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期 刊 ：植物遗传资源学报 2014年 15卷 6期

关键词：丝瓜；性状；主成分分析；聚类分析；

Keywords:Luffa, characteristics, principal component analysis, cluster analysis,

摘 要 ：为进行丝瓜品种选育，以32个不同丝瓜种质资源为研究材料，调查结瓜习性、叶缘、瓜棱、雌花节率等共22个性状，对得到的性状数据采用DPS软件进行主成分分析和系统聚类分析。结果表明：22个性状可综合为5个主成分，其累积贡献率达81.308%，根据前5个主成分与性状的相关性，选出14个影响力较大的性状。在主成分分析的基础上，对32个丝瓜种质资源进行了系统聚类分析，在欧氏距离的水平上首先将其划分成2大类，又可进一步划分为6个亚类。

Abstract:In order to breed the Luffa varieties, with 32 different luffa germplasm resources as research materials, 22 characteristics including bearing fruit habit, leaf margin, fruit ribbing, percentage of nodes with female flowers to total nodes and obtained various data of characteristics were performed using the principal component analysis and the cluster analysis method by the DPS software. The results showed that the 22 characteristics coule be integrated into 5 principal components and the cumulative contribution rate reached 81.308%. According to the correlation between the former 5 principal components and characters, 14 influential characteristics were selected. Based on the principal components, the 32 luffa germplasm resources could be divided into 2 groups by the Euclidean distance on the first level and further divided into 6 subgroups using cluster analysis method.

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