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在地统计学和地理信息系统支持下,采用多种插值方法对玉米品种多环境测试数据进行空间插值研究。多环境测试数据为东华北、黄淮海试验点的多年平均值,利用几种空间插值方法对数据各个表型性状进行插值分析,比较各个插值方法的均方根预测误差,选取精度最高的插值方法,得出各个表型性状的空间分布情况。结果表明,平均单产适合普通克里格插值方法,百粒重、穗行数、穗位高、穗长、株高、倒伏率、倒折率、纹枯病、玉米螟适合使用反距离加权插值法,单穗粒重、秃尖长适合使用简单克里格插值法,空秆率适合使用径向基函数插值法。
With the support of geostatistics and geographic information system, a variety of interpolation methods were used to study the spatial interpolation of maize variety multi-environment test data. The multi-environment test data is the multi-year average of the test points in East China and Huang-Huai-Hai region. Several spatial interpolation methods were used to analyze the data of each phenotypic trait. The root mean square prediction error of each interpolation method was compared. The interpolation method with the highest accuracy , Get the spatial distribution of each phenotypic trait. The results showed that the average yield was suitable for ordinary kriging interpolation method. The results showed that the average kernel yield per 100 kernel weight, panicle number, ear height, ear length, plant height, lodging rate, refolding rate, sheath blight and corn borer were suitable for using inverse distance weighted interpolation Method, grain weight per spike, bald long suitable for using simple Kriging interpolation method, empty stalk rate suitable for use of radial basis function interpolation.