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贵州地方向日葵种质资源表型性状多样性分析
引用本文:奉斌,李慧琳,杨胜先,林涛,魏忠芬.贵州地方向日葵种质资源表型性状多样性分析[J].中国农业科技导报,2018,20(7):34-41.
作者姓名:奉斌  李慧琳  杨胜先  林涛  魏忠芬
作者单位:贵州省油料研究所, 贵阳 550006
基金项目:国家自然科学基金项目(31760398);贵州省科技支撑计划项目(黔科合支撑[2016]2604号和[2017]2501号);贵州省科技合作计划项目(黔科合LH字[2015]7078号);贵州省农业科学院自主创新专项([2014]013号);贵州省科研机构服务企业行动计划项目(黔科合服企[2014]4004号)资助。
摘    要:为研究贵州地方向日葵的遗传多样性,对不同生态区域的65份向日葵种质资源的25个主要农艺性状如株高、叶形、叶色等进行遗传多态性、主成分及聚类分析。结果发现,17个主要农艺质量性状的变异系数平均值为26.71%,遗传多样性指数达0.73;数量性状方面子实长度、百粒重等8个指标的变异系数平均值为20.11%,遗传多样性指数达1.96;主成分分析结果显示茎粗、株高和叶片数在8个测量性状中累计贡献率为80.58%;基于25个表型性状的聚类分析发现,向日葵资源分为两个大类四个亚类,以上结果说明贵州地方向日葵具有十分丰富的多样性。

关 键 词:向日葵  种质资源  主成分分析  聚类分析  
收稿时间:2017-08-28

Analysis of Genetic Diversity of Sunflower Germpasm Resources in Guizhou
FENG Bin,LI Huilin,YANG Shengxian,LIN Tao,WEI Zhongfen.Analysis of Genetic Diversity of Sunflower Germpasm Resources in Guizhou[J].Journal of Agricultural Science and Technology,2018,20(7):34-41.
Authors:FENG Bin  LI Huilin  YANG Shengxian  LIN Tao  WEI Zhongfen
Institution:Guizhou Oil Research Institute, Guiyang 550006, China
Abstract:In order to study sunflower genetic diversity, this paper analyzed polymorphism, principal component and cluster based on plant height, leaf shape, leaf color, etc. 25 major agronomic traits of 65 sunflower germplasm resources from different ecological regions. The results indicated that the mean variation coefficient of 17 main agronomic quality traits was 26.71%, genetic diversity index was 0.73. The average variance coefficients of 8 indexes such as cafa length, hundred-grain weight, etc. were 20.11%, genetic polymorphism index was 1.96. The results of principal component analysis showed that the cumulative contribution rate in 8 tested traits like stem diameter, plant height, and leaf number was 80.58%. Clustering analysis on 25 phenotypic traits showed that sunflower resources could be divided into 2 categories and 4 subgroups. The above results showed that the local sunflower germplasm resources in Guizhou Province had abundant genetic diversity.
Keywords:sunflower  germplasm resources  analysis of principal components  cluster analysis  
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