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Role of Modelling in International Crop Research: Overview and Some Case Studies

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International Maize and Wheat Improvement Center (CIMMYT), El Batán, Texcoco CP 56130, Mexico
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International Food Policy Research Institute (IFPRI), 2033 K St, NW, Washington, DC 20006-1002, USA
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International Rice Research Institute (IRRI), Los Baños, Laguna 4031, Philippines
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CIMMYT, China Collaborative Innovation Center, Henan Agricultural University, Zhengzhou 450002, China
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CIMMYT-India, NASC Complex, DPS Marg, New Delhi 110012, India
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CIMMYT, ICRAF House, United Nation, Avenue, Gigiri, P. O. Box 1041-063 Village Market, Nairobi 00621
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International Institute of Tropical Agriculture (IITA), Abomey Calavi, 08 BP 0932 Tri Postal, Cotonou, Benin
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International Crop Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, Telangana 502324, India
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Institut de Recherche pour le Development (IRD), Université de Montpellier, UMR DIADE, 911 Avenue Agropolis, BP 64501, 34394 Montpellier CEDEX 5, France
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Author to whom correspondence should be addressed.
Agronomy 2018, 8(12), 291; https://doi.org/10.3390/agronomy8120291
Received: 5 November 2018 / Revised: 26 November 2018 / Accepted: 27 November 2018 / Published: 4 December 2018
Crop modelling has the potential to contribute to global food and nutrition security. This paper briefly examines the history of crop modelling by international crop research centres of the CGIAR (formerly Consultative Group on International Agricultural Research but now known simply as CGIAR), whose primary focus is on less developed countries. Basic principles of crop modelling building up to a Genotype × Environment × Management × Socioeconomic (G × E × M × S) paradigm, are explained. Modelling has contributed to better understanding of crop performance and yield gaps, better prediction of pest and insect outbreaks, and improving the efficiency of crop management including irrigation systems and optimization of planting dates. New developments include, for example, use of remote sensed data and mobile phone technology linked to crop management decision support models, data sharing in the new era of big data, and the use of genomic selection and crop simulation models linked to environmental data to help make crop breeding decisions. Socio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. These approaches are discussed in this paper which also calls for closer collaboration among disciplines in order to better serve the crop research and development communities by providing model based recommendations ranging from policy development at the level of governmental agencies to direct crop management support for resource poor farmers. View Full-Text
Keywords: crop modelling; international agricultural research; CGIAR; crop management; foresight; food security; agri-food-systems; global phenotyping networks; data sharing; big data crop modelling; international agricultural research; CGIAR; crop management; foresight; food security; agri-food-systems; global phenotyping networks; data sharing; big data
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MDPI and ACS Style

Reynolds, M.; Kropff, M.; Crossa, J.; Koo, J.; Kruseman, G.; Molero Milan, A.; Rutkoski, J.; Schulthess, U.; Balwinder-Singh; Sonder, K.; Tonnang, H.; Vadez, V. Role of Modelling in International Crop Research: Overview and Some Case Studies. Agronomy 2018, 8, 291.

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