Résumé
Traits related to crop performance (sugar, grain, biomass) are complex and their genetic bases difficult to study. To take advantage, in the process of selection, of tools now provided by molecular genetics, these traits need to be 'dissected' into elemental processes, more simple genetically and less prone to GxE (genotype X environment) interactions (Dingkuhn et al. 2007). However, evaluating a component trait individually is meaningless as plant and crop performance is the dynamic result of physiological, and sometimes genetic, linkages between traits in a given environment. This represents today a great challenge in the context of plant phenotyping and selection. Modelling enables formalizing biological processes as equations with G-dependent parameters, potentially linked to genetic information (eg. QTL). The use of model parameters as phenotypic traits for genetic analyses already showed its relevance in the case of simple models (Reymond et al. 2003; Yin et al. 1999). More recently, a few studies demonstrated the interest of using more integrative plant models for discriminating genotypes, based on parameter values within component, process based modules (Lecoeur et al. 2008; Luquet et al. 2008). Among them is Ecomeristem (Luquet et al. 2006), model simulating cereals' crop performance based on a simple formalism of plant vegetative morphogenesis, i.e. of meristem activity and its GxE regulation (organ creation, size, etc). Its use for QTL detection in a rice mapping population (based on parameters related to tillering, leaf size, phyllochron) gave even promising preliminary results (Ahmadi et al. 2008). DELICAS is a project that aims to identify, for sugar cane, molecular markers associated with genes of yield formation (Nibouche et al. 2010). Crop modelling is intended to support the phenotyping of component processes. In this context, Ecomeristem is currently adapted to sugar cane in order to take advantage of its plant level approach of morphogenesis and source-sink relationships. This paper aims to present this new model version, before it is tested and compared to other modelling approach(es) for its discriminative value (Martiné et al. 2010).