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中国农学通报 ›› 2019, Vol. 35 ›› Issue (29): 8-13.doi: 10.11924/j.issn.1000-6850.casb18050078

所属专题: 小麦

• 农学 农业基础科学 • 上一篇    下一篇

35个小麦品种农艺性状的相关及聚类分析

祝 旋1, 钱登坤1, 汤婷1, 谢实龙1, 田莉莉2, 蔡 健1   

  1. 1.阜阳师范学院生物与食品工程学院;2.阜阳第一中学
  • 收稿日期:2018-05-14 修回日期:2018-09-21 接受日期:2018-09-25 出版日期:2019-10-14 发布日期:2019-10-14
  • 通讯作者: 蔡 健
  • 基金资助:
    安徽省高校省级自然科学基金重点项目(KJ2018A0352);2016年度阜阳市政府—阜阳师范学院横向合作科研项目(XDHX2016027);2017年国家级大学生创新创业训练计划项目(201540810104,201540810127);2017年度研究生创新研究计划项目(2017CXJH02)。

Correlation and Cluster Analysis of Agronomic Characters of 35 Wheat Varieties

  • Received:2018-05-14 Revised:2018-09-21 Accepted:2018-09-25 Online:2019-10-14 Published:2019-10-14

摘要: [目的] 通过对35个小麦品种产量、亩基本苗、最高茎蘖、亩有效穗、株高、穗粒数、千粒重7个农艺性状进行调查,为小麦的遗传改良提供理论依据。[方法]实验采用相关分析、多重比较分析、聚类分析,以探讨小麦品种产量影响因子。[结果] 相关分析结果表明:产量与亩有效穗和穗粒数的相关系数分别为0.685,0.439,均达到极显著水平;产量与亩基本苗的相关系数为0.368,达到了极显著水平。多重分析结果表明:产量与亩基本苗、最高茎蘖、亩有效穗、株高、穗粒数、千粒重的相关系数分别为435.2742857,358.8485714,413.7485714,371.8142857,419.8914286,406.7571429,均达到了显著水平。聚类分析结果表明:根据遗传距离为3可将35个小麦品种划分为7个类群,Ⅰ类为‘安农1202’、‘安农1207’、‘乐麦W11160’、‘SC1201’、‘烟农173’、‘太科081’、‘涡麦06040’、‘天润5126’、‘柳麦66’、‘济麦5319’;Ⅱ类为‘中麦155’、‘未来0591’、‘仲麦1号’、‘阜0608’、‘谷神麦9号’、‘益科麦6号’、‘隆安麦968’、‘濉1209’、‘绿雨13号’、‘郑麦110’、‘隆安麦968’;Ⅲ类为‘龙科1221’、‘龙麦109’、‘长河23’;Ⅳ类为‘荃麦504’、‘皖麦998’、‘鉴182’;Ⅴ类为‘安1202’、‘安1240’、‘远丰0735’、‘阜麦9375’、‘远育15’、‘宿11033’;Ⅵ类为‘新民8号’;Ⅶ类为‘济麦6852’。[结论]此次研究结果为亩基本苗、株高、穗粒数这三个性状均是制约产量的最大因素,同时也为高产小麦选育、优质小麦杂交、组培选配提供了理论基础。

关键词: 黄瓜, 黄瓜, 数量性状, 聚类分析, 遗传距离, 杂种优势

Abstract: The aim is to provide a basis for genetic improvement of wheat. 35 wheat varieties were used as materials. 7 agronomic characters, such as yield, stem length, grain number per spike and so on were investigated with correlation analysis, multiple comparison analysis and cluster analysis. The influence factors of yield were discussed. Correlation analysis showed that the correlation coefficient between yield and effective panicles per unit area and grain number per spike was 0.685 and 0.439, respectively, reaching a very significant level. The correlation coefficient of yield and the basic seedlings per unit area was 0.368, which also reached a very significant level. Multiple comparison analysis results showed that the correlation coefficient of yield and basic seedlings per unit area, the highest stem tillers, effective spikes per unit area, stem length, grain number per spike and 1000-grain weight was 435.2742857, 358.8485714, 413.7485714, 371.8142857, 419.8914286, 406.7571429, respectively, and they all reached a significant level. The results of cluster analysis showed that the 35 wheat varieties were divided into 7 groups. The basic seedlings per unit area, stem length and grain numbers per spike are the most important factors that restricting the yield, and the study provides a theoretical basis for breeding, hybridization and tissue culture selection of high-yield wheat.