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Article
H. Webber ; D. Cooke ; C. Wang ; S. Asseng ; P. Martre ; F. Ewert ; B. Kimball ; G. Hoogenboom ; S. Evett ; A. Chanzy ; S. Garrigues ; A. Olioso ; K.S. Copeland ; J.L. Steiner ; D. Cammarano ; Y. Chen ; M. Crepeau ; E. Diamantopoulos ; R. Ferrise ; L. Manceau ; T. Gaiser ; Y. Gao ; S. Gayler ; J.R. Guarin ; T. Hunt ; G. Jégo ; G. Padovan ; E. Pattey ; D. Ripoche ; A. Rodriguez ; M. Ruiz-Ramos ; V. Shelia ; A.K. Srivastava ; I. Supit ; F. Tao ; K. Thorp ; M. Viswanathan ; T. Weber ; J. White |Under climate change and increasingly extreme weather, projections of water demand and drought stress from process-based crop models can inform risk management and adaptation strategies. Previous studies investigating maize crop models demonstra[...]
Article
Y. Gao ; S.A. Camtepe ; N.H. Sultan ; H.T. Bui ; A. Mahboubi ; H. Aboutorab ; M. Bewong ; R. Islam ; M.Z. Islam ; A. Chauhan ; P. Gauravaram ; D. Singh |In light of their remarkable predictive capabilities, artificial intelligence (AI) models driven by deep learning (DL) have witnessed widespread adoption in the agriculture sector, contributing to diverse applications such as enhancing crop mana[...]
Article
Encouraging farmers to adopt environmentally friendly technology through the rational use of social learning and agricultural technology extension is an effective way to overcome the bottleneck caused by the slow diffusion of environmentally fri[...]
