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中国农学通报 ›› 2016, Vol. 32 ›› Issue (7): 152-156.doi: 10.11924/j.issn.1000-6850.casb15080142

所属专题: 园艺 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

茶树干燥型大冻害气象因素的logistic回归分析

段永春   

  1. 日照市茶叶科学研究所
  • 收稿日期:2015-08-28 修回日期:2015-09-30 接受日期:2015-10-16 出版日期:2016-03-18 发布日期:2016-03-18
  • 通讯作者: 段永春
  • 基金资助:
    山东省科技发展计划项目“北方茶树安全越冬技术集成研究”(2010GZX20948)。

Logistic Regression Analysis of Meteorological Factors of Dry Heavy Freezing Damage of Tea Plant

  • Received:2015-08-28 Revised:2015-09-30 Accepted:2015-10-16 Online:2016-03-18 Published:2016-03-18

摘要: 茶树大冻害是制约北方茶叶发展的一个重要因素。为解决这一问题,从山东主茶区的日照、青岛、临沂三个地区42年、共计126年的气象资料中,选择可能导致茶树干燥型大冻害形成的30个气象因子作为自变量,以干燥型大冻害作为因变量,进行单因素logistic 回归分析。根据单因素分析的结果,从30 个气象因子中筛选出10个有统计学意义的气象因子进行多因素logistic回归分析,建立茶树干燥型大冻害发生的logistic回归模型,并对模型进行评价。结果显示,1月平均气温、上年8月平均气温、上年11月空气相对湿度3个气象因子是茶树干燥型大冻害发生的主要决定因素。研究结论为山东以及其他北方茶区有效预防茶树干燥型大冻害提供了重要依据。

关键词: 舞毒蛾, 舞毒蛾, 海藻糖, 葡萄糖, 小分子多元醇, 甘油, 滞育, 低温刺激, 平均卵重

Abstract: Heavy freezing injury is an important factor restricting the development of tea industry in northern China. To solve this problem, the author studied the meteorological data of 42 years in Qingdao, Rizhao, Linyi (which are major tea producing areas in Shandong Province), and chose 30 meteorological factors as dependent variable, chose the dry heavy freezing injury as independent variable and made single factor logistic regression analysis. According to the result of single fac tor logistic regression analysis, the author chose 10 meteorological factors with statistical significance to make multivariate logistic regression analysis, established the logistic model of tea plant dry heavy freezing injury. By evaluating the model, the author found out that the average air temperature in January, the average air temperature in last August and the relative air humidity in last November were the main determinants that caused the tea plant dry heavy freezing injury. Conclusions would provide a basis for effectively preventing dry heavy freeze injury of tea plant in Shandong and other northern tea areas.

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