Studies in the Management of Pythium Seed and Root Rot of Soybean

Home , Pythiaceae, Pythium, Pythium aphanidermatum, Pythium irregulare, Pythium myriotylum, Pythium ultimum

Studies in the Management of Pythium Seed and Root Rot of Soybean: Efficacy of Fungicide Seed Treatments, Screening Germplasm for Resistance, and Comparison of Quantitative Disease Resistance Loci to Three Species of Pythium and Phytophthora sojae

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in

the Graduate School of The Ohio State University

Kelsey Lynn Scott

Graduate Program in Plant Pathology

The Ohio State University

2018

Thesis Committee:

Dr. Anne Dorrance, Advisor

Dr. Jason Slot

Dr. Leah McHale

Dr. Melanie Lewis Ivey

Copyrighted by

Kelsey Lynn Scott

2018

Abstract

In Ohio, soybean seedling damping-off and seed rot are problems routinely encountered soon after planting. Reduced tillage systems that lead to inoculum build-up combined with saturated soil conditions are ideal environments for seedling diseases, which cause large losses of soybean stand and thus yield. Prior Ohio field surveys identified multiple species of Pythium and Phytophthora that contribute to soybean seedling damping-off. Among the most common and aggressive species are

Phytophthora sojae, Pythium irregulare, Pythium ultimum var. ultimum, and Pythium ultimum var. sporangiiferum. Fungicide seed treatment and host resistance are two management strategies that are used to minimize yield loss caused by these pathogens.

Thus, the objectives of these studies were to: i) evaluate new active ingredients for efficacy in the lab and field, and ii) identify and characterize new sources of resistance towards the most common seedling pathogens. These are key strategies for the development of effective strategies for the management of soybean seedling disease.

During 2014-2015, at two environments, ethaboxam seed treatments combined with metalaxyl on a susceptible cultivar significantly increased yield compared to other fungicide treatments containing metalaxyl or mefenoxam alone. Soybeans treated with ethaboxam plus metalaxyl had significantly higher plant populations when compared to the nontreated control at all four 2016 field locations, while one environment had

iii significantly higher yield. In laboratory seed plate and greenhouse cup assays, ethaboxam plus metalaxyl in a commercial formulation provided equal or better protection against multiple species of Pythium when compared with other seed treatments that contained metalaxyl or mefenoxam only. These results indicate that ethaboxam with metalaxyl is effective at managing seed and rot root caused by the diverse species of Pythium and Phytophthora and provides another seed treatment fungicide available to producers which can be used in an integrated disease management program.

The parents that were used to develop six nested association mapping (NAM) populations were previously identified as segregating for resistance towards Phytophthora sojae, Pythium irregulare, Pythium ultimum var. ultimum, and Pythium ultimum var. sporangiiferum. Following inoculation in a cup assay, the resistance was quantitatively inherited in each of the NAM populations towards the four seedling pathogens. In total, 33 QDRL from the six populations surpassed the genome- wide logarithm of odds (LOD) threshold and there was a large number of suggestive

QDRL that surpassed the chromosomal LOD threshold. Of these 33 significant QDRL,

10 explained more than 15% of the phenotypic variation. Only four QDRL conferred resistance to more than one of the oomycete pathogens; one on chromosome 3, one on chromosome 17, and two located at separate locations on chromosome 13. This indicates that there may be multiple mechanisms for resistance to these root pathogens. Further analyses are needed to precisely map these QDRL so they may be selectively bred into highly resistant germplasm in order to manage seed and seedling damping-off. These

NAM populations will serve as a rich resource for breeders to incorporate resistance into adapted soybean cultivars.

I would like to dedicate this thesis to my family, my friends, my Andy, and also Diego.

Acknowledgements

I would like to thank and acknowledge Anne Dorrance for her constant support and direction through this entire process, from planting beans in the field to finishing this thesis. Thank you, Jason, Leah, and Melanie, for your knowledge, guidance, and time. A big thank-you to Valent, the Center for Applied Plant Sciences, the Soybean Center, The

Ohio Soybean Council and the United Soybean Board for making this research possible. I would also like to thank The Ohio State University Plant Pathology Department for providing such an amazing space to learn and grow. Thank you, Christine Balk, who performed the research that is the basis of my own QTL study. Thanks Clifton, who organized the prior field research and was a fantastic mentor when I was an intern here at

OARDC. Many thanks to all members of the Dorrance lab who inspired me daily with their drive and dedication. I am so grateful to those that helped with this project, especially Deloris for the lab work, Jonell for the field and greenhouse work, and the small army of interns for everything in between. Thank you Jonell, Amilcar, Linda, and

Meredith for our fun times together and your friendship- my memories of you will always hold a special place in my heart. Most of all, I thank Andy for everything.

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Vita

November 18, 1993……………………………………………………..Born- Elba, NY

2011………………………………………………………………….Elba Central School

2015……………………………………………………….B.S. Biology, SUNY Geneseo

2018…………………………..………..M.S. Plant Pathology, The Ohio State University

Publications

Scott, K., Eyre, M. and Dorrance, A. 2016. Screening soybean germplasm for resistance towards Pythium species. Phytopathology. 106:S12:90.

Scott, K., Vargas, A., Eyre, M. and Dorrance, A. 2016. Efficacy of three soybean fungicide seed treatments against Pythium species in seed plate and growth chamber assays. Phytopathology. 106:S12:68.

Fields of Study

Major Field: Plant Pathology

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Table of Contents

Abstract ...... iii Acknowledgements ...... vii Vita ...... viii List of Tables ...... xi List of Figures ...... xix Chapter 1. Literature Review ...... 1 Significance of soybean: ...... 1 Pathogens: Pythium, Phytophthora, and Phytopythium ...... 3 Pythium seed and root rot of soybean ...... 8 Disease management strategies ...... 10 Chapter 2: The efficacy of ethaboxam as a component in soybean seed treatments towards oomycetes in Ohio ...... 19 Introduction ...... 19 Materials and Methods ...... 24 Field experiments ...... 24 Pythium, Phytopythium, and Phytophthora isolates ...... 26 Seed plate assay to evaluate seed treatments ...... 27 Cup assay to evaluate seed treatments ...... 29 Results ...... 31 Field trials ...... 31 Seed plate assay ...... 34 Cup assay ...... 35 Discussion ...... 37

Chapter 3: Identifying the Quantitative Disease Resistance Loci in Nested Association Mapping populations towards Phytophthora sojae and three different species of Pythium ...... 76 Introduction ...... 76 Materials and methods ...... 80 NAM background and seed increase ...... 80 Assays and inoculum production to determine resistance phenotype ...... 80 QDRL Identification ...... 86 Results ...... 87 QDRL to Ph. sojae in four NAM RIL populations: ...... 87 QDRL to Py. irregulare in three RIL populations ...... 89 QDRL to Py. ultimum var. ultimum in three RIL populations: ...... 95 QDRL to Py. ultimum var. sporangiiferum in two RIL populations: ...... 101 Summary of QDRL for Ph. sojae ...... 105 Summary of QDRL for Py. irregulare ...... 106 Summary of QDRL for Py. ultimum var. ultimum...... 107 Summary of QDRL for Py. ultimum var. sporangiiferum ...... 108 Discussion ...... 109 References ...... 148

List of Tables

Table 2.1. Planting and harvest dates, precipitation, seeding rate, total row length counted for stand counts, and soil type for the field trials used to evaluate fungicide seed treatments in Ohio during 2014-2016. Boxes with a “-“ indicate there was no irrigation at that field site...... 43

Table 2.2. Fungicide seed treatments evaluated in each field environment. Select fungicides were also screened in the laboratory seed plate assay and the growth chamber cup assay...... 44

Table 2.3. List of cultivars used in each field site and year in order to determine the effect of cultivar choice on management of seed and root pathogens in Ohio fields...... 46

Table 2.4. List of Pythium (Py.), Phytophthora (Ph.), and Phytopythium (Pp.) isolates included in the plate assay used to evaluate the efficacy of three fungicide seed treatments and determine the seed-rotting ability of each isolate...... 47

Table 2.5. Isolates used in the growth chamber cup assay to evaluate the efficacy of fungicide seed treatments and determine the root-rotting ability of each isolate...... 49

Table 2.6. P-values for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for stand at stage V1/V2 and stand at stage V3/V4 data

(plants/Ha) for the 2014-2015 locations. Degrees of freedom (df) for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) are shown.

Inches of precipitation (natural and irrigated combined) in the 14 days after planting

(dap) are shown for each location (Loc.)...... 51

Table 2.7. Significance of cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for plant stand at stage R8 (plants/Ha) and yield data

(Bu/A) for the 2014-2015 field locations...... 52

Table 2.8. P-values for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for stand at stage V1/V2 and stand at stage V3/V4 data

(plants/Ha) for the 2016 locations. Degrees of freedom (df) for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) are shown. Inches of precipitation (natural and irrigated combined) in the 14 days after planting (dap) are shown for each location (Loc.)...... 53

Table 2.9. Significance of cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for plant stand at stage R8 (plants/Ha) and yield data

(Bu/A) for the 2016 field locations...... 54

Table 2.10. Significance of cultivar, fungicide seed treatment, location, and interactions for stand at growth stages V1/V2, V3/V4, R8, and yield (Bu/A) for the 2016 locations. 55

Table 2.11. Comparison of different combinations on soybean population and yield in

Northwest Branch 2014 (Cv. Sloan). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha), as well as yield (Kg/H and Bu/A). Treatments are compared to each other separately for each growth stage as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 56

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Table 2.12. Comparison of different fungicide combinations on soybean population and yield in Northwest Branch 2014 (Cv. Conrad). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 57

Table 2.13. Comparison of different fungicide combinations on soybean population and yield in Van Wert 2014 (Cv. Sloan). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 58

Table 2.14. Comparison of different fungicide active ingredients on soybean population and yield in Van Wert 2014 (Cv. Conrad). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 59

Table 2.15. Comparison of different fungicide active ingredients on soybean population and yield in Defiance 2015 (Cv. Conrad). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to

xiii each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 60

Table 2.16. Comparison of different fungicide active ingredients on soybean population and yield in Defiance 2015 (Cv. Sloan). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 61

Table 2.17. Comparison of different fungicide active ingredients on soybean population and yield in Defiance 2015 (Cv. Kottman). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 62

Table 2.18. Comparison of different fungicide active ingredients on soybean population and yield in Defiance 2015 (Cv. Lorain). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05)...... 63

Table 2.19. Comparison of different fungicide active ingredients on soybean population and yield in Northwest Branch 2015 (Cv. Conrad). Active ingredient rates are estimates

xiv based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

...... 64

Table 2.20. Comparison of different fungicide active ingredients on soybean population and yield in Northwest Branch 2015 (Cv. Kottman). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

...... 65

Table 2.21. Comparison of different fungicide active ingredients on soybean population and yield in Northwest Branch 2015 (Cv. Lorain). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

...... 66

Table 3.1. The six Nested Association Mapping (NAM) RIL populations evaluated for resistance towards Phytophthora sojae in a tray test and Pythium irregulare, Py. ultimum var. ultimum, and Py. ultimum var. sporangiiferum. Cells marked with an “X” indicate

xv that phenotypic screens and QTL analysis were carried out for the NAM RIL population x pathogen species combination. Data was collected by Balk (2014)...... 116

Table 3.2. Complete list of all QDRL, arranged by chromosome and position, for Ph. sojae (Phs), Py. irregulare (Pirr), Py. ultimum var. ultimum (Puu), and Py. ultimum var. sporangiiferum (Pus) identified by composite interval mapping (CIM) using F5 RILs in separate SoyNAM populations. Traits shown are total dry root weight (DRW), adjusted root weight (ARW), percent germination (%G), root rot score (RRS), and mean lesion length (MLL). Major QDRL (>15.0 PVE) are indicated in bold. Suggestive QTL are indicated in italics. QDRL that did not have a marker at the identified peak are marked with a dash. Marker range is the position in bp of the neighboring markers; some QDRL did not have both a right and a left marker...... 117

Table 3.3. Comparison of QTL for resistance towards oomycete pathogens Phytophthora sojae, Pythium irregulare, Py. ultimum var. ultimum, and Py. ultimum var. sporangiiferm in the six NAM populations generated by crossing IA3023 with 4J105-3-4, HS6-976,

LD02-9050, S06-13640, LG05-4832, and LG00-3372. Suggestive QDRL (significant at the chromosome LOD threshold) are indicated in bold. QDRL that overlap in position are noted by having a shared letter. Major QDRL (explanation of >15.0% phenotypic variance) are indicated in bold. Cells containing a “X” indicate that no major or minor

QDRL detected for the indicated NAM RIL population x pathogen combination. Cells containing “--” indicate that the NAM RIL population x pathogen combination was not screened with phenotype assays...... 131

