早稻纹枯病发生的气象条件分析及预报  

Analysis and Prediction of Meteorological Conditions for Early Rice Sheath Blight

作　　者：林汉龙 谢春生 袁传 陈红春 陈观浩 LIN Hanlong;XIE Chunsheng;YUAN Chuan;CHEN Hongchun;CHEN Guanhao(Daqiao Agricultural Technology Extension Station,Huazhou,Guangdong 525132,China;Pingding Agricultural Technology Extension Station,Huazhou,Guangdong 525135,China;Guanqiao Agricultural Technology Extension Station,Huazhou,Guangdong 525145,China;Forecast Station of Plant Disease and Insect Pests of Huazhou,Huazhou,Guangdong 525100,China)

机构地区：[1]广东省化州市笪桥镇农业技术推广站,广东化州525132 [2]广东省化州市平定镇农业技术推广站,广东化州525135 [3]广东省化州市官桥镇农业技术推广站,广东化州525145 [4]广东省化州市病虫测报站,广东化州525100

出　　处：《生物灾害科学》2021年第3期294-299,共6页Biological Disaster Science

基　　金：广东省科技计划项目(2013B020416002)。

摘　　要：【目的】为探索并掌握化州市水稻纹枯病流行规律,提高病害预报的科学性和准确性。【方法】利用化州市1986-2014年早稻纹枯病病情资料和同期气象资料,采用相关分析法分析了水稻纹枯病发生程度与气象条件的关系。【结果】早稻纹枯病发生程度与4-6月水稻生长季降水日数、相对湿度、降水量、降雨系数、温湿系数、温雨系数等呈正相关,而与日照时数、气温呈负相关。采用逐步回归分析方法建立了发生程度预测模型,模型的复相关系数R为0.932 7,通过α=0.01的显著性检验。模型拟合预报符合率为95.9%。利用预测模型对2015-2018年化州市早稻纹枯病进行预测,平均试报符合率达95.0%,预测和试报效果均较理想。【结论】所建立的气象预测模型具有较高的准确率,可应用于生产中水稻纹枯病的监测和预报。[Objective] The study was conducted to explore and grasp the epidemic law of rice sheath blight in Huazhou City, and to improve the scientificity and accuracy of disease forecasting. [Method] Using the disease data of early rice sheath blight in Huazhou from 1986 to 2014 as well as the meteorological data over the same period, the correlation analysis method was used to analyze the relationship between the incidence of rice sheath blight and meteorological conditions. [Result] The occurrence degree of early rice sheath blight was positively correlated with the number of days of precipitation, relative humidity, precipitation, rainfall coefficients,temperature and humidity coefficients, temperature and rain coefficients, etc., during the rice growing season from April to June, but was negatively correlated with sunshine hours and temperatures. A stepwise regression analysis method was used to establish the occurrence degree prediction model. The multiple correlation coefficient R of the model was 0.932 7, which passed the significance test of α=0.01. The prediction coincidence rate of the model fitting was 95.9%. Using the prediction model to predict early rice sheath blight in Huazhou from 2015 to 2018, it was found the average trial report coincidence rate reached 95.0%, showing that the prediction and trial report effects were satisfactory. [Conclusion] The established meteorological forecast model had a high accuracy rate and could be applied to the monitoring and forecasting of rice sheath blight in rice production.

关 键 词：水稻纹枯病 气象条件 相关性分析 预测模型 

分 类 号：S435.111.42[农业科学—农业昆虫与害虫防治]