Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
Tipo:
Título:
Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
Creador/a:
Yunbi Xu;
Zhang Xingping;
Huihui Li;
Hongjian Zheng;
Jianan Zhang;
Olsen, M.;
Varshney, R.K.;
Prasanna, B.M.;
Qian Qian
Zhang Xingping;
Huihui Li;
Hongjian Zheng;
Jianan Zhang;
Olsen, M.;
Varshney, R.K.;
Prasanna, B.M.;
Qian Qian
Año:
2022
Copyright:
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Revista:
Molecular Plant
Volumen de la Revista:
15
No de Revista:
11
Páginas:
1664-1695
Lugar de publicación:
USA
Editor:
Cell Press
Cita:
Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction. 2022. 15 (11) DOI: 10.1016/j.molp.2022.09.001 Cell Press.
Iniciativas del CGIAR
Iniciativa:
Accelerated Breeding
Breeding Resources
Breeding Resources
Área de impacto:
Nutrition, health & food security
Poverty reduction, livelihoods & jobs
Poverty reduction, livelihoods & jobs
Área de acción:
Genetic Innovation
Donante o financiador:
National Key Research and Development Program of China
Central Public-interest Scientific Institution Basal Research Fund
Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences
Shijiazhuang Science and Technology Incubation Program
Hebei Innovation Capability Enhancement Project
Project of Hainan Yazhou Bay Seed Laboratory
Department of Science and Technology of Ninxia Project
Bill & Melinda Gates Foundation
CGIAR Research Program on Maize
Central Public-interest Scientific Institution Basal Research Fund
Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences
Shijiazhuang Science and Technology Incubation Program
Hebei Innovation Capability Enhancement Project
Project of Hainan Yazhou Bay Seed Laboratory
Department of Science and Technology of Ninxia Project
Bill & Melinda Gates Foundation
CGIAR Research Program on Maize
URL en CGSpace: