摘要
目的分析蔬菜中农药残留空间格局分布变化及规律,找到聚集热点区域,为蔬菜中农药残留监测、监管提供科学依据。方法用空间统计方法对某省2014—2016年蔬菜中农药残留监测信息结合地理信息进行空间格局分布及空间聚集性分析。结果 2014—2016年区域内监测的蔬菜中农药残留检出率和超标率两者分布格局较一致,但三年对比变化较大,检出较高区域集中分布在西南部和东北部;超标率涉及区县较少,散在分布在西南部和东北部。2014年监测区域的蔬菜中农药检出率全局存在正相关性(P<0.05,Moran's I=0.410),局部相关主要分布在西南部、北部和南部地区;2016年监测区域的蔬菜中农药超标率全局存在正相关性(P<0.05,Moran's I=0.111),局部相关主要分布在西南部地区;2016年监测区域的蔬菜中农药检出率全局存在负相关性(P<0.05,Moran's I=-0.087),局部相关主要分布在中部地区。时空扫描统计量分析结果显示监测区域内超标率和检出率均有聚集性,超标率有一个聚类区域(LLR=27.11,P<0.05,RR=20.04),分布在东北部区县;检出率有两个聚类区域,一类聚类区域(LLR=43.24,P<0.05,RR=6.9)分布在东北部和南部区县,二类聚类区域(LLR=19.13,P<0.05,RR=4.13)分布在西南部区县。结论 2014—2016年监测区域的蔬菜中农药残留检出率和超标率呈现较为一致的下降趋势。空间自相关性和时空扫描统计量结果显示存在聚集性,聚集区域主要为东北部和西南部邻近区县,且聚集区域的相对风险度RR值均>4,提示这些聚集区县较其他区县农药残留风险高,是监管部门应该关注的热点区域。
Objective The change and regularity of spatial pattern distribution of pesticide residues in vegetables were analyzed,the gathered hot region was found,for the monitoring,and it could provide scientific basis for supervision.Methods The pesticide residues in vegetables in 2014-2016 was analyzed by spatial statistical method for spatial distribution and spatial clustering. Results The detection rate and violation rate of pesticide residues in the vegetables were in the same distribution pattern in 2014-2016. However,the change in the past three years was relatively large. The areas with high detection rate were concentrated in the southwest and the northeast. The violation was distributed in the southwest and north. In 2014,the detection rate had an overall positive correlation in the monitoring area（ P 0. 05,Moran＇s I = 0. 410）,and the local correlation was mainly distributed in the southwest,north and south. The violation rate had an overall positive correlation（ P 0. 05,Moran＇s I = 0. 111） in 2016,and the local correlation was mainly distributed in the southwest region. In 2016,the detection rate had a negative correlation（ P 0. 05,Moran＇s I =-0. 087）,and the local correlation was mainly distributed in the central region. The time and space scan statistics analysis showed that the violation rate and detection rate in the monitoring area were clustered. There was a clustering area（ LLR = 27. 11,P 0. 05,RR = 20. 04）. The detection rate had two clustering areas. Class I cluster area（ LLR = 43. 24,P 0. 05,RR =6. 9） was distributed in the northeast and south counties. Class II clustering area（ LLR = 19. 13,P 0. 05,RR = 4. 13）was distributed in the southwest area and counties. Conclusion The detection rate and violation rate of pesticide residues in vegetables showed a consistent decline during 2014-2016. The result of spatial autocorrelation and space-time scanning statistics showed the existence of aggregation. The gathering area was mainly located in the northeast and southwestern neighboring counties. The relative risk of the gathering area was greater than 4,indicating that the risk of pesticide residues in these districts was higher than that in other counties,which was a hot area for regulators to pay close attention.
作者
杨蕙
李宁
计融
何平
肖革新
YANG Hui;LINing;JI Rong;HE Ping;XIAO Ge-xin(Guizhou Provincial Center for Disease Control and Prevention, Guizhou Guiyang 550004, China;China National Center for Food Safety Risk Assessment, Beijing 100022, China)
出处
《中国食品卫生杂志》
北大核心
2018年第1期73-78,共6页
Chinese Journal of Food Hygiene
关键词
蔬菜
空间统计
农药残留
风险分析
Vegetables
spatial statistics
pesticide residues
risk analysis
