@article{fdi:010074868,
  title = {{R}ole of modelling in international crop research : overview and some case studies},
  author = {{R}eynolds, {M}. and {K}ropff, {M}. and {C}rossa, {J}. and {K}oo, {J}. and {K}ruseman, {G}. and {M}ilan, {A}. {M}. and {R}utkoski, {J}. and {S}chulthess, {U}. and {B}alwinder, {S}ingh and {S}onder, {K}. and {T}onnang, {H}. and {V}adez, {V}incent},
  editor = {},
  language = {{ENG}},
  abstract = {{C}rop modelling has the potential to contribute to global food and nutrition security. {T}his paper briefly examines the history of crop modelling by international crop research centres of the {CGIAR} (formerly {C}onsultative {G}roup on {I}nternational {A}gricultural {R}esearch but now known simply as {CGIAR}), whose primary focus is on less developed countries. {B}asic principles of crop modelling building up to a {G}enotype x {E}nvironment x {M}anagement x {S}ocioeconomic ({G} x {E} x {M} x {S}) paradigm, are explained. {M}odelling 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. {N}ew 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. {S}ocio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. {T}hese 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.},
  keywords = {crop modelling ; international agricultural research ; {CGIAR} ; crop management ; foresight ; food security ; agri-food-systems ; global phenotyping networks ; data sharing ; big data ; {AFRIQUE} {SUBSAHARIENNE} ; {INDE} ; {BANGLADESH} ; {MONDE} ; {ANDES} ; {ZONE} {TROPICALE}},
  booktitle = {},
  journal = {{A}gronomy},
  volume = {8},
  numero = {12},
  pages = {art. 291 [46p.]},
  ISSN = {2073-4395},
  year = {2018},
  DOI = {10.3390/agronomy8120291},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074868},
}