To sustain the future world demand in sugar, bioenergy and biofuels, sugarcane crops with higher productivity are needed. This relies in first place on the creation of varieties with higher yield potential. New approaches exist that use known linkages between genome regions and agronomic traits of interest (Yin et al., 1999). In this respect, the DELICAS ANR project aims at identifying molecular markers associated with genes involved in the elaboration of sugarcane yield (Nibouche et al. poster, same session). The success of such an approach relies on the identification of simple process based traits constituting yield formation, more simple genetically and less prone to genotype by environment interactions (GxE, Hammer et al., 2005). As growth models mimic dynamically elemental processes of yield formation, related process based parameters could be considered as finer phenotypic traits and used in a phenotyping approach. Since a few years, model assisted phenotyping has been used on various plants with simple models (Yin et al., 1999). On Sugarcane, modelling studies mainly dealt with crop growth model (Canegro, Apsim, Qcane, Mosicas) applied to very few varieties in not too contrasted E. This did not provide to date a clear view of the genetic variability of their crop parameters. Also, O'Leary (2000) and Singels et al. (2005) underlined the need to explore the genetic variability that can be accounted for by the parameters in existing sugarcane crop models, this, to consequently adapt those models to support breeding purposes. The objective of this study is to determine the genetic and environmental variability of the crop parameters of two dynamic sugarcane crop growth models applied to 18 sugarcane genotypes in two contrasted environments in La Réunion Island: 1/ Mosicas [ Martiné & Todoroff, 2002] a population level model used widely for agronomic purposes, 2/ and Ecomeristem [Luquet et al., 2006], simulating rice and sorghum plant growth in its stand and