摘要
对39份春大豆种质的7个主要农艺性状进行主成分分析,获得2个主成分因子,其中:第一主成分(MF1)与株高、底荚高度、主茎节数呈正相关;第二主成分(MF2)与单株粒数和单株粒重呈正相关、与百粒重和有效分枝数呈负相关。用SPSS 22.0软件对39份大豆种质分别基于综合主成分值和基于性状数据的聚类分析,前者将参试种质分成3个大类2个亚类,后者将参试种质分成3个大类4个亚类,两种聚类方法的分析结果基本一致。
7 major agronomic traits of 39 soybean germplasm resources were analyzed with the method of principal component analysis(PCA),and two principal component factors were obtained.The first principal component(MF 1)was positively correlated with plant height,bottom pod height and the number of main stem segments.The second principal component(MF 2)was positively correlated with the number of grains per plant and the grain weight per plant,and negatively correlated with the number of 100-grain weight and effective branches.The cluster analysis were studied through the integrated principal component values and the agronomic trait normalization data.39 germplasms were divided into 3 major categories and 2 sub-categories through the former method,and divided into 3 major categories and 4 sub-categories through the latter method.By comparison,the analysis results of the two clustering methods were generally consistent.
作者
林文磊
吕美琴
李明松
康蓉蓉
曾红英
姚文
蔡锦玲
LIN Wen-lei;Lv Mei-qin;LI Ming-song;KANG Rong-rong;ZENG Hong-ying;YAO Wen;CAI Jin-ling(Quanzhou Institute of Agricultural Sciences,Quanzhou,Fujian 362212,China)
出处
《福建农业学报》
CAS
北大核心
2018年第10期1016-1022,共7页
Fujian Journal of Agricultural Sciences
基金
泉州市科技计划项目(2016N003)
关键词
春大豆
主成分分析
聚类分析
spring soybean
principal component analysis
cluster analysis
