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Crop modelling approach


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From 6 to 8 December, CCAFS theme 1 organized a workshop staged on the Addis Ababa campus of the International Livestock Research Institute (ILRI). The workshop titled 'Developing climate-smart crops for 2030 world' involved over 40 participants from 16 countries, broadly divided along either side of the breeding / modeling continuum.

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Crop modelling approach

  1. 1. Modeling ApproachScenario source selection – Quality check: simulations with hindcasts vs historical climate – Present, 2030 pessimistic, 2030 optimistic? => Establishment of operational scenario databaseGlobal study – Simple model (GLAM) – Spatialized gridded approach – No detail of varietal differences => Global mapping of crop response to CCZoom-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. 2. Need 3 types of crop modelsConsensus tools to translate environment scenarios– Accurate impact prediction to guide policy– Seasonal forecasting, robust standards for yield insurance– Set rational long-term priorities in researchGxExM models to assist in technology generation– TPE characterization– Ideotype concepts for breeding strategies– Extrapolation of technologiesHeuristic model application in phenotyping– Intelligent phenotyping: Extract G from GxExMxN(oise)– Extract « hidden traits » from simple plant observations– Genotypic reaction norms (behavioural traits)
  3. 3. Crop Type RIDEV ORYZA EcoMeristem SAMARA Rice Flooded-irrigated Rainfed-lowlandCrop Sorghum Upland Grainmodel Feature Bio-EtOH (FF) Traitskills Phenology Photoperiodism Thermal response Microclimate resp. Architecture Phyllochron Organ size & NbGreen = available TilleringOrange = 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. 4. Environmental challenges (1) Irrigated rice cropping calendars in the SahelMigration 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. 5. 15 High yielding, dwarf, early, sweet type2 Plant Height 2.0 m LAI Virtual varieties (sorghum): 10 Impact of trait modification Tillers1 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. 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. 7. Merci