Modeling ApproachScenario 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 environmentÞ Ideotype composition for adapted crops

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 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)

Crop model skills

Crop Type RIDEV ORYZA EcoMeristem SAMARA

Rice Flooded-irrigated        

  Rainfed-lowland    

  Upland        

Sorghum Grain        

  Bio-EtOH (FF)        

Feature Trait

Phenology Photoperiodism        

  Thermal response        

  Microclimate resp.        

Architecture Phyllochron        

  Organ size & Nb    

  Tillering        

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        

Green = availableOrange = coming

Saint-Louis

Rosso

Matam

Tillaberi

Sorghum varietal Zoning for W Africa

Irrigated rice cropping calendars in the Sahel

Environmental challenges (1)

Migration of agro-climatic zones• Latitudinal & altitudinal migration• Cropping calendars, crop phenology

– Change in comparative advantage of crop/system

– Change in comparative advantage of different land uses

– Change in pressure on agro-ecologies and natural resource base

=> Trust in adaptation capacity of markets and stake holders

=> Anticipate, inform, assist Þ Let policies ease the transition

Effect of tallness + lateness• Biomass + 44%• Grain yield – 45%• more tillers, more mortality• LAI 3 => 7• Sugar reserves much smaller

High yielding, dwarf, early, sweet typePlant Height 2.0 m LAI

Tillers

Sugars

GY

2

1

0

15

10

5

0

Virtual varieties (sorghum):Impact of trait modification

2 traits changed:plant height & photoperiodismincreased(4.8 m, + 40 d)

7

6

5

4

3

2

1

0

20

15

10

5

0

Ic

90d

130d

7060

50

50607050

60

70

506070

Culms/hill

agDM

LAI

GY

706050

InternodeNSC

SAMARA: Short phyllochron improves vigor but not GY

SAHEL108 in WS 2010 at AfricaRice, Senegal (source limited situation)Phyllochron 50 °Cd: fast-DRPhyllochron 60 °Cd: ‘normal’Phyllochron 70 °Cd: slow-DR

FPI MS

Confirmed by

phenotyping r

esults

Merci