| 小麦叶锈菌越夏与气象因子相关性初步分析 |
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| 引用本文： | 夏小双,李泓甫,张芹芹,高 利,刘 博,陈万权,刘太国.小麦叶锈菌越夏与气象因子相关性初步分析[J].植物保护,2022,48(3):98-103. |
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| 作者姓名： | 夏小双 李泓甫 张芹芹 高 利 刘 博 陈万权 刘太国 |
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| 作者单位： | 1. 中国农业科学院植物保护研究所, 植物病虫害生物学国家重点实验室, 北京 100193;2. 农业农村部国家植物保护甘谷观测实验站, 天水 741200; 3. 农业农村部农产品质量安全生物性危害因子植物源控制重点实验室, 北京 100193 |
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| 基金项目： | 国家自然科学基金（31671967）；国家重点研发计划（2018YFD0200500，2018YFD0200400）；中国农业科学院科技创新工程（CAAS-ASTIP-ZDRW202002）；国家小麦产业技术体系（CARS-03） |
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| 摘 要： | 小麦叶锈病是一种严重威胁小麦安全生产、依靠气流传播的真菌病害，近年来发生呈逐年加重趋势。为明确气象因子对小麦叶锈菌越夏的影响，本研究通过对全国698个气象站点7月-8月最热10 d的日均温和平均日最高气温进行回归分析，对7月-8月0 cm平均地温、平均风速、平均降水量、平均日照时数和平均相对湿度进行空间插值，提取了93个小麦叶锈菌越夏调查点的气象数据，再与调查点小麦叶锈菌能否越夏进行相关性分析，结果显示小麦叶锈菌越夏与7月-8月最热10 d日均温和最热10 d平均日最高气温之间存在极显著相关性(P<0.01),与其他气象因子相关性不显著(P> 0.05),结果为小麦叶锈病的越夏区划奠定了基础。
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| 关 键 词： | 小麦叶锈病 越夏 气象因子 回归分析 地理信息系统 相关性分析 |
| 收稿时间： | 2021/3/31 0:00:00 |
| 修稿时间： | 2021/5/7 0:00:00 |
A preliminary correlation analysis between oversummering of Puccinia triticina and meteorological factors |
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| XIA Xiaoshuang,LI Hongfu,ZHANG Qinqin,GAO Li,LIU Bo,CHEN Wanquan,LIU Taiguo.A preliminary correlation analysis between oversummering of Puccinia triticina and meteorological factors[J].Plant Protection,2022,48(3):98-103. |
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| Authors: | XIA Xiaoshuang LI Hongfu ZHANG Qinqin GAO Li LIU Bo CHEN Wanquan LIU Taiguo |
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| Institution: | 1. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; 2. National Agricultural Experimental Station for Plant Protection at Gangu, Ministry of Agriculture and Rural Affairs, Tianshui 741200, China; 3. Key Laboratory of Control of Biological Hazard Factors Plant Origin for Agri-product Quality and Safety, Ministry of Agriculture and Rural Affairs, Beijing 100193, China |
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| Abstract: | Wheat leaf rust is one of the fungal diseases that spread by air and seriously threaten the safety of wheat production. In recent years, the occurrence of wheat leaf rust is increasing year by year. In this study, the average day-temperature and the average maximum day-temperature of the 10 warmest days from July to August of 698 meteorological stations were analyzed by regression analysis, and the mean values of ground surface temperature, wind speed, precipitation, sunshine time and relative humidity were analyzed by spatial interpolation. The meteorological data of 93 investigation sites of wheat leaf rust were obtained afterwards. Then the correlation analysis was carried out between oversummering and meteorological factors. The results showed that oversummering had a significant correlation with the average day-temperature and average maximum day-temperature of the 10 warmest days from July to August (P<0.01), but had no significant correlation with other meteorological factors (P>0.05), which laid a foundation for classification of the oversummering regions of wheat leaf rust. |
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| Keywords: | wheat leaf rust oversummering meteorological factors regression analysis GIS correlation analysis |
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