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Title Crop sciencie: a foundation for advancing predictive agriculture
 
Names Messina, C.D.
Cooper, M.
Reynolds, M.P.
Hammer, G.L.
Date Issued 2020 (iso8601)
Abstract This special issue in Crop Science provides a diverse cross section of views from prior and current efforts to enable prediction in agriculture. The contributions discuss and demonstrate how current advances in phenomics, genomics, and artificial intelligence are being combined to explore new modeling paradigms and prediction frameworks to advance crop science and improve decision making in agriculture. The synthesis of these views can motivate a transdisciplinary dialogue to define predictive agriculture as a discipline and guide future research efforts for the integration of data‐driven and science‐based methodologies. Collectively, these methods can provide the needed foundation for design in agricultural and food systems (National Academies of Sciences, Engineering, and Medicine, 2019).
Genre Article
Access Condition Open Access
Identifier 1435-0653 (Print)