Sclerotinia stem rot (SSR) is a major disease of soybean across the Upper Midwest region of the United States. Management of this disease has relied on fungicide applications, but due to the environmental conditions necessary for SSR to develop, many of these applications are unnecessary. To mitigate this, predictive models have been developed using localized weather data for predicting the formation of Sclerotinia sclerotiorum apothecia, the inoculum source of SSR, and these models were integrated into a decision support system called Sporecaster. However, these models do not account for the soybean resistance levels to SSR. In this study, fungicide trials were performed across seven site-years in Wisconsin between 2020 and 2022 examining fungicide applications applied at one of three action thresholds (low, moderate, and high) following Sporecaster recommendations in combination with four soybean varieties representing three SSR resistance levels (susceptible, moderately resistant, and resistant). From these trials, the low and moderate action thresholds resulted in similarly low disease severity index (DIX) levels comparable to the standard across all varieties. However, the low action threshold was most accurate for predicting SSR development in the susceptible variety, and the high action threshold was most accurate for predicting SSR development for the three resistant varieties. Both the susceptible soybean and a moderately resistant line yielded similarly high results. Additionally, the use of all fungicide applications led to similar partial profits at grain sale prices of either $0.44 or $0.55 kg-1. Overall, this study uncovered relationships between soybean resistance levels to SSR and Sporecaster, allowing for improved recommendations for fungicide applications.
Keywords: Sclerotinia sclerotiorum; Sclerotinia stem rot; fungicides; genetic resistance; predictive models; white mold.