eprintid: 11426
rev_number: 20
eprint_status: archive
userid: 3170
dir: disk0/00/01/14/26
datestamp: 2020-03-31 10:44:58
lastmod: 2020-03-31 10:44:58
status_changed: 2020-03-31 10:44:58
type: article
metadata_visibility: show
creators_name: Ramirez‐Villegas, J
creators_name: Molero Milan, A
creators_name: Alexandrov, N
creators_name: Asseng, S
creators_name: Challinor, A J
creators_name: Crossa, J
creators_name: Eeuwijk, F
creators_name: Ghanem, M E
creators_name: Grenier, C
creators_name: Heinemann, A B
creators_name: Wang, J
creators_name: Juliana, P
creators_name: Kehel, Z
creators_name: Kholova, J
creators_name: Koo, J
creators_name: Pequeno, D
creators_name: Quiroz, R
creators_name: Rebolledo, M C
creators_name: Sukumaran, S
creators_name: Vadez, V
creators_name: White, J W
creators_name: Reynolds, M
creators_gender: Female
icrisatcreators_name: Kholova, J
icrisatcreators_name: Vadez, V
affiliation: International Center for Tropical Agriculture (CIAT), (Cali)
affiliation: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), (Cali)
affiliation: International Maize and Wheat Improvement Center,(Texcoco)
affiliation: International Rice Research Institute (IRRI), (Los Baños)
affiliation: Agricultural and Biological Engineering Department, University of Florida, Gainesville, (Florida)
affiliation: School of Earth and Environment, University of Leeds, (Leeds)
affiliation: Department of Plant Sciences, Wageningen University, (Wageningen)
affiliation: International Center for Agricultural Research in the Dry Areas (ICARDA), Biodiversity and Crop Improvement Program (BCIP), Avenue HafianeCherkaoui, (Rabat)
affiliation: Mohammed VI Polytechnic University (UM6P), AgroBioSciences (AgBS), (Ben Guerir)
affiliation: CIRAD, UMR AGAP, F-34398, Montpellier, France, AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, (Montpellier)
affiliation: Embrapa Arroz e Feijão Rodovia, Santo Antônio de Goiás, GO, (Brazil)
affiliation: The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, (Beijing)
affiliation: ICRISAT (Patancheru)
affiliation: International Food Policy Research Institute (IFPRI), (Washington)
affiliation: International Potato Center (CIP), (Lima)
affiliation: Tropical Agricultural Research and Higher Education Center (CATIE), Turrialba, (Costa Rica)
affiliation: ALARC, USDA-ARS, 21881 North Cardon Lane, Maricopa, (Arizona)
country: Columbia
country: Mexico
country: Philippines
country: USA
country: UK
country: Netherland
country: Morocco
country: France
country: Brazil
country: China
country: India
country: Peru
title: CGIAR modeling approaches for resource‐constrained scenarios: I. Accelerating crop breeding for a changing climate
ispublished: pub
subjects: CPM
subjects: CR1
subjects: PLB1
subjects: s2.8
divisions: CRPS4
crps: crp1.3
crps: crp1.5
crps: crp1.7
crps: crp1.8
crps: crp1.10
full_text_status: public
keywords: Crop Improvement, Breeding, Climate Change, Modeling
note: The authors would like to express their gratitude to USAIDand to the donors to the CGIAR System Council. This workwas supported by the CGIAR research programs (CRPs) onGrain Legumes (GL), RICE, MAIZE, and WHEAT agri-foodsystems, the CGIAR Platform for Big Data in Agriculture,and Excellence in Breeding. JR-V and AJC acknowledge sup-port from the CGIAR Research Program on Climate Change,Agriculture and Food Security (CCAFS) through its Flagship2 on Climate-Smart Practices and Technologies. CCAFS iscarried out with support from CGIAR Trust Fund Donorsand through bilateral funding agreements. For details, pleasevisit https://ccafs.cgiar.org/donors. The views expressed inthis paper cannot be taken to reflect the official opinionsof these organizations. Authors thank Martin J. Kropff forinsightful comments, encouragement and literature on mod-eling G×E×M interactions and gene-to-phenotype mod-els. Authors also thank two anonymous reviewers and CharlieMessina (Editor) for their constructive feedback.
abstract: Crop improvement efforts aiming at increasing crop production (quantity, quality)and adapting to climate change have been subject of active research over the pastyears. But, the question remains ‘to what extent can breeding gains be achievedunder a changing climate, at a pace sufficient to usefully contribute to climate adap-tation, mitigation and food security?’. Here, we address this question by criticallyreviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on InternationalAgricultural Research but now known simply as CGIAR) breeding programs. Cropmodeling can underpin breeding efforts in many different ways, including assessinggenotypic adaptability and stability, characterizing and identifying target breedingenvironments, identifying tradeoffs among traits for such environments, and mak-ing predictions of the likely breeding value of the genotypes. Crop modeling sciencewithin the CGIAR has contributed to all of these. However, much progress remainsto be done if modeling is to effectively contribute to more targeted and impactfulbreeding programs under changing climates. In a period in which CGIAR breedingprograms are undergoing a major modernization process, crop modelers will needto be part of crop improvement teams, with a common understanding of breedingpipelines and model capabilities and limitations, and common data standards and pro-tocols, to ensure they follow and deliver according to clearly defined breeding prod-ucts. This will, in turn, enable more rapid and better-targeted crop modeling activities,thus directly contributing to accelerated and more impactful breeding efforts.
date: 2020-03
date_type: published
publication: Crop Science (TSI)
publisher: Crop Science Society of America
pagerange: 1-21
id_number: doi:10.1002/csc2.20048
refereed: TRUE
issn: 0011-183X
official_url: https://doi.org/10.1002/csc2.20048
related_url_url: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&as_ylo=2020&q=10.1002%2Fcsc2.20048&btnG=
related_url_type: pub
citation:   Ramirez‐Villegas, J and Molero Milan, A and Alexandrov, N and Asseng, S and Challinor, A J and Crossa, J and Eeuwijk, F and Ghanem, M E and Grenier, C and Heinemann, A B and Wang, J and Juliana, P and Kehel, Z and Kholova, J and Koo, J and Pequeno, D and Quiroz, R and Rebolledo, M C and Sukumaran, S and Vadez, V and White, J W and Reynolds, M  (2020) CGIAR modeling approaches for resource‐constrained scenarios: I. Accelerating crop breeding for a changing climate.  Crop Science (TSI).  pp. 1-21.  ISSN 0011-183X     
document_url: http://oar.icrisat.org/11426/1/csc2.20048.pdf