http://oar.icrisat.org/id/eprint/7695 2017-09-04T08:38:11Z info:eu-repo/semantics/descriptiveMetadata http://oar.icrisat.org/7695/ Coping with drought: Resilience versus risk. Targeting the most suitable G*E*M options by crop simulation modeling* Vadez, V Kholova, J Agriculture-Farming, Production, Technology, Economics Crop production is axiomatically related to water consumption of transpiring leaves. Crop adaptation to water limitation then becomes an exercise of matching water supply and demand in away that the crop has enough water to complete its cropping cycle. Weather conditions vary greatly across years within environments while both weather and soil conditions vary across locations, which means that drought scenario are extremely variable and these need to be properly characterized as a pre-requisite to undertake drought research. Once the weather scenarios are defined, traits contributing to the crop adaptation to any of these scenarios need to be identified.We believe that much of these traits revolve around the need to optimize plant water use and make it efficient, together with the need to maximize water capture from the soil.Optimization of plant water use consist in identifying traits that will ensure maximum crop growth while keeping sufficient water for the grain filling period, and it deals with controlling water losses, and minimizing leaf canopy development. While tapping more water is surely important, the timing of water extraction to critical crop stages, e.g. the grain filling stage, is even more critical. It depends in great part on the way water has been managed by the plant at earlier stages, in particular to the capacity to develop a smaller crop canopy, or the capacity to restrict plant transpiration, especially under high evaporative demand. Clearly, the development of cultivars capable of better performance under water limited conditions is the result of many possible characteristics that interact with one another andwith the environment, and it is difficult to experimentally determinewhich among these traits has a predominant effect on yield in a given situation. Crop simulation modeling comes in to help to navigate biological complexity by allowing to test the effect of traits on yield acrossmany years of weather andmany locations. It also helps combining both agronomic and genetic options to maximize crop production at the plot level. John Libbey Eurotext 2013 Article PeerReviewed application/pdf en http://oar.icrisat.org/7695/1/Secheresse_2013_24_274-281.pdf Vadez, V and Kholova, J (2013) Coping with drought: Resilience versus risk. Targeting the most suitable G*E*M options by crop simulation modeling*. Secheresse, 24. pp. 274-281. ISSN 1147-7806 http://www.jle.com/en/revues/agro_biotech/sec/sommaire.phtml info:eu-repo/semantics/objectFile info:eu-repo/semantics/humanStartPage