CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate

Ramirez-Villegas Julian, Molero Milan Anabel, Alexandrov Nickolai, Asseng Senthold, Challinor Andrew J., Crossa José, van Eeuwijk Fred, Ghanem Michel Edmond, Grenier Cécile, Heinemann Alexandre, Wang Jiankang, Juliana Philomin, Kehel Zakaria, Kholova Jana, Koo Jawoo, Pequeno Diego, Quiroz Roberto, Rebolledo Cid Maria Camila, Sukumaran Sivakumar, Vadez Vincent, White Jeffrey W., Reynolds Matthew P.. 2020. CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate. Crop Science, 60 (2), n.spéc. Predictive agriculture : 547-567.

https://doi.org/10.1002/csc2.20048

Article de revue ; Article de synthèse ; Article de revue à facteur d'impact

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Quartile : Q2, Sujet : AGRONOMY

Résumé : 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, '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.

Mots-clés Agrovoc : amélioration des plantes, changement climatique, adaptation aux changements climatiques, modélisation des cultures, production végétale, productivité agricole, amélioration génétique

Mots-clés libres : Modelling, CGIAR, Climatic Change, Breeding

Classification Agris : F30 - Génétique et amélioration des plantes
P40 - Météorologie et climatologie
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 6 (2019-) - Changement climatique

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