Snyder 10 None 4 PBNC lost 939 MSa10.5a Snyder 10 None 5 PCA Unknown 940 MSa10.5b Snyder 10 None 5 PBNC lost 941 MSa11.1a Snyder 11 K 1 PCA Unknown B 942 MSa11.1b Snyder 11 K 1 PBNC lost 943 MSa11.2a Snyder 11 K 2 PCA Unknown 944 MSa11.2b Snyder 11 K 2 PBNC oomycete 945 MSa11.3a Snyder 11 K 3 PCA Fusarium sp. 946 MSa11.3b Snyder 11 K 3 PBNC Unknown 947 MSa11.4a Snyder 11 K 4 PCA Fusarium graminearum 948 MSa11.4b Snyder 11 K 4 PBNC lost 949 MSa11.5a Snyder 11 K 5 PCA Fusarium sp. 950 MSa11.5b Snyder 11 K 5 PBNC Unknown 951 MSa12.1a Snyder 12 PK 1 PCA Fusarium sp. 952 MSa12.1b Snyder 12 PK 1 PBNC lost 953 MSa12.2a Snyder 12 PK 2 PCA Unknown 954 MSa12.2b Snyder 12 PK 2 PBNC Unknown 955 MSa12.3a Snyder 12 PK 3 PCA Unknown A 956 MSa12.3b Snyder 12 PK 3 PBNC Unknown 957 MSa12.4a Snyder 12 PK 4 PCA Fusarium sp. 958 MSa12.4b Snyder 12 PK 4 PBNC Unknown 959 MSa12.5a Snyder 12 PK 5 PCA Unknown A 960 MSa12.5b Snyder 12 PK 5 PBNC lost 961 MSa13.1a Snyder 13 P 1 PCA Fusarium sp. 962 MSa13.1b Snyder 13 P 1 PBNC lost 963 MSa13.2a Snyder 13 P 2 PCA Fusarium graminearum 964 MSa13.2b Snyder 13 P 2 PBNC Fusarium sp. 965 MSa13.3a Snyder 13 P 3 PCA Fusarium graminearum 966 MSa13.3b Snyder 13 P 3 PBNC Unknown 967 MSa13.4a Snyder 13 P 4 PCA Fusarium graminearum 968 MSa13.4b Snyder 13 P 4 PBNC Unknown 969 MSa13.5a Snyder 13 P 5 PCA Unknown with septa 970 MSa13.5b Snyder 13 P 5 PBNC lost 971 MSa14.1a Snyder 14 K 1 PCA Fusarium sp. 972 MSa14.1b Snyder 14 K 1 PBNC lost 973 MSa14.2a Snyder 14 K 2 PCA Unknown 974 MSa14.2b Snyder 14 K 2 PBNC Unknown 975 MSa14.3a Snyder 14 K 3 PCA Fusarium graminearum 976 MSa14.3b Snyder 14 K 3 PBNC Rhizopus contamination 977 MSa14.4a Snyder 14 K 4 PCA Fusarium sp. 978 MSa14.4b Snyder 14 K 4 PBNC Unknown 979 MSa14.5a Snyder 14 K 5 PCA Fusarium graminearum 980 MSa14.5b Snyder 14 K 5 PBNC Fusarium sp. 981 MSa15.1a Snyder 15 None 1 PCA Rhizopus contamination 982 MSa15.1b Snyder 15 None 1 PBNC oomycete 983 MSa15.2a Snyder 15 None 2 PCA Rhizopus contamination 984 MSa15.2b Snyder 15 None 2 PBNC lost 985 MSa15.3a Snyder 15 None 3 PCA Unknown 986 MSa15.3b Snyder 15 None 3 PBNC Unknown 987 MSa15.4a Snyder 15 None 4 PCA Fusarium graminearum 988 MSa15.4b Snyder 15 None 4 PBNC Rhizopus contamination 989 MSa15.5a Snyder 15 None 5 PCA Unknown with septa 990 MSa15.5b Snyder 15 None 5 PBNC Unknown 991 MSa16.1a Snyder 16 PK 1 PCA Unknown 992 MSa16.1b Snyder 16 PK 1 PBNC Unknown 993 MSa16.2a Snyder 16 PK 2 PCA Unknown


172

# Sample code Field Plot Trt Plant Media Preliminary ID 994 MSa16.2b Snyder 16 PK 2 PBNC Unknown B 995 MSa16.3a Snyder 16 PK 3 PCA Rhizopus contamination 996 MSa16.3b Snyder 16 PK 3 PBNC lost 997 MSa16.4a Snyder 16 PK 4 PCA Unknown A 998 MSa16.4b Snyder 16 PK 4 PBNC Unknown 999 MSa16.5a Snyder 16 PK 5 PCA Fusarium sp.

1000 MSa16.5b Snyder 16 PK 5 PBNC Unknown

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MeredithEyre.MastersThesis.OSU (1)

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