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Table 3.4. Comparison of major and minor QDRL significant at the genome-wide threshold mapped in the NAM RIL population generated from the cross of IA3023 x

LD02-9050. Traits shown are adjusted root weight (ARW), percent germination (%G), root rot score (RRS), and mean lesion length (MLL). Major QTL (>15.0 PVE) are indicated in bold...... 133

Table 3.5. Comparison of major and minor QDRL for resistance towards Ph. sojae (Phs),

Py. ultimum var. ultimum (Puu), Py. irregulare (Pirr), and Py. ultimum var. sporangiferum (Pus) significant at the genome-wide threshold mapped in the NAM F5

RIL population derived from the cross of HS6-3976 x IA3023. Traits shown are total dry root weight (DRW), adjusted root weight (ARW), root rot score (RRS), and mean lesion length (MLL). Major QTL (>15.0 PVE) are indicated in bold...... 135

Table 3.6. Comparison of QDRL to Py. irregulare significant at the genome-wide threshold mapped in the NAM RIL population generated from the cross of IA3023 x

LG00-3372. Traits shown are total dry root weight (DRW), adjusted root weight (ARW), and percent germination (%G)...... 139

Table 3.7. Comparison of major and minor QDRL for Py. ultimum var. ultimum which were significant at the genome-wide threshold mapped in the NAM F5 RIL population derived from the cross of IA3023 x 4J105-3-4. Traits shown are total dry root weight

(DRW), percent germination (%G), and root rot score (RRS). Major QDRL (>15.0 PVE) are indicated in bold...... 141

Table 3.8. Comparison of major QDRL to Py. ultimum var. ultimum significant at the genome-wide threshold mapped in the NAM RIL population generated from the cross of

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IA3023 x S06-13640. Traits shown are percent germination (%G) and root rot score

(RRS). Major QDRL (>15.0 PVE) are indicated in bold...... 144

Table 3.9. Comparison of major and minor QDRL to Py. ultimum var. sporangiiferum significant at the genome-wide threshold mapped in the NAM RIL population generated from the cross of IA3023 x LG05-4832. Traits shown are total dry root weight (DRW), percent germination (%G), and root rot score (RRS). Major QTL (>15.0 PVE) are indicated in bold...... 147

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List of Figures

Figure 2.1. Root rot scoring system used in the growth chamber cup to evaluate the pathogenicity and aggressiveness of isolates of Pythium recovered from soybean in Ohio.

For this score 1 = healthy roots with no infection, 2 = lesions covering 1-25% of roots, 3

= 26-75% of roots with lesions, 4 = 76-100% of roots with lesions, and 5 = total colonization of the seed with no germination...... 50

Figure 2.2. Early stand at stage V1/V2 (plants/Ha) of the seed planted at Northwest

Branch in 2016, with standard deviation shown. Bars sharing a letter are not significantly different from each other (p<0.05)...... 67

Figure 2.3. Yields (Bu/A) of the seed planted at Northwest Branch in 2016, with standard deviation shown. Bars sharing a letter are not significantly different from each other (p<0.05)...... 68

Figure 2.4. The relative pathogenicity of each Pythium (Py.), Phytophthora (Ph.), and

Phytopythium (Pp.) species evaluated in the seed plate assay, with standard error shown.

Results were calculated from the seed rot scores on the inoculated plates with nontreated seed (cv. Kottman). Bars sharing a letter are not significantly different from each other

(p<0.05). The higher the relative marginal effect, the greater the degree of seed rot...... 69

Figure 2.5. The response of the 27 isolates representing 14 oomycete species (n = number of isolates per the species) of Pythium and Phytopythium to Intego Suite,

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Acceleron, and CruiserMaxx Advanced fungicide seed treatments applied at the commercial rate. All the oomycete species were analyzed together and no within species differences were found within this group; data is separated into four separate graphs for visual clarity. Bars sharing a letter are not significantly different from one another

(p<0.05). Standard error is shown. The larger the relative marginal effect, the greater the degree of seed rot...... 70

Figure 2.6. The response of the six isolates representing two Phytopthora species (n = number of isolates per the species) to Intego Suite, Acceleron, and CruiserMaxx

Advanced fungicide seed treatments applied at the commercial rate. All oomycete spp. were analyzed together and no within species differences were found within this group;

Phytophthora data is shown separately for visual clarity. Bars sharing a letter are not significantly different from one another (p<0.05). Standard error is shown ...... 71

Figure 2.7. Oomycete species that exhibited a differential response when screened with the fungicide seed treatments. Seed treatments were compared to the nontreated control seed within each species. Bars with the same letter are not significantly different

(p=0.05). The larger the relative marginal effect, the greater the degree of seed rot...... 72

Figure 2.8. Response of each of the six Py. ultimum var. ultimum isolates to the three fungicide seed treatments used in the plate assay, with standard error shown. Within each isolate, the level of seed rot on the seed treatments was compared with the seed rot on the nontreated control seeds. Bars with the same letter are not significantly different

(p=0.05). The larger the relative marginal effect, the greater the degree of seed rot...... 73

Figure 2.9. Relative pathogenicity of isolates of Pythium (Py.), Phytopythium (Pp.), and

Phytophthora (Ph.) tested in a growth chamber cup assay with surface sterilized soybean seed of the cultivar Kottman, with standard deviation shown. Results are based on the average adjusted root weights of the plants. Bars sharing a letter are not significantly different from each other. There was a significantly difference in the pathogenicity of the oomycete species (P=<0.0001). The lower the adjusted root weight, the higher the pathogenicity of the isolate...... 74

Figure 2.10. The response of the screened oomycete species to fungicide seed treatments in the cup assay, with standard deviation shown. The fungicide treated seed for each species was compared to the nontreated control within each species. Bars sharing a letter are not significantly different from one another (p=0.05). The lower the adjusted root weight, the more the roots were rotted by the oomycete pathogen...... 75

Figure 3.1. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks mean lesion length for RIL populations following inoculation with Ph. sojae in a tray assay. Shown are (A)

HS6-3976 x IA3023 and (B) IA3023 x LD02-9050 (isolate 371a92_Windfall_Ind) and populations (C) IA3023 x LG05-4832 and (D) IA3023 x LG00-3372 (isolate

(2)2_Dayton_739_LA_02). BLUE values not indicated on the graphs are (B) Conrad

(5.9), (C) Conrad (7.0), and (D) Resnik (3.6) and Conrad (7.0). BLUP values were inverted; lower values indicate more susceptible (S) lines and higher BLUP values indicate lines with greater resistance (R) to the pathogen ...... 132

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Figure 3.2. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross HS6-3976 x IA3023 following inoculation with Py. irregulare in a greenhouse cup assay. BLUE values not indicated on the graphs are (A) Clermont (-12.5) and Sloan (-14.6), (B) Clermont (-0.58), Sloan (-

0.42), and Lorain (-0.25), (C) Clermont (-0.10) and Sloan (-0.06), and (D) Clermont (-

35.0). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant (R) lines. .. 136

Figure 3.3. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross IA3023 x LD02-9050 following inoculation with Py. irregulare in a greenhouse cup assay. Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher

BLUP values indicate more resistant (R) lines...... 137

Figure 3.4. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross IA3023 × LG00-3372 following inoculation with Py. irregulare in a greenhouse cup assay. BLUE values not indicated on the graphs are (A) Lorain (-22.5), (B) Clermont (0.20), Sloan (-0.40), and Lorain (-0.8),

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and (D) Lorain (-104.1). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant

(R) lines...... 138

Figure 3.5. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross IA3023 x 4J105-3-4 following inoculation with Py. ultimum var. ultimum in a greenhouse cup assay. BLUE values not indicated on the graphs are (A) Lorain (13.75), (B) Lorain (0.30), and (C) Lorain (0.08).

Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant (R) lines...... 140

Figure 3.6. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross HS6-3976 x IA3023 following inoculation with Py. ultimum var. ultimum in a greenhouse cup assay. BLUE values not indicated on the graphs are (A) Clermont (10.4) and Sloan (6.3), (B) Clermont (0.33),

Sloan (0.17), and Lorain (0.08), and (D) Sloan (15.8) and Lorain (63.1). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant (R) lines...... 142

Figure 3.7. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent

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germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross IA3023 x S06-13640 following inoculation with Py. ultimum var. ultimum in a greenhouse cup assay. BLUE values not indicated on the graphs are (B) Clermont (0.38) and Sloan (0.38), and (D) Clermont

(82.9). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant (R) lines. .. 143

Figure 3.8. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross HS6-3976 x IA3023 following inoculation with Py. ultimum var. sporangiiferum in a greenhouse cup assay. BLUE values not indicated on the graphs are (A) Sloan (-18.8) and Clermont (15.6), (B)

Clermont (-0.17), Sloan (0.08), and Lorain (-0.5), (C) Sloan (-0.08), and (D) Sloan (-

126.3) and Lorain (-61.2). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant

(R) lines...... 145

Figure 3.9. Frequency distributions of the best linear unbiased predictors (BLUP) values for the RILs and best linear unbiased estimates (BLUE) of the checks for percent germination (A), root rot score (B), average root weight (C), and total dry root weight (D) from the NAM population derived from the cross IA3023 x LG05-4832 following inoculation with Py. ultimum var. sporangiiferum in a greenhouse cup assay. BLUE values not indicated on the graphs are (B) Lorain (-0.50), (C) Clermont (-0.15) and

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Lorain (-0.18), and (D) Sloan (-118.6). Root rot score values were inverted; for all traits, lower BLUP values indicate more susceptible (S) lines and higher BLUP values indicate more resistant (R) lines...... 146

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Chapter 1. Literature Review

Significance of soybean:

Soybean [Glycine max (L.) Merr.] is historically and currently the number one crop produced in Ohio. During 2014 and 2015, there were over 4.6 million harvested acres each year totaling over 2.5 billion dollars in value (National Agricultural Statistics

Service, USDA, 2015). The economic importance of soybean is not limited to Ohio; it is also a leading crop both in terms of acres planted and production value in many other states in the north central region. The United States (US) is the world’s top producer of soybean, followed closely by Argentina and Brazil (FAOSTAT, 2015). In 2014 the US exported 48.7 million metric tons, totaling over 30 trillion US dollar (USD) in value

(Global Agricultural Trade System Online, 2015).

The majority of soybeans harvested in Ohio are made into meal or oil for both animal feed and human consumption, respectively. Soybean has a relatively high amount of protein with low amounts of saturated fat, making it a valuable source of nutrition for both humans and livestock (Dwevedi and Kayastha 2011). Soybean is prized for its oil- producing capability; soybean-derived vegetable oils make up most of the vegetable oil consumed in the US (United States Census Bureau, 2010). Soybeans can also be processed into foods such as dairy or meat alternatives, flour, or tofu. Within the past

three decades there was an increase in demand for the “healthy-alternative” high oleic soybean oil; there is an active effort in the development of high oleic soybean and some cultivars are currently available (Pham et al., 2012; La et al., 2014). The livestock industry is highly dependent on high quality seed for soybean meal as feed for poultry, swine, and cattle due to its high protein content (Yin et al., 2007).

High quality soybeans and high yields are crucial to soybean growers’ profits as well as those of the many connected industries. The profitability of soybean in Ohio is at risk from a variety of factors, including weeds, nutrient deficiencies, insect pests, and pre- and post-harvest diseases (Beuerlein and Dorrance, 2004; Koenning and Wrather,

2010). Soybean seed and seedling diseases are caused by several different pathogens that target either the seed itself or the very young developing seedling. These diseases are regularly caused by a number of fungal and watermold species including: Fusarium,

Macrophomina, Pythium, Phytophthora, and Rhizoctonia (Ajayi-Oyetunde and Bradley,

2017; Broders et al., 2007a,b; Dorrance et al., 2003a,b; Dorrance et al., 2004; Navi and

Yang, 2016; Pearson et al., 1984; Rizvi and Yang 1996; Rojas et al., 2017a, b; Yang and

Feng, 2001).

In the past twenty years, based on annual soybean disease surveys, seed and seedling diseases have been consistently the third most important cause of yield loss behind soybean cyst nematode and sudden death syndrome in the US (Allen et al., 2017;

University of Illinois Extension and Outreach, 2016; Wrather et al., 2001; Wrather and

Koenning, 2006; Wrather et al., 2009). Based on reports from 2014 alone, the total yield loss due to disease was estimated to be nearly 500 million bushels, of which the loss of

approximately 60 million bushels were attributed to seed and seedling diseases (Allen et al., 2017). Pythium contributes to reduced yield by infecting and killing seedlings and seeds, thereby decreasing stand (Beuerlein and Dorrance, 2004). The presence of seedling disease in a field may also necessitate replanting and negatively impact the vigor of any surviving plants due to do damaged root systems (Yang, 1999).

