398份裸大麦种质资源表型性状遗传多样性分析
作者:
作者单位:

江苏沿江地区农业科学研究所/南通市循环农业重点实验室,南通 226001

作者简介:

研究方向为大麦遗传育种,E-mail : 1185077523@qq.com

通讯作者:

魏亚凤,研究方向为大麦遗传育种,E-mail: w-yafeng@163.com

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基金项目:

南通市科技项目(JC2021152);江苏省“六大人才高峰”高层次人才项目(NY-200);南通市科技项目(MS22020035);江苏沿江地区农业科学研究所青年科技基金 [YJ (2021) 001]资助


Phenotypic Diversity Analysis of 398 Naked Barley Germplasm Resources
Author:
Affiliation:

Jiangsu Yanjiang Area Institute of Agricultural Sciences/Key Laboratory of Recycling Agriculture of Nantong City, Nantong 226001

Fund Project:

The Scientific and Technological Project of Nantong City (JC2021152);Six Talent Peaks Project in Jiangsu Province (NY-200);The Scientific and Technological Project of Nantong City (MS22020035);Youth Science and Technology Fund of Jiangsu Yanjiang Area Institute of Agricultural Sciences [YJ(2021)001]

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    摘要:

    为了提高我国裸大麦种质资源的利用效率,通过变异系数、多样性指数、相关性分析、主成分分析和聚类分析,分析了398份国内外裸大麦种质资源表型性状的多样性水平。结果显示:18个表型性状在不同裸大麦资源间存在丰富的变异,18个表型性状的多样性指数为0.66~2.06,平均为1.42,以芒型的多样性指数最小,株高与每穗粒数的多样性指数最大;变异系数在4.71%~61.03%之间,平均为26.59%,其中籽粒颜色的变异系数最高,抽穗期的离散程度最低。相关性分析表明,单株穗数、穗长、每穗粒数、千粒重和结实率可作为今后选育高产裸大麦品种的指导目标性状。主成分分析结果显示,5个主成分子的累计贡献率达 64.297%,其中抽穗期、株高、棱型和千粒重等性状是裸大麦表型变异的主要因素。结合隶属函数值计算综合得分(F值)获得排名前10的品种:江苏元麦33号、Ⅶ-131、玉米麦、江苏元麦58号、建湖团六棱子、戴帽元麦、江苏元麦65号、江苏元麦23号、江苏元麦20号和江苏元麦22号。系统聚类将裸大麦资源分为4类,聚类结果与地理位置相关性不显著。相关结果为不同地域裸大麦种质资源的利用及品种选育提供重要参考。

    Abstract:

    In order to improve the utilization efficiency of naked barley germplasm resources in China, 398 accessions of naked barley from different regions were used to analyze the phenotypic diversity at 18 traits, followed by the analysis of coefficient of variation analysis, diversity index analysis, correlation analysis, principal component analysis and cluster analysis. The results revealed abundant variations among phenotypic traits in different resources. The diversity index of the nine quality traits was 0.66 to 2.06, with an average value of 1.42, and the highest value in plant height, kernels per spike and the smallest value in kernel rows. The traits had 4.71% (kernel color) to 61.03% (heading date) of the coefficient of variation, with an average value of 26.59%. The correlation analysis of nine quantitative traits indicated that spikes per plant, spike length, kernels per spike, thousand kernels weight and setting rate could be deployed as the main target traits for high yield naked barley varieties breeding in the future. The results of principal component analysis showed that the cumulative contribution rate of the five principal component factors was 64.297%. Among them, heading date, plant height, row type and thousand kernels weight were the main factors contributing to the phenotypic differences of naked barley. Combined with the membership function analysis, the comprehensive scores (F value) were calculated. Jiangsuyuanmai No. 33, VII-131, Yumimai, Jiangsu yuan mai No. 58, Jianhutuanliulengzi, Daimaoyuanmai, Jiangsuyuanmai No. 65, Jiangsuyuanmai No. 23, Jiangsuyuanmai No. 20 and Jiangsuyuanmai No. 22 had the highest scores. These materials were divided into four groups by systematic clustering analysis and the clustering results were not strongly correlated with geographic location. These results could provide an important reference for the utilization of naked barley accessions and variety breeding.

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李赢,刘海翠,石晓旭,等.398份裸大麦种质资源表型性状遗传多样性分析[J].植物遗传资源学报,2023,24(5):1311-1320.

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  • 收稿日期:2023-03-01
  • 最后修改日期:2023-03-17
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  • 在线发布日期: 2023-08-30
  • 出版日期: 2023-08-30
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