Estimating genetic parameters of DSSAT-CERES model with the GLUE method for winter wheat (Triticum aestivum L.) production
Estimating genetic parameters of DSSAT-CERES model with the GLUE method for winter wheat (Triticum aestivum L.) production
复制标题
利用 GLUE 方法估算冬小麦 (Triticum aestivum L.) 生产 DSSAT-CERES 模型的遗传参数
DOI：
10.1016/j.compag.2018.09.009
复制
发表时间：
2018-11-01
影响因子：
8.3
通讯作者：
Li, Zhenhong
中科院分区：
文献类型：
--
作者：
Li, Zhenhai;He, Jianqing;Li, Zhenhong
作物生长模型整合了基因型、环境和管理，可以作为研究这些因素对作物生长、生产和农业规划影响的分析工具。参数定标是作物生长模型局部应用前的首要步骤。在本研究中，通过在中国北京的一个现场进行为期五年（2008-2013）的现场实验，收集了实验现场数据。利用2009/2010和2012/2013两个季节的实验数据，采用广义似然不确定性估计（GLUE）方法和系统方法对DSSAT-CERES模型进行校准。利用2008/2009年、2010/2011年和2011/2012年三个季节的实验数据，对校正后的模型的预测性能进行了评价。结果表明，GLUE方法能准确估计小麦的基因型参数；模拟叶面积指数（LAI）、地上生物量（AGB）、地上氮素（AGN）和籽粒产量（GY）与实测值接近；DSSAT-CERES-Wheat模型可用于北京周边地区小麦种子播期规划和氮肥施用优化。综上所述，DSSAT-CERES-Wheat模型是北京地区冬小麦生产的有效决策工具。
Crop growth models integrate genotype, environment and management and can serve as an analytical tool by which to study the influences of these factors on crop growth, production, and agricultural planning. Parameter calibration is the primary step taken before the local application of crop growth models. In this study, experimental field data were collected by way of a five-year (2008-2013) set of field experiments at a field site in Beijing, China. The DSSAT-CERES model was calibrated by integrating the generalized likelihood uncertainty estimation (GLUE) method and a systematic approach, and used experimental data relating to two seasons 2009/2010 and 2012/2013. The calibrated model was evaluated for its prediction performance using experimental data relating to the three seasons 2008/2009, 2010/2011 and 2011/2012. The results showed that the GLUE method can accurately estimate the genotype parameters of wheat; that the simulated leaf area index (LAI), aboveground biomass (AGB), aboveground nitrogen (AGN) and grain yield (GY) were close to the measured values; and that the DSSAT-CERES-Wheat model can be used to schedule wheat seed sowing dates, and optimize N fertilizer application in areas around Beijing. In general, the DSSAT-CERES-Wheat model was proved to be a useful decision-making tool for winter wheat production in the Beijing area.