In order to prevent yield loss, the most efficient and effective disease management strategies for seed and seedling diseases must be identified for Ohio soybean farmers to implement into their production practices.

Pathogens: Pythium, Phytophthora, and Phytopythium

The genus Pythium (Py.) has a high proportion of soilborne and generalist plant pathogens (Middleton, 1943; van der Plaats-Niterink, 1981). Pythium belongs in the class

Oomycota and family Pythiaceae. It is characterized by the production of a thick-walled oospore, an elongated antheridium, cell walls made of cellulose, and irregularly branched, coenocytic hyphae (Schroeder et al., 2013).

Most species of Pythium are able to reproduce both sexually and asexually.

During asexual reproduction, a specialized structure called a sporangium will hold a number of mobile propagules called zoospores, which are formed inside a vesicle; however some species of Pythium do not produce zoospores (Middleton, 1943). The morphological shape of the sporangium can range from spherical to filamentous and can be used to help identify some species (Middleton, 1943).

Once mature, biflagellate motile zoospores are released from the vesicle and swim freely through water under saturated soil conditions. These motile zoospores act as the primary infective agent on susceptible seeds and seedlings. Zoospores exhibit a positive chemotropism response to sugars and amino acids in the surrounding environment

(Donaldson and Deacon, 1993; Jones et al. 1991). Root tips produce exudate, which is composed of sugars and amino acids, and attracts zoospores to this vulnerable growing region. After sensing and moving towards the growing soybean root, the zoospore will encyst on the root tissue, lose mobility, form an appressorium, and produce enzymes that will facilitate the germ tube’s direct penetration through the root barrier (Raftoyannis and

Dick 2006; van West et al., 2003). Pythium species produce pectinases and some species produce cellulases to partly dissolve the cell wall, to feed on the less complex sugars present within the host’s cells (Zerillo et al., 2013). Once inside the root, Pythium colonizes the surrounding healthy tissue and ultimately the root system, or in some cases the entire plant, to acquire nutrients.

Due to the zoospores’ ability to move through water the distribution of Pythium and subsequently, disease incidence is much higher in soils with a high moisture content.

Pythium species in particular can devastate greenhouse production operations if there is not proper prevention and care (Watanabe et al., 2008). The ability of zoospores to move through water and very accurately sense the apical portions of plant roots favors Pythium infection in hydroponic growth conditions (Jenkins and Averre, 1983; Sutton et al.,

2006).

Species of Pythium can either be heterothallic (mating of two different genotypes) or homothallic (self-fertilization) (Middleton, 1943). Sexual reproduction involves the transfer of nuclei from the antheridium to the oogonium via a fertilization tube, which results in the formation of the zygote (Marchant, 1968). To protect the newly formed zygote, the oogonium develops into the oospore by thickening the outer cell wall. These oospores are especially hardy and act as the survival structure through winter and over long periods of drought, either on infected plant material or in the soil (Schroeder et al.,

2013).

Chlamydospores are vegetative resting structures produced by Pythium that are also thick-walled and allow the oomycete to withstand harsh conditions. The mycelium of Pythium does not fare well under long-term stressful conditions, but oospores and chlamydospores allow Pythium to persist even in harsh conditions or over long periods of time in the soil. When the environmental conditions are suitable for growth or a host plant is sensed nearby, the oospores/chlamydospores germinate and hyphae grow toward sources of nutrients or directly produce sporangia to begin the disease cycle anew

(Middleton, 1943; van West et al., 2003). The pathogen has a rapid response to the detection of a suitable host; the oospores of Py. aphanidermatum and the sporangia of Py. ultimum germinate between 1.5 and 3 hours after being exposed to bean or pea exudates

(Lifshitz et al., 1986; Stanghellini and Burr, 1973; Stanghellini and Hancock, 1971a,b).

Most Pythium species are generalist and necrotrophic and/or saprophytic

(Middleton, 1943; Schroeder et al., 2013). Pythium can survive as mycelium on infected tissue in or on the soil surface. Reduced tillage or an excess of plant debris on the soil

surface is a conducive environment for Pythium, resulting in increased disease severity

(Larkin et al., 1995; Pankhurst et al., 1995). Low-tillage and no-till further compounds the problem due to reduced drainage, greater soil retention of water, and the buildup of inoculum in the top layers of soil (Bescansa et al., 2006; Workneh et al., 1999). Though no-till farming has benefits such as the reduction of erosion and decreased labor costs, the potential increase in disease incidence and disease severity from debris- and water-loving pathogens must be considered. The use of cover crops (such as rye grass, clover, or oilseed radish) can decrease the severity of many root rot pathogens, including Pythium, in some host systems (Abawi and Widmer, 2000). However, planting cover crops can also increase disease incidence or severity. Recently, planting a grass cover crop leads to increased infection rates in corn seedlings during the following growing season (Bakker et al., 2016). The type of cover crop must also be taken into consideration; legume cover crops have been associated with the increase of Pythium populations in soil (Rothrock et al., 1995). Since Pythium is generalist pathogen, crop rotation is not an effective strategy in reducing inoculum (Pankhurst et al., 1995). For example, Py. irregulare commonly infects both corn and soybean, so the corn-soybean rotation commonly used in Ohio may not be an effective means of managing this pathogen (Broders et al., 2007). The impacts of the previously mentioned production practices on disease incidence are important to keep in mind, especially because no-tillage farming is firmly established in Ohio and the use of cover crops is increasing in the US (USDA, National Agricultural Statistics

Service).

Within the Pythium genus, there are many plant-pathogenic species that are economically important in agriculture. The pathogenicity of a species of Pythium depends on both the species in question as well as the environmental conditions (Dorrance et al.,

2004; Rojas et al., 2017a, b; Zhang and Yang, 2000). Soil type and nutrient availability also impact which Pythium species can survive in a location (Broders et al., 2009; Zitnik-

Anderson et al., 2017). Most Pythium species typically have a higher proliferation rate and pathogenicity at temperatures around 20ºC, with some exceptions (Gold and

Stanghellini, 1985; Littrell and McCarter, 1969; Thomson et al., 1971). For instance, Py. irregulare is more pathogenic at 20ºC than at 28ºC, whereas Py. aphanidermatum and

Py. myriotylum exhibit the reverse pattern and exhibits greater pathogenicity at higher temperatures (Ben-Yephet and Nelson, 1999; McCarter and Littrell, 1970; Littrell and

McCarter, 1969; Thomson et al., 1971). The general trend of Pythium species’ preference for wet conditions makes Pythium seed and root rot a key disease to scout for in the spring, soon after planting regardless of soil temperatures.

Oomycetes in the genus Phytophthora (Ph.) are closely related to the genus

Pythium and also contain a large number of economically important plant-parasitic pathogens (Cooke et al., 2000). Phytophthora sojae and Ph. sansomeana are commonly found on soybean in Ohio (Dorrance, 2003b; Schmitthenner, 1985; Zelaya-Molina et al.

2010). Pythium species tend to be more generalist, whereas Phytophthora sojae is limited to soybean. Phytophthora and Pythium are similar in appearance under the microscope and both can cause extensive root-rot on soybean seedlings, but there are several key differences. There are microscopic morphological differences between Pythium and

Phytophthora: Zoospores are produced directly in the sporangia in Phytophthora, and in

Pythium the zoospores form in a vesicle produced by the sporangia (de Cock and

Levesque, 2004). The sporangia of Phytophthora are typically ovoid to lemon-shaped, as opposed to the globose, filamentous, or oval-shaped sporangia of Pythium species. The sporangia of most species of Phytophthora are terminal, whereas the sporangia of

Pythium are either terminal or intercalary.

Phytopythium (Pp.) is a recently described genus that encompasses oomycete plant pathogens closely related to both Pythium and Phytophthora (de Cock et al., 2015).

Previously, Pythium was grouped into distinct clades mainly based on molecular systematic analyses and further supported by morphological traits (Levesque and de

Cock, 2004). The previously described Clade K of Pythium had morphological traits of both Pythium and Phytophthora; this group was recently described as the separate genus

Phytopythium (de Cock et al., 2015). Similar to Pythium and Phytophthora,

Phytopythium can be pathogenic on soybeans (Broders et al., 2009; Dorrance et al., unpublished data; Radmer et al., 2017; Rojas et al., 2017a,b; Rojas-Flechas, 2016).

Examples of Phytopythium species found in Ohio on soybean are Pp. vexans and Pp. helicoides (Broders et al., 2009; Dorrance et al., unpublished data).

Pythium seed and root rot of soybean

Pythium is a major cause of seedling root rot in soybean and can cause both pre- and post-emergence damping off. Pythium can cause reduction in seedling vigor and early death, which ultimately leads to a reduced stand, yield, and seed quality (Broders et

al., 2007a; Hwang et al., 2001; Yang, 1999). Seedlings in more favorable growing conditions may withstand the initial attack and continue to grow, albeit with reduced yield, growth, and performance (Dodd and White, 1999). Lesions typically form on the crown of the seedling, weakening the tissue and eventually causing the seedling to collapse near the soil line. Root rot can be easily seen; the pathogen will infect and destroy the taproot or the more delicate lateral roots and cause brown-colored lesions.

Due to their general preference for cooler temperatures and high soil moisture conditions, most Pythium species cause severe early-season stand losses. Slower growth of soybean seedlings at lower temperatures leaves them more prone to infection and allows for a longer infection period, which then increases the risk of Pythium disease and yield loss (Sanei et al., 1978). Low quality seeds or seeds with low vigor are especially at risk of seedling disease (Hamman et al., 2002; Poag at al., 2005; Rupe et al., 2011). There are more than 35 different species of Pythium associated with seed and seedling rot on soybean in Ohio and pathogenicity is highly variable both within and among the species identified in a given field (Broders et al., 2007a; Broders et al., 2009; Ellis et al., 2013;

Dorrance et al., 2004; Dorrance et al., unpublished data). Some species of Pythium are more likely to cause seed decay (pre-emergence damping off), while others are more pathogenic on seedlings (post-emergence damping off) (Rojas-Flechas, 2016). A wide variety of soil and environmental conditions such as location, precipitation, temperature, soil electrical conductivity, and clay content dictate the community composition and distribution of oomycete species in Ohio and North America (Broders et al. 2009; Rojas et al., 2017b; Zitnik-Anderson et al. 2017).

Disease management strategies

Management of Pythium seed and root rot requires the integration of cultural practices, seed treatments, and host resistance. One management strategy against

Pythium-caused diseases is crop rotation; since Pythium species have different levels of pathogenicity to different species of plants, rotating in a crop that is more resistant can potentially reduce the inoculum level in the field (McCarter and Littrell, 1969). However, due to the generalist nature of Pythium and the diversity of Pythium species within a field, crop rotation may not be a reliable method of reducing inoculum (Njoroge et al,.

2009; Pankhurst et al., 1995). There are many species of Pythium that are highly pathogenic to both corn and soybean; since one of the most common crop rotations in both Ohio and Iowa is soybean-corn, this rotation may not actually result in a decrease in

Pythium inoculum (Broders et al., 2007a; Zhang and Yang 2000).

Seed treatments are a useful tool for managing Pythium seed and root rot. Several biological seed treatments are available, but present additional challenges and considerations. Inoculants of less aggressive Pythium oligandrum or Penicillium oxalicum were effective at reducing the incidence of seed rot and pre-emergence damping off of chickpea caused by more virulent Pythium species such as Py. irregulare or Py. ultimum var. ultimum (Casas et al., 1990). Priming sweet corn seed with an isolate of

Pseudomonas fluorescens protected against Py. ultimum with effects similar to a metalaxyl treatment (Callan et al., 1990). Biocontrol seed treatments are an attractive option when chemical control is not available or not desired, but there are special

considerations: shelf life, efficacy of the biocontrol agent in different soil environments, longevity of the biocontrol agent in the field (Sharma et al., 2015; Walker et al., 2004), in addition to efficacy towards the diversity of the species found in these fields as well as the ability colonize and proliferate in the diversity of environmental conditions

(Dorrance, personal communication).

Fungicide seed treatments are another commonly deployed disease management strategy against seed and seedling diseases in Ohio. Seed treatments can provide protection to the seed prior to germination and during germination when systemic fungicides are used (Cohen et al., 1979; Munkvold and O’Mara, 2002). Fungicide seed treatments on high-quality seed remain one of the most effective ways of protecting plants from seedling diseases (Poag et al., 2005).

The effectiveness of the active ingredient of the fungicide is dependent on the targeted pathogen, as different fungicides have varying levels of efficacy against certain pathogens (Beuerlein and Dorrance, 2004; Bradley, 2008; Broders et al., 2007a,b;

Broders et al., 2009; Radmer et al., 2017; Rojas et al., 2017b; Weiland et al., 2014).

