基于GIS的小麦孢囊线虫病在江苏省的发生分布与群体密度分析

 2009-2011年间对江苏省12地1市共59个区县市290个乡镇的小麦孢囊线虫病发生情况进行了系统调查，并结合GIS软件，绘制了该病害的发生分布、群体密度及其与土壤质地之间关系的地理信息矢量图。调查结果表明： 在580个调查点中，有47个区市县152个乡镇的301个调查点发现CCN；在苏北的徐州地区、苏中的泰州和扬州地区以及苏南的镇江地区CCN发生较为普遍，而江苏其他地区发生率相对较低。不同地区平均CCN群体密度差异较大， 徐州、扬州和泰州地区样品分别为34.4、17.5和17.1个孢囊/100 mL土，而连云港、南通和苏州等地区仅为3~5个孢囊/100 mL土；ArcGIS矢量图显示江苏省小麦孢囊线虫病发病田的孢囊群体密度与土壤质地有密切的关系，在土壤质地为沙土和沙壤土的发病田孢囊群体密度普遍较高，徐州沛县王店镇的CCN样品孢囊群体密度最高达到了191.0个/100 mL土，而土壤质地为粘土的病田小麦孢囊线虫群体密度相对较低。本研究为宏观了解小麦孢囊线虫病在江苏省的发生情况和监测发病重灾区CCN的田间发生动态规律提供参考, 并为今后的病害综合防控技术示范与推广提供理论依据。

Analyses of distribution and population density of cereal cyst nematodes on wheat in Jiangsu Province based on GIS

A survey of cereal cyst nematodes (CCN) on wheat was carried out in 290 towns from 59 counties of 13 districts in Jiangsu Province during 2009 to 2011, and the vector graphics of geographical relationships between the distribution of disease, the population density of CCN and the soil types were analysized by Geographic Information System (GIS) software. The results showed 301 out of 580 investigated fields, which from 152 towns of 47 counties, were detected with CCN. It was widely distributed in wheat growing areas of Xuzhou district in northern part of the Province, Taizhou and Yangzhou in middle part and Zhenjiang in sou-thern part. The average population densities of CCN varied in different districts. The population densities of Xuzhou, Yangzhou and Taizhou district was 34.4、17.5 and 17.1cysts per 100mL soil, respectively, and the districts of Liangyungang, Nantong and Suzhou were 3-5 cysts per 100mL soil. The vector graphics made by ArcGIS revealed the close relationships between the population density of CCN and the soil types in infested fields. The population densities were generally higher in sandy and sandy-clay soil than those in clay soil. The population density in Wangdian Town of Peixian, Xuzhou district was 191.0 cysts/100 mL sandy soil. The research not only benefited the macroscopical understanding of CCN distribution in whole province and the inspecting dynamics of population density in seriously infested areas, but also provided the basis knowledge for CCN integrated management.