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基于电子溯源建立食品安全风险评估决策系统
引用本文:任鹏程,苏亮,陈思,李志兴,王亚男,岑嶒,宿晨. 基于电子溯源建立食品安全风险评估决策系统[J]. 中国食品卫生杂志, 2020, 32(2): 206-211
作者姓名:任鹏程  苏亮  陈思  李志兴  王亚男  岑嶒  宿晨
作者单位:国家食品安全风险评估中心,北京 100022,国家食品安全风险评估中心,北京 100022,国家食品安全风险评估中心,北京 100022,吉林省食品生产许可证审核中心,吉林 长春 130000,国家食品安全风险评估中心,北京 100022,国家食品安全风险评估中心,北京 100022,国家食品安全风险评估中心,北京 100022
基金项目:基于电子溯源的食品安全风险评估关键技术研究与应用(2015BAK36B04)
摘    要:目的实现食品安全风险评估决策工作的高度流程化与自动化,加强各业务部门间的数据融合。方法构建涵盖膳食暴露评估、危害因子评价、时空聚集探测等方法的时态模型库,可自动连接食品溯源各环节基础数据获取相应多种数据,并通过选择的风险评估模型计算得出风险评估结果,构建风险评估矩阵。基于ETL(extract-transform-load)技术和R语言的数据分析算法,集成基础数据仓库、风险评估模型库、风险决策支持系统。结果食品安全风险评估决策系统的建立有效改善传统风险评估工作耗时费力、数据清洗困难的问题,基于对原有风险评估过程的电子化,实现模型输入、计算、输出一体化,融合多年历史监测数据,快速定制常见食品分类中有害因素的风险评估研判场景。结论该系统有助于提高相关业务人员的工作效率,推动跨业务部门间数据交换及协同共享。

关 键 词:风险评估  决策  数据融合  食品安全
收稿时间:2020-02-12

Realization of a unified platform based on electronic traceability for food safety risk assessment decision
REN Pengcheng,SU Liang,CHEN Si,LI Zhixing,WANG Yanan,CEN Ceng and XU Chen. Realization of a unified platform based on electronic traceability for food safety risk assessment decision[J]. Chinese Journal of Food Hygiene, 2020, 32(2): 206-211
Authors:REN Pengcheng  SU Liang  CHEN Si  LI Zhixing  WANG Yanan  CEN Ceng  XU Chen
Affiliation:China National Center for Food Safety Risk Assessment, Beijing 100022, China,China National Center for Food Safety Risk Assessment, Beijing 100022, China,China National Center for Food Safety Risk Assessment, Beijing 100022, China,Jilin Province Center for Food Production License Audit, Jilin Changchun 130000, China,China National Center for Food Safety Risk Assessment, Beijing 100022, China,China National Center for Food Safety Risk Assessment, Beijing 100022, China and China National Center for Food Safety Risk Assessment, Beijing 100022, China
Abstract:Objective To achieve a high degree of process-oriented and automated decision-making on food safety risk assessment and data fusion among various business units. Methods Establish a temporal model library covering method such as dietary exposure assessment, hazard factor assessment, and spatio-temporal clustering detection, which can automatically connect to the basic data of each link of food traceability to obtain corresponding data, and calculate the risk assessment result through the selected risk assessment model construct a risk assessment matrix. Based on extract-transform-load (ETL) technology and data analysis algorithm implemented by R language, the basic data warehouse, risk assessment model base and risk decision support system were integrated. Results The establishment of a food safety risk assessment decision-making system would effectively resolve the problems of time-consuming and labor-intensive traditional data assessment and data cleaning difficulties. Based on the electronization of the original risk assessment process, the model input, calculation, and output would be integrated, and multi-year historical monitoring would be integrated to quickly customize the risk assessment research scenarios for harmful factors in common food categories. Conclusion This platform help improve the work efficiency of relevant business personnel, and promote data exchange and collaborative sharing between business units.
Keywords:Risk assessment  decision  unified platform  food safety
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