Metalaxyl is a common oomycete fungicide that has been shown to reduce seed rot caused by Pythium (Hwang et al., 2001); however the efficacy of this treatment varies among Pythium species (Brantner et al., 1998; Broders et al., 2007a,b; Dorrance et al.,

2004). There are multiple reports across the US of oomycete pathogen populations developing insensitivity to fungicides, including insensitivity to mefenoxam and metalaxyl (Broders et al. 2007a; Dorrance et al. 2004; Moorman and Kim, 2004; Taylor et al., 2002).

The interaction of fungicide and target pathogen can be complex. In addition to the variable susceptibility of fungicide resistance within a pathogen population, the effectiveness of a fungicide is also impacted by the active ingredient concentration and environmental conditions. Low concentrations of mefenoxam stimulate growth and increase the pathogenicity of several oomycete species (Garzón et al., 2011; Pradhan et al., 2017). Temperature also has an impact on the fungicide sensitivity of multiple

Pythium species; Py. torulosum has a high resistance to multiple fungicides at 13ºC, while Py. sylvaticum has higher resistance to fungicides at temperatures greater than 13ºC

(Matthiesen et al., 2016). To more effectively manage Pythium seed and root rot, as well as oomycete and fungal diseases in general, fungicide seed treatments require routine screening to evaluate efficacy and monitor for the development of insensitivity.

Mefenoxam, ethaboxam, and strobilurin fungicides have a range of effectiveness towards different species of Pythium and other root rot pathogens (Radmer et al., 2017).

Recently two new fungicide active ingredients, ethaboxam and oxathiapiprolin, have been introduced into the market. The availability of new active ingredients and the varying susceptibility of root pathogens to the different available fungicide active ingredients requires further research to determine the fungicide seed treatment best suited for any particular field environment.

In addition to cultural practices and seed treatments, another disease management strategy towards seed and seedling diseases is planting resistant cultivars. Resistance can be qualitative or quantitative. Each type of resistance has benefits over the other and both types are very useful, time-efficient, and economic means of controlling seed and root rot

of soybean. Some cultivars that express more resistance to certain Pythium spp. have been identified (Anderson et al., 2017; Balk, 2014; Balk et al., 2014; Bates et al., 2008;

Kirkpatrick et al., 2006; Rosso et al., 2008; Rupe et al. 2011).

Qualitative resistance, also called race-specific or R-gene mediated resistance, is conferred by a single resistance gene (R-gene) in the host plant and provides a strong level of protection against certain races of a particular pathogen (Chisholm et al., 2006).

When a pathogen infects a host with qualitative resistance to that particular isolate, the hypersensitive response is activated at points of infection (Morel and Dangl, 1997). This reaction results in the death of the few infected cells and prevents any further development of the disease. Identification and deployment of qualitative resistance genes in soybean is common for biotrophic or hemibiotrophic pathogens, such as the hemibiotrophic watermold Phytophthora sojae and fungus Cercospora sojina

(Schmitthenner, 1985; Mian et al., 1999). Though qualitative resistance is very effective in protecting plants against disease, the intense selection pressure placed on a the invading pathogen population can result in the pathogen population overcoming these resistance genes over time (Abney et al. 1997; Dorrance et al., 2003b,c; Dorrence et al.,

2016; Schmitthenner, 1985). R-gene mediated resistance is thought to best control biotrophic pathogens; the resulting programmed cell death from the recognition of a biotrophic pathogen would prevent the cell being used as a food source (Glazebrook,

2005). On the other hand, the programmed death of a targeted cell by a necrotrophic pathogen would simply provide a nutrient source and be ineffective in preventing pathogen growth (Glazebrook, 2005). Although Pythium species are generally thought to

be necrotrophs, one R-gene has been proposed for Pythium aphanidermatum in soybean

(Rosso et al., 2008; Rupe et al., 2011).

Quantitative resistance, also called partial resistance, is most often conferred by a multitude of genes at several loci in a host plant and is the most commonly deployed resistance against necrotrophic plant pathogens (St. Clair, 2010). This type of resistance is commonly effective against multiple races of a pathogen. Quantitative resistance results in an overall decrease, but not a total elimination, of disease symptoms in an infected plant. Regions of the genome that contribute to the overall resistance of the plant are called quantitative disease resistance loci (QDRL) (St. Clair, 2010). These individual genes may have minor separate effects, but their combined overall effects contribute to the plant having resistance towards the pathogen (Kou and Wang, 2010). Unlike qualitative resistance, partial resistance does not involve the hypersensitive response and typically allows for some symptoms to develop (Kou and Wang, 2010). This type of resistance is also thought to put less selection pressure on pathogen populations, so partial resistance is more durable long-term in preventing the development of pathogens that can overcome host crop resistance (Kou and Wang, 2010; St Clair, 2010; Michelmore, 2013).

To incorporate resistance genes into new cultivars, first the genetic source of resistance must be identified. The best sources of resistance are soybean cultivars that are already adapted to a region and have high yield. The second step is to identify the genomic regions where resistance is located. Genetic mapping has been used extensively to identify the regions in genomes that contribute to the expression of partial resistance to numerous pathogens (Collard et al., 2005; Lee et al., 2013a,b; Lindhout, 2002; Poland et

al., 2009; Young, 1996). Quantitative resistance to a few species of Pythium has been mapped in soybean. Urrea et al. (2017) found two QRL to Py. aphanidermatum on chromosome 4 and 7. Stasko et al. (2016) identified two QTL conferring resistance to Py. irregulare on chromosome 14 and chromosome 19-2. The region on chromosome 14 is especially interesting because it is near (approximately 12kb from) another previously identified Py. irregulare resistance QTL (Ellis et al., 2013). Ellis et al. (2013) found resistance to Py. irregulare QTL on chromosomes 1, 6, 8, 11, and 13 using composite interval mapping associated with partial resistance to Py. irregulare recombinant inbred line (RILs) populations (Ellis et al., 2013; Stasko et al., 2016). A comparison of regions that were associated with resistance to Py. irregulare were different from those that were associated with resistance to Fusarium graminearum, another necrotrophic pathogen and

Ph. sojae, that causes seedling disease (Stasko et al., 2016). The difference in location of resistance QTL in this one soybean RIL population indicates that there could be different mechanisms for resistance to Py. irregulare, F. graminearum and Ph. sojae in soybean.

Discovery and identification of the QTL responsible for soybean partial resistance to oomycete pathogens is necessary for the development of cultivars with durable resistance, which contribute to maintaining soybean production. There are many approaches to mapping and identification of QTL. One such technique is linkage association, which can identify QTL with relatively sparse marker coverage across the genome. However, this technique also requires a recent cross of inbred plant lines and produces genetic maps with low resolution (Beckmann and Soller, 1988; Darvasi and

Weller, 1992; Doerge, 2002). Another commonly used technique is association mapping

(aka linkage disequilibrium mapping), which does not require a recent cross because it uses the ‘historic recombination’ in the plant, and can produce maps with high resolution

(Hall et al., 2010; Zhu et al., 2008). This technique is reliant on either prior knowledge of a gene of interest, or scanning the genome with many markers (Hirschhorn and Daly,

2005). Nested association mapping (NAM) is the combination of linkage analysis and association mapping, and offers the advantages of both techniques and avoids the disadvantages (Yu et al., 2008). Once the genomic SNPs of a population are identified,

NAM can provide high resolution maps even with low marker density. The NAM technique was originally developed to be used in maize to identify the genetic sources of agronomic traits of interest, such as flowering time (Buckler et al, 2009; McMullen et al.,

2009). This technique has been implemented to identify QTL in maize associated with disease resistance, leaf architecture, and kernel composition (Cook et al., 2012; Poland et al., 2011; Tian et al., 2011). Nested association mapping populations are being developed for other plants species such as Arabidopsis thaliana, rapeseed, wheat, and soybean

(Bajgain et al., 2016; Li et al., 2014; Song et al., 2017; Stich, 2009).

A soybean NAM population was developed by crossing 40 diverse lines with the common parent IA3023 and producing 40 different Recombinant Inbred Line (RIL) populations, each containing 140 F5-dervied RILs (Song et al., 2017). Each of the 40 donor parents were selected due to their diverse ancestry, high yield, or drought tolerance. Each of the NAM parents and resulting populations were genotyped with the

SoySNP6K Illumina Infinium BeadChip Genotyping Array and had a linkage map generated based on this genotype data (Song et al., 2017; SoyNAM, soybase.org). The

soybean NAM project’s goals were to map QTL controlling desirable traits across diverse soybean germplasm, and then use this information to develop improved germplasm

(Diers, 2015). The genotype information of the NAM parents and RILs is publicly available at http://soybase.org, making the NAM population a great resource for QTL research (SoyNAM, SoyBase.org).

The species Phytophthora sojae, Py. irregulare, Py. ultimum var. ultimum, and

Py. ultimum var. sporangiiferum were chosen for this study because they have been recovered from symptomatic seedlings from many fields across Ohio and can cause severe root rot on susceptible soybean seeds and seedlings (Broders et al., 2009; Balk,

2014; Eyre et al., 2016; Dorrance et al., unpublished data). Balk (2014) identified six

NAM parents that had lower levels of root rot compared to the hub parent to these oomycete species, making the resulting NAM populations from crosses of these parents with IA3023 ideal for identification of QDRL.

In summary, the objectives of this research were to investigate two different avenues for managing Pythium seed and root rot of soybean. The first objective was to evaluate the efficacy of commercially available fungicides applied as a seed treatment in preventing seed and root rot of soybean caused by multiple oomycete species. Soybean growers need to be able to make informed decisions on how to most economically manage seedling diseases while considering yearly and local field conditions. Evaluating ethaboxam as a new active ingredient is important so soybean yields can be protected from seedling disease, while also preventing the development of further fungicide- resistant oomycete pathogen populations. This research also provides the level of

pathogenicity of different oomycete species on soybean seeds and seedling roots. Testing the efficacy of several recently available fungicide seed treatments, screening commonly used cultivars, and characterizing the level of pathogenicity of common Ohio oomycete species would be of great use to both soybean producers and the seed treatment industry, as well as public and private soybean breeders. The second objective was to map QDRL to Ph. sojae, Py. irregulare, Py. ultimum var. ultimum, and Py. ultimum var. sporangiiferum in order to identify sources of resistance. This information is important because the results from QDRL mapping can used by soybean breeders to develop lines with more resistance to infection by different oomycete species.

Chapter 2: The efficacy of ethaboxam as a component in soybean seed treatments towards oomycetes in Ohio

Introduction

Soybean (Glycine max L. Merrill) seedling diseases caused by oomycetes are a major problem in the United States (US) (Allen et al., 2017; Bradley, 2008; Broders et al.,

2007a; Koenning and Wrather, 2010; Rojas et al., 2017a,b). The oomycetes comprise a diverse number of genera, some of which cause extensive soybean pre- and post- emergence damping-off. This results in reduced yields due to delayed planting and reduced vigor of the surviving plants due to root damage. Depending on the severity of the yield loss, Pythium seed and root rot may require that the soybean fields be replanted.

In Ohio, field surveys and subsequent pathogenicity assays have identified primarily

Pythium (Py.) and Phytophthora (Ph.) species that pose a serious risk to soybean stand and yield. (Broders et al., 2007a; Broders et al., 2009; Dorrance et al., 2003b; Dorrance et al., 2004; Eyre, 2016)

Members of the oomycete genus Pythium can cause Pythium seed and root rot on soybean. Pathogenic Pythium spp. injure and kill seedlings by wounding the roots of plants and leeching nutrients, thereby reducing stand and decreasing the vigor of any surviving seedlings (Broders et al., 2007a; Hong and Moorman, 2005; Martin and Loper,

1999). Saturated soil creates favorable environmental conditions for infection, development, and reproduction of the pathogen (Kirkpatrick et al., 2006). Soybeans at the seedling stage are the most vulnerable to this disease. Crop rotation is not an effective means to manage Pythium seed and root rot, as Pythium spp. are generalists and will also infect commonly rotated crops such as corn or wheat (Broders et al., 2007b; Ingram and

Cook, 1990). The combination of poorly drained soils and reduced tillage, which promotes inoculum build-up (Workneh et al., 1998), provides the perfect conducive conditions for large scale oomycete disease epidemics.

More than one species of Pythium has been isolated from a single infected seedling, indicating a probable Pythium disease complex (Broders et al., 2007a, 2009;

Wei et al., 2010). Pythium can also form a seed and seedling complex with other soilborne pathogens such as Phytophthora sojae and Rhizoctonia spp. (Rizvi and Yang,

1996).

