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中国农学通报 ›› 2022, Vol. 38 ›› Issue (30): 56-64.doi: 10.11924/j.issn.1000-6850.casb2022-0073

所属专题: 生物技术 资源与环境 园艺

• 林学·园艺·园林 • 上一篇    下一篇

香蕉种质资源叶片表型性状多样性分析

赵丽娟(), 只佳增, 张建春, 杜浩, 周劲松, 刘学敏(), 张荣琴   

  1. 云南省红河热带农业科学研究所,云南河口 661300
  • 收稿日期:2022-02-11 修回日期:2022-04-02 出版日期:2022-10-25 发布日期:2022-10-27
  • 通讯作者: 刘学敏
  • 作者简介:赵丽娟,女,1998年出生,研究实习员,研究方向:香蕉种质资源研究与利用。通信地址:661300 云南省红河热带农业科学研究所,Tel:18806959089,E-mail: 3147992469@qq.com
  • 基金资助:
    云南省省属转制科研院所技术开发研究专项项目“抗枯萎病香蕉品种适应性筛选及综防措施研究”(202004AR040006);云南省技术创新人才培养对象项目(202005AD160004)

Diversity Analysis of Leaf Phenotypic Characters of Musa spp. Germplasms

ZHAO Lijuan(), ZHI Jiazeng, ZHANG Jianchun, DU Hao, ZHOU Jinsong, LIU Xuemin(), ZHANG Rongqin   

  1. Honghe Research Institute of Tropical Agriculture, Hekou, Yunnan 661300
  • Received:2022-02-11 Revised:2022-04-02 Online:2022-10-25 Published:2022-10-27
  • Contact: LIU Xuemin

摘要:

为了解香蕉种质资源叶片表型性状的多样性,提高云南香蕉优异种质的保护和利用。对49份香蕉种质的18个叶片表型性状进行观测和描述,并对数据进行变异分析、Shannon-weaver多样性指数分析、相关性分析、主成分分析和聚类分析。香蕉种质叶片表型数量性状的遗传多样性指数高于质量性状;数量性状变异程度高,香蕉种质间差异明显。相关性分析发现31对性状相关性达到极显著水平(P<0.01),18对性状相关性达到显著水平(P<0.05),叶片表型性状间互相影响,关系密切。进一步进行主成分分析,将18个叶片表型性状简化为6个主成分,前6个主成分累计贡献率为78.80%,反映了香蕉种质叶片表型性状的大部分信息。对49份香蕉种质进行聚类分析,在欧式遗传距离为10时香蕉种质分为4个类群,分别为丛生野生蕉、大蕉和粉蕉、野生蕉、香芽蕉,同时发现叶姿、叶柄基部边缘形状、叶柄基部斑块颜色、叶柄槽形状是区分不同类群的主要性状。香蕉种质资源叶片表型多样性丰富,分析筛选得到的11个性状为香蕉种质资源叶片表型性状多样性分析的关键指标。

关键词: 香蕉, 叶片表型性状, 相关性分析, 主成分分析, 聚类分析

Abstract:

In order to understand the diversity of leaf phenotypic characters of Musa spp. (banana) germplasm resources and improve the protection and utilization of excellent banana germplasms in Yunnan, 18 leaf phenotypic characters of 49 Musa spp. germplasms were observed and described, and the data were analyzed by variation analysis, Shannon-weaver diversity index analysis, correlation analysis, principal component analysis and cluster analysis. The genetic diversity index of leaf phenotypic quantitative characters was higher than that of qualitative characters. The variation degree of quantitative characters was high, and the differences among Musa spp. germplasms were obvious. The correlation analysis showed that 31 pairs of characters had extremely significant correlation (P<0.01), and 18 pairs had significant correlation (P<0.05). The leaf phenotypic characters were closely related to each other. The principal component analysis showed that the 18 characters were transformed into 6 principal components, and the cumulative contribution rate was 78.80%, which reflected most information of leaf phenotypic characters of banana germplasms. Cluster analysis was conducted on the 49 banana germplasms. The germplasms were divided into four groups at the European genetic distance of 10, which were M. acuminate, M. paradisiaca and M. sapientum, wild Musa, and M. cauendisihii. The leaf orientation, shape of leaf base edge, color of petiole base plaques and petiole groove shape were the main characters to distinguish different groups. The leaf phenotypic diversity of Musa spp. germplasm resources is rich, and the 11 characters obtained by analysis and screening are the key indexes for the analysis of leaf phenotypic diversity of Musa spp. germplasm resources.

Key words: Musa spp., leaf phenotypic characters, correlation analysis, principal component analysis, cluster analysis

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