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International audience ; 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

International audience ; 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

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. ; IFPRI3; HarvestChoice ; EPTD ; PR ; CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Wheat (WHEAT); CGIAR Research Program on Rice (GRiSP)

International audience ; 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

Developing countries are at considerable risk from climate variability and climate change, both of which threaten poverty reduction and development efforts. The Climate Services for Resilient Development (CSRD) partnership is led by the United States Government has developed a consortium of global leaders in science, technology and development finance to assist at-risk nations to adapt to these problems. CSRD is aligned with the the Global Framework for Climate Services and works in Bangladesh, Ethiopia, and Colombia to creating and provide timely and useful climate data, information, tools, and services. Within South Asia, efforts to develop agricultural climate services under CSRD are led by the International Maize and Wheat Improvement Center (CIMMYT). CSRD in turn works to support Investment Options Paper (IOP) for Climate Services for Resilient Development in Bangladesh, compiled by the Asian Development Bank (ADB) in 2016. CSRD's core objectives are to prepare farmers, extension services, and agricultural policy makers with actionable climate information and crop management advisories to reduce agricultural production risks and to increase the resilience of smallholder farming communities. This report summarizes CSRD activities, achievements, and challenges during the project's inception phase (from the end of November 2017 through April of 2017).

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. ; Peer Review

Recognizing that strengthening the climate resilience of developing nations can be achieved through relevant climate data and scientific insights, the partnership Climate Services for Resilient Development (CSRD) is aligned with the Global Framework for Climate Services and brings together climate science, data streams, and decision support tools, while also facilitating training for decision-makers on climate services. CSRD in South Asia is supported by the United States Government and with a steering consortium committee comprised of the UK Government Department for International Development (DFID), UK Meteorological Office, Environmental Systems Research Institute (ESRI), Google, the Inter-American Development Bank (IADB), the Asian Development Bank (ADB), and the American Red Cross (ARC). In South Asia, CSRD activities are led by the International Maize and Wheat Improvement Center (CIMMYT). This report details activities of the CSRD project in South Asia during the first half of 2019.

A global partnership that is aligned with the Global Framework for Climate Services, Climate Services for Resilient Development (CSRD) works to link climate science, data streams, decision support tools, and training with decision-makers in developing countries. CSRD is led by the United States Government and is supported by the UK Government Department for International Development (DFID), UK Meteorological Office, ESRI, Google, the Inter-American Development Bank, the Asian Development Bank, and the American Red Cross. Led by the International Maize and Wheat Improvement Center (CIMMYT), the CSRD initiative in South Asia works with partners to conduct applied research and facilitate the use of climate information to reduce risk for smallholder farmers. This report details activities of the CSRD project in South Asia during 2018, with emphasis on the second half of 2018 (activities in the first half of 2018 can be found in the semi-annual report).

Aligned with the Global Framework for Climate Services, Climate Services for Resilient Development (CSRD) is a global partnership that works to link climate science, data streams, decision support tools, and training with decision-makers in developing countries. CSRD is led by the United States Government and is supported by the UK Government Department for International Development (DFID), UK Meteorological Office, ESRI, Google, the Inter-American Development Bank, the Asian Development Bank, and the American Red Cross. Led by the International Maize and Wheat Improvement Center (CIMMYT), the CSRD initiative in South Asia implements applied research and facilitates an expanding network of partners assure that actionable climate information and crop management advisories can be generated, refined, and delivered to smallholder farmers. This report details activities of the CSRD project in South Asia during the first six months of 2018.