草地学报 ›› 2026, Vol. 34 ›› Issue (3): 840-852.DOI: 10.11733/j.issn.1007-0435.2026.03.010

• 研究论文 • 上一篇    

465份燕麦种质资源表型遗传多样性分析及优异资源筛选

卫纪1, 高杨淼1, 汪辉1,2, 陈有军1,2, 周青平1,2, 王沛1,2, 雷映霞1,2   

  1. 1. 西南民族大学, 草地资源学院, 四川 成都 610041;
    2. 西南民族大学, 四川若尔盖高寒湿地生态系统国家野外科学观测研究站, 四川 成都 610041
  • 收稿日期:2025-08-18 修回日期:2025-10-11 发布日期:2026-03-23
  • 通讯作者: 雷映霞,E-mail:leiyingxia@hotmail.com;王沛,E-mail:wangpei@swun.edu.cn
  • 作者简介:卫纪(1999-),男,汉族,四川泸定人,硕士研究生,主要从事牧草育种研究,E-mail:weiwin996@163.com;
  • 基金资助:
    农业科技重大项目(NK20220402);四川省科技计划面上项目(2024NSFSC0310);中央高校项目(ZYN2025029);西藏自治区科技计划项目(XZ202501ZY0086)资助

Phenotype Genetic Diversity Analysis and Screening for Elite Germplasm Resources in 465 Oat Accessions

WEI Ji1, GAO Yang-miao1, WANG Hui1,2, CHEN You-jun1,2, ZHOU Qing-ping1,2, WANG Pei1,2, LEI Ying-xia1,2   

  1. 1. College of Grassland Resources, Southwest Minzu University, Chengdu, Sichuan Province 610041, China;
    2. Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, Sichuan Province 610041, China
  • Received:2025-08-18 Revised:2025-10-11 Published:2026-03-23

摘要: 为分析燕麦(Avena sativa L.)表型遗传多样性特征,筛选具有优良性状的种质,本研究对来自26个国家的465份燕麦资源的24个表型性状进行综合分析。结果表明,13个数量性状的变异系数为13.19%~46.70%,11个质量性状的遗传多样性指数为0.12~1.00。相关性分析显示,植株的生长性状(如株高、茎粗)与产量及穗部部分性状之间存在极显著正相关关系(P<0.01),而抗倒伏性与千粒重呈显著负相关关系(P<0.05)。聚类分析将供试材料分为6个类群:类群Ⅰ为高生物量皮燕麦,适于饲草育种;类群Ⅱ兼具高产与抗倒伏性;类群Ⅲ为裸燕麦,适宜粮用;类群Ⅳ~Ⅵ具有特殊性状,可作为特色基因库。基于主成分分析(累计贡献率65.05%)和综合得分(F值),筛选出5份高产抗倒伏的优良种质(174,Y586,Y1062,Y341,150),这些材料可作为优良亲本或基础研究材料。

关键词: 燕麦, 表型性状, 遗传多样性, 主成分分析, 聚类分析

Abstract: To analyze the genetic diversity characteristics of the phenotypic traits and identify germplasm with superior traits in oats (Avena sativa L.), this study conducted a comprehensive evaluation of 24 phenotypic traits in 465 oat accessions collected from 26 countries. The results showed that the coefficient of variation for 13 quantitative traits ranged from 13.19% to 46.70%, while the genetic diversity index for 11 qualitative traits varied between 0.12 and 1.00. Correlation analysis revealed significant positive correlations (P<0.01) between plant growth traits (e.g., plant height, stem diameter) and yield-related or panicle traits, whereas a significant negative correlation (P<0.05) was observed between lodging resistance and thousand-kernel weight. Cluster analysis classified the accessions into six distinct groups: Group I, high-biomass hulled oats suitable for forage breeding; Group II, accessions combining high yield and lodging resistance; Group III, naked oats ideal for grain use; Groups IV-VI, accessions with distinctive characteristics, which can serve as a specialized gene bank. Based on principal component analysis (cumulative contribution rate of 65.05%) and comprehensive evaluation scores (F value), five elite accessions (174, Y586, Y1062, Y341, 150) with high yield and lodging resistance were identified, demonstrating potential as excellent parental lines or fundamental research materials.

Key words: Oat(Avena sativa L.), Phenotypic traits, Genetic diversity, Principal component analysis, Cluster analysis

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