基于风险的食品安全监测方法:化学污染物排序算法

D. A. Makarov, T. Balagula, O. I. Lavrukhina, L. Shirkin
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引用次数: 0

摘要

基于风险的食品安全监测方法表明,污染物和(或)产品的数量分析取决于产品污染造成的风险,首先是为了消费者的健康和经济(预防不安全产品的实现)。面向风险的抽样、规划和分配研究可以与代表性相反,其目的是获得关于主要类型产品污染的可靠信息,并考虑到数理统计的要求。通常,各种基于风险的方法的核心是根据风险程度对污染物/污染物组和“污染物-产品”组合进行排序。排名算法可以细分为定性(口头特征)和定量(分数估计)。本文综述了食品安全国家中最成功的权威机构提出的食品化学污染物排序算法。所提出的方法具有一定的(有时是有限的)应用范围,并为加强化合物控制,统一毒理学特征,消费,鉴定和其他有关外源性生物制剂的信息提供了科学的数据基础。排名有效性的一个严重限制可能是兽药(抗生素)残留低于最大允许水平的数据缺失。对于健康风险还有其他但重要的标准,例如药物引起病原微生物耐药性的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Risk-based approach in food safety monitoring: algorithms for chemical pollutants ranking
A risk-based approach in food safety monitoring suggests that the number analysis of contaminants and (or) products depends on the risk caused by product contamination, first of all for consumer health and economic (prevention of unsafe products realization). Risk-oriented sampling, planning and assignment of studies can be opposed with representative, aimed at obtaining reliable information about the contamination of the main types of products and conducted taking into account the requirements of mathematical statistics. The core of the various risk-based approaches as a rule is the ranking of contaminants/groups of contaminants and combinations of «contaminant-product» according to the risk degree. Ranking algorithms may be subdivided into qualitative (verbal characteristics) and quantitative (scores estimation). Algorithms for food chemical contaminants ranking proposed by authority agencies of the most successful in food safety countries are reviewed in this paper. The proposed approaches have a certain (sometimes limited) scope of application and provide scientifically based data for enhance compound control, unite toxicological characteristics, consumption, identification, and other information about xenobiotics. A serious limitation of the ranking effectiveness may be missing data of veterinary drugs (antibiotics) residues below maximum permissible level. There are additional but important criteria for health risk, the ability of drugs to cause pathogenic microorganisms’ resistance for the example.
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