Developing a multiscale model for plants, capable of managing complex plant response to environmental conditions and its underlying genetic diversity, is a major issue in agronomy and biology. The Resource Balance Analysis framework is promising to integrate the finest scales (genes) to the individual scale, by refining the organ description in existing functional-structural plant models and by taking advantage of new omics data, such as quantitative proteomics. Dealing with multicellular organisms such as the plant opens mathematical and computational challenges for building, calibrating and simulating such multiscale models in steady-state and dynamical conditions. This project aims to first address these mathematical challenges, develop and experimentally validate the first multiscale model of the plant Arabidopsis thaliana. Second, the model will help biologists study the plant's resource allocation strategy under normal and limiting environmental conditions, primarily using data sets generated by one of the most robust plant phenotyping systems. The model will be used to generate new biological knowledge or hypotheses (e.g., cellular functions affected in plant plasticity to nutritional stress). This clearly represents a significant advance in the context of plant adaptation, and to decipher the specific responses of other A. thaliana genotypes to complex environmental conditions. The modeling framework will address important challenges such as the integration of heterogeneous and multiscale data (from omics to phenotypic traits), genotype-phenotype relationships in complex environments, and the integration of genetic diversity into modeling.