Fitting a Functional-Structural Growth Model with Plant Architectural Data

机译：用植物建筑数据拟合功能结构增长模型

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GreenLab is a recurrent discrete-time functional-structural model of plant growth and architecture. A method is presented estimating its parameters: the model is fitted to plant morphological and architectural data observed at one point of time. Since GreenLab output variables (number, size and fresh mass of organs) implicitly and nonlinearly depend on the model parameters, the fitting problem is solved by minimizing a generalized least-squares criterion and by implementing an iterative procedure. Fitting is satisfactorily performed on unbranched plants (cotton, maize, sunflower) using real data. The method is extended to more complex plants (i.e. with branches): a preliminary test on a virtual tree shows that the fitting algorithm also applies to such structured plants.

机译：GreenLab是植物生长和结构的周期性离散时间功能结构模型。提出了一种估计其参数的方法：该模型适合于在某一时间点观察到的植物形态和建筑数据。由于GreenLab的输出变量（器官的数量，大小和新鲜质量）隐式且非线性地取决于模型参数，因此可通过最小化广义最小二乘准则并执行迭代过程来解决拟合问题。使用真实数据对未分支的植物（棉花，玉米，向日葵）进行满意的拟合。该方法扩展到更复杂的植物（即带有分支的植物）：对虚拟树的初步测试表明，拟合算法也适用于此类结构化植物。

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来源
《International Symposium on Plant Growth Modeling, Simulation, Visualization and their Applications; 20031013-20031016; Beijing; CN》|2003年|P.236-249|共14页
会议地点 Beijing(CN);Beijing(CN)
作者
Z.-G. Zhan; P. De Reffye; F. Houllier; B.-G. Hu;
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作者单位

LIAMA, Institute of Automation, Chinese Academy of Sciences, China;

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原文格式 PDF
正文语种 eng
中图分类 Q945.9;
关键词
nonlinear fitting; least squares method; modeling; plant architecture; plant growth;

机译：非线性拟合最小二乘法建模植物结构植物生长;

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Fitting a Functional-Structural Growth Model with Plant Architectural Data

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