The project aims to harmonize tools / protocols for climate measurement and control, with sufficient spatial and temporal resolution to allow parameters evaluation and design cost-effective CO2 control devices for the controlled application of high CO2 treatments. We aim to challenge modelling hypotheses by performing experiments under combined stresses (Water deficit / High Temp. / CO2) in greenhouses and climate chambers, under constant or fluctuating conditions. Key variables/parameters (biomass, leaf area, architecture and carbon allocation) and physiological parameters (photosynthesis, stomatal conductance, chlorophyll fluorescence parameters and specific metabolites) will be used to parameterize models. We will compare available state-of-the art models/modelling approaches to climatic variability and combined stresses to identify specific model deficiencies; further develop modelling approaches to improve the capacity of crop models to integrate climatic variability and combined stresses and evaluate the value of traits (and trait combinations) measured in phenotyping platforms with the ultimate aim of developing climate change-ready wheat and oilseed rape genotypes.
Climate change accelerates the need for a smarter, more efficient, more secure agriculture. Because climate change is predicted to increase spatial and temporal variability, crop models able to predict the best local allele/phene combinations within a species, in addition to the best management systems (such as, for instance, species choice, rotations, sowing dates...) will be of great value for farmers and breeders worldwide. Aware of these issues and avenues, breeding companies now massively invest in crop and climate modelling. However, current crop models have large uncertainties, in particular under drought and high temperatures that often occur in combination and while their occurrences are likely to increase in several regions of the world. Whereas major environmental drivers of growth such as temperature, light and evaporative demand are now well captured in experiments, in particular following a concerted effort of the community, the availability of these information under various [CO2] is the exception. Our project will aim at delivering to simple, low cost, principles and solutions for manipulating combined stresses, including elevated CO2, in experimental set-ups. We will start to apply these principles to the different platforms that are part of the current project.
Status | Finished |
---|
Effective start/end date | 31 Mar 2015 → 30 Mar 2018 |
---|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):