| 基于风险值自动计算—信息多维采集的农药残留大数据评估市售果蔬安全水平 |
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| 引用本文： | 庞国芳,梁淑轩,常巧英,申世刚,徐建中,范春林,李慧,白若镔.基于风险值自动计算—信息多维采集的农药残留大数据评估市售果蔬安全水平[J].中国科学院院刊,2018,33(3):318-329. |
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| 作者姓名： | 庞国芳 梁淑轩 常巧英 申世刚 徐建中 范春林 李慧 白若镔 |
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| 作者单位： | 中国检验检疫科学研究院;河北大学化学与环境科学学院;北京合众恒星检测科技有限公司; |
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| 基金项目： | “十二五”国家科技支撑计划项目（2012BAD29B01），国家科技基础性工作专项（2015FY111200） |
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| 摘 要： | 采用食品安全指数和风险系数模型,初步建立了农药残留膳食暴露风险和预警风险评估体系。开发"风险值自动计算—信息多维采集与分析"定制软件,基于2012—2015年我国市售果蔬农残检测大数据,从农药种类、限量标准、果蔬种类、地域等多个维度,分别对果蔬中残留农药之于人体的膳食暴露风险、预警风险进行了评估和解析。结果显示,气相色谱-四极杆-飞行时间质谱(GC-Q-TOF/MS)和液相色谱-四极杆-飞行时间质谱(LC-Q-TOF/MS)技术侦测的9 823例和12 551例市售果蔬,绝大多数膳食风险为可接受,但仍有0.56%和0.54%为风险不可接受。禁用农药膳食暴露风险不可接受比例是非禁用农药的20倍(GC-Q-TOF/MS组)和55倍(LC-Q-TOF/MS组);禁用农药高度预警风险比例是非禁用农药的17倍(GC-Q-TOF/MS组)和23倍(LC-Q-TOF/MS组),可见农药残留风险亟需控制,尤其应严格监管"禁药禁用"。文章据以上评估给出了高风险排名前10的农药和果蔬。另外,还发现欧盟的农药最大残留限量标准(MRLs)明显严于我国,我国相关标准建立亟待加快。研究结果可作为果蔬等食品风险水平实时诊断和风险农药精准监管的重要依据,以减少食源性农药残留风险,保障食品安全。
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| 关 键 词： | 大数据融合技术 信息多维采集 农药残留 膳食暴露风险 预警风险 |
| 收稿时间： | 2018/3/11 0:00:00 |
Assessment of Safety of Marketed Fruits and Vegetables in China Based on Large Data Fusion Technology of Risk Value Automatic Calculation-Multidimensional Information Collection |
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| PANG Guofang,LIANG Shuxuan,CHANG Qiaoying,SHEN Shigang,XU Jianzhong,FAN Chunlin,LI Hui and BAI Ruobin.Assessment of Safety of Marketed Fruits and Vegetables in China Based on Large Data Fusion Technology of Risk Value Automatic Calculation-Multidimensional Information Collection[J].Bulletin of the Chinese Academy of Sciences,2018,33(3):318-329. |
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| Authors: | PANG Guofang LIANG Shuxuan CHANG Qiaoying SHEN Shigang XU Jianzhong FAN Chunlin LI Hui and BAI Ruobin |
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| Institution: | Chinese Academy of Inspection and Quarantine, Beijing 100176, China,College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China,Chinese Academy of Inspection and Quarantine, Beijing 100176, China,College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China,College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China,Chinese Academy of Inspection and Quarantine, Beijing 100176, China,College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China and Beijing Uni-Star Inspection Technology Co. Ltd., Beijing 100176, China |
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| Abstract: | Two systems of dietary exposure and prewarning risk assessment of pesticide residue were constructed using models of food safety index and risk coefficient, respectively. A customized software of risk value automatic calculation-multidimensional information collection was developed. The risks of pesticide residues in the marketed fruit and vegetable samples in China from 2012 to 2015 were assessed on the basis of detection data. Multi-dimensional information was collected and analyzed including fruit and vegetable species, pesticide category, regions, maximum residue limit standards, and so on. The assessment results of dietary exposure risk indicate that the majority of risks are acceptable in the marketed fruits and vegetables of 9 823 (LC-Q-TOF/MS) and 12 551 samples (LC-Q-TOF/MS), respectively, but there are still 0.56% and 0.54% of them unacceptable. By the comparison of prohibited and non-prohibited pesticides, the frequency ratios of unacceptable dietary risks in total frequency are hiked at 20 (GC-Q-TOF/MS) and 55 (LC-Q-TOF/MS) times, while the ratios of high prewarning risk are 17 (GC-QTOF/MS) and 23 (LC-Q-TOF/MS) times respectively. The risks of the prohibited pesticides are significantly higher than that of the non-banned pesticides. Strict supervision and regulation of banned pesticides should be strengthened. The top fruits and vegetables with unacceptable dietary exposure risks of high prewarning risk are listed in this study. In addition, it could be found that the maximum residual limit standards established by European Union were obviously more strict and complete than that of China, so China must speed up the establishment of relevant standards. This study could provide important basis for real-time diagnosis and precise supervision of risk level of fruits and vegetables, thus reduce the risk of food borne pesticide residues and ensure people''s tongue safety. |
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| Keywords: | large data fusion technology multidimensional information collection pesticide residue dietary exposure risk prewarning risk |
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