Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt

Abstract This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions, investigate which combinations of hybri...

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Autores principales: Mohsen Shahhosseini, Guiping Hu, Isaiah Huber, Sotirios V. Archontoulis
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/33f06b500da54359bd032ea96d19cf9b
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