Parameter optimization and field validation of the functional-structural model GREENLAB for maize
Parameter optimization and field validation of the functional-structural model GREENLAB for maize
复制标题
DOI：
10.1093/aob/mcj033
复制
发表时间：
2006-02-01
期刊：
影响因子：
4.2
通讯作者：
De Reffye, P
中科院分区：
文献类型：
--
作者：
Guo, Y;Ma, YT;De Reffye, P
背景与目的
基于结构原理和器官发生过程构建植物的作物模型需求日益增加，原因有三：（1）开发新作物的现实理念需要此类模型的指导；（2）基于可变结构和形态的作物表型可塑性越来越受到关注；（3）机械化种植系统的工程设计需要作物结构方面的信息。最近提出了功能 - 结构模型GREENLAB，它模拟植物结构的资源依赖性可塑性。本研究引入了一种针对测量数据优化作物参数的新方法，称为多重拟合，用独立的田间数据验证了玉米校准模型，并描述了一种输出的三维可视化技术。
方法
2000年、2001年和2003年（两个播种日期）夏季，在北京附近采用区组设计种植玉米，重复4 - 5次。在这四种作物的整个生长过程中，对植株结构进行了详细的形态学和拓扑学观察。2000年获得的数据用于使用广义最小二乘法建立参数优化的目标文件，并通过变异系数评估参数准确性。原位植物数字化用于建立器官的三维符号文件，然后用于将模型输出在模型执行的每个时间步直接转换为三维表示。
关键结果与结论
针对不同生长阶段获得的多个目标文件进行多重拟合，比仅在成熟期进行单一拟合能获得更好的参数准确性，并且能够从静态观察中提取通用的器官扩展动力学。2000年的模型对其他三个具有不同温度条件的季节的植株结构和营养生长做出了出色的预测，但对灌浆期间生物量分配的季节间变异性的预测不太准确。这可能是由于对控制果穗库大小和顶叶衰老的过程考虑不足。讨论了模型改进的进一步展望。
Background and Aims There are three reasons for the increasing demand for crop models that build the plant on the basis of architectural principles and organogenetic processes: (1) realistic concepts for developing new crops need to be guided by such models; (2) there is an increasing interest in crop phenotypic plasticity, based on variable architecture and morphology; and (3) engineering of mechanized cropping systems requires information on crop architecture. The functional-structural model GREENLAB was recently presented that simulates resource-dependent plasticity of plant architecture. This study introduces a new methodology for crop parameter optimization against measured data called multi-fitting, validates the calibrated model for maize with independent field data, and describes a technique for 3D visualization of outputs.Methods Maize was grown near Beijing during the 2000, 2001 and 2003 (two sowing dates) summer seasons in a block design with four to five replications. Detailed morphological and topological observations were made on the plant architecture throughout the development of the four crops. Data obtained in 2000 was used to establish target files for parameter optimization using the generalized least square method, and parameter accuracy was evaluated by coefficient of variance. In situ plant digitization was used to establish 3D symbol files for organs that were then used to translate model outputs directly into 3D representations for each time step of model execution.Key Results and Conclusions Multi-fitting against several target files obtained at different growth stages gave better parameter accuracy than single fitting at maturity only, and permitted extracting generic organ expansion kinetics from the static observations. The 2000 model gave excellent predictions of plant architecture and vegetative growth for the other three seasons having different temperature regimes, but predictions of inter-seasonal variability of biomass partitioning during grain filling were less accurate. This was probably due to insufficient consideration of processes governing cob sink size and terminal leaf senescence. Further perspectives for model improvement are discussed.