冬小麦返青后株高模拟模型及生长可视化研究  

Plant Height Simulation Model and Growth Visualization of Reviving Winter Wheat

作　　者：李书钦[1,2] 诸叶平[2] 刘海龙[2] 李世娟[2] 刘升平[2] 张红英[2] 高伟[3] LI Shu-qin ZHU Ye-ping LIU Hal-long LI Shi-juan LIU Sheng-ping ZHANG Hong-ying GAO Wei(Information Center, North China University of Technology, Beijing 100144, China Agricultural Information Institute, Chinese Academy of Agricultural Sciences/ Key Laboratory of Agri- Information Service Technology, Ministry of Agriculture, Beijing 100081, China Institute of Agricultural Resources and Environment Sciences, Tianjin Academy of Agricultural Sciences, Tianjin 300192, China)

机构地区：[1]北方工业大学信息中心,北京100144 [2]中国农业科学院农业信息研究所/农业部农业信息服务技术重点实验室,北京100081 [3]天津市农业科学院农业资源与环境研究所,天津300192

出　　处：《福建农业学报》2017年第6期670-675,共6页Fujian Journal of Agricultural Sciences

基　　金：国家863计划项目(2013AA102305);国家自然科学基金项目(61271364);国家重点研发计划项目(2016YFD0200601);中国农业科学院科技创新工程项目(CAAS-ASTIP-2016-AII-03);中国农业科学院协同创新项目(CAAS-XTCX2016006)

摘　　要：小麦生长模拟模型对小麦生长管理调控、产量预测和经济效益分析等有重要指导作用,针对小麦生长模拟模型和生长可视化不易实现的问题,以冬小麦品种衡观35、济麦22和衡4399为材料,于2015-2016年小麦生长季内开展不同品种和施氮水平的田间试验,通过分析各品种冬小麦返青后株高和有效积温的定量关系,用Logistic方程构建了冬小麦返青后株高模拟模型,经数据检验,株高模拟模型绝对误差在0.01~2.72cm,根均方差(RMSE)在0.4~1.26cm,平均绝对误差(d_a)在0.36~1.11cm,平均绝对误差与实测值平均数的比值(d_(ap))在1.32%~3.46%,结果表明所建模拟模型精度较高,对不同品种冬小麦株高生长具有较好预测性。借助该模拟模型和已有研究成果,本研究构造了不同品种、不同施氮水平下的冬小麦株高生长状态,逼真模拟冬小麦返青后株高动态生长过程,实现了不同品种冬小麦在不同施氮水平下的生长可视化。A mathematic model that can reliably simulate the growth of wheat would facilitate the management, production forecast and economic analysis for the farming operation. Thus, field experiments were conducted to generate data for establishing such a model. After winter dormancy and spring reviving, the growth （plant height） of 3 varieties of wheat, i. e. , Hengguan 35 （Hg35）, Jimai 22 （Jm22） and Heng 4399 （H4399）, under varied nitrogen levels in relation to the effective accumulated atmosphere temperature during 2015-2016 was monitored. Subsequently, the logistic equations obtained were validated with data collected from separate experiments to show the plant height prediction by the models to be 0.01--2.72 cm on the absolute error, 0.4-1. 26 cm on RMSE, 0.36 -1. 11cm on da, and 1. 32 %3.46% on dap. It appeared that the models were accurate in simulating the growth of the 3 varieties of winter wheat. Based on the models, as well as relevant information gathered previously, virtual visualization of the morphology and dynamic growth process of the winter wheat was now realized.

关 键 词：冬小麦 有效积温 株高模拟模型 生长可视化 

分 类 号：S512.1[农业科学—作物学] TP391.9[自动化与计算机技术—计算机应用技术]