Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment
Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2021
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/114893 |
| _version_ | 1855515589862227968 |
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| author | Sousa, Kauê de Etten, Jacob van Poland, Jesse A. Fadda, Carlo Jannink, Jean-Luc Gebrehawaryat Kidane, Yosef Lakew, Basazen Fantahun Mengistu, Dejene Kassahun Pè, Mario Enrico Solberg, Svein Øivind Dell’Acqua, Matteo |
| author_browse | Dell’Acqua, Matteo Etten, Jacob van Fadda, Carlo Gebrehawaryat Kidane, Yosef Jannink, Jean-Luc Lakew, Basazen Fantahun Mengistu, Dejene Kassahun Poland, Jesse A. Pè, Mario Enrico Solberg, Svein Øivind Sousa, Kauê de |
| author_facet | Sousa, Kauê de Etten, Jacob van Poland, Jesse A. Fadda, Carlo Jannink, Jean-Luc Gebrehawaryat Kidane, Yosef Lakew, Basazen Fantahun Mengistu, Dejene Kassahun Pè, Mario Enrico Solberg, Svein Øivind Dell’Acqua, Matteo |
| author_sort | Sousa, Kauê de |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments. |
| format | Journal Article |
| id | CGSpace114893 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1148932025-11-11T17:41:35Z Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment Sousa, Kauê de Etten, Jacob van Poland, Jesse A. Fadda, Carlo Jannink, Jean-Luc Gebrehawaryat Kidane, Yosef Lakew, Basazen Fantahun Mengistu, Dejene Kassahun Pè, Mario Enrico Solberg, Svein Øivind Dell’Acqua, Matteo data abiotic stress breeding climate change biodiversity participatory research plant breeding triticum durum wheat estrés abiotico mejora cambio climatico Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments. 2021-08-19 2021-09-07T08:58:21Z 2021-09-07T08:58:21Z Journal Article https://hdl.handle.net/10568/114893 en https://hdl.handle.net/10568/108545 Open Access application/pdf Springer de Sousa, K.; van Etten, J.; Poland, J.; Fadda, C.; Jannink, J.L.; Gebrehawaryat, Y.; Lakew, B.F.; Mengistu, D.K.; Pè, M.E.; Solberg, S.Ø.; Dell'Acqua, M. (2021) Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment. Communications Biology 4: 944. 9 p. ISSN: 2399-3642 |
| spellingShingle | data abiotic stress breeding climate change biodiversity participatory research plant breeding triticum durum wheat estrés abiotico mejora cambio climatico Sousa, Kauê de Etten, Jacob van Poland, Jesse A. Fadda, Carlo Jannink, Jean-Luc Gebrehawaryat Kidane, Yosef Lakew, Basazen Fantahun Mengistu, Dejene Kassahun Pè, Mario Enrico Solberg, Svein Øivind Dell’Acqua, Matteo Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title | Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title_full | Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title_fullStr | Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title_full_unstemmed | Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title_short | Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| title_sort | data driven decentralized breeding increases prediction accuracy in a challenging crop production environment |
| topic | data abiotic stress breeding climate change biodiversity participatory research plant breeding triticum durum wheat estrés abiotico mejora cambio climatico |
| url | https://hdl.handle.net/10568/114893 |
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