Integrated disease management that combines resistant cultivars and fungicide seed treatments is recommended for the management of oomycete seedling diseases in soybean (Dorrance et al., 2009; Urrea et al., 2013). Albeit, few sources of host resistance to Pythium spp. have been identified in germplasm (Bates et al., 2008; Ellis et al. 2013;

Rosso et al., 2008; Stasko et al., 2016; Urrea et al., 2017), but overall very little is known about the level of resistance towards Pythium among cultivars currently used by farmers.

Due to these current limitations on the knowledge of host resistance towards Pythium,

Pythium seed and root rot is typically managed with fungicide seed treatments (Bradley,

2008; Esker and Conley, 2012; Gaspar et al., 2017). The management of Phytophthora

sojae involves similar challenges; the quantitative resistance towards Ph. sojae is not effective until the plant is at least in the V1 growth stage (when the seedling has one set of trifoliate leaves) (Dorrance and McClure, 2001). Additionally, the population diversity of Phytophthora on soybean in the north central region of the US has a greater population of isolates that have adapted to commonly used resistance genes (Dorrance et al., 2016;

Guy et al., 1989; Stewart et al., 2016). These challenges have led to fungicides and fungicide seed treatments becoming a popular method of management for Ph. sojae. and other oomycetes (Anderson and Buzzell, 1982; Bradley, 2008; Dorrance and McClure,

2001).

Fungicide seed treatments are a valuable means of managing early season diseases caused by oomycetes. The phenylamide active ingredients, metalaxyl and its active isomer mefenoxam, have been reliable active ingredients in controlling oomycete infections by reducing the losses from damping-off, thereby increasing yield (Bradley,

2008; Bradley et al., 2001; Dorrance and McClure, 2001, Gaspar et al., 2015; Guy et al.,

1989; Lueschen et al., 1991; Radmer et al., 2017), even when reduced tillage is being practiced (Guy and Oplinger, 1989). These active ingredients work by inhibiting the ribosomal ribonucleic acid (RNA) synthesis in oomycetes (Davidse et al., 1983). In Ohio and across the US, Pythium isolates have been recovered from corn and soybean fields that are insensitive to metalaxyl and mefenoxam (Broders et al., 2007a; Dorrance et al.,

2004; Taylor et al., 2002; Radmer et al., 2017; Rojas et al., 2017a,b). Quinone outside respiration inhibitor (QoIs) fungicides have also been used to manage some diseases caused by oomycetes and fungi (Bradley, 2008; Broders et al., 2007a,b; Ellis et al., 2011;

Matthiesen et al., 2016; Radmer et al., 2017), but as with phenylamide fungicides, they are at high risk for the development of resistance in the pathogen population (Broders et al., 2007a; Gisi and Sieotzki, 2002; Radmer et al., 2017). To maintain management of seedling diseases and prevent poor stands, replanting, and potential yield loss, new chemistries need to be evaluated for efficacy against soilborne seed and seedling pathogens such as Pythium and Phytophthora.

Ethaboxam is a fungicide that is reported to be effective in managing several diseases caused by different oomycete species (Kim et al., 2004; Matthiesen et al., 2016;

Radmer et al., 2017). The mode-of-action for ethaboxam is the disruption of microtubulin assembly, as modeled in Phytophthora infestans, the causal agent of late blight of potato

(Uchida et al., 2005). Ethaboxam is considered a low to medium-risk active ingredient for the development of pathogen resistance (Kim et al., 2004). Ethaboxam is thus a good candidate for an effective fungicide active ingredient for the management of seed and root disease caused by Pythium, Phytophthora, and Phytopythium (Pp.) species.

We hypothesize that ethaboxam in commercial formulations will be effective in controlling a wide range of oomycete species when compared to other commercial formulations without this fungicide. Our objective was to evaluate and compare the efficacy of fungicides with different active ingredients in field, greenhouse, and laboratory assays to determine the ability of ethaboxam to manage oomycete seed and seedling diseases. Our study will mainly focus on Phytophthora spp., Pythium spp., and

Phytopythium spp. that have previously been found to be prevalent and pathogenic on

soybean in Ohio. Preliminary reports of these studies were published previously

(Dorrance et al., 2012; Scott et al., 2016).

Materials and Methods

Field experiments

Fields to study the effects of seed treatments on soybean plant populations and yield were selected due to a prior history of seedling disease, high incidence of damping off, or poor drainage. The dates for planting and harvest, rainfall data, soil type, total row length counted for stand counts, and seeding rate for each location are listed in Table 2.1.

In this study, an “environment” refers to a single field site within a growing season (e.g.

VW-16 is the Van Wert field in 2016). Each year, there was one field planted at the Ohio

Agricultural Research and Development Center (OARDC) Northwest Agricultural

Research Station (NWB-14, -15, -16). These fields were irrigated to ensure saturated soil conditions for optimal disease development. Other field locations in Ohio were Defiance

(DEF-15, -16), Van Wert (VW-14, -16), and Snyder Farm at OARDC, Wooster (SNY-

16); these fields did not have irrigation and were dependent on natural rainfall to produce an environment conducive for oomycete seedling disease.

Two field environments were planted in 2014 to evaluate the effects of seven fungicide seed treatments and a nontreated control (Table 2.2) with the cultivars Conrad

(Fehr et al., 1989) and Sloan (Bahrenfus and Fehr, 1980) (Table 2.3). During 2015, three seed treatments were evaluated at Northwest Branch (NWB-15) and Defiance (DEF-15)

(Table 2.2). The 2015 field sites compared the effect on four cultivars with different levels and combinations of resistance towards Pythium and Phytophthora sojae; these cultivars were Conrad, Sloan, Kottman (St Martin et al., 2001), and Lorain (OSU-

OARDC) (Table 2.3).

Four field locations were planted in 2016 to evaluate the effect of one seed treatment formulation, ethaboxam with clothianidin plus ipconazole plus metalaxyl

(Intego Solo in combination with Inovate Pro, Table 2.2), on seven cultivars (Table 2.3) with different levels and combinations of resistance for early and late plant populations and yield. The seven cultivars Clermont (OSU-OARDC), Dennison (St Martin et al.,

2008), Kottman, Streeter (OSU-OARDC), Conrad, Lorain, and Sloan were planted at the following locations: Northwest Branch (NWB-16), Defiance (DEF-16), Van Wert (VW-

16), and Snyder Farm at OARDC, Wooster (SNY-16).

Each field study was planted as randomized split plot design with the cultivar as the whole plot and the seed treatments as the sub-plots with 4-6 replicates, dependent on how much space was available in each field (Table 2.1). From each plot at each location, data for stand on a subsection of each of the experimental plots was collected three times in each growing season: i) developmental stage when there were one or two trifoliate leaves (V1-V2), ii) at the three or four trifoliate leaf stage (V3-V4), and iii) the maturity stage when most of the pods are brown or tan (R7-R8). Stand counts were converted into the number of plants per hectare (plants/Ha).

Fields at Snyder were harvested with an Almaco Specialized Plot Combine

(Almaco SPC20) (Almaco, Nevada, IA) equipped with a Harvestmaster GrainGage system. Plot data were collected and stored with an Allegro MX (Juniper Systems,

Logan, UT) with Field Research Software (FRS) (Juniper Systems, Logan, UT). Fields at

NWB were harvested with a Kincaid 8-XP (Kincaid Equipment Manufacturing, Haven,

KS) paired with a High Capacity GrainGage weigh system (Juniper Systems, Logan,

UT). The Defiance and Van Wert fields were harvested by Tech Services, Inc. (Bluffton,

IN) with a Massey Ferguson 8-XP combine paired with an Almaco LRX electronic system (ALMACO, Nevada, Iowa). The yield data for all locations was standardized to

13.5% moisture and converted to bushels/acre and kilograms/hectare. The data collected from the field experiments were individually analyzed using ANOVA with PROC GLM in SAS (SAS version 9.4; SAS Institute, Cary, NC) and mean comparisons were performed with Fisher’s protected LSD (p<0.05). The 2016 field data was analyzed across all four of the locations in order to test for significance of the location, cultivar, fungicide, and each of the corresponding interactions on stand and yield; this analysis was done using ANOVA with PROC GLM in SAS (SAS version 9.4; SAS Institute,

Cary, NC) and mean comparisons performed with Fisher’s protected LSD (p<0.05).

Pythium, Phytopythium, and Phytophthora isolates

All isolates used in these experiments were recovered from Ohio fields from infected seedlings, many from the field experiments in 2015 or through soil baiting from fields with a history of losses due to seedling diseases or isolates from the soybean pathology lab collection. Each isolate was identified to the species level based on morphological characteristics from cultures grown on potato carrot agar plates or from grass blade cultures using a monographic key for the genus Pythium (van der Plaats-

Niterink, 1981; Waterhouse, 1968), as well as sequence analysis of the entire internal transcribed spacer (ITS) region, as previously described by Broders et al. (2007a).

Isolates were grown on V8 broth at ambient temperature for 2-6 days, and the mycelia

were collected on filter paper placed in a Buchner funnel, transferred to a mortar, frozen with liquid nitrogen, and ground into a powder. DNA was extracted using the method described by Zelaya-Molina et al. (2011). Cleaned amplicons were submitted for sequencing at the Ohio Agricultural Research and Development Center (OARDC)

Molecular and Cellular Imaging Center (MCIC) in Wooster, OH. Sequence was trimmed with codon-code aligner and then blasted against the sequences in the NCBI database.

Sequence identities of 99% were considered a match for species identification. The isolates used in the seed plate assay and the cup assay are listed in Table 2.4 and Table

2.5, respectively.

Seed plate assay to evaluate seed treatments

Three commercial formulations of seed treatments were compared to nontreated seed in two laboratory based assays (Table 2.2). The seed treatments were: i) ethaboxam combined with an insecticide, clothianidin plus metalaxyl and ipconazole, ii) thiamethoxam plus mefenoxam plus fludioxonil, and iii) pyraclostrobin plus metalaxyl plus fluxapyroxad plus an insecticide imidacloprid (Table 2.2). Seed of the cultivar

Kottman, which is susceptible to both Pythium spp. and some isolates of Phytophthora spp., was treated by Valent at Leland, MS. Seed was treated at the commercial rate for each fungicide listed in Table 2.2. Nontreated seeds were surface sterilized in a 10% bleach solution for 1.5 minutes, rinsed under running deionized water for one minute, and allowed to dry thoroughly before use.

The seed plate assay was used to compare the efficacy of the fungicide seed treatment and the relative pathogenicity of the isolates as previously described by Broders et al. (2007a). Briefly, Pythium and Phytopythium isolates were grown on 2% potato carrot agar (PCA) for 3 days at 20ºC in darkness. Phytophthora isolates were grown on

PCA for 4 days at 25ºC in the dark on 2% PCA. Mycelial plugs, 5 mm in diameter, were aseptically removed from the growing margins of the culture and transferred to the center of a 100 mm 1.2% PCA plate. Pythium and Phytopythium isolates were allowed to colonize the plates for 3 days at 20ºC and Phytophthora isolates were grown for 7 days at

25°C. The seeds (n=10) were pushed into the agar, evenly spaced, approximately 1 cm from the edge of the plate. Plates were incubated in the dark for 7 days. Data were collected on the percent germination and disease incidence (DI) for each plate. Seeds were only considered germinated if the radicle was >1 cm. A score was assigned to the ten seeds on each plate based on the following ordinal scale: 0 = 100% germination with no infection; 1 = 70-99% germination with lesions on the roots; 2 = 30-69% germination with lesions on the roots; 3 = 0-29% germination with lesions on the roots.

There were three replicate plates of each seed treatment by isolate combination and the experiment was replicated twice, for a total of six replicate plates for each treatment by isolate combination. Plates within an experiment were arranged in a randomized complete block design within the incubator. Isolates recovered from the field from the years 2014-2016 were used in this experiment. Isolates that did not cause seed rot were not included in the pathogenicity or fungicide efficacy analysis. A total of 44 oomycete isolates were pathogenic on nontreated soybean seed were used in this

experiment (Table 2.4). Subsets of the isolates were evaluated against the fungicide seed treatments over time in an incomplete block design for a total of 14 subsets, with a range of four to ten isolates evaluated in each experiment. An isolate of Py. ultimum var. ultimum (Miami 137) was used in each experiment to verify the responses of the isolates were the same across all experiments. All data were combined for final analysis. The data collected from this experiment were analyzed using a nonparametric relative marginal effects analysis as described by Shah and Madden (2004). Data were analyzed with

PROC MIXED in SAS (SAS Institute, Cary, NC).

The seed plate assay data for the six Py. ultimum var. ultimum isolates (Table 2.4) were also analyzed in a separate nonparametric relative marginal effects analysis as described by Shah and Madden (2004) with PROC MIXED in SAS (SAS Institute, Cary,

NC), in order to identify variation within a species.

