Deep learning applications for genomic selection in wheat breeding

Detalles Bibliográficos
Autor principal: CGIAR Research Program on Wheat
Formato: Case Study
Lenguaje:Inglés
Publicado: 2021
Materias:
Acceso en línea:https://hdl.handle.net/10568/124282
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author CGIAR Research Program on Wheat
author_browse CGIAR Research Program on Wheat
author_facet CGIAR Research Program on Wheat
author_sort CGIAR Research Program on Wheat
collection Repository of Agricultural Research Outputs (CGSpace)
format Case Study
id CGSpace124282
institution CGIAR Consortium
language Inglés
publishDate 2021
publishDateRange 2021
publishDateSort 2021
record_format dspace
spelling CGSpace1242822023-03-14T12:39:00Z Deep learning applications for genomic selection in wheat breeding CGIAR Research Program on Wheat monitoring and evaluation agrifood systems rural development 2021-12-31 2022-10-06T20:20:52Z 2022-10-06T20:20:52Z Case Study https://hdl.handle.net/10568/124282 en Open Access application/pdf CGIAR Research Program on Wheat. 2021. Deep learning applications for genomic selection in wheat breeding. Reported in Wheat Annual Report 2021. MELIA.
spellingShingle monitoring and evaluation
agrifood systems
rural development
CGIAR Research Program on Wheat
Deep learning applications for genomic selection in wheat breeding
title Deep learning applications for genomic selection in wheat breeding
title_full Deep learning applications for genomic selection in wheat breeding
title_fullStr Deep learning applications for genomic selection in wheat breeding
title_full_unstemmed Deep learning applications for genomic selection in wheat breeding
title_short Deep learning applications for genomic selection in wheat breeding
title_sort deep learning applications for genomic selection in wheat breeding
topic monitoring and evaluation
agrifood systems
rural development
url https://hdl.handle.net/10568/124282
work_keys_str_mv AT cgiarresearchprogramonwheat deeplearningapplicationsforgenomicselectioninwheatbreeding