摘要
估算了我国和东南亚等地区100份黄麻品种11个产量和纤维品质性状的主成分,以主成分欧氏距离为基础作系统聚类分析;以第一和第二主成分向量作二维排序分类,结果表明: 1.前3个主成分分别为生产力因子(80.3％)、纤维强力因子(8.2％)、纤维支数因子(6.2％),其累计贡献率达94.74％。根据品种主成分表现,评选出681、梅峰4号、7110等8个综合性状优良的品种。 2.在D^2=3.75水平上,100份品种系统聚类可分为2个大类群和5个相互距离较远的单一品种自成体系的类,结果与自然类型分组相近。 3.二维排序分类与系统聚类结果基本一致,具有直观、简便等优点。 本文还对主成分分析、系统聚类分析、二维排序分析进行了讨论和比较,认为在种质资源分类时,应包括较多的性状和足够大的样本容量,才能有较好的稳定性、可靠性。
Principal components (PC) of eleven yield and quality characters were estimated for 100 jute varieties from Southeast Asia and China. Hierarchical cluster was carried out based on the first three PC vectors. Furthermore, the varieties were classified according to the scatter plot of the first two PC vectors. The results reveal that the first three PCs, which might be regarded as yield component factor (80. 3%), fiber strength factor (8. 2%) and fiber fineness factor (6. 2%), account for 94. 7% variation among the varieties. Based on the coefficients of the first three PCs, eight elite varieties were identified. At the level of D2 = 3. 75, all varieties were clustered into two major groups and five single-variety groups. The result is similar to that of traditional classification. The classification by scatter plot of the first two PCvectors is a more direct and simpler method, which is also effective. The influence of sample size and the number of observed characters on the quantitative classification was discussed.
出处
《作物学报》
CAS
CSCD
北大核心
1996年第5期587-594,共8页
Acta Agronomica Sinica
基金
"八五"国家科技攻关项目85-01-03-02专题"麻类作物种质资源繁种鉴定和优异种质利用评价"研究的一部分
关键词
黄麻
种质资源
主成分
数量分类
Jute
Germplasm resource
Principal component
Quantitative classification
