Participatory AI for inclusive crop improvement
Crop breeding in the Global South faces a 'phenotyping bottleneck' due to reliance on manual visual phenotyping, which is both error-prone and challenging to scale across multiple environments, inhibiting selection of germplasm adapted to farmer production environments. This limitation impedes rapid...
| Autores principales: | , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/172411 |
| _version_ | 1855539127326343168 |
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| author | Lasdun, Violet Guerena, David Tonatiuh Ortiz-Crespo, Berta Mutuvi, Stephen Mutisya Selvaraj, Michael Gomez Assefa, Teshale |
| author_browse | Assefa, Teshale Guerena, David Tonatiuh Lasdun, Violet Mutuvi, Stephen Mutisya Ortiz-Crespo, Berta Selvaraj, Michael Gomez |
| author_facet | Lasdun, Violet Guerena, David Tonatiuh Ortiz-Crespo, Berta Mutuvi, Stephen Mutisya Selvaraj, Michael Gomez Assefa, Teshale |
| author_sort | Lasdun, Violet |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Crop breeding in the Global South faces a 'phenotyping bottleneck' due to reliance on manual visual phenotyping, which is both error-prone and challenging to scale across multiple environments, inhibiting selection of germplasm adapted to farmer production environments. This limitation impedes rapid varietal turnover, crucial for maintaining high yields and food security under climate change. Low adoption of improved varieties results from a top-down system in which farmers have been more passive recipients than active participants in varietal development. |
| format | Journal Article |
| id | CGSpace172411 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1724112025-11-11T19:05:43Z Participatory AI for inclusive crop improvement Lasdun, Violet Guerena, David Tonatiuh Ortiz-Crespo, Berta Mutuvi, Stephen Mutisya Selvaraj, Michael Gomez Assefa, Teshale on-farm research evaluation data collection varieties artificial intelligence phenotyping participatory plant breeding imagery Crop breeding in the Global South faces a 'phenotyping bottleneck' due to reliance on manual visual phenotyping, which is both error-prone and challenging to scale across multiple environments, inhibiting selection of germplasm adapted to farmer production environments. This limitation impedes rapid varietal turnover, crucial for maintaining high yields and food security under climate change. Low adoption of improved varieties results from a top-down system in which farmers have been more passive recipients than active participants in varietal development. 2024-10 2025-01-29T15:38:58Z 2025-01-29T15:38:58Z Journal Article https://hdl.handle.net/10568/172411 en Open Access application/pdf Elsevier Lasdun, V.; Guerena, D.T.; Ortiz-Crespo, B.; Mutuvi, S.M.; Selvaraj, M.G.; Assefa, T. (2024) Participatory AI for inclusive crop improvement. Agricultural Systems 220: 104054. ISSN: 0308-521X |
| spellingShingle | on-farm research evaluation data collection varieties artificial intelligence phenotyping participatory plant breeding imagery Lasdun, Violet Guerena, David Tonatiuh Ortiz-Crespo, Berta Mutuvi, Stephen Mutisya Selvaraj, Michael Gomez Assefa, Teshale Participatory AI for inclusive crop improvement |
| title | Participatory AI for inclusive crop improvement |
| title_full | Participatory AI for inclusive crop improvement |
| title_fullStr | Participatory AI for inclusive crop improvement |
| title_full_unstemmed | Participatory AI for inclusive crop improvement |
| title_short | Participatory AI for inclusive crop improvement |
| title_sort | participatory ai for inclusive crop improvement |
| topic | on-farm research evaluation data collection varieties artificial intelligence phenotyping participatory plant breeding imagery |
| url | https://hdl.handle.net/10568/172411 |
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