Enhancing EcoMeristem model to better predict rice crop performance in response to increasing atmospheric CO2 concentrations

Atmospheric CO2 is expected to reach near 800 ppm in 2100, accompanied by a rise of temperature. This will considerably impact crop performance due to a direct impact on leaf C assimilation, and finally on yield components' elaboration (tillering, leaf area, panicle number, grain filling). Making crop models more predictive in future climate scenario is essential and implies firstly to better simulate the C gain generated by photosynthesis response to CO2. Crop models commonly compute biomass production using light interception (εi) and use (εb) efficiencies (Monteith's approach). Few of them consider for so key crop architectural traits, leaf photosynthesis and stomatal conductance. EcoMeristem is a functional-structural crop model, simulating cereals' plant growth and phenotypic plasticity at the organ level in response to plant C and water status. It is thus relevant to capture yield components' regulation by climate parameters, particularly CO2. However it was initially developed using εi and εb. Also, a light interception model accounting for key crop architectural parameters and leaf photosynthesis model inspired from FvCB model accounting for key climate change and leaf parameters, were recently implemented and confronted to experimental data on rice. This study aims to compare the original and the novel version of EcoMeristem in the way they simulate the regulation of yield elaboration for a few morphologically contrasted rice genotypes in response to radiation, temperature and CO2. Sensitivity analyses and simulation results will be presented and discussed with respect to the challenge of using crop modelling to support breeding in climate change context