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农学学报

农学学报 ›› 2020, Vol. 10 ›› Issue (2): 92-95.doi: 10.11923/j.issn.2095-4050.cjas20190700115

所属专题： 小麦； 农业气象

• 农业信息 农业气象 • 上一篇    下一篇

主要气象因子与冬小麦产量的灰色关联度分析

胡园春1, 安广池2, 杨宁2, 李全景3, 崔云鹏1   

  1. 1 山东省枣庄市峄城区气象局,山东峄城 277300
    2 山东省枣庄市农业技术推广中心,山东枣庄 277800
    3 山东省枣庄市气象局,山东枣庄 277800
  • 收稿日期:2019-07-10 修回日期:2019-08-20 出版日期:2020-02-24 发布日期:2020-02-24
  • 作者简介:胡园春,女,1964年出生,山东庆云人,高级工程师,本科,研究方向：农业气象服务工作。通信地址：277300 山东枣庄峄城区坛山路（文体中心） 峄城区气象局,Tel：0632-8356080,E-mail：qyyc64@163.com。
  • 基金资助:
    十三五山东重大气象工程项目“山东现代农业气象服务保障工程”(鲁改发农经[2017]号)

Main Meteorological Factors and Winter Wheat Yield: Grey Correlation Degree Analysis

Hu Yuanchun1, An Guangchi2, Yang Ning2, Li Quanjing3, Cui Yunpeng1   

  1. 1 Yicheng District Meteorological Bureau in Zaozhuang, Yicheng 277300, Shandong, China
    2 Zaozhuang Agricultural Technology Promotion Center, Zaozhuang 277800, Shandong, China
    3 Zaozhuang Meteorological Bureau, Zaozhuang 277800, Shandong, China
  • Received:2019-07-10 Revised:2019-08-20 Online:2020-02-24 Published:2020-02-24

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摘要：

为了客观评价气象因子对小麦产量的影响,合理利用气候资源,提高鲁南地区小麦产量。利用灰色关联度分析法和逐步回归分析法,对鲁南地区2008—2017年冬小麦产量和主要气象因子的关系进行分析。灰色关联度分析结果表明,影响鲁南地区冬小麦产量的主要气象因子是≥10℃积温,关联系数0.4721;其次是生育期的降水量,关联系数0.4201;其余依次为≥0℃积温、冷量、≥20℃积温、日照时数,关联系数分别是0.3992、0.3756、0.3621、0.3131。逐步回归分析结果与灰色关联度分析结果一致,≥10℃积温是影响冬小麦产量主要因子,其次为降水量,且均为正效应;所得回归方程(P=0.0408, R 2=0.9811)可以适用于鲁南地区冬小麦产量的预测。

关键词: 鲁南地区, 主要气象因子, 冬小麦产量, 关联系数, 积温, 回归分析

Abstract:

To evaluate the influence of meteorological factors on wheat yield, make rational use of climate resources and improve wheat yield in southern Shandong, we analyzed the relationship between winter wheat yield and main meteorological factors in southern Shandong from 2008 to 2017 by using the methods of grey correlation and stepwise regression. The results of grey correlation analysis showed that: the main meteorological factors affecting winter wheat yield in southern Shandong were orderly ≥10℃ accumulated temperature, the precipitation during the growth period, ≥0℃ accumulated temperature and the cooling capacity, ≥20℃ accumulated temperature and sunshine hours, with the correlation coefficient of 0.4721, 0.4201, 0.3992, 0.3756, 0.3621 and 0.3131, respectively; the results of stepwise regression analysis were consistent with the results of grey correlation analysis, ≥10℃ accumulated temperature was the main factor affecting winter wheat yield and was followed by precipitation, and both of them caused positive effects; the regression equation (P=0.0408, R 2=0.9811) could be applied to the prediction of winter wheat yield in southern Shandong.

Key words: Southern Shandong, Main Meteorological Factors, Winter Wheat Yield, Correlation Coefficient, Accumulated Temperature, Regression Analysis

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