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化州市化橘红种质资源主成分分析和聚类分析
引用本文:曹征,陈国军,何春玲,曾祥有.化州市化橘红种质资源主成分分析和聚类分析[J].中国农学通报,2021,37(10):77-83.
作者姓名:曹征  陈国军  何春玲  曾祥有
作者单位:茂名市农业科技推广中心,广东茂名 525000
基金项目:茂名市科技计划项目“南药化橘红品种选育与培育”(KJ016)
摘    要:应用主成分分析和聚类分析,从宏观和微观2个层面分析鉴别化橘红种质资源,以期为化橘红种质资源的鉴定、评价、保护、开发和利用提供参考依据。利用SPSS 19.0对化橘红种质资源17项主要植物学数量性状指标和6项理化指标进行变异性和主成分分析,采用MEGA7对SNP结果进行聚类分析。研究发现,不同化橘红种质资源在有效成分、花和叶片性状上变异明显;存在黄酮因子、果形因子等6个主成分因子和柚皮苷、总黄酮、雌蕊粗度等12项影响力较大的指标;种质资源共聚为2类,不同聚类拥有各自性状特征。本研究分析化橘红种质资源的方法和结果,可为进一步系统评价化橘红种质资源提供参考。

关 键 词:化橘红  种质资源  主成分分析  聚类分析  评价  
收稿时间:2020-05-29

Principal Component Analysis and Cluster Analysis of Citri grandis Exocarpium Germplasm Resources in Huazhou
Cao Zheng,Chen Guojun,He Chunling,Zeng Xiangyou.Principal Component Analysis and Cluster Analysis of Citri grandis Exocarpium Germplasm Resources in Huazhou[J].Chinese Agricultural Science Bulletin,2021,37(10):77-83.
Authors:Cao Zheng  Chen Guojun  He Chunling  Zeng Xiangyou
Institution:Maoming Agricultural Science and Technology Extension Center, Maoming Guangdong 525000
Abstract:The purpose is to apply principal component analysis and cluster analysis to analyze and identify Citri grandis exocarpium germplasm resources in macro and micro level, and provide a basis for identifying, evaluating, protecting, developing and utilizing Citri grandis exocarpium germplasm resources. SPSS 19.0 was used to analyze the variability and principal components of 17 major botanical quantitative trait indexes and 6 physical and chemical indexes of Citri grandis exocarpium germplasm resources, MEGA7 was used to conduct the cluster analysis based on the SNP results. It is found that different Citri grandis exocarpium germplasm resources vary significantly in effective components, flower and leaf traits; and there are 6 main component factors including flavonoid factor and fruit shape factor and 12 influential indicators including naringin, total flavonoids and pistil thickness; germplasm resources are clustered into 2 categories and each has its own characteristics.
Keywords:Citri grandis exocarpium  germplasm resources  principal component analysis  cluster analysis  evaluation  
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