By Paul D. Esker and Tyler Scott Mcfeaters
Sporecaster mobile app: The Sporecaster app is a forecasting tool that uses the location, weather, and cultural practices to estimate the risk for white mold in soybeans. The app was developed at the University of Wisconsin-Madison and is available for free on both iPhone and Android platforms. White mold is an annual issue in Pennsylvania soybeans. We will again be monitoring disease risk and scouting for white mold in 2022. Previous results from the Sporecaster validation in 2020 and 2021 can be found on this webpage . Briefly, we found the app was most accurate for predicting white mold incidence in PA fields when using a 50-60% action threshold. The updated version of the Sporecaster app in 2021 uses a more precise weather data source, so its utility in forecasting white mold risk should continue to improve.
Validation of the Sporecaster app: Twenty- eight fields in PA are being monitored for white mold risk during soybean flowering and will be scouted at the end of the growing season to determine the model accuracy. Field scouting will occur when the soybean crop reaches the R5 growth stage (when seeds are 1/8 inch long in the pod at one of the four uppermost nodes of the main stem) and symptoms are visible.
Risk Information for June 28, 2022
Parameters we use to run the model include:
- 30-inch or 15-inch row spacing
- > 40% canopy closure (Figure 2)
- Flowers present
- Non-irrigated
- 50% action threshold
Figure 1. Dense canopy during flowering is favorable for white mold development. Photo from our 2022 white mold fungicide trial in Lebanon County (Credit: Paul Esker).
Soybeans are beginning to flower in the southeast region and consistent scouting and growth staging is critical to get good timing on fungicide applications to protect flowers from white mold. If you have had a history of white mold, consider factors such as variety and local microclimate conditions (fog, dew, etc.) as part of your management decisions. Sporecaster predictions shown are for specific locations within each of the counties being monitored and may not accurately represent the risk in your field. To estimate your farm level risk, we recommend that you run the Sporecaster model with your field's GPS location for the most accurate predictions.
Source : psu.edu