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中国农学通报

中国农学通报 ›› 2023, Vol. 39 ›› Issue (8): 74-78.doi: 10.11924/j.issn.1000-6850.casb2022-0290

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

基于判别分析的湖北省马铃薯晚疫病气象风险等级预报模型

汤阳1(), 刘可群1(), 杨俊杰2, 邓环环1, 邓爱娟1, 车俊志3   

  1. 1 武汉区域气候中心，武汉 430074
    2 湖北省植物保护总站，武汉 430072
    3 随州市气象局，湖北随州 441399
  • 收稿日期:2022-04-11 修回日期:2022-06-18 出版日期:2023-03-15 发布日期:2023-03-14
  • 通讯作者: 刘可群，男，1963年出生，湖北汉川人，正高级工程师，本科，主要从事生态学和应用气象学研究。通信地址：430074 湖北省武汉市洪山区东湖东路3号 湖北省气象局武汉区域气候中心，Tel：027-67847964，E-mail：kequnliu@126.com
  • 作者简介:

    汤阳，男，1982年出生，湖北丹江口人，副高级工程师，硕士，研究方向：应用气象、气候变化。通信地址：430074 湖北省武汉市洪山区东湖东路3号 湖北省气象局武汉区域气候中心，Tel：027-67847968，E-mail：。

  • 基金资助:
    2019年度中国气象局国内外作物产量气象预报专项“马铃薯气象监测评估与产量预报技术集成应用”; 湖北省气象局科技发展基金研发项目“基于多源数据的格点尺度干旱监测与农业损失评估技术研究与应用”(2020Y05); “湖北省马铃薯晚疫病预报方法研究”(2018Q06)

Prediction Model of Meteorological Risk Grade for Potato Late Blight in Hubei Province Based on Discriminant Analysis

TANG Yang1(), LIU Kequn1(), YANG Junjie2, DENG Huanhuan1, DENG Aijuan1, CHE Junzhi3   

  1. 1 Wuhan Regional Climate Center, Wuhan 430074
    2 Hubei Plant Protection Station, Wuhan 430072
    3 Suizhou Meteorological Bureau, Suizhou, Hubei 441399
  • Received:2022-04-11 Revised:2022-06-18 Online:2023-03-15 Published:2023-03-14

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摘要：

开展马铃薯晚疫病发病率气象风险等级中长期预报方法研究，以期为科学防控晚疫病提供依据。对湖北省2011—2019年平原低山丘陵区马铃薯晚疫病发病率与气象因子进行相关性分析，筛选出对马铃薯晚疫病发生流行影响较大的气象因子，并利用2011—2017年数据及判别分析方法，结合人为防治因子建立了平原低山丘陵区马铃薯晚疫病发病率气象风险等级预报模型。结果表明：晚疫病发病率与3月中旬最低气温、4月上旬日照时数以及4月下旬风速相关性较好(P<0.05)，晚疫病发病率模型自身回代及交叉验证准确率分别为75.9%和75.3%，2018—2019年试报准确率达到61.7%。晚疫病发病率气象风险等级预报模型能够基本满足业务服务需求，通过预测马铃薯晚疫病当年发病情况可以为农技人员提前开展晚疫病防控提供参考。

关键词: 晚疫病, 判别分析, 平原低山丘陵区, 预报模型, 交叉验证

Abstract:

The long-term prediction methods of meteorological risk grade for incidence of potato late blight were studied to provide a basis for scientific prevention and control of the disease. With the data in the low hilly and plain area of Hubei Province from 2011 to 2019, the correlations between incidence of potato late blight and meteorological factors were analyzed, and the meteorological factors which had great influence on the occurrence and epidemics of potato late blight were selected. By using discriminant analysis method and data of the meteorological factors selected above and artificial control factor from 2011 to 2017, prediction model of meteorological risk grade for incidence of potato late blight was established. The results showed that the incidence of late blight was correlated with the mean minimum temperature in middle March, sunshine duration in early April and wind speed in late April obviously (P<0.05). It was also indicated that the accuracy of the prediction model was 75.9% in self-validation and 75.3% in cross-validation, and the accuracy of the prediction model was 61.7%, which was tested with data from 2018 to 2019. It proved that the prediction model of meteorological risk grade for incidence of potato late blight could basically meet the needs of meteorological service, and it could provide reference for agricultural technicians to carry out late blight prevention and control in advance by predicting the incidence of potato late blight of the year.

Key words: late blight, discriminant analysis, the low hilly and plain area, prediction model, cross-validation