Journal of Arid Meteorology

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Meteorological Forecast Model for Stripe Rust of Wheat in Shaanxi Province

LI Dengke1, QUAN Wenting1, XIE Feizhou2   

  1. 1. Shaanxi Remote Sensing Information Center for Agriculture, Xi’an 710014, China;
    2. Shaanxi Station of Plant Protection, Xi’an 710003, China
  • Received:2016-05-03 Revised:2016-11-29 Online:2017-02-28 Published:2017-03-01

陕西省小麦条锈病气象预报模型

李登科1,权文婷1,谢飞舟2   

  1. 1.陕西省农业遥感信息中心,陕西 西安 710014;2.陕西省植物保护工作总站,陕西 西安 710003
  • 作者简介:李登科(1963-),男,陕西眉县人,正研级高工,主要从事农业气象、遥感应用业务和研究工作. E-mail: ldk81711@sohu.com
  • 基金资助:

    公益性行业(气象)科研专项(201406083)

Abstract:

A scientific basis can be provided for carrying out comprehensive prevention and control of the epidemic damage of wheat stripe rust in appropriate period with predicting the trend for local area using relationship between wheat stripe rust occurring degree and meteorological conditions. Correlation between occurrence degree of stripe rust of wheat in Shaanxi Province in past years and monthly air temperature, precipitation, relative humidity, sunshine hours from last November to April was analyzed, then meteorological factors which were sensitive to occurrence degree of stripe rust of wheat were selected, and they were normalized and weighted combination to make up stripe rust of wheat meteorological indexes and establish the meteorological forecast model for wheat stripe rust. The results show that the meteorological indexes were closely related to occurrence degree of stripe rust of wheat, and the correlation coefficient passed the 0.001 significance level. According to the difference between in the back substitution values obtained from the forecast model of northern and southern Shaanxi and the measured ones, it indicated that approximately 94.5% of the samples were within two levels, and 57.3% of the samples were within one level. For the difference in prediction of occurrence degree of wheat stripe rust in 2014, the 90% of the samples were within two levels, and 40% of the samples were within one level. The general test result was correct or overestimated.

Key words: strip rust of wheat , meteorological factors, forecast model , Shaanxi Province

摘要:

利用小麦条锈病发生程度与气象条件的关系,预测其流行趋势,可以为当地麦区适期开展综合防治、控制其流行为害提供科学依据。通过对陕西省小麦条锈病历年发生程度与上年11月至4月气温、降水量、相对湿度和日照时数月资料相关分析,选择对小麦条锈病发生程度敏感的气象因子,经过归一化处理和加权组合,组成小麦条锈病气象指数,进而建立小麦条锈病气象预报回归模型。结果表明:气象指数与小麦条锈病发生程度高度相关,相关系数通过0.001显著性检验;关中、陕南地区预报模型回代值与调查值差值在2个等级以内的样本占94.5%,差值在1个等级以内的样本占57.3%;对2014年小麦条锈病发生程度预报相差2个等级以内的样本占90%,相差1个等级以内的样本占40%;总体检验结果为正确或偏高。

关键词: 条锈病, 气象因子预报模型, 陕西省

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