论文部分内容阅读
本文介绍了典型相关分析的基本原理及分析方法,并以一组小麦的试验结果为例介绍了典型相关分析方法在遗传育种中的应用。把小麦的籽粒产量看作是有相互关系的三组性状(即产量因素、产量生理性状及形态性状)综合作用的结果,利用典型相关分析研究了这三组性状的相关。结果表明:这三组性状两两之间都存在显著的相关;产量因素与产量生理性状的相关主要是由收获指数与穗粒数、饱满度指数与千柱重的相关所引起的。其前两个典型相关系数包含了总相关信息的75%;产量因素与形态性状的相关主要是分蘖整齐度与穗粒重的相关引起的,前两个典型相关系数占总相关信息的84%;产量生理性状与形态性状的相关主要是由饱满度指数与分蘖整齐度的相关引起的,前两个典型相关系数占总相关信息的71%。
This paper introduces the basic principles and analysis methods of canonical correlation analysis, and introduces the application of canonical correlation analysis in genetics and breeding based on the test results of a group of wheat. Taking the grain yield of wheat as the result of the combined effect of three groups of traits (yield factors, yield physiological traits and morphological traits), the correlations of these three traits were studied by canonical correlation analysis. The results showed that there was a significant correlation between these two traits. The correlation between yield factors and yield physiological traits was mainly caused by the correlation between harvest index and grains per spike, plumpness index and 1000-pound weight. The first two typical correlation coefficients included 75% of the total related information. The correlation between yield factors and morphological traits was mainly due to the correlation between tillering uniformity and ear kernel weight. The first two typical correlation coefficients accounted for 84% The correlation between yield physiological traits and morphological traits was mainly caused by the correlation between plumpness index and tiller uniformity. The first two typical correlation coefficients accounted for 71% of the total related information.