湖北农业科学 ›› 2019, Vol. 58 ›› Issue (3): 42-44.doi: 10.14088/j.cnki.issn0439-8114.2019.03.011

• 资源·环境 • 上一篇    下一篇

阜阳市气象要素与小麦千粒重的关系分析及预测

王晓玲1, 张庆奎1, 张桂芳2   

  1. 1.阜阳市气象局,安徽 阜阳 236000;
    2.阜阳市农业科学院,安徽 阜阳 236000
  • 收稿日期:2018-08-14 出版日期:2019-02-10 发布日期:2019-11-29
  • 作者简介:王晓玲(1971-),女,安徽利辛人,工程师,主要从事专业、专项气象服务的研究与应用,(电话)0558-2577167(电子信箱)fyys0558@163.com。
  • 基金资助:
    阜阳市气象局科技发展基金项目(KF201702); 阜阳市社科规划项目(FSK2013003)

Relationship Analysis and Prediction between the Meteorological Elements and Thousand Kernel Weight in Fuyang City

WANG Xiao-ling1, ZHANG Qing-kui1, ZHANG Gui-fang2   

  1. 1.Fuyang Meteorological Bureau,Fuyang 236000,Anhui,China;
    2.Fuyang Academy of Agricultural Sciences,Fuyang 236000,Anhui,China
  • Received:2018-08-14 Online:2019-02-10 Published:2019-11-29

摘要: 利用2006—2015年小麦(Triticum aestivum L.)抽穗至成熟期间千粒重和同期气象数据,采用SPSS统计分析工具分析了二者之间的关系。结果表明,该时段日最低气温对小麦千粒重的影响最为明显,其次是日照时间和总日照时间。并建立了以气象主要影响因子与千粒重的多元线性回归预测模型作为预测小麦千粒重的依据,2016—2017年独立预测检验精度在67%,说明该模型具有较高的应用价值。

关键词: 小麦(Triticum aestivum L.), SPSS, 气象要素, 千粒重

Abstract: Based on the thousand kernel weight and the meteorological data between heading period and mature period of wheat (Triticum aestivum L.) during 2006 to 2015, the relationship between the two was analyzed by using SPSS statistical analysis tool. The results showed that the daily minimum temperature had the most significant effect on the thousand kernel weight, followed by sunshine hours and total sunshine hours. The multivariate linear regression prediction model based on the correlation between the main influencing factors and thousand kernel weight was established as a basis for predicting the thousand grain weight of wheat. The independent forecasts inspection accuracy during 2016 to 2017 was about 67%, showed that the model has good application value.

Key words: wheat(Triticum aestivum L.), SPSS, meteorological elements, thousand grain weight

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