Cup assay to evaluate seed treatments

The same treatments were evaluated against 11 isolates of Pythium spp., 3 isolates of Phytopythium spp., and 1 isolate of Ph. sansomeana (Table 2.5) using a cup assay modified from Ellis et al. (2013). Briefly, isolates were grown on potato carrot agar

(PCA) were grown at 20°C for three to four days. Eight 10-mm plugs of each isolate were taken from the growing margin and transferred to a sterilized Spawn bag (Myco

Supply, Pittsburgh, PA) containing 950 ml play sand (Quikrete, Ravenna, Ohio), 50 ml corn meal (Quaker Oats Company, Chicago, IL), and 250 ml deionized water. The Spawn bags were closed with an electrical-impulse sealer (Harbor Freight Tools, Camarillo, CA)

to prevent contamination. These bags were grown at room temperature for ten days and shaken every other day to ensure the pathogen grew uniformly. The inoculated sand- cornmeal mixture was then mixed with fine vermiculite in a 1:4 ratio and placed into 600 ml polystyrene cups in a growth chamber at 20ºC, 16 hr light, and 60% RH. The cups were regularly watered with deionized water to provide a conducive environment for disease development. The cups were arranged in a randomized complete block design with 3 replications. Each cup had eight seeds placed directly on the inoculum, then covered with 100 ml of coarse vermiculate. The plants were grown for 14 days, then each cup had the plants removed and the roots washed. Data collected included: a visual root rot score, percent seed germination, total plant weight, and adjusted root weight. The root rot score ranged from 1-5, where 1 = no lesions on roots, 2 = 1-20% root have lesions, 3

= 20-70% roots have lesions, 4 = 71-100% root have lesions, and 5 = no germination of seed (Figure 2.1). Adjusted root weight was calculated by dividing the total root weight of the plants in a single cup by the number of plants.

Data analysis of the cup assay root rot scores used a nonparametric relative marginal effects analysis as described by Shah and Madden (2004) with PROC MIXED in SAS. All other data was analyzed with PROC GLM in SAS.

Results

Field trials

Fields were considered to have disease pressure if there were significant differences in plant population at the V1/V2 or V3/V4 stage between treated seed and nontreated control seed as well as observations of seedlings with damping-off (data not shown). Fungicide, cultivar, and fungicide by cultivar effects for each separately analyzed environment are listed in Tables 2.6-2.9. The location, cultivar, fungicide, and each corresponding interaction effects for the analysis across all 2016 locations are listed in Table 2.10.

There were significant differences for early plant population (V1/V2 stage) at the

NWB-14, DEF-15, NWB-16, VW-16 and SNY-16 environments (Tables 2.6 and 2.8), so these fields were considered to have high levels of disease pressure. The variation in disease pressure across the different environments was due in part to differences in total precipitation during the 14 days after planting (Table 2.1). Rainfall alone contributed to conducive environments for the development of seedling blight. However, the environment NWB-15 had flooding injury due to 5.7 in. of combined natural and irrigated precipitation and lost most of the plants in the study for the one cultivar Sloan.

The 2014 field studies indicated that the plant population and yield (kg/ha, Bu/A) were significantly impacted by cultivar and fungicide seed treatment for the NWB-14 environment (Tables 2.6 and 2.7). At NWB-14 for both Conrad and Sloan, the combination of metalaxyl plus ethaboxam resulted in significantly higher yield when compared to metalaxyl alone (6.2 µg active ingredient/seed) or mefenoxam alone (23.0

µg a.i./seed), as well as other seed treatment combinations based on mean separation with

Fishers Protected LSD (P<0.05) (Tables 2.11 and 2.12). For the cultivar Conrad, the higher rate of mefenoxam alone (23.0 µg a.i./seed) was not significantly different from both combinations of ethaboxam plus metalaxyl (Table 2.12). Interestingly, the difference or loss of yield due to seed and seedling rot at NWB-14 was 57.9% and 90.8% for Sloan and Conrad, respectively. For the second environment in 2014, VW-14, there was a significant effect of fungicide seed treatment for yield (P=0.047) (Table 2.7).

However, only mefenoxam alone at the highest rate (23.0 µg a.i./seed) resulted in significantly higher yield when compared with the nontreated seed for both cultivars

(Tables 2.13-2.14).

Since most seed treatments are sold and marketed as mixtures, the 2015 evaluations focused on the comparison of three formulations on four cultivars. There was a cultivar by fungicide interaction in DEF-15 for stand at stages V1/V2 and V3/V4, and for yield (Tables 2.6 and 2.7). For seed of cultivar Conrad, only the seed treated with ethaboxam plus metalaxyl (Table 2.2) had the mean early plant populations significantly differ from the nontreated seed (Table 2.15). For the cultivar Sloan, there was a similar trend for mean early plant populations, but both the ethaboxam plus metalaxyl and the pyraclostrobin plus metalaxyl seed treatment was also significantly higher than the nontreated control (Table 2.16). The cultivars with resistance to Ph. sojae, Kottman and

Lorain, had significantly higher early plant populations with ethaboxam plus metalaxyl and mefenoxam plus thiamethoxam plus fludioxonil when compared to the nontreated

(Tables 2.17 and 2.18). However, the cultivars Kottman and Lorain did not have any

significant differences between any of the seed treatments for yield in DEF-15 (Tables

2.17 and 2.18). At NWB-15 there was not a significant fungicide effect on yield (Table

2.7); the analysis broken down by each of the cultivars is recorded in Tables 2.19-2.21.

There was a significant interaction for fungicide seed treatment and cultivar by location, thus the effect of cultivar and the fungicide seed treatment was analyzed separately for all four locations in 2016 (Table 2.10). The fungicide seed treatment, metalaxyl plus ethaboxam (Table 2.2), had a significant effect on mean early plant population and yield at 3 of the 4 environments (Table 2.10). For NWB-16, VW-16, and

SNY-16, seed treated with ethaboxam plus metalaxyl fungicide seed treatment resulted in significantly greater stands when compared with the nontreated seed taken at stages

V1/V2, V3/V4, and R8 (Tables 2.8 and 2.9).

Of all the 2016 field sites, only NWB-16 had a significant fungicide effect on yield (P=0.0002) (Table 2.9). For early stand (V1/V2 stage), the seed treated with the ethaboxam plus metalaxyl fungicide resulted in significantly greater stand when compared with the nontreated control seed (P=0.0002) (Figure 2.2). Overall, the treated seed also had a significantly increased yield when compared with the nontreated control seed (Figure 2.3). The yield at the DEF-16 environment was very low; this location received heavy rainfall 3 to 4 week after planting which may have impacted the overall study.

Seed plate assay

There was a wide range of mean seed rot severity on the nontreated seed, which indicates the relative pathogenicity for each oomycete species (Figure 2.4). Pythium ultimum var. ultimum, Py. diclinum, Py. cryptoirregulare, and Pp. helicoides had the greatest degree of seed rot on the nontreated Kottman seed. Isolates of Ph. sojae and Ph. sansomeana caused a relatively low amount of seed rot, which may be an indication of the level of resistance of the cultivar Kottman to both of these species. Kottman has resistance genes Rps1k and Rps3a (Dorrance et al., 2009). Only the isolates that had a relative marginal effect score of >0.30 on the nontreated seed were examined for the effects of seed treatments.

There was a significant effect of fungicide seed treatment (P<0.0001) and oomycete species (P<0.0001) on seed rot severity, as well as a species by fungicide seed treatment interaction (P<0.0001). The seed treated with any one of the three fungicide seed treatments had significantly less (P<0.05) seed rot when compared with nontreated seed for isolates of 19 species of oomycetes (Figures 2.5-2.7).

There was a significant treatment by species interaction (P<0.0001); for the species Py. ultimum var. ultimum, Py. oopapillum, and Pp. helicoides, the seed treatments comparatively differed in their efficacy (Figure 2.7). Pp. helicoides had a significant reduction in seed rot with all three of the seed treatments, but CruiserMaxx Advanced was less effective than Acceleron or Intego Suite (Figure 2.7). Py. oopapillum also had a significant reduction in seed root for each treatment, but Intego Suite and CruiserMaxx

Advanced were less effective in preventing seed rot than Acceleron (Figure 2.7).

Similarly, Py. ultimum var. ultimum had a reduction in seed rot with each of the seed treatments, but CruiserMaxx Advanced and Acceleron were less effective than Intego

Suite (Figure. 2.7).

Within the six screened Py. ultimum var. ultimum isolates, there was a differential response to the three fungicide seed treatments (Figure 2.8). Two of the included isolates did not have a significant reduction in seed rot when treated with CruiserMaxx

Advanced. In all six of the included isolates, Intego Suite resulted in a significantly reduced seed rot when compared with the nontreated control seed.

Cup assay

There was a wide range of adjusted root weight values for each of the oomycete species for the nontreated seed, which is the primary indicator of the relative pathogenicity for each oomycete isolate (Figure 2.9). There was a significant effect of isolate on the adjusted root weight (P=0.0009), though 10 of the isolates used in the cup assay did not have a significantly different adjusted root weight compared to the uninoculated control (Figure 2.9). The isolates of Pythium ultimum var. ultimum, Py. torulosum, Py. irregulare, and Pp. helicoides had root rot on the nontreated seed; the nontreated seed either did not germinate or the seedlings damped-off (Figure 2.9). One isolate of Ph. sansomeana resulted in a significantly higher adjusted root weight when compared with the uninoculated control (Figure 2.9). Only the isolates that had a significantly lower adjusted root weight than the noninoculated control were analyzed for fungicide effects.

There was a significant effect (P<0.0001) of fungicide seed treatment and an isolate by treatment interaction (P=0.0328) on adjusted root weight. Each of the fungicides significantly increased the adjusted root weight when compared with the nontreated control for each of the four highly pathogenic species, with the exception of

CruiserMaxx Advanced to Py. irregulare (Figure 2.10). The Acceleron seed treatment provided the most protection against root rot from the species Py. irregulare and Py. ultimum var. ultimum. For each of the four pathogenic species in the cup assay, Py. irregulare, Py. ultimum var. ultimum, Py. torulosum, and Pp. helicoides, the Intego Suite seed treatment resulted in a significantly increased adjusted root weight when compared with the nontreated control seed (Figure 2.10).

Discussion

In Ohio and other soybean production areas, seedling diseases are typically managed using a combination of fungicide seed treatment and cultivars with host resistance (Bradley, 2008; Esker and Conley, 2012; Dorrance et al., 2009; Gaspar et al.,

2017; Urrea et al., 2013). In recent years, some oomycetes species that cause seed rot and damping off have been found that are insensitive to metalaxyl and strobilurins (Broders et al., 2007a; Dorrance et al., 2004; Matthiesen et al., 2016; Radmer et al., 2017; Rojas et al., 2017a,b).

This study investigated the efficacy of ethaboxam in combination with metalaxyl in different concentrations as a seed treatment in order to protect against seed and seedling rot in field and laboratory assays. Ethaboxam in a wettable powder form was initially used in Korea to manage oomycete pathogens that cause cucumber downy mildew, potato late blight, and pepper Phytophthora blight starting in the late 1990s (Kim et al., 1999; Kim et al., 2003). In recent years, ethaboxam has been labeled for soybean seed treatment in the US.

Pathogen population and diversity are highly influenced by environmental conditions such as the level of soil saturation, soil type, nutrient availability, amount of crop debris, and degree of tillage (Bescansa et al., 2006; Broder et al., 2009; Kirkpatrick et al., 2006; Workneh et al., 1999; Zitnik-Anderson et al., 2017). This environmental variation plays a part in the differences observed in the fungicide effects across the field location. In particular, the amount of rainfall in the 14 days after planting has a significant impact on the amount of oomycete disease pressure, as noted in prior field

seed treatment studies (Bradley, 2008; Dorrance et al., 2009). Four out of the five field sites that received greater than 1.0 in. of water 14 dap (days after planting) had a significant fungicide effect on yield. Since the efficacy of fungicide seed treatments can only be determined with adequate disease pressure, efforts should be taken to properly irrigate research field sites to encourage pathogen development. However, overwatering or flooding may mask any effects by a fungicide or otherwise impact the study (Henshaw et al., 2007a,b; Kirkpatrick et al., 2006; VanToai et al., 1994). This can be seen in the field site NWB-15 with 5.7 in. of water 14 dap and in VW-16 and DEF-16 with nearly

19.0 in. water total in the growing season; despite these fields being having a history of

Pythium and Phytophthora infection, there were no significant fungicide effects on yield.

The field sites in 2014 compared ethaboxam and metalaxyl combinations to metalaxyl alone. The metalaxyl treatment (6.0 µg a.i./seed) did not protect against seed and root disease for both cultivars Conrad and Sloan. This finding is consistent with previous reports of low rates of metalaxyl having limited efficacy towards Ph. sojae

(Dorrance and McClure, 2001). Additionally, this supports previous research that there is the emergence of populations of Pythium with insensitivity to this fungicide (Broders et al., 2007a; Dorrance et al., 2004; Matthiesen et al., 2016; Radmer et al., 2017; Rojas et al., 2017a,b).

