CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate
cg.authorship.types | CGIAR multi-centre | en |
cg.contributor.affiliation | Bioversity International and the International Center for Tropical Agriculture | en |
cg.contributor.affiliation | CGIAR Research Program on Climate Change, Agriculture and Food Security | en |
cg.contributor.affiliation | International Maize and Wheat Improvement Center | en |
cg.contributor.affiliation | International Rice Research Institute | en |
cg.contributor.affiliation | University of Leeds | en |
cg.contributor.affiliation | Wageningen University & Research | en |
cg.contributor.affiliation | International Center for Agricultural Research in the Dry Areas | en |
cg.contributor.affiliation | Université Mohammed VI Polytechnique | en |
cg.contributor.affiliation | Centre de Coopération Internationale en Recherche Agronomique Pour le Développement | en |
cg.contributor.affiliation | Empresa Brasileira de Pesquisa Agropecuária | en |
cg.contributor.affiliation | National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences | en |
cg.contributor.affiliation | International Crops Research Institute for the Semi-Arid Tropics | en |
cg.contributor.affiliation | International Food Policy Research Institute | en |
cg.contributor.affiliation | International Potato Center | en |
cg.contributor.affiliation | Centro Agronómico Tropical de Investigación y Enseñanza | en |
cg.contributor.affiliation | United States Department of Agriculture | en |
cg.contributor.affiliation | International Center for Tropical Agriculture | en |
cg.contributor.crp | Big Data | |
cg.contributor.crp | Climate Change, Agriculture and Food Security | |
cg.contributor.crp | Maize | |
cg.contributor.crp | Grain Legumes and Dryland Cereals | |
cg.contributor.crp | Wheat | |
cg.contributor.crp | Rice | |
cg.contributor.donor | United States Agency for International Development | en |
cg.creator.identifier | Julian Ramirez-Villegas: 0000-0002-8044-583X | en |
cg.creator.identifier | Cecile Grenier: 0000-0001-5390-8344 | en |
cg.creator.identifier | Jose Crossa: 0000-0001-9429-5855 | en |
cg.creator.identifier | Philomin Juliana: 0000-0001-6922-0173 | en |
cg.creator.identifier | Jawoo Koo: 0000-0003-3424-9229 | en |
cg.creator.identifier | Matthew Paul Reynolds: 0000-0002-4291-4316 | en |
cg.creator.identifier | Fred van Eeuwijk: 0000-0003-3672-2921 | en |
cg.identifier.doi | https://doi.org/10.1002/csc2.20048 | en |
cg.identifier.project | IFPRI - Environment and Production Technology Division | en |
cg.identifier.publicationRank | A | en |
cg.isijournal | ISI Journal | en |
cg.issn | 0011-183X | en |
cg.issue | 2 | en |
cg.journal | Crop Science | en |
cg.reviewStatus | Peer Review | en |
cg.subject.alliancebiovciat | AGRICULTURE | en |
cg.subject.alliancebiovciat | CLIMATE CHANGE | en |
cg.subject.alliancebiovciat | FOOD SECURITY | en |
cg.volume | 60 | en |
dc.contributor.author | Ramírez Villegas, Julián Armando | en |
dc.contributor.author | Molero Milan, Anabel | en |
dc.contributor.author | Alexandrov, Nickolai | en |
dc.contributor.author | Asseng, Senthold | en |
dc.contributor.author | Challinor, Andrew J. | en |
dc.contributor.author | Crossa, José | en |
dc.contributor.author | Eeuwijk, Fred A. van | en |
dc.contributor.author | Ghanem, Michel Edmond | en |
dc.contributor.author | Grenier, Cécile | en |
dc.contributor.author | Heinemann, Alexandre B. | en |
dc.contributor.author | Wang, Jiankang | en |
dc.contributor.author | Juliana, Philomin | en |
dc.contributor.author | Kehel, Zakaria | en |
dc.contributor.author | Kholová, Jana | en |
dc.contributor.author | Koo, Jawoo | en |
dc.contributor.author | Pequeno, Diego Notelo Luz | en |
dc.contributor.author | Quiróz, Roberto | en |
dc.contributor.author | Rebolledo, Maria C. | en |
dc.contributor.author | Sukumaran, Sivakumar | en |
dc.contributor.author | Vadez, Vincent | en |
dc.contributor.author | White, Jeffrey W. | en |
dc.contributor.author | Reynolds, Matthew P. | en |
dc.date.accessioned | 2020-05-25T21:38:19Z | en |
dc.date.available | 2020-05-25T21:38:19Z | en |
dc.identifier.uri | https://hdl.handle.net/10568/108316 | |
dc.title | CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate | en |
dcterms.abstract | 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. | en |
dcterms.accessRights | Open Access | |
dcterms.available | 2020-03-04 | en |
dcterms.bibliographicCitation | 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. | en |
dcterms.extent | p. 547-567 | en |
dcterms.issued | 2020-03-04 | en |
dcterms.language | en | |
dcterms.license | Copyrighted; all rights reserved | |
dcterms.publisher | Wiley | en |
dcterms.relation | https://dx.doi.org/10.3390/agronomy8120291 | en |
dcterms.replaces | https://ebrary.ifpri.org/digital/collection/p15738coll5/id/7066 | en |
dcterms.subject | agricultura | en |
dcterms.subject | agriculture | en |
dcterms.subject | climate | en |
dcterms.subject | clima | en |
dcterms.subject | production | en |
dcterms.subject | analysis | en |
dcterms.subject | análisis | en |
dcterms.subject | producción | en |
dcterms.subject | modelling | en |
dcterms.subject | crop modelling | en |
dcterms.subject | cgiar | en |
dcterms.subject | resources | en |
dcterms.subject | crops | en |
dcterms.subject | cultivation | en |
dcterms.subject | crop production | en |
dcterms.subject | climate change | en |
dcterms.subject | climate change adaptation | en |
dcterms.subject | breeding | en |
dcterms.subject | plant breeding | en |
dcterms.subject | crop improvement | en |
dcterms.type | Journal Article |