Simulation of environmental and genotypic variations of final leaf number and anthesis date for wheat

The rate of organ emergence and the duration of developmental phases are key components of plant fitness to its environment. Here, we describe a hybrid genetic algorithm for the estimation of the parameters of complex non-linear simulation models that we used to estimate the varietal parameters of a well-evaluated ecophysiological model (Sirius) of wheat phenology. The aim of this study was to analyze the correlations between the varietal parameters of Sirius and to determine the minimum number of parameters that need to be estimated in order to accurately simulate the effect of the genotype and environment on wheat anthesis date. A panel of 16 bread wheat cultivars was grown under controlled conditions with different vernalization and daylength treatments and in a field nursery with different sowing dates in order to characterize their vernalization and photoperiodic requirements and earliness per se. These cultivars were also grown in the field in two consecutive growing seasons in France and in the UK along a 800 km latitude transect, where the dynamics of leaf appearance and anthesis date were determined. Variation in both final leaf number and anthesis date in response to the environment and the genotype was predicted with a mean error of 0.55 leaves and 3.94 d, respectively, after estimation of only three of the seven varietal parameters of Sirius: the phyllochron, the response of vernalization rate to temperature, and the daylength response of leaf production. Among them, the phyllochron was reasonably well estimated and showed a positive association with earliness per se (Spearman's coefficient of rank correlation = 0.59). This study showed that the number of varietal parameters in Sirius was overestimated and that considering only three varietal parameters reduced the correlations between the parameters and the root mean square error of prediction for final leaf number and anthesis date. We conclude that a phenomenogical model of wheat development can be used to estimate key phenological parameters that are difficult to determine in the field: offering the possibility to conduct large-scale quantitative genetic studies to understand better the genetic control of flowering time in cereals. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.