Adapting the Apsim model for assessing maize cultivars performances through European stressing environments

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Lacube, Sébastien | Tardieu, Francois, F. | Parent, Boris | Hammer, Graeme

Edité par CCSD -

National audience. Genetic progress will largely depend on the adaptation of new genotypes to the diversity of environments, market requirements and types of agriculture. Most experiments for cultivar evaluation use networks of field experiments to assess the suitability of hundreds of genotypes to environmental conditions. In most cases, most of them run for a few years, thereby taking into account a small fraction of the climatic variability. The use of crop models for predicting plant performance under different climatic conditions (annual variation and/or different locations) is a feasible alternative , assuming that models have an efficient capacity for simulating genotype by environment interactions (i.e. : response of plant to specific environmental conditions using genotypic parameters). If the designed model is convenient, it can be used to analyse the sensitivity of a given trait to changes in specific environment variables, assisting breeding decisions. Our first aim is to adapt the current formalisms of the APSIM model to integrate genotypic variability on key development processes affected by environmental stress, with specific parameters for each genotype that can be measured in a phenotyping platform. For that purpose, a new leaf growth module has been implemented in the model, incorporating genotypic variability of phyllochron, number of leaves and sensitivity of leaf growth to water deficit and vapour pressure deficit. All these parameters are measured in the platform PhenoArch, thereby generating a specific vector of parameters for each genotype. The objective will be to simulate the ranking of different existing genotypes in a grid of locations around Europe and analyse specific traits advantages to define the best suited ideotype for each environmental conditions, under current and future climatic conditions (incorporating climate change scenarios).

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