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Development And Evaluation Of Ordinary Least Squares Regression Models For Predicting Irrigated And Rainfed Maize And Soybean Yields, Vivek Sharma, Daran R. Rudnick, Suat Irmak

Department of Biological Systems Engineering: Papers and Publications

Understanding the relationships between climatic variables and soil physical and chemical properties with crop yields on large scales is critical for evaluating crop productivity to make better assessments of local and regional food security, policy, land and water resource allocation, and management decisions. In this study, ordinary least squares(OLS) regression models were developed to predict irrigated and rainfed maize and soybean yields at the county level as a

function of explanatory variables [precipitation (P), actual crop evapotranspiration (ETa), organic matter content (OMC), cation exchange capacity (CEC), clay content (CC), and available soil water capacity (ASW)] of the dominant soil type …