| 摘要: |
| 作物品种生态型的基本特点及其演变规律,对制定作物育种目标、亲本选配、杂种后代选择,以及品种适应性鉴定等一系列基本育种环节,都具有极为重要的指导意义。因此品种生态类型的研究,日益引起育种工作者的关注。本文在前人研究的基础上,给出了生态型基本特征和可变特征的含义,并给出了区分它们的初步的统计方法——单变量分析法和多变量分析法。单变量分析法运用方差分析和多重比较来判断品种性状的区分能力,以确定性状的稳定性,运用 Nair 水平分组法给出各性状的定量的区分类型。多变量分析法运用 R 型因子分析来判断品种生态型的基本特征和可变特征。相关矩阵的第一主成分代表品种生态型的基本特征,第二、第三等主成份代表生态型的可变特征。按主日子进行聚类来区分生态型的亚型。运用 Q 型因子分析判断生态地区的代表品种。多变量分析方法比单变量分析方法获得的信息丰富、集中,且便于分类和解释。 |
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| Research on Statistical and Analytical Method of Ecotypes of wheat varieties and Their Evolution |
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| Abstract: |
| The basic characters and evolution laws of ecotypes of wheat varieties are of great significance in a series of basic breeding key links such as working out the breeding objectives/parent material matching/selection of hybid descendants/identification of accommodation of wheat varieties.As a result,research on ecotypes of wheat varieties has increasingly arrested great attention from the breeders. Based on research by the predecessors,this paper defined the basic characters of ecotypes and variable meanings and presented the primary statistical method of classification-univariant analysis and multivaiate analysis. Univariant analysis is to use the variance analysis and multiple comparison to judge the differential capacity of performances of wheat varieties so as to determine the stability of performances of them.The quantitive differential types of their performances were given by means of Nair level group method. Multivariate analysis is to use R-type factor to judge the basic characters and variable natures of ecotypes of wheat varieties.The first component of correlation matric stands for the basic characters of ecotypes of wheat arieties.The second and third compenents stand for the variable natures of ecotypes.The subecotypes were differentiated in the terms of accumulation of major factors.The representative spieces in the eco-enviroment were analysed and determined by Q-type factors.Information obtained by multivariate analysis is richer,more concentrated and easier to do classification and explanation than that by univariant analysis. |
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