春小麦品种农艺性状的主成分分析与聚类分析

为给春小麦育种中品种资源的合理利用提供依据,选取国内外43个春小麦品种为试验材料,根据株高、主茎穗长、主茎穗小穗数、单株有效穗数、主茎穗粒数、抽穗期、散粉期、成熟期、单株粒数、单株粒重和千粒重11个农艺性状进行主成分及聚类分析。结果表明,通过主成分分析将11个农艺性状简化为彼此互不相关的5个主成分,即籽粒产量因子、成熟因子、有效穗数因子、穗长因子和千粒重因子,提供的信息量占全部信息量的90.05%。利用这5个主成分因子进行系统聚类,将43个春小麦品种划分为7大类群,其中第4类群的品种综合产量性状好。分类结果与品种系谱基本一致。

Principal Component and Cluster Analysis of Different Spring Wheat Cultivars Based on Agronomic Traits

In order to use genetic resources effectively in wheat breeding and reduce blindness in making cross combination, this study was to test the agronomic performance of 43 spring wheat cultivars. Principal component and cluster analysis were conducted based on the agronomic traits such as plant height, spike length, number of spikelets per spike, number of fertile spike, kernel number per spike, heading date, flowering date, maturation date, kernel number per plant, kernel weight per plant, and thousand kernel weight. The results showed that the 11 agronomic traits were composed of 5 independent principal components, which included grain yield factor, maturation factor, fertile spike number, spike length, and thousand kernel weights. The cumulative contribution of the 5 factors was 90.05%. Through cluster analysis based on the five principal components, the spring wheat cultivars in the present study were divided into 7 groups.and the yield traits of group 4 were the best. The cluster analysis result was generally agreed with the pedigree of these cultivars.