Crop modelling approach
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The document discusses a modeling approach for assessing the impact of climate change on crop responses, focusing on diverse scenarios and the use of various crop models for accurate predictions. It highlights the importance of identifying trait variations and developing ideotypes for breeding according to environmental challenges. Additionally, it emphasizes the necessity for consensus tools to inform policy and adapt agricultural practices in light of changing agro-climatic conditions.
Crop modelling approach
- 1. Modeling Approach Scenario source selection – Quality check: simulations with hindcasts vs historical climate – Present, 2030 pessimistic, 2030 optimistic? => Establishment of operational scenario database Global study – Simple model (GLAM) – Spatialized gridded approach – No detail of varietal differences => Global mapping of crop response to CC Zoom-ins: virtual experiments – GxExM model (SAMARA, RIDEV, CROPGRO…) – Model calibration for key varietal types – Identification of trait (crop parameter) ranges – Zooming in on TPEs for each crop (Total of 10-12?) – Sensitivity analyses: trait variation vs environment Ideotype composition for adapted crops
- 2. Need 3 types of crop models Consensus tools to translate environment scenarios – Accurate impact prediction to guide policy – Seasonal forecasting, robust standards for yield insurance – Set rational long-term priorities in research GxExM models to assist in technology generation – TPE characterization – Ideotype concepts for breeding strategies – Extrapolation of technologies Heuristic model application in phenotyping – Intelligent phenotyping: Extract G from GxExMxN(oise) – Extract « hidden traits » from simple plant observations – Genotypic reaction norms (behavioural traits)
- 3. Crop Type RIDEV ORYZA EcoMeristem SAMARA Rice Flooded-irrigated Rainfed-lowland Crop Sorghum Upland Grain model Feature Bio-EtOH (FF) Trait skills Phenology Photoperiodism Thermal response Microclimate resp. Architecture Phyllochron Organ size & Nb Green = available Tillering Orange = coming Yield GY GYC Stem sugar Biomass Water stresses Drought Water logging Submergence Thermal stresses Cold sterility Heat sterility Avoidance: TC Avoidance: TOF Salinity Salt tolerance CO2 response TE, Amax Canopy heating Resource use WUE NUE RUE
- 4. Environmental challenges (1) Irrigated rice cropping calendars in the Sahel Migration of agro-climatic zones Saint-Louis • Latitudinal & altitudinal migration • Cropping calendars, crop phenology – Change in comparative advantage of Rosso crop/system – Change in comparative advantage of different land uses – Change in pressure on agro-ecologies and Matam natural resource base => Trust in adaptation capacity of markets and stake holders => Anticipate, inform, assist Tillaberi Let policies ease the transition Sorghum varietal Zoning for W Africa
- 5. 15 High yielding, dwarf, early, sweet type 2 Plant Height 2.0 m LAI Virtual varieties (sorghum): 10 Impact of trait modification Tillers 1 Ic 5 GY Sugars 7 2 traits changed: plant height & 0 06 photoperiodism 20 90d increased 5 (4.8 m, + 40 d) 15 Effect of tallness + lateness 4 • Biomass + 44% 3 10 • Grain yield – 45% • more tillers, more mortality 2 • LAI 3 => 7 5 • Sugar reserves much smaller 1 0 0 130d
- 6. SAMARA: Short phyllochron improves vigor but not GY 50 60 50 70 Culms/hill 60 70 GY 70 60 50 50 60 LAI 70 S PI F M Internode SAHEL108 in WS 2010 at AfricaRice, NSC Senegal (source limited situation) 70 Phyllochron 50 °Cd: fast-DR Phyllochron 60 °Cd: ‘normal’ 60 Phyllochron 70 °Cd: slow-DR 50
- 7. Merci