Machine Learning Models for Corn Yield Prediction A Survey of Literature

Mohsen Shahhosseini and Guiping Hu
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Guiping Hu: Department of Industrial and Manufacturing Systems Engineering, Iowa State University, USA

International Journal of Environmental Sciences & Natural Resources, 2020, vol. 25, issue 3, 80-83

Abstract: The ability to predict crop yields enables the timely and effective decision making for crop management, and regional agriculture system planning. The field crop corn is the largest crop in the U.S. and hence significant efforts have been devoted to predicting corn yields through various means. The present survey reviews the studies that used machine learning models and their variations to predict corn yield.

Keywords: earth and environment journals; environment journals; open access environment journals; peer reviewed environmental journals; open access; juniper publishers; ournal of Environmental Sciences; juniper publishers journals; juniper publishers reivew (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:adp:ijesnr:v:25:y:2020:i:3:p:80-83

DOI: 10.19080/IJESNR.2020.25.556161

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