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松材线虫病的检测及综合防治技术
引用本文:曾端香,余曦玥,于敬文,贾建平,彭德良,黄文坤.松材线虫病的检测及综合防治技术[J].中国农学通报,2022,38(4):86-91.
作者姓名:曾端香  余曦玥  于敬文  贾建平  彭德良  黄文坤
作者单位:1.国家林业和草原局管理干部学院,北京 102600;2.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
基金项目:国家自然科学基金(32172382);
摘    要:松材线虫病(Bursaphelenchus xylophilus)是世界林业重大病害之一,严重威胁森林资源和生态环境.中国是松材线虫病危害的重灾区之一,截至2020年,中国已有18个省(市)成为松材线虫病疫区,发生面积已达180.92万hm2,病死松树量已达1947万株,且发病面积不断加大.为有效治理这一病害,中国采取...

关 键 词:松材线虫  松墨天牛  致病机制  防治方法  检测技术
收稿时间:2021-10-19

Detection and Integrated Control Technology of Bursaphelenchus xylophilus
ZENG Duanxiang,YU Xiyue,YU Jingwen,JIA Jianping,PENG Deliang,HUANG Wenkun.Detection and Integrated Control Technology of Bursaphelenchus xylophilus[J].Chinese Agricultural Science Bulletin,2022,38(4):86-91.
Authors:ZENG Duanxiang  YU Xiyue  YU Jingwen  JIA Jianping  PENG Deliang  HUANG Wenkun
Institution:1.National Academy of Forestry and Grassland Administration, Beijing 102600;2.The State Key Laboratory for Biology of Plant Disease and Insect Pests/ Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193
Abstract:Bursaphelenchus xylophilus is one of the major forest diseases in the world, which seriously threatens forest resources and ecological environment. China is one of the most seriously infected countries by B. xylophilus. Up to 2020, pine woods in 18 provinces of China were infected by B. xylophilus and the epidemic areas reached 1.8092 million hm2. The number of dead pine trees was 19.47 million and the incidence areas were increasing continuously. In order to prevent and control this nematode disease, China has adopted disease detection and epidemic monitoring methods, combined with other integrated management measures. The study reviewed the occurrence, infection, pathogenic mechanism, monitoring and detection technology, and integrated control technology of B. xylophilus, aiming to provide a theoretical basis for reducing the damage of B. xylophilus in the future.
Keywords:Bursaphelenchus xylophilus  Monochamus alternatus  pathogenic mechanism  prevention and control methods  detection technology  
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