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稻曲病气象风险评估及适宜度等级预测技术 被引量:10

Meteorological conditions and prediction techniques of suitability grades for the occurrence of rice false smut
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摘要 为了弄清适宜稻曲病发生发展的气象条件以及对应的气象适宜度等级,提高水稻气象型病害防控能力,本文利用江苏省稻曲病大田调查资料,结合历史气象资料,通过评估发病敏感时段和致病风险,以及分析江苏省稻曲病最大成灾风险度出现日期以及空间分布情况,指出8月下旬为稻曲病高发期,对于发病风险高且程度重的沿淮、沿江以及江淮之间地区需要加强病害防御。在此基础上,综合考虑不同连续致病天数对稻曲病流行的影响,利用最优化技术,构建了综合稻曲病指数,并划分气象条件适宜度等级。通过单站和多站检验发现该指数对"中等、大流行"发病实况的判定准确率极高,但容易高估"轻度流行"的程度。 In order to understand the suitable meteorological conditions for rice false smut occurrence and the cor- responding degrees and further improve the service ability of resisting agrometeorological diseases, this study was conducted. The historical meteorological data and field survey data of actual occurrence of the rice false smut were used, based on the assessment of sensitive period and risk of disease occurrence, to analyze the distribution of the dates and values of maximum risk degree for rice false smut occurrence in Jiangsu Province. It showed that late August was the peak onset period, and more prevention was needed for high-risk areas located along the Huai Riv- er and Yangtze River and between them. Then, considering the influences from the different continued days and by applying the optimization techniques, the composite index of rice false smut was constructed, and meteorologi- cal grades for fitting rice blast occurrence were determined. By single and multi-station test, it was found that the accuracy of judging the situation of medium and pandemic burst by using the composite index could reach a high level. However, the mild occurrences were often overestimated.
作者 任义方 高苹 朱凤 刘梅 Ren Yifang Gao Ping Zhu Feng Liu Mei(Jiangsu Meteorological Service Center, Nanjing 210008, China Jiangsu Provincial Plant Protective Station, Nanjing 210046, China Jiangsu Meteorological Observatory, Nanjing 210008, China)
出处 《植物保护》 CAS CSCD 北大核心 2017年第1期61-67,共7页 Plant Protection
基金 江苏省气象局科研基金(KM201504) 公益性行业(气象)科研专项(GYHY201306035)
关键词 水稻稻曲病 风险评估 综合稻曲病指数 气象等级预测 rice false smut risk assessment composite index of false smut meteorological grade prediction
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