植物营养与肥料学报2012，Vol.18Issue(5)：1064-1072,9.
DSSAT作物模型的统计和图形校验方法
Statistical and graphical methods for evaluation of DSSAT crop model
摘要
Abstract
This paper discussed statistical and graphical evaluation methods for DSSAT model using field experiments of maize, soybean, potato and winter wheat. The results indicated that R2 is not a good statistic for model evaluation because it tests the goodness of fit of a linear regression y = α ＋ βx ＋ ε where random error, ε, was assumed to follow normality, independence and equal variance. Model evaluation aims at testing residual error d = y -x（y measured data, x simulated data）,but not estimating regression coefficients, α, β, RMSE, E, EF and d are all good “difference measures”, they do not need follow three assumptions, and they have clear physical meaning. Large sample size increase reliability of statistics. Graphical evaluation is a necessary method for model evaluation. Time series and residual error graphs are two basic graphical methods for model evaluation if there are measured data. Simulation graphs can also be used to display relationships among outputs or against time, to analyze residual errors or mistakes even if no measured data. EasyGrapher program is a useful tool for statistical and graphical evaluations of DSSAT model’s output.关键词
DSSAT模型/EasyGrapher/软件/统计校验/图形校验Key words
DSSAT model EasyGrapher program statistical evaluation graphical evaluation分类
农业科技引用本文复制引用
杨靖民,杨靖一,Hoogenboom Gerrit..DSSAT作物模型的统计和图形校验方法[J].植物营养与肥料学报,2012,18(5):1064-1072,9.基金项目
基金项目：吉林省科技厅项目（20040548-2,20100581）资助.致谢：真诚感谢DSSATv4.5模型所提供的田间试验和测量数据.EasyGrapher软件研究和开发得到加拿大农业与食品科学部的研究资金支持. （）
