Meng-Zhen Kang

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Numerical simulation of plant growth has been facing a bottleneck due to the cumbersome computation implied by the complex plant topological structure. In this paper, we present a new mathematical model for plant growth, GreenLab, overcoming these difficulties. GreenLab is based on a powerful factorization of the plant structure. Fast simulation algorithms(More)
A stochastic functional–structural model simulating plant development and growth is presented. The number of organs (internodes, leaves and fruits) produced by the model is not only a key intermediate variable for biomass production computation, but also an indicator of model complexity. To obtain their mean and variance through simulation is time-consuming(More)
An optimal control methodology is proposed for plant growth. This methodology is demonstrated by solving a water supply problem for optimal sunflower fruit filling. The functional–structural sunflower growth is described by a dynamical system given soil water conditions. Numerical solutions are obtained through an iterative optimization procedure, in which(More)
In this paper, a recursive algorithm that can build complex tree structure quickly is presented briefly. The plant structural growth is based on a dual-scale automaton, in which 'macrostate' and 'microstate' are used to simulate the growth unit and the metamers inside growth unit separately. Each state is characterized by its 'physiological age'. The(More)
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