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中国农学通报 ›› 2020, Vol. 36 ›› Issue (14): 156-164.doi: 10.11924/j.issn.1000-6850.casb19010094

所属专题: 小麦

• 农业信息·科技教育 • 上一篇    

基于python语言的冬小麦品种稳定性分析

李晓航1,2, 王映红1()   

  1. 1 河南省新乡市农业科学院,河南新乡 453000
    2 中国农业科学院农田灌溉研究所,河南新乡 453000
  • 收稿日期:2019-01-17 修回日期:2019-03-12 出版日期:2020-05-15 发布日期:2020-05-20
  • 通讯作者: 王映红
  • 作者简介:李晓航,女,1987年出生,河南安阳人,助理研究员,硕士,主要从事小麦育种节水栽培研究。通信地址:453000 河南省新乡市红旗区新二街518号,Tel:0373-6202008,E-mail:li.xiaohang@163.com。
  • 基金资助:
    国家现代农业产业技术体系建设专项资金项目“冬小麦优质高效节水机理研究”(CARS-3-2-35);2018年河南省重大科技专项“优质专用小麦新品种选育与示范”(18110011020)

Stability Analysis of Winter Wheat Varieties Based on Python Language

Li Xiaohang1,2, Wang Yinghong1()   

  1. 1 Xinxiang Academy of Agricultural Sciences, Henan Province, Xinxiang Henan 453000
    2 Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences, Xinxiang Henan 453000
  • Received:2019-01-17 Revised:2019-03-12 Online:2020-05-15 Published:2020-05-20
  • Contact: Wang Yinghong

摘要:

旨在挑选出适宜的冬小麦品种稳定性分析参数及其计算方法。利用冬小麦实验数据,首次通过python语言计算了5个稳定性参数,并采用秩相关性和主成分分析,研究了参数的相关性。结果表明,python语言可以方便、灵活的计算各类参数,计算相关性和进行主成分分析。相关分析表明,PCOA和产量显著正相关,CVBi和产量极显著负相关。研究表明,PCOA模型能够同时评价品种产量及其稳定性。多元统计方法是单变量参数模型的有益补充。

关键词: 冬小麦, 品种, 稳定性, python语言, 程序, 秩相关性

Abstract:

The study aims at selecting suitable stability analysis parameters and calculation methods for winter wheat varieties. Using the experimental data of winter wheat, five stability parameters were calculated by Python for the first time. The correlations of parameters were studied by rank correlation and principal component analysis. The results showed that the Python language could easily and flexibly calculate various parameters and rank correlation and analyze principal components. The correlation analysis showed that PCOA was significantly and positively correlated with yield; CV and Bi were significantly and negatively correlated with yield. The results indicate that the PCOA model can simultaneously evaluate yield and stability of varieties, and the multivariate method can be a useful complement to the univariate parameter model.

Key words: winter wheat, variety, stability, python language, program, rank correlation

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