浙江农业学报 ›› 2016, Vol. 28 ›› Issue (9): 1508-1513.DOI: 10.3969/j.issn.1004-1524.2016.09.08

• 园艺科学 • 上一篇    下一篇

大蒜品种资源生育和产量性状主成分聚类分析及评价

刘国伟, 任艳云, 高园园, 张龙平*, 刘艳芝, 徐祥文, 高发瑞, 马井玉, 张连秋   

  1. 济宁市农业科学研究院,山东 济宁 272031
  • 收稿日期:2015-11-09 出版日期:2016-09-15 发布日期:2016-11-23
  • 通讯作者: 张龙平,E-mail: zhanglp258@126.com
  • 作者简介:刘国伟(1979—),男,山东济宁人,农艺师,从事作物栽培学与耕作学研究。E-mail: lgw_8303@163.com
  • 基金资助:
    山东省农业重大应用技术创新课题“大蒜无公害安全生产技术体系建立与应用”(2012); 山东省现代农业产业技术体系项目(SDAIT-02-022-10); 济宁市科技发展计划项目“大蒜种质资源引进评价及创新利用研究”(2013)

Cluster analysis and evaluation of agronomic characters in garlic variety resources based on principal components

LIU Guo-wei, REN Yan-yun, GAO Yuan-yuan, ZHANG Long-ping*, LIU Yan-zhi, XU Xiang-wen, GAO Fa-rui, MA Jing-yu, ZHANG Lian-qiu   

  1. Jining Institute of Agricultural Sciences, Jining 272031, China
  • Received:2015-11-09 Online:2016-09-15 Published:2016-11-23

摘要: 根据数值分类学的原理,分别于大蒜生长期和收获后,对来源于我国各地的57份大蒜品种资源的15个性状指标进行调查,并进行了主成分和聚类分析。前4个主成分对总的特征根累计贡献率为85.54%,其中第一主成分贡献率为63.68%,主要生物学信息为蒜头产量构成因子。根据主成分分析,评选出性状优良品种资源9份,分别可作为蒜头和蒜薹品种改良的目标种质。欧式距离聚类图在D=26.00时把57个品种资源划分为4个类群加7个品种,揭示了不同地区品种资源的相对遗传距离和区域生态特点,根据不同类群品种间的亲缘关系和性状特点,结合主成分分析的因子特点,可为大蒜品种改良利用提供科学依据。

关键词: 大蒜, 主成分, 聚类分析, 综合评价

Abstract: Based on the principal of numerical classification, 15 agronomic traits of 57 garlic variety resources were investigated in the growth period and harvest period, and principal component analysis and cluster analysis were carried out in this paper. The first 4 principal accounted for 85.54%of variation among the cultivars. The first principal accounted for 63.68% which might be regarded as garlic bulb yield component factor. The top 9 cultivars were selected based on the principal component which could be garlic bulb and sprout variety improvement. At the level of D=26.00, all variety resources were classified into 4 groups and 7 cultivars. The two classifying ways, which explained the relative genetic distance and regional ecological characteristics, could both provide scientific evidence to the garlic varieties improvement.

Key words: garlic, principal component, cluster analysis, comprehensive evaluation

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