At the DEF-15 field site, there was a significant fungicide by cultivar interaction;

Conrad and Sloan exhibited yield differences among fungicide treatments whereas cultivars Lorain and Kottman did not. This difference in fungicide effect may be due to the host resistance of Lorain and Kottman performing better against the particular

pathogen population in that environment. Kottman has resistance genes Rps1k and Rps3a

(Dorrance et al., 2009) and Lorain has resistance gene Rps1c (OSU-OARDC), and both of these cultivars have moderately high levels of partial resistance to Pythium ultimum var. ultimum, Py. ultimum var. sporangiiferum, and Py. irregulare (Balk, 2014; Dorrance lab, unpublished data). Comparatively, Conrad and Sloan have relatively low amounts of partial resistance to Pythium spp. and no Rps genes for Ph. sojae.

The 2016 locations also evaluated cultivar by fungicide seed treatment interactions; the plant populations were higher for seed treatment at three of the four locations and there was a fungicide effect on yield at only one environment (NWB-16).

Soybean cultivars with different levels of resistance to Ph. sojae and Pythium spp. did not respond the same to the seed treatment at each location (Table 2.9). In a highly favorable environment for seedling disease, the more susceptible cultivars performed better with the ethaboxam seed treatment when compared to the nontreated seed and there were no significant differences between treatments for cultivars with more resistance.

Overall, the cultivars treated with Inovate Pro plus Intego Solo had significantly greater yield (P=0.0002) and early stand at V1/V2 (P<0.0001) when compared with the nontreated seed. There was also a significant cultivar effect for both yield (P<0.0001) and early stand (PP=0.0206). The NWB-16 field environment had the more susceptible cultivars perform better with the ethaboxam seed treatment when compared to nontreated seed; there was no significant differences between treatments for the more resistant cultivars (Figures 2.2 and 2.3). Since the effects of fungicides were more easily seen on the cultivars with greater susceptibility to oomycete pathogens, future field studies should

include cultivars with a range of level of host resistance, taking care to include highly susceptible cultivars. This study is in agreement with other studies that suggest that cultivar selection should be used in combination with fungicide use to protect against fungi and oomycete pathogen diseases (Dorrance et al., 2009; Kandel et al., 2016;

Matthiesen et al., 2016; Marburger et al., 2014).

Overall, our findings from the field assays support prior studies that found that fungicide seed treatment have stand- and yield-protecting benefits against a variety of fungal and oomycete pathogens (Bradley, 2008; Esker and Conley, 2012; Gaspar et al.,

2014; Gaspar et al., 2017; Guy and Oplinger, 1989; Guy et al., 1998; Poag et al., 2005;

Urrea et al., 2013).

A seed plate assay is used to determine the effect of fungicide treated seed on a single isolate, compared to nontreated seed with the same isolate. This method allows commercial fungicide combinations to be screened with any pathogenic isolate. The seed plate assay was used previously to evaluate the relative pathogenicity of each oomycete species on nontreated seed (Broders et al., 2007a), as well as to determine the effect of temperature on Pythium spp. aggressiveness (Matthiesen et al., 2016). Similar findings were reported in this study as there was a wide range of pathogenicity among the

Phytophthora, Pythium, and Phytopythium isolates recovered from these same fields, as well as a varied response to the seed treatments within the screened Py. ultimum var. ultimum isolates. All pathogenic isolates had a reduction in seed rotting ability for each of the fungicide seed treatments compared to the nontreated seed. For the three Pythium species that had a differential response to the different fungicides, the treatment

containing ethaboxam (Intego Suite) provided equal or greater protection against seed rot when compared with the Acceleron package or CruiserMaxx Advanced.

The majority of isolates screened in the cup assay were also screened in the plate assay, though these assays differed in their assessment of isolate pathogenicity. All of the included isolated in the seed plate assay had a significantly greater degree of seed root than the uninoculated control, indicating that each of the isolates were pathogenic on the soybeans. However, the cup assay only identified some isolates of Py. ultimum var. ultimum, Py. irregulare, Py. torulosum, and Pp. helicoides that resulted in significantly decreased adjusted root weight when compared with the uninoculated control. Both assays identified P. ultimum var. ultimum and Pp. helicoides as highly pathogenic species. Py. torulosum had opposite results across the laboratory assays; the cup and plate assay identified it as strong and weakly pathogenic, respectively. The cup assay may be more comparable to field studies; the plants are allowed to mature further and the greenhouse mimics field conditions more closely than a Petri dish. However, the seed plate assay still provides invaluable information on how a single isolate reacts to a fungicide seed treatment.

Research from both the field studies and the laboratory assays suggest that ethaboxam can be used in combination to manage a variety of oomycete species

(Phytophthora, Pythium, and Phytopythium) commonly isolated from Ohio fields that are able to cause seedling damping off on soybean. Results indicate that the active ingredient ethaboxam has equal or greater effects in controlling these species when compared to other commonly used active ingredients, such as mefenoxam, metalaxyl, and strobilurins

used in combination in commercially available fungicide seed treatments. Due to the low risk of pathogens developing resistance towards ethaboxam and efficacy in controlling multiple oomycete species, this active ingredient could be a valuable disease management strategy for soybean seedling disease in Ohio.

Overall, the results from these studies indicate that fungicide seed treatments containing ethaboxam have comparable efficacy to other commercially available fungicide seed treatments tested in this study. Cultivar selection was also shown to influence yield, with more susceptible cultivars benefiting more (more yield protection) from fungicide seed treatments under heavy disease pressure than more resistant cultivars. These field experiments highlight how both cultivar selection and fungicide treatment must be taken into consideration when managing seed and root disease. Ideally, both a resistant cultivar and an effective fungicide seed treatment should be used in order to protect yield from soybean seed and root rot pathogens.

Table 2.1. Planting and harvest dates, precipitation, seeding rate, total row length counted for stand counts, and soil type for the field

trials used to evaluate fungicide seed treatments in Ohio during 2014-2016. Boxes with a “-“ indicate there was no irrigation at that

field site.

Total Seeding Total row No. Planting Harvest Irrigation Rainfall Precip.c rate length Env.a reps date date (in.) 14-dapb (in.) (in.) (seeds/ft) counted (ft.) Soil Type VW-14 5 26-May 13-Oct - 1.90 17.2 8.0 30.0 Latty Silty clay NWB-14 5 3-Jun 24-Oct 2.92 4.10 12.5 4.1 12.0 Hoytville clay NWB-15 4 22-Jun 20-Oct 1.60 5.71 18.8 6.0 12.0 Hoytville clay DEF-15 4 26-May 27-Sep - 3.23 19.4 8.0 30.0 Silty clay

NWB-16 5 1-Jun 17-18-Oct 2.8 3.25 13.49 5.0 12.0 Hoytville Clay Wooster Riddles SNY-16 6 20-May 6-Oct - 0.67 13.95 4.1 12.0 Silt Loam VW-16 6 25-May 8-Oct - 0.97 18.86 4.1 12.0 Latty Silty Clay DEF-16 6 26-May 15-Oct - 0.97 18.86 4.1 12.0 Paulding Clay a Indicates the field location and year (environment). b Rainfall and irrigation combined in the 14 days after planting (dap). c Total precipitation indicates the total rainfall and irrigation combined from planting date to harvest date.

Table 2.2. Fungicide seed treatments evaluated in each field environment. Select fungicides were also screened in the laboratory seed plate assay and the growth chamber cup assay.

Active ingredient and rate Environment (µg a.i./seed) Trade name NWB-14 Inovate Pro (2.47 lb Clothianidin (75.1) + ipconazole VW-14 a.i./gal) + Sebring (2.65 lb (3.8) + metalaxyl (6.2) a.i./gal) NWB-14 VW-14 Clothianidin (75.1) + ipconazole Inovate Pro (2.47 lb NWB-16 (3.8) + metalaxyl (3.2) + a.i./gal) + Intego Solo (3.2 VW-16 ethaboxam (12.0) lb a.i./gal) SNY-16 DEF-16 Inovate Pro (2.47 lb Clothianidin (75.1) + ipconazole NWB-14 a.i./gal) + Sebring (2.65 lb (3.8) + metalaxyl (6.2) + VW-14 a.i./gal) + Intego Solo (3.2 ethaboxam (12.0) lb a.i./gal) Thiamethoxam (77.8) + NWB-14 CruiserMaxx Plus (2.47 lb mefenoxam (11.7) + fludioxonil VW-14 a.i./gal) (3.8) Thiamethoxam (77.8) + CruiserMaxx Plus (2.47 lb NWB-14 mefenoxam (23.0) + fludioxonil a.i./gal) + Apron XL (3.0 VW-14 (3.8) lb a.i./gal) Evergol Energy (1.47 lb Metalaxyl (24.9) Prothioconazole NWB-14 a.i./gal) + Allegiance-FL (8.1) + Penflufen (4.0) + VW-14 (2.65lb a.i./gal) + Gaucho imidacloprid (101.0) (5 lb a.i./gal) Acceleron package: NWB-14 Acceleron DX 109 (0.8 fl VW-14 Pyraclostrobin (16.9) + metalaxyl oz/ cwt) + Acceleron DX NWB-15 (13.2) + fluxapyroxad (8.3) + 309 (0.4 fl oz/cwt) + DEF-15 imidacloprid (127.0) Acceleron DX 612 (0.240 Seed plate assay fl oz/ cwt) + Acceleron IX Cup assay 409 (2.00 fl oz/ cwt) NWB-15 Clothianidin (81.0) + ipconazole DEF-15 Intego Suite (3.37 fl oz/ (4.0) + metalaxyl (3.2) + Seed plate assay cwt) ethaboxam (12.0) Cup assay Continued

Table 2.2 continued.

Active ingredient and rate Environment (µg a.i./seed) Trade name NWB-15 Thiamethoxam (77.9) + DEF-15 CruiserMaxx Advanced mefenoxam (11.7) + fludioxonil Seed plate assay (3.2 fl oz/ cwt) (3.8) Cup assay NWB-16 Clothianidin (75.1) + ipconazole Inovate Pro (2.47 lb VW-16 (3.8) + metalaxyl (3.2) + a.i./gal) + Intego Solo (3.2 SNY-16 ethaboxam (12.0) lb a.i./gal) DEF-16

Table 2.3. List of cultivars used in each field site and year in order to determine the effect of cultivar choice on management of seed and root pathogens in Ohio fields.

Environment Cultivars planted NWB-14 Conrad, Sloan VW-14 NWB-15 Conrad, Sloan, Kottman, Lorain DEF-15 NWB-16 DEF-16 Conrad, Sloan, Kottman, Lorain, Clermont, VW-16 Dennison, Streeter SNY-16

Oomycete Spp. Isolate Code Year Location Py. attrantheridium MDa4.2b 2015 Defiance MVa12.5b 2015 Van Wert 17SNY111.3- 2017 Snyder Py. cryptoirregulare Erie 2-6-4 2006/2007 Erie Co. Craw 1-1-10 2006/2007 Crawford Co. Py. diclinum MVa3.5b 2015 Van Wert Py. dissotocum MDa2.1a 2015 Defiance D411.1 2016 Defiance N405.1 2016 NWB Py. heterothallicum MDa6.5b 2015 Defiance Py. inflatum MDa11.2a 2015 Defiance MVa3.3a 2015 Van Wert MVa5.3a 2015 Van Wert Py. irregulare Mont 1-4-7 2006/2007 Montgomery Co. Sand 1-6-22 2006/2007 Sandusky Co. Wood 1-6-9 2006/2007 Wood Co. Py. lutarium MVa20.4b 2015 Van Wert MVa23.5b 2015 Van Wert Py. nodosum MWa9.1a1 2015 Waterman Py. oopapillum MDa2.4b 2015 Defiance MVa1.4a 2015 Van Wert N110.1 2016 NWB Py. pleroticum MVa13.3b 2015 Van Wert Py. torulosum MDa4.4b 2015 Defiance Co. MVa7.2a 2015 Van Wert Py. ultimum var. ultimum MDa5.2b 2015 Defiance Co. Miami137 2006/2007 Miami Co. MVa1.2a 2015 Van Wert MVa21.4b 2015 Van Wert N508.1 2016 NWB N201.2(2) 2016 NWB Continued

Table 2.4. continued.

Oomycete Spp. Isolate Code Year Location Ph. sansomeana MVa2.5b 2015 Van Wert MVa8.4b 2015 Van Wert 17SNY208.5- 2017 Snyder 17CLN111.2 2017 Clinton Co. Ph. sojae OH.12108.06.03 2012 Van Wert R25_1-97-01 Standard isolate Pp. helicoides MVa14.4b 2015 Van Wert D502.1 2016 Defiance Pp. litorale D206.3 2016 Defiance Pp. mercurial N109.1(2) 2016 NWB Pp. vexans MWa12.1a 2015 Wood Co. 17SNY101.1+ 2017 Snyder 17CLN111.1 2017 Clinton Co.

