Knowledge from botany and ecophysiology has to be adapted and integrated properly inside a mathematical model. The effort to simplify the complexity is an important part ofthe modeling work. It leads to the identification of the relevant parameters that are used in the equations that control plant morphogenesis and functioning. As previously mentioned, a detailed qualitative knowledge alone is not sufficient to understand such a complex system as plant development and growth. Plant functioning has to be grasped through the behavior of the equations. Thanks to these, we can hope to solve the inverse problem that leads to the calibration of the model parameters in real situations. The final goal is to monitor plant growth in variable climate conditions and to optimize crop production.
Depending on methods, aims, and processes concerned, three main classes of models may be distinguished. They are currently referred to as geometrical models (GMs), process-based models (PBMs), and functional structural models (FSMs).
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