摘要：INTRODUCTION: Developed recently, Functional Structural Models of Plant Growth (FSPM) aim at describingplant structural development (organogenesis and geometry), functional growth (biomass accumulation andallocation) and the complex interactions between both. They serve as a framework to integrate complex biologicaland biophysical processes in interaction with the environment, at different scales. The resulting complexity of suchmodels regarding the dimensionalities of the parameter space and state space often makes them difficult toparameterize. There is usually no systematic model identification from experimental data and such models stillremain ill-adapted for applicative purposes. The objective of this study is to explore how global sensitivity analysiscan help for the parameterization of FSPM, by quantifying the driving forces during plant growth and the relativeimportance of the described biophysical processes regarding the outputs of interest. The tests are performed on theGreenLab model. Its particularity is that both structural development and functional growth are describedmathematically as a dynamical system (Cournède et al., 2006). Its parameterization relies on parameter estimationfrom experimental data. Sensitivity analysis may help to optimize the trade-off between experimental cost andaccuracy. This is crucial to develop a predictive capacity that scales from genotype to phenotype for FSPM.
