| 水稻白叶枯病发生流行与气象条件关系及预测模型研究 |
| |
| 引用本文： | 彭荣南,陈 冰,陈观浩,何泽华,邱世善,宋祖钦,梁盛铭. 水稻白叶枯病发生流行与气象条件关系及预测模型研究[J]. 农学学报, 2020, 10(2): 29-33. DOI: 10.11923/j.issn.2095-4050.cjas20190700101 |
| |
| 作者姓名： | 彭荣南 陈 冰 陈观浩 何泽华 邱世善 宋祖钦 梁盛铭 |
| |
| 作者单位： | 1. 广东省化州市气象局,广东化州 525100;2. 广东省化州市病虫测报站,广东化州 525100 |
| |
| 基金项目： | 广东省科技计划项目“超级稻主要病虫害发生特点及防控技术集成与推广”(2013B020416002);茂名科技计划项目“水稻主要病虫害灾变 气象条件及预测研究与应用”(2019455)。 |
| |
| 摘 要： | 为了明确气象条件与水稻白叶枯病发生的关系,提高预报能力,利用1985—2015年化州市晚稻白叶枯病病情资料及气象数据进行相关性分析。结果表明：9—10月降水量、降水日数、相对湿度、台风与发病程度呈正相关;日照时数、气温与发病程度呈负相关。影响白叶枯病发生的关键气象因子分别是8月中旬—9月中旬降水量、9—10月降雨系数、8月下旬降水强度和9月台风次数。采用逐步回归统计方法建立晚稻白叶枯病发病程度气象等级预测模型,模型的复相关系数R为0.9000,通过α=0.01的显著性检验。模型拟合准确率为89.4%。利用该模型对2016—2018年白叶枯病发生等级进行试报检验,平均试报准确率达93.3%。模型拟合结果和试报准确率均较好,为白叶枯病的综合防治及科学决策提供了依据。
|
| 关 键 词： | 水稻白叶枯病 气象条件 相关性分析 预测模型 逐步回归 流行规律 |
| 收稿时间： | 2019-07-03 |
| 修稿时间： | 2019-08-22 |
Rice Bacterial Blight: Relationship Between the Epidemic and Meteorological Conditions and Its Prediction Model |
| |
| Peng Rongnan,Chen Bing,Chen Guanhao,He Zehua,Qiu Shishan,Song Zuqin,Liang Shengming. Rice Bacterial Blight: Relationship Between the Epidemic and Meteorological Conditions and Its Prediction Model[J]. Journal of Agriculture, 2020, 10(2): 29-33. DOI: 10.11923/j.issn.2095-4050.cjas20190700101 |
| |
| Authors: | Peng Rongnan Chen Bing Chen Guanhao He Zehua Qiu Shishan Song Zuqin Liang Shengming |
| |
| Affiliation: | 1. Meteorological Bureau of Huazhou, Huazhou 525100, Guangdong, China;2. Forecast Station of Plant Disease and Insect Pests of Huazhou, Huazhou 525100, Guangdong, China |
| |
| 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. |
| |
| Keywords: | Rice Bacterial Blight (RBB) Meteorological Condition Correlation Analysis Prediction Model Stepwise Regression Epidemics |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《农学学报》浏览原始摘要信息 |
|
点击此处可从《农学学报》下载免费的PDF全文 |
|
