Annual decreases in soybean (Glycine max L. Merrill) yield caused by diseases were estimated by surveying university-affiliated plant pathologists in 28 soybean-producing states in the United States and in Ontario, Canada, from 2010 through 2014. Estimated yield losses from each disease varied greatly by state or province and year. Over the duration of this survey, soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) was estimated to have caused more than twice as much yield loss than any other disease. Seedling diseases (caused by various pathogens), charcoal rot (caused by Macrophomina phaseolina (Tassi) Goid), and sudden death syndrome (SDS) (caused by Fusarium virguliforme O’Donnell & T. Aoki) caused the next greatest estimated yield losses, in descending order. The estimated mean economic loss due to all soybean diseases, averaged across U.S. states and Ontario from 2010 to 2014, was $60.66 USD per acre. Results from this survey will provide scientists, breeders, governments, and educators with soybean yield-loss estimates to help inform and prioritize research, policy, and educational efforts in soybean pathology and disease management.

No abstract

Annual decreases in corn yield caused by diseases were estimated by surveying members of the Corn Disease Working Group in 22 corn-producing states in the United States and in Ontario, Canada, from 2012 through 2015. Estimated loss from each disease varied greatly by state and year. In general, foliar diseases such as northern corn leaf blight, gray leaf spot, and Goss's wilt commonly caused the largest estimated yield loss in the northern United States and Ontario during non-drought years. Fusarium stalk rot and plant-parasitic nematodes caused the most estimated loss in the southern-most United States. The estimated mean economic loss due to yield loss by corn diseases in the United States and Ontario from 2012 to 2015 was $76.51 USD per acre. The cost of disease-mitigating strategies is another potential source of profit loss. Results from this survey will provide scientists, breeders, government, and educators with data to help inform and prioritize research, policy, and educational efforts in corn pathology and disease management. Accepted for publication 26 August 2016.

Willyerd, K. T., Li, C., Madden, L. V., Bradley, C. A., Bergstrom, G. C., Sweets, L. E., McMullen, M., Ransom, J. K., Grybauskas, A., Osborne, L., Wegulo, S. N., Hershman, D. E., Wise, K., Bockus, W. W., Groth, D., Dill-Macky, R., Milus, E., Esker, P. D., Waxman, K. D., Adee, E. A., Ebelhar, S. E., Young, B. G., and Paul, P. A. 2012 [MR_UT]) were used in multivariate meta-analyses, and mean log response ratios across trials were estimated and transformed to estimate mean percent control ( C ) due to the management combinations relative to S_UT. All combinations led to a significant reduction in index and DON (P < 0.001). MR_TR was the most effective combination, with a C of 76% for index and 71% for DON, followed by MS_TR (71 and 58%, respectively), MR_UT (54 and 51%, respectively), S_TR (53 and 39%, respectively), and MS_UT (43 and 30%, respectively). Calculations based on the principle of treatment independence showed that the combination of fungicide application and resistance was additive in terms of percent control for index and DON. Management combinations were ranked based on percent control relative to S_UT within each trial, and nonparametric analyses were performed to determine management combination stability across environments (trials) using the Kendall coefficient of concordance (W). There was a significant concordance of management combinations for both index and DON (P < 0.001), indicating a nonrandom ranking across environments and relatively low variability in the within-environment ranking of management combinations. MR_TR had the highest mean rank (best control relative to S_UT) and was one of the most stable management combinations across environments, with low rank stability variance (0.99 for index and 0.67 for DON). MS_UT had the lowest mean rank (poorest control) but was also one of the most stable management combinations. Based on Piepho's nonparametric rank-based variance homogeneity U test, there was an interaction of management combination and environment for index (P = 0.011) but not for DON (P = 0.147), indicating that the rank ordering for index depended somewhat on environment. In conclusion, although the magnitude of percent control will likely vary among environments, integrating a single tebuconazole + prothioconazole application at anthesis with cultivar resistance will be a more effective and stable management practice for both index and DON than either approach used alone.

Pathotype diversity of Phytophthora sojae was assessed in 11 states in the United States during 2012 and 2013. Isolates of P. sojae were recovered from 202 fields, either from soil samples using a soybean seedling bioassay or by isolation from symptomatic plants. Each isolate was inoculated directly onto 12 soybean differentials; no Rps gene or Rps 1a, 1b, 1c, 1k, 3a, 3b, 3c, 4, 6, 7, or 8. There were 213 unique virulence pathotypes identified among the 873 isolates collected. None of the Rps genes were effective against all the isolates collected but Rps6 and Rps8 were effective against the majority of isolates collected in the northern regions of the sampled area. Virulence toward Rps1a, 1b, 1c, and 1k ranged from 36 to 100% of isolates collected in each state, while virulence to Rps6 and Rps8 was less than 36 and 10%, respectively. Depending on the state, the effectiveness of Rps3a ranged from totally effective to susceptible to more than 40% of the isolates. Pathotype complexity has increased in populations of P. sojae in the United States, emphasizing the increasing importance of stacked Rps genes in combination with high partial resistance as a means of limiting losses to P. sojae.

