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The dynamic model of plant growth GreenLab describes plant architecture and functional growth at the level of individual organs. Structural development is controlled by formal grammars and empirical equations compute the amount of biomass produced by the plant, and its partitioning among the growing organs, such as leaves, stems and fruits. The number of organs initiated at each time step depends on the trophic state of the plant, which is evaluated by the ratio of biomass available in plant to the demand of all the organs. The control of the plant organogenesis by this variable induces oscillations in the simulated plant behaviour. The mathematical framework of the GreenLab model allows to compute the conditions for the generation of oscillations and the value of the period according to the set of parameters. Two case-studies are presented, corresponding to emergence of oscillations associated to fructification and branching. Similar alternating patterns are commonly reported by botanists. In this article, two examples were selected: alternate patterns of fruits in cucumber plants and alternate appearances of branches in Cecropia trees. The model was calibrated from experimental data collected on these plants. It shows that a simple feedback hypothesis of trophic control on plant structure allows the emergence of cyclic patterns corresponding to the observed ones. [ABSTRACT FROM AUTHOR]

The development of functional-structural plant models has opened interesting perspectives for a better understanding of plant growth as well as for potential applications in breeding or decision aid in farm management. Parameterization of such models is however a difficult issue due to the complexity of the involved biological processes and the interactions between these processes. The estimation of parameters from experimental data by inverse methods is thus a crucial step. This paper presents some results and discussions as first steps towards the construction of a general framework for the parametric estimation of functional-structural plant models. A general family of models of Carbon allocation formalized as dynamic systems serves as the basis for our study. An adaptation of the 2-stage Aitken estimator to this family of model is introduced as well as its numerical implementation, and applied in two different situations: first a morphogenetic model of sugar beet growth with simple plant structure, multi-stage and detailed observations, and second a tree growth model characterized by sparse observations and strong interactions between functioning and organogenesis. The proposed estimation method appears robust, easy to adapt to a wide variety of models, and generally provides a satisfactory goodness-of-fit. However, it does not allow a proper evaluation of estimation uncertainty. Finally some perspectives opened by the theory of hidden models are discussed. [ABSTRACT FROM PUBLISHER]