Application of Machine Learning Methodologies for Predicting Corn Economic Optimal Nitrogen Rate

Core Ideas A Machine Learning approach was innovatively used to predict corn EONR. Two features were created to approximate hydrological conditions for modeling EONR. Soil hydrology conditions were found essential in successful modeling in‐season EONR. Determination of in‐season N requirement for corn ( Zea mays L.) is challenging due to interactions of genotype, environment, and management. Machine learning (ML), with its predictive power to...