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中国农学通报 ›› 2021, Vol. 37 ›› Issue (30): 39-46.doi: 10.11924/j.issn.1000-6850.casb2021-0269

• 农学·农业基础科学 • 上一篇    下一篇

基于灰色关联度分析和主成分分析法评估糖用甜菜品种的适应性

苏欣欣1(), 肖洋1(), 胡晓航1,2(), 马亚怀1,2, 李彦丽1,2   

  1. 1黑龙江大学现代农业与生态环境学院,哈尔滨 150080
    2国家糖料改良中心,哈尔滨 150080
  • 收稿日期:2021-03-17 修回日期:2021-05-13 出版日期:2021-10-25 发布日期:2021-12-08
  • 通讯作者: 肖洋,胡晓航
  • 作者简介:苏欣欣,女,1998年出生,河南济源人,研究生,研究方向:作物学。通信地址:150080 黑龙江省哈尔滨市南岗区学府路74号,E-mail: s1359212463@163.com
  • 基金资助:
    黑龙江省省属高等学校基本科研业务费项目“DSSAT-CERES-BEET模型在东北寒地甜菜生产中的适用性评价”(2020-KYYWF-1025);2021年黑龙江大学创新科研项目“基于灰色关联度筛选糖用甜菜区试品种的研究”(YJSCX2021-223HLJU);农业农村部农业技术试验示范与服务支持(品种试验)项目“试验示范与服务支持品种试验”(NJZ[2020]-I13)

The Adaptability Evaluation of Sugar Beet Varieties Based on Grey Relational Analysis and Principal Component Analysis

Su Xinxin1(), Xiao Yang1(), Hu Xiaohang1,2(), Ma Yahuai1,2, Li Yanli1,2   

  1. 1Acaademy of Modern Agriculture and Ecology Environment, Heilongjiang University, Harbin 150080
    2National Sugar Improvement Center, Harbin 150080
  • Received:2021-03-17 Revised:2021-05-13 Online:2021-10-25 Published:2021-12-08
  • Contact: Xiao Yang,Hu Xiaohang

摘要:

为了筛选出最适宜黑龙江哈尔滨地区种植的产质量高并抗根腐病的糖用甜菜品种。2020年在黑龙江省哈尔滨市黑龙江大学呼兰校区试验基地,以21个引种的KWS系列及1个BTS2730糖用甜菜品种(KWS1197为对照)为试材,采用主成分分析和灰色关联度分析法对根产量、含糖率、产糖量和根腐病4个指标进行综合评价。两种方法得出的甜菜品种的排序大致一致;第一主成分根产量的贡献率为69.704%,第二主成分含糖率的贡献率为26.283%,累计贡献率为95.987%,因此能够全面地反映甜菜的产质量性状;最适合本地种植的综合评价值高于对照的6个品种为:KWS0023(0.8231)>KWS0015(0.7685)> KWS6661(0.7511) >KWS9921(0.7103)>KWS0860(0.7097)>BTS2730(0.7065)>CK(0.6823);其他品种的综合评价值低于对照。主成分分析法和灰色关联度分析能够较为全面得分析甜菜品种,得出的结果具有可靠性。

关键词: 糖用甜菜, 品种, 主成分分析, 灰色关联度分析, 适应性

Abstract:

The aim is to screen out the most suitable sugar beet variety with high production quality and resistance to root rot in Harbin, Heilongjiang Province. In 2020, the test was carried out at the test base of Hulan Campus of Heilongjiang University, with 21 introduced KWS series and 1 BTS2730 sugar beet (KWS1197 as control) as the test materials, 4 indexes of root yield, sugar content, sugar yield and root rot were comprehensively evaluated by principal component analysis (PCA) and grey relation analysis (GRA). The sorts of the sugar beet varieties obtained by the two methods were roughly the same. The contribution rate of the first primary component (root yield) was 69.704%. The contribution rate of the second primary component (sugar content) was 26.283%, and the accumulated contribution rate was 95.987%, which could fully reflect the production quality of sugar beet. 6 varieties suitable for local planting selected by comprehensive evaluation value were better than the control: KWS0023 (0.8231)>KWS0015(0.7685)> KWS6661(0.7511)> KWS9921(0.7103)> KWS0860(0.7097) >BTS2730(0.7065) >CK(0.6823). The comprehensive evaluation value of other varieties was lower than the control. In conclusion, the principal component analysis and gray relational analysis could analyze sugar beet varieties more comprehensively, and the results obtained are reliable.

Key words: sugar beet, variety, principal component analysis, grey relational analysis, adaptability

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