Stochastic models in floral biology and its application to the study of oilseed rape (Brassica napus L.) fertility

Abstract : The number of seeds per pod is an important determinant of yield. New clues of yield and seed quality improvement can be provided by studying the relation between the developmental patterns of floral organs and seed production. In this article, a probabilistic model of plant inflorescence fertility is presented. From a biological point of view, seed development can be viewed as the combination of several physiological processes that can be modeled with stochastic laws. Experiments were made on oilseed rape in Grignon (France) in 2008 to calibrate the model. A Generalized Least Square method was implemented to estimate the model parameters. The variations of parameters were analyzed according to the position of flowers. Furthermore, we discussed the causes that lead to the variation of seed production within the inflorescence and related them to our model. The model reproduces well the distribution of the number of ovules per flower as well as the number of final seeds per pod. We deduced a law to describe the distribution of pollen grains on the stigma that is quite difficult to be observed experimentally. This model is the first step towards a dynamic model taking into account the complexity of the oilseed rape architecture, which is aimed to quantify the influence of pollination or trophic competition on seed production.
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Communication dans un congrès
Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA09), Nov 2009, Beijing, China. 2010
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  • HAL Id : inria-00529375, version 1

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Wang Xiujuan, Amélie Mathieu, Paul-Henry Cournède, Jean-Michel Allirand, Alexandra Jullien, et al.. Stochastic models in floral biology and its application to the study of oilseed rape (Brassica napus L.) fertility. Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA09), Nov 2009, Beijing, China. 2010. 〈inria-00529375〉

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