White mold, caused by Sclerotinia sclerotiorum, is one of the most problematic diseases impacting soybean production in the northern portion of Illinois.
Fungicides can be used to suppress this disease; however, the optimal timing for fungicide application, or the need for a fungicide application, may vary from region to region and year to year. Thus, producers may apply a fungicide, only to not encounter favorable conditions for white mold development, or not apply a fungicide because they were not sure if conditions were favorable for disease, only to suffer disease-related losses.
This is where the development of Sporecaster, a white mold forecasting application, can be an extremely valuable tool for producers.
Sporecaster was recently developed by the Smith group at the University of Madison from data collected from numerous soybean white mold trials conducted throughout the Midwest over several years. This tool uses environmental variables, as well as factors such as row spacing and flowering, to deliver a highly accurate white mold risk assessment.
Unlike older white mold models, which focused on symptoms, Sporecaster focuses on conditions that favor spore release. By knowing the factors that favor spore release, we can predict the likelihood that white mold will develop.
This information is excellent for growers as it can help them determine when a fungicide is likely to be most efficacious and profitable, and reduce unneeded applications when conditions are unfavorable for the disease.
I strongly encourage growers, CCA’s and others in the agronomic community who is involved in white mold management to down this free application, and try it out on your fields. The application is very straight forward, and contains easy to access and understand help files within the application.
To learn more about Sporecaster, please see this post from UW Madison IPM.