CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate
Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains ‘to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to useful...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2020
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/108316 |
| _version_ | 1855524071574339584 |
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| author | Ramírez Villegas, Julián Armando Molero Milan, Anabel Alexandrov, Nickolai Asseng, Senthold Challinor, Andrew J. Crossa, José Eeuwijk, Fred A. van Ghanem, Michel Edmond Grenier, Cécile Heinemann, Alexandre B. Wang, Jiankang Juliana, Philomin Kehel, Zakaria Kholová, Jana Koo, Jawoo Pequeno, Diego Notelo Luz Quiróz, Roberto Rebolledo, Maria C. Sukumaran, Sivakumar Vadez, Vincent White, Jeffrey W. Reynolds, Matthew P. |
| author_browse | Alexandrov, Nickolai Asseng, Senthold Challinor, Andrew J. Crossa, José Eeuwijk, Fred A. van Ghanem, Michel Edmond Grenier, Cécile Heinemann, Alexandre B. Juliana, Philomin Kehel, Zakaria Kholová, Jana Koo, Jawoo Molero Milan, Anabel Pequeno, Diego Notelo Luz Quiróz, Roberto Ramírez Villegas, Julián Armando Rebolledo, Maria C. Reynolds, Matthew P. Sukumaran, Sivakumar Vadez, Vincent Wang, Jiankang White, Jeffrey W. |
| author_facet | Ramírez Villegas, Julián Armando Molero Milan, Anabel Alexandrov, Nickolai Asseng, Senthold Challinor, Andrew J. Crossa, José Eeuwijk, Fred A. van Ghanem, Michel Edmond Grenier, Cécile Heinemann, Alexandre B. Wang, Jiankang Juliana, Philomin Kehel, Zakaria Kholová, Jana Koo, Jawoo Pequeno, Diego Notelo Luz Quiróz, Roberto Rebolledo, Maria C. Sukumaran, Sivakumar Vadez, Vincent White, Jeffrey W. Reynolds, Matthew P. |
| author_sort | Ramírez Villegas, Julián Armando |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains ‘to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?’. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts. |
| format | Journal Article |
| id | CGSpace108316 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1083162025-11-12T04:57:14Z CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate Ramírez Villegas, Julián Armando Molero Milan, Anabel Alexandrov, Nickolai Asseng, Senthold Challinor, Andrew J. Crossa, José Eeuwijk, Fred A. van Ghanem, Michel Edmond Grenier, Cécile Heinemann, Alexandre B. Wang, Jiankang Juliana, Philomin Kehel, Zakaria Kholová, Jana Koo, Jawoo Pequeno, Diego Notelo Luz Quiróz, Roberto Rebolledo, Maria C. Sukumaran, Sivakumar Vadez, Vincent White, Jeffrey W. Reynolds, Matthew P. agricultura agriculture climate clima production analysis análisis producción modelling crop modelling cgiar resources crops cultivation crop production climate change climate change adaptation breeding plant breeding crop improvement Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains ‘to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?’. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts. 2020-03-04 2020-05-25T21:38:19Z 2020-05-25T21:38:19Z Journal Article https://hdl.handle.net/10568/108316 en https://dx.doi.org/10.3390/agronomy8120291 Open Access application/pdf Wiley Ramirez‐Villegas, J.; Molero Milan, A.; Alexandrov, N.; Asseng, S.; Challinor, A.J.; Crossa, J.; van Eeuwijk, F.; Ghanem, M.E.; Grenier, C.; Heinemann, A.B.; Wang, J.; Juliana, P.; Kehel, Z.; Kholova, J.; Koo, J.; Pequeno, D.; Quiroz, R.; Rebolledo, M.C.; Sukumaran, S.; Vadez, V.; White, J.W.; Reynolds, M. 2020 CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate. Crop Science ISSN: 0011-183X 21 p. |
| spellingShingle | agricultura agriculture climate clima production analysis análisis producción modelling crop modelling cgiar resources crops cultivation crop production climate change climate change adaptation breeding plant breeding crop improvement Ramírez Villegas, Julián Armando Molero Milan, Anabel Alexandrov, Nickolai Asseng, Senthold Challinor, Andrew J. Crossa, José Eeuwijk, Fred A. van Ghanem, Michel Edmond Grenier, Cécile Heinemann, Alexandre B. Wang, Jiankang Juliana, Philomin Kehel, Zakaria Kholová, Jana Koo, Jawoo Pequeno, Diego Notelo Luz Quiróz, Roberto Rebolledo, Maria C. Sukumaran, Sivakumar Vadez, Vincent White, Jeffrey W. Reynolds, Matthew P. CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title_full | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title_fullStr | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title_full_unstemmed | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title_short | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate |
| title_sort | cgiar modeling approaches for resource constrained scenarios i accelerating crop breeding for a changing climate |
| topic | agricultura agriculture climate clima production analysis análisis producción modelling crop modelling cgiar resources crops cultivation crop production climate change climate change adaptation breeding plant breeding crop improvement |
| url | https://hdl.handle.net/10568/108316 |
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