Welcome to Journal of Agriculture,

Journal of Agriculture ›› 2020, Vol. 10 ›› Issue (2): 29-33.doi: 10.11923/j.issn.2095-4050.cjas20190700101

Special Issue: 水稻 农业气象

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Rice Bacterial Blight: Relationship Between the Epidemic and Meteorological Conditions and Its Prediction Model

Peng Rongnan1, Chen Bing1(), Chen Guanhao2, He Zehua1, Qiu Shishan1, Song Zuqin1, Liang Shengming2   

  1. 1 Meteorological Bureau of Huazhou, Huazhou 525100, Guangdong, China
    2 Forecast Station of Plant Disease and Insect Pests of Huazhou, Huazhou 525100, Guangdong, China
  • Received:2019-07-03 Revised:2019-08-20 Online:2020-02-24 Published:2020-02-24
  • Contact: Bing Chen E-mail:522033051@qq.com

Abstract:

The paper aims to clarify the relationship between meteorological conditions and the occurrence of rice bacterial blight, and to improve the ability to predict the occurrence of the disease. Based on the data of late rice bacterial blight and the meteorological data in Huazhou during 1985-2015, we conducted the correlation analysis. The results showed that: the precipitation, rainy days, relative humidity and typhoon from September to October were positively correlated with the degree of disease; the sunshine duration and temperature were negatively correlated with the degree of disease; the key meteorological factors affecting the occurrence of bacterial blight were precipitation from mid-August to mid-September, precipitation coefficient from September to October, precipitation intensity in late August and typhoon frequency in September. We established the prediction model of meteorological grade for the incidence degree of late rice bacterial blight by the stepwise regression statistical method; the multiple correlation coefficient R of the model was 0.9000, which passed the significance test of a=0.01; the fitting accuracy of model was 89.4%; the average test accuracy of the occurrence level of bacterial blight during 2016-2018 by the model was 93.3%. The model fitting results and the test accuracy are good, providing the basis for scientific decision-making on the comprehensive control of rice bacterial blight.

Key words: Rice Bacterial Blight (RBB), Meteorological Condition, Correlation Analysis, Prediction Model, Stepwise Regression, Epidemics

CLC Number: