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Benchmarking Yield Potential for Soybean in North Central States

By Peyton Ginakes
The University of Minnesota is partnering with nine other North Central states to close the soybean yield gap by combining big data from producers with location-specific modelling.
Models are capable of predicting maximum yield potentials based on soil type, weather data, and management practices. However, yield gaps exist where producers’ soybean yields fall short of maximum yield potentials. That’s why ten North Central states are conducting a survey for more detailed information from soybean producers. Survey results from thousands of producers across the region allows researchers to use a ‘big data’ approach in determining which management practices can close the yield gap in localized regions. More information on what researchers have concluded thus far can be found in the Corn & Soybean Digest article, Data pegs soybean yield gap.