The purpose of Sporecaster is to assist farmers in making management decisions for white mold in soybean
Sporecaster
What is it about?
The purpose of Sporecaster is to assist farmers in making management decisions for white mold in soybean. The best time to manage white mold is during flowering (R1 and R2 growth stages) when apothecia (small, mushroom-like structures) are present on the soil surface. Apothecia release spores which infect senescing soybean flowers, leading to the development of white mold. University research has indicated that the appearance of apothecia can be predicted using several variables including weather and amount of soybean row closure in a field. Based on this research, models have been developed to forecast the risk of apothecia being present in a soybean field. Farmers can easily input site-specific information about their soybean field into this app, which combines this information with the research-based models to predict the best timing for white mold treatment or if treatment is even needed at the time.
App Screenshots
App Store Description
The purpose of Sporecaster is to assist farmers in making management decisions for white mold in soybean. The best time to manage white mold is during flowering (R1 and R2 growth stages) when apothecia (small, mushroom-like structures) are present on the soil surface. Apothecia release spores which infect senescing soybean flowers, leading to the development of white mold. University research has indicated that the appearance of apothecia can be predicted using several variables including weather and amount of soybean row closure in a field. Based on this research, models have been developed to forecast the risk of apothecia being present in a soybean field. Farmers can easily input site-specific information about their soybean field into this app, which combines this information with the research-based models to predict the best timing for white mold treatment or if treatment is even needed at the time.
Sporecaster uses GPS coordinates to determine if past local weather has been favorable for the development of apothecia during soybean flowering in a field. Models in the app use 30-day averages of maximum temperature, relative humidity, and maximum wind speed to predict favorable conditions for most soybean growing regions. Based on these predictions and crop phenology, a site-specific risk prediction is generated for three scenarios (non-irrigated soybeans, soybeans planted on 15" row-spacing and irrigated, or soybeans planted on 30" row-spacing and irrigated).
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