| 苎麻种质资源农艺性状主成分及聚类分析 |
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| 引用本文： | 李林林,黄敏升,崔国贤,白玉超,李雪玲,刘楠楠,崔丹丹,苏小惠,王继龙.苎麻种质资源农艺性状主成分及聚类分析[J].中国农业科技导报,2019,21(3):34-41. |
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| 作者姓名： | 李林林 黄敏升 崔国贤 白玉超 李雪玲 刘楠楠 崔丹丹 苏小惠 王继龙 |
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| 作者单位： | 1.湖南农业大学苎麻研究所, 长沙 410128; 2.中国农业科学院麻类研究所, 长沙 410205; 3.芭田生态工程股份有限公司, 深圳 518000 |
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| 基金项目： | 现代农业产业技术体系项目(CARS-16-E11)资助。 |
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| 摘 要： | 为了揭示我国丰富的苎麻种质资源,充分发掘利用其有益基因,利用主成分分析和聚类分析方法对收集的94份苎麻种质的7个主要农艺性状进行评价分析。利用主成分分析将苎麻的7个性状简化为4个主成分因子,其累积贡献率高达90.35%;其中第一主成分以株高、茎粗、有效株率的影响为主;第二主成分各个性状系数均为正,可以看作是苎麻种质农艺性状的综合反映;第三主成分以分株数、总株数的影响为主;第四主成分以有效株率的影响为主。采用系统聚类分析,将94份苎麻种质材料在阈值为3.79时聚为三个大类,可划分为高株细茎型、矮株粗茎型和1个特殊型。上述结果将苎麻种质资源农艺性状简化为4个主成分因子,并将94个苎麻品种分为3种类型,为苎麻优质品种选育和多功能应用提供参考依据。
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| 关 键 词： | 苎麻 农艺性状 主成分分析 聚类分析 |
Principal Component and Cluster Analysis of the Main Agronomic Characters of Ramie Germplasm |
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| LI Linlin,HUANG Minsheng,CUI Guoxian,BAI Yuchao,LI Xueling,LIU Nannan,CUI Dandan,SU Xiaohui,WANG Jilong.Principal Component and Cluster Analysis of the Main Agronomic Characters of Ramie Germplasm[J].Journal of Agricultural Science and Technology,2019,21(3):34-41. |
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| Authors: | LI Linlin HUANG Minsheng CUI Guoxian BAI Yuchao LI Xueling LIU Nannan CUI Dandan SU Xiaohui WANG Jilong |
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| Institution: | 1.Ramie Research Institute of Hunan Agricultural University, Changsha 410128; 2.Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha 410205; 3.Batian Ecological Engineering Co. Ltd., Shenzhen 518000, China |
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| Abstract: | The 7 agronomic characters of 94 ramie germplasm from China were investigated through principal component analysis and cluster analysis in order to identify the diversity of ramie germplasm and find the benefit genes. The results of principal components analysis showed that the 7 traits were simplified into 4 principal components (over 90.35% accumulated contribution). The first principal component was given priority to plant height, stem diameter, effective strain rate. The coefficients of the second principal component were all positive, which could be regarded as the comprehensive reflection of the agronomic characters of ramie germplasm. The third principal component was given priority to single stump points number and total number. The fourth principal component was given priority to the influence of the effective strain rate. Using system clustering analysis, 94 ramie varieties were clustered into three categories at the genetic distance 3.79, including high plant and thin stem, short plant and thick stem, and a special type. In this study, the agronomic traits of ramie germplasm resources were simplified into 4 principal component factors, and 94 ramie varieties were divided into three categories, which provided a reference for the breeding of high quality ramie varieties and their multi-functional application. |
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| Keywords: | ramie agronomic character principal component analysis clustering analysis |
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