647份海岛棉优异种质资源遗传多样性分析
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1.新疆巴音郭楞蒙古自治州农业科学研究院/国家农业农村部新疆早中熟及早熟陆地棉、长绒棉观测实验站;2.新疆农业大学

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基金项目:

新疆维吾尔自治区创新环境(人才、基地)建设专项(PT2011)


Genetic Diversity Analysis of 647 Sea Island Cotton Germplasm Resources
Author:
Affiliation:

1.Academy of Agricultural Sciences in Xinjiang Bayingoleng Mongolia Autonomous Prefecture/Xinjiang Early-middle-maturing and Early-maturing Upland Cotton and Long-staple Cotton Observation Experimental Station Ministry of Agriculture and Rural Area of China, Korla;2.Xinjiang Agricultural University

Fund Project:

The innovation environment ( talent, base ) construction project of Xinjiang(PT2011)

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    摘要:

    通过对647份海岛棉种质资源进行变异系数分析、遗传多样性分析、相关性分析、主成分分析和聚类分析,以期为今后海岛棉亲本选配和品种选育筛选出类型更加多样的海岛棉种质资源材料。结果表明,647份海岛棉种质资源数量性指标变异范围在2.46%~36.43%之间,表明海岛棉种质资源间差异大,种质资源类型丰富;描述性指标遗传多样性分析表明,海岛棉种质资源茎毛多少、叶片颜色、叶茸毛多少、花瓣基斑大小、主茎硬度、果枝类型、花柱长度,种质资源外在描述性类型较为多样,可直接用于开展品种植株形态的改良使用;数量性指标遗传多样性分析表明,反映纤维品质的指标较反映产量的指标多样性更为丰富,种质资源材料可用于纤维品质、熟性的改良使用。相关性分析表明,不同数量性状间呈现出显著的相关性,相互制约、相互作用、相互影响,在材料创制时应当相互考量,综合分析。主成分分析表明,前5个特征值的累计贡献率达到了75.76%,第1主成分与纤维品质有关,第2主成分与籽棉产量有关,第3主成分与伸长率有关,第4主成分与熟性有关,第5主成分与衣分有关;聚类分析在遗传距离为10时,将种质资源划分为6个类群,第II类群综合表现较好,在实际育种中可根据育种目标进行针对性选择和改良。

    Abstract:

    The variation coefficient analysis, genetic diversity analysis, correlation analysis, principal component analysis and cluster analysis of 647 island cotton germplasm resources were carried out in order to screen more diverse types of island cotton germplasm resources for parent selection and variety breeding in the future. The variation range of quantitative indexes of 647 sea island cotton germplasm resources was 2.46%~36.43%, indicating the rich diversity among sea island cotton germplasm resources. The number of stem hairs, leaf color, leaf hairs, petal basal spot size, main stem hardness, fruit branch type and style length of island cotton germplasm resources were variable, and these external descriptive traits could be directly used for the improvement of plant morphology. Genetic diversity analysis of quantitative indicators showed that the diversity of indicators reflecting fiber quality was more abundant than that reflecting yield, and germplasm resources could be used for improving fiber quality and maturity. Correlation analysis revealed a significant correlation between different quantitative traits. The complicated interaction mode implied a comprehensive evaluation by integrating multiple datasets in germplasm innovation. The principal component analysis showed that the cumulative contribution rate of the first five eigenvalues reached 75.76%. The first principal component was related to fiber quality, the second principal component was related to seed cotton yield, the third principal component was related to elongation, the fourth principal component was related to maturity, and the fifth principal component was related to lint percentage. When the genetic distance was 10, the germplasm resources were divided into 6 groups by cluster analysis. The comprehensive performance of cluster II was better. In actual breeding, targeted selection and improvement can be carried out according to breeding objectives.

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  • 收稿日期:2022-08-15
  • 最后修改日期:2022-08-31
  • 录用日期:2022-09-19
  • 在线发布日期: 2022-09-23
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