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A data-driven crop model for maize yield prediction

Agriculture

A data-driven crop model for maize yield prediction

Y. Chang, J. Latham, et al.

This innovative research, conducted by Yanbin Chang, Jeremy Latham, Mark Licht, and Lizhi Wang, presents a novel data-driven crop model that merges process-based and data-driven methodologies to accurately predict crop yields. By analyzing extensive US Corn Belt data, this model showcases its potential in enhancing food security and aiding farmers in selecting the best seeds for their crops.

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