Table 2.5. Isolates used in the growth chamber cup assay to evaluate the efficacy of fungicide seed treatments and determine the root-rotting ability of each isolate.

Isolate Oomycete spp. code Year Location Py. heterothallicum MDa6.5b 2015 Defiance Py. irregulare Br_235 2006/2007 Brown Co. Gr_151 2006/2007 Greene Co. Py. lutarium MVa23.5b 2015 Van Wert Py. nodosum MWa9.1a1 2015 Wood Co. Py. oopapillum MVa1.4a 2015 Van Wert Py. torulosum MDa4.4b 2015 Defiance MVa12.3a 2015 Van Wert MVa5.4a 2015 Van Wert Py. ultimum var. ultimum MVa1.2a 2015 Van Wert MVa21.4b 2015 Van Wert Ph. sansomeana MVa2.5b 2015 Van Wert Pp. helicoides MVa14.4b 2015 Van Wert MVa5.1a 2015 Van Wert Pp. vexans MWa12.1a 2015 Wood Co.

Figure 2.1. Root rot scoring system used in the growth chamber cup to evaluate the pathogenicity and aggressiveness of isolates of

Pythium recovered from soybean in Ohio. For this score 1 = healthy roots with no infection, 2 = lesions covering 1-25% of roots, 3 =

26-75% of roots with lesions, 4 = 76-100% of roots with lesions, and 5 = total colonization of the seed with no germination.

Table 2.6. P-values for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for stand at stage

V1/V2 and stand at stage V3/V4 data (plants/Ha) for the 2014-2015 locations. Degrees of freedom (df) for cultivar (cult.), fungicide

seed treatment (fung.), and cultivar by fungicide interactions (CxF) are shown. Inches of precipitation (natural and irrigated combined)

in the 14 days after planting (dap) are shown for each location (Loc.).

Environment df V1/V2 V3/V4 rain 14 Loc. dap Cult Fung CxF Mean Cult. Fung. CxF Mean Cult. Fung. CxF

51 VW-14 1.9'' 1 7 7 268,471.8 0.5789 0.9486 0.5650 - - - - a a a a

NWB-14 4.1'' 1 7 7 181,995.8 0.0075 <0.0001 0.3721 182,301.2 0.0059 <0.0001 0.3008 a a a a a a DEF-15 3.2'' 3 3 9 225,238.0 <0.0001 <0.0001 0.0169 224,991.1 <0.0001 <0.0001 0.0120 b a NWB-15 5.7'' 2 3 6 262,004.0 0.6600 0.8213 0.0598 257,645.0 0.6540 0.7308 0.0462 - indicates no data collected. a indicates significance at 95% confidence using ANOVA. b indicates significance at 90% confidence using ANOVA.

Table 2.7. Significance of cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for plant stand

at stage R8 (plants/Ha) and yield data (Bu/A) for the 2014-2015 field locations.

Environment R8 Bu/A rain Location 14 dap Mean Cult. Fung. CxF Mean Cult. Fung. CxF a a VW-14 1.9'' 282,277.7 0.0438 0.8109 0.9572 46.5 0.1873 0.0470 0.9877 a a a a NWB-14 4.1'' 178,255.6 0.0129 <0.0001 0.3800 23.2 0.0233 <0.0001 0.3592 a a a a DEF-15 3.2'' 242,769.5 0.5245 0.0141 0.1985 20.6 <0.0001 <0.0001 0.0179 b NWB-15 5.7'' 243,635.0 0.5196 0.5979 0.0600 31.9 0.3042 0.3686 0.2832 a indicates significance at 95% confidence using ANOVA. 52 b indicates significance at 90% confidence using ANOVA.

Table 2.8. P-values for cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for stand at stage

V1/V2 and stand at stage V3/V4 data (plants/Ha) for the 2016 locations. Degrees of freedom (df) for cultivar (cult.), fungicide seed

treatment (fung.), and cultivar by fungicide interactions (CxF) are shown. Inches of precipitation (natural and irrigated combined) in

the 14 days after planting (dap) are shown for each location (Loc.).

Environment df V1/V2 V3/V4 rain 14 Location dap Cult Fung CxF Mean Cult. Fung. CxF Mean Cult. Fung. CxF a a b a a b NWB-16 3.23'' 6 1 6 359,316.8 0.0206 <0.0001 0.0822 392,452.1 0.0015 0.0001 0.0920 53 DEF-16 0.97'' 6 1 6 215,472.8 0.4308 0.1655 0.4591 239,990.1 0.0136a <0.0001a 0.1540

a VW-16 0.97'' 6 1 6 303,945.7 0.1745 0.0064 0.3991 302,408.0 0.1956 0.2909 0.6601 a a SNY-16 0.67'' 6 1 6 166,068.1 0.6334 0.0138 0.9092 165,384.7 0.5337 0.0428 0.8956 a indicates significance at 95% confidence using ANOVA. b indicates significance at 90% confidence using ANOVA.

Table 2.9. Significance of cultivar (cult.), fungicide seed treatment (fung.), and cultivar by fungicide interactions (CxF) for plant stand

at stage R8 (plants/Ha) and yield data (Bu/A) for the 2016 field locations.

Environment R8 Bu/A rain 14 Location dap Mean Cult. Fung. CxF Mean Cult. Fung. CxF a a b a a NWB-16 3.23'' 377,678.4 0.0012 0.0003 0.0975 47.3 <0.0001 0.0002 0.1315 a a a DEF-16 0.97'' 222,881.6 0.0002 0.0181 0.3708 21.0 <0.0001 0.2239 0.3601 a VW-16 0.97'' 241,755.6 0.4258 0.3718 0.8218 37.8 <0.0001 0.4787 0.1421 b b b SNY-16 0.67'' 162,565.7 0.4993 0.0813 0.9643 37.6 0.0790 0.0742 0.7110 a indicates significance at 95% confidence using ANOVA. b

54 indicates significance at 90% confidence using ANOVA.

Table 2.10. Significance of cultivar, fungicide seed treatment, location, and interactions for stand at growth stages V1/V2, V3/V4, R8, and yield (Bu/A) for the 2016 locations.

Stand at Stand at V1/V2 V3/V4 Stand at R8 Yield Cultivar 0.0771b 0.0002a <0.0001a <0.0001a Location <0.0001a <0.0001a <0.0001a <0.0001a Fungicide <0.0001a <0.0001a <0.0001a 0.1757 Fungicide x Location 0.0639b 0.0037a 0.0362a 0.0070a Cultivar x Location 0.0263a <.0001a 0.0003a <0.0001a Cultivar x Fungicide 0.2726 0.1125 0.5153 0.8226 a indicates significance at 95% confidence using ANOVA. b indicates significance at 90% confidence using ANOVA.

Table 2.11. Comparison of different combinations on soybean population and yield in Northwest Branch 2014 (Cv. Sloan). Active

ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each

growth stage (plants/Ha), as well as yield (Kg/H and Bu/A). Treatments are compared to each other separately for each growth stage

as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

Plant population / Ha Yield Rate Treatment (µg a.i./ seed) V1/V2 V3/4 R7 Kg/H Bu/A Metalaxyl1 6.2 71,758 c 76,063 c 78,934 b 1,073.7 cd 16.0 cd 56 Metalaxyl + ethaboxam1 3.0 + 12.0 299,948 a 302,818 a 285,237 a 2,275.8 a 33.8 a

Metalaxyl + ethaboxam1 6.0 + 12.0 289,902 a 294,207 a 281,650 a 2,200.2 a 32.7 a Mefenoxam2 11.7 68,888 c 71,758 c 66,376 b 775.7 d 11.5 d Mefenoxam2 23.0 134,905 bc 137,775 bc 71,758 b 1,113.6 cd 16.6 cd Metalaxyl + Prothioconazole 24.9 + 8.1 + 126,294 bc 130,599 bc 123,782 b 1,143.5 c 17.0 c + Penflufen + imidacloprid 4.0 + 101.0 Pyraclostrobin + metalaxyl + 16.9 + 13.2 + 152,127 b 150,691 b 141,722 b 1,631.8 b 24.3 b fluxapyroxad + imidacloprid 8.3 + 127.0 Nontreated check 0 87,545 bc 83,239 c 68,170 b 872.4 cd 13.0 cd Overall mean - 153,920.9 155,893.9 139,703.6 1,385.8 20.6 LSD (P < 0.05) - 66,329 66,990 77,329 357.9 5.3 1Seed also treated with clothianidin (75.1 µg/seed) and ipconazole (3.8 µg/seed) 2Seed also treated with thiamethoxam (77.8 µg/seed) and fludioxonil (3.8 µg/seed)

Table 2.12. Comparison of different fungicide combinations on soybean population and yield in Northwest Branch 2014 (Cv.

Conrad). Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant

population at each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth

stages as well as yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

Plant population / Ha Yield Rate Treatment (µg a.i./ seed) V1/V2 V3/4 R7 Kg/H Bu/A Metalaxyl1 6.2 169,349 cd 172,219 bc 166,837 bc 1,186.4 d 17.6 d Metalaxyl + ethaboxam1 3.0 + 12.0 322,910 a 325,781 a 317,528 a 2,409.7 a 35.8 a

57 Metalaxyl + ethaboxam1 6.0 + 12.0 295,642 ab 302,818 a 308,559 a 2,461.7 a 36.6 a Mefenoxam2 11.7 166,478 cd 159,302 c 179,395 bc 1,331.6 cd 19.8 cd Mefenoxam2 23.0 254,023 abc 258,328 ab 260,122 ab 1,994.7 ab 29.7 ab Metalaxyl + Prothioconazole 24.9 + 8.1 + 179,395 cd 182,265 bc 175,807 bc 1,609.7 bcd 23.9 bcd + Penflufen + imidacloprid 4.0 + 101.0 Pyraclostrobin + metalaxyl + 16.9 + 13.2 + 196,616 bcd 166,837 bc 200,922 abc 1,878.9 abc 27.9 abc fluxapyroxad + imidacloprid 8.3 + 127.0 Nontreated check 0 96,156 d 99,026 c 98,667 c 1,033.8 d 15.4 d Overall mean - 210,071.1 209,385.7 213,479.6 1,738.3 25.8 LSD (P < 0.05) - 100,863 94,507 124,455 632.8 9.4 1Seed also treated with clothianidin (75.1 µg/seed) and ipconazole (3.8 µg/seed) 2Seed also treated with thiamethoxam (77.8 µg/seed) and fludioxonil (3.8 µg/seed)

Table 2.13. Comparison of different fungicide combinations on soybean population and yield in Van Wert 2014 (Cv. Sloan). Active

ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at each

growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well as

yield data. Treatments sharing a letter indicate that they are not significantly different from each other (p<0.05).

Plant Population / Ha Yield Rate Treatment (µg a.i./ seed) V1/V2 R7 Kg/H Bu/A Metalaxyl1 6.0 272,961 a 261,468 a 2,937.2 ab 43.7 ab Metalaxyl + ethaboxam1 3.0 + 12.0 265,203 a 261,756 a 3,009.2 ab 44.8 ab

58 Metalaxyl + ethaboxam1 6.0 + 12.0 277,846 a 267,789 a 2,949.4 ab 43.8 ab Mefenoxam2 11.7 265,491 a 261,756 a 2,919.3 ab 43.4 ab Mefenoxam2 23.0 258,308 a 265,203 a 3,247.6 a 48.3 a Metalaxyl + Prothioconazole + 24.9 + 8.1 274,973 a 267,502 a 3,152.1 ab 46.9 ab Penflufen + imidacloprid +4.0 + 101.0 Pyraclostrobin + metalaxyl + 16.9 + 13.2 + 278,708 a 276,984 a 2,787.5 ab 41.4 ab fluxapyroxad + imidacloprid 8.3 + 127.0 Nontreated check 0 271,812 a 262,546 a 2,712.7 b 40.3 b Overall mean - 270,662.8 265,625.5 2,968.7 44.1 LSD (P < 0.05) - NS NS 524.19 7.8 1Seed also treated with clothianidin (75.1 µg/seed) and ipconazole (3.8 µg/seed) 2Seed also treated with thiamethoxam (77.8 µg/seed) and fludioxonil (3.8 µg/seed)

Table 2.14. Comparison of different fungicide active ingredients on soybean population and yield in Van Wert 2014 (Cv. Conrad).

Active ingredient rates are estimates based on label information. Overall mean across all treatments are shown for plant population at

each growth stage (plants/Ha) and yield (Kg/H and Bu/A). Treatments are compared to each other separately for growth stages as well