The use of foliar fungicides on field corn has increased greatly over the past 5 years in the United States in an attempt to increase yields, despite limited evidence that use of the fungicides is consistently profitable. To assess the value of using fungicides in grain corn production, random-effects meta-analyses were performed on results from foliar fungicide experiments conducted during 2002 to 2009 in 14 states across the United States to determine the mean yield response to the fungicides azoxystrobin, pyraclostrobin, propiconazole + trifloxystrobin, and propiconazole + azoxystrobin. For all fungicides, the yield difference between treated and nontreated plots was highly variable among studies. All four fungicides resulted in a significant mean yield increase relative to the nontreated plots (P < 0.05). Mean yield difference was highest for propiconazole + trifloxystrobin (390 kg/ha), followed by propiconazole + azoxystrobin (331 kg/ha) and pyraclostrobin (256 kg/ha), and lowest for azoxystrobin (230 kg/ha). Baseline yield (mean yield in the nontreated plots) had a significant effect on yield for propiconazole + azoxystrobin (P < 0.05), whereas baseline foliar disease severity (mean severity in the nontreated plots) significantly affected the yield response to pyraclostrobin, propiconazole + trifloxystrobin, and propiconazole + azoxystrobin but not to azoxystrobin. Mean yield difference was generally higher in the lowest yield and higher disease severity categories than in the highest yield and lower disease categories. The probability of failing to recover the fungicide application cost (p(loss)) also was estimated for a range of grain corn prices and application costs. At the 10-year average corn grain price of $0.12/kg ($2.97/bushel) and application costs of $40 to 95/ha, p(loss) for disease severity <5% was 0.55 to 0.98 for pyraclostrobin, 0.62 to 0.93 for propiconazole + trifloxystrobin, 0.58 to 0.89 for propiconazole + azoxystrobin, and 0.91 to 0.99 for azoxystrobin. When disease severity was >5%, the corresponding probabilities were 0.36 to 95, 0.25 to 0.69, 0.25 to 0.64, and 0.37 to 0.98 for the four fungicides. In conclusion, the high p(loss) values found in most scenarios suggest that the use of these foliar fungicides is unlikely to be profitable when foliar disease severity is low and yield expectation is high.

Soybean (Glycine max (L.) Merr.) is produced across a vast swath of North America, with the greatest concentration in the Midwest. Root rot diseases and damping-off are a major concern for production, and the primary causal agents include oomycetes and fungi. In this study, we focused on examination of oomycete species distribution in this soybean production system and how environmental and soil (edaphic) factors correlate with oomycete community composition at early plant growth stages. Using a culture-based approach, 3,418 oomycete isolates were collected from 11 major soybean-producing states and most were identified to genus and species using the internal transcribed spacer region of the ribosomal DNA. Pythium was the predominant genus isolated and investigated in this study. An ecology approach was taken to understand the diversity and distribution of oomycete species across geographical locations of soybean production. Metadata associated with field sample locations were collected using geographical information systems. Operational taxonomic units (OTU) were used in this study to investigate diversity by location, with OTU being defined as isolate sequences with 97% identity to one another. The mean number of OTU ranged from 2.5 to 14 per field at the state level. Most OTU in this study, classified as Pythium clades, were present in each field in every state; however, major differences were observed in the relative abundance of each clade, which resulted in clustering of states in close proximity. Because there was similar community composition (presence or absence) but differences in OTU abundance by state, the ordination analysis did not show strong patterns of aggregation. Incorporation of 37 environmental and edaphic factors using vector-fitting and Mantel tests identified 15 factors that correlate with the community composition in this survey. Further investigation using redundancy analysis identified latitude, longitude, precipitation, and temperature as factors that contribute to the variability observed in community composition. Soil parameters such as clay content and electrical conductivity also affected distribution of oomycete species. The present study suggests that oomycete species composition across geographical locations of soybean production is affected by a combination of environmental and edaphic conditions. This knowledge provides the basis to understand the ecology and distribution of oomycete species, especially those able to cause diseases in soybean, providing cues to develop management strategies.

Charcoal rot (CR) disease caused by Macrophomina phaseolina is responsible for significant yield losses in soybean production. Among the methods available for controlling this disease, breeding for resistance is the most promising. Progress in breeding efforts has been slow due to the insufficient information available on the genetic mechanisms related to resistance. Genome-wide association studies (GWAS) enable unraveling the genetic architecture of resistance and identification of causal genes. The aims of this study were to identify new sources of resistance to CR in a collection of 459 diverse plant introductions from the USDA Soybean Germplasm Core Collection using field and greenhouse screenings, and to conduct GWAS to identify candidate genes and associated molecular markers. New sources for CR resistance were identified from both field and greenhouse screening from maturity groups I, II, and III. Five significant single nucleotide polymorphism (SNP) and putative candidate genes related to abiotic and biotic stress responses are reported from the field screening; while greenhouse screening revealed eight loci associated with eight candidate gene families, all associated with functions controlling plant defense response. No overlap of markers or genes was observed between field and greenhouse screenings suggesting a complex molecular mechanism underlying resistance to CR in soybean with varied response to different environments; but our findings provide useful information for advancing breeding for CR resistance as well as the genetic mechanism of resistance.