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中国农学通报 ›› 2023, Vol. 39 ›› Issue (10): 45-55.doi: 10.11924/j.issn.1000-6850.casb2022-0327

所属专题: 园艺

• 林学·园艺·园林 • 上一篇    下一篇

‘蜂糖李’栽培群体果实性状遗传多样性及数量分类分析

董华1,2(), 陈红1,2()   

  1. 1 贵州大学农学院,贵阳 550025
    2 贵州省果树工程技术研究中心,贵阳 550025
  • 收稿日期:2022-04-27 修回日期:2022-09-09 出版日期:2023-04-05 发布日期:2023-03-27
  • 通讯作者: 陈红,男,1975年出生,重庆潼南人,副教授,博士,主要从事生物技术与果树遗传育种研究。通信地址:550025 贵州省贵阳市花溪区贵州大学西校区崇学楼,E-mail:chenhong96@aliyum.com。
  • 作者简介:

    董华,男,1997年出生,贵州铜仁人,硕士研究生,研究方向为贵州李种质资源的鉴定及保存。通信地址:550025 贵州省贵阳市花溪区贵州大学西校区崇学楼,E-mail:

  • 基金资助:
    贵州省科技计划项目“贵州蜂糖李优质高产关键技术集成与示范”(黔科合支撑[2022]重点018号)

Study on Genetic Diversity and Quantitative Classification of Fruit Traits in Cultivated Population of Prunus salicina ‘Fengtang’

DONG Hua1,2(), CHEN Hong1,2()   

  1. 1 College of Agriculture, Guizhou University, Guiyang 550025
    2 Guizhou Fruit Tree Engineering Technology Research Center, Guiyang 550025
  • Received:2022-04-27 Revised:2022-09-09 Online:2023-04-05 Published:2023-03-27

摘要:

为深入了解‘蜂糖李’栽培群体的遗传多样性,对‘蜂糖李’栽培群体中的74个李单株的26个果实性状(12个数量性状和14个描述型性状)开展数量分类研究,并与‘蜂糖李’果实性状进行比较,旨在为贵州地方李资源科学保护和合理开发利用提供参考。根据《李种质资源描述规范和数据标准》,采用性状分布频率、变异系数、Shannon-Wiener信息指数、Simpson遗传多样性指数、表观聚类、主成分分析和显著性差异分析等方法进行分析研究。结果表明:(1)26个果实性状的Shannon-Wiener多样性指数和Simpson遗传多样性指数的范围分别为0.3425~2.1838和0.1928~0.8775;14个描述型性状中,果核形状无变异类型,其余描述型性状平均变异类型2.9个;12个数量性状的变异系数为0.50%~31.92%,其中Vc变异系数最大,其次为单果重。(2)Q型聚类分析结果显示,在欧式距离为16.65时,可将74份材料分为A、B、C、D 4个组群,各组群材料数依次为16、12、28、18份。其中A组群、B组群、C组群与‘蜂糖李’亲缘关系较近,D组群与‘蜂糖李’的亲缘关系较远,且D组群与‘蜂糖李’的果实数量性状大多存在显著差异。(3)R型聚类分析结果显示,在相关系数为2.08处,可将26个果实性状分为2个大组,第一大组为A组,在相关系数为1.35处,又可将第二大组分为B组、C组和D组,结合数量性状相关性分析,发现多数性状间表现为两两相关,部分性状间逻辑相关性明显。(4)主成分分析发现,特征值大于1.0的主成分共9个,累计贡献率达到70.79%,其中各性状的贡献率较为分散,表明疑似‘蜂糖李’种质的分类受到多个性状共同影响。综上可得,‘蜂糖李’栽培群体的74个单株的果实性状多样性丰富,描述型性状变异类型较多,数量性状变异较为明显,遗传多样性丰富。26个果实表观性状有较强相关性,采用果实性状对供试材料进行数量分类研究,方法合理。且得到18份与‘蜂糖李’亲缘关系较远的种质资源,可作为重要资源材料加以保护和利用。

关键词: ‘蜂糖李’, 栽培群体, 遗传多样性, 果实性状, 聚类分析, 主成分分析

Abstract:

To gain an in-depth understanding of the genetic diversity of the Prunus salicina ‘Fengtang’ cultivated population, a quantitative classification study was conducted on 26 fruit traits of 74 single plants in the P. salicina cultivated population (12 quantitative and 14 descriptive traits). The fruit traits were compared with those of P. salicina ‘Fengtang’ to provide reference for scientific conservation and rational exploitation of local plum resources in Guizhou. The trait distribution frequencies, coefficients of variation, Shannon-Wiener information index, Simpson genetic diversity index, epistatic clustering, principal component analysis and significant difference analysis were used to analyze and study the traits according to the Specifications and Data Standards for the Description of Plum Germplasm Resources. The results are as follows. (1) The ranges of Shannon-Wiener diversity index and Simpson genetic diversity index for the 26 fruit traits were 0.3425-2.1838 and 0.1928-0.8775, respectively. Among the 14 descriptive traits, no variation type was found for kernel shape, while 2.9 average variation types occurred for the remaining descriptive traits. The coefficients of variation for 12 quantitative traits ranged from 0.50% to 31.92%. Among them, the coefficient of variation of Vc was the largest, followed by single fruit weight. (2) The results of the Q-cluster analysis showed that at the Euclidean distance of 16.65, the 74 materials could be divided into four clusters, A, B, C and D. The number of materials in each cluster was 16, 12, 28 and 18 in order. Among them, group A, group B and group C were more closely related to P. salicina ‘Fengtang’. Group D was more distantly related to P. salicina ‘Fengtang’, and most of the fruit quantitative traits of group D and P. salicina ‘Fengtang’ were significantly different. (3) The results of R-type cluster analysis showed that at the correlation coefficient of 2.08, the 26 fruit traits could be divided into two major groups, and the first major group was group A. At the correlation coefficient of 1.35, the second major group could be divided into group B, group C and group D. Combined with the correlation analysis of quantitative traits, it was found that most of the traits showed pairwise correlations with each other, and some of the traits showed obviously logical correlations with each other. (4) Principal component analysis revealed that there were nine principal components with eigenvalues greater than 1.0. Their cumulative contribution rate reached 70.79%, among which the contribution rate of each trait was more dispersed. This indicated that the classification of the probable P. salicina ‘Fengtang’ germplasm was influenced by several traits together. In conclusion, it can be concluded that the 74 individual plants of the P. salicina ‘Fengtang’ cultivated population were rich in fruit trait diversity, with more types of descriptive trait variation, more obvious quantitative trait variation, and rich genetic diversity. There were strong correlations in 26 fruit phenotypic traits, and it was a reasonable method to use fruit traits for quantitative classification study of the test material. The study yielded 18 germplasm resources that are distantly related to P. salicina ‘Fengtang’, which can be conserved and utilized as important resource materials.

Key words: Prunus salicina ‘Fengtang’, cultivated population, genetic diversity, fruit trait, cluster analysis, principal component analysis