Risk-based approach in food safety monitoring: algorithms for chemical pollutants ranking

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Abstract

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.

About the authors

Dmitry A. Makarov

The Russian State Center for Animal Feed and Drug Standardization and Quality

Email: phorez@yandex.ru
ORCID iD: 0000-0003-3834-0695

старший научный сотрудник, отделение фармакологических лекарственных средств, безопасности пищевой продукции и кормов

5 Zvenigorodskoye Shosse, Moscow, 123022, Russian Federation

Tatiana V. Balagula

Federal Service for Veterinary and Phytosanitary Surveillance

Email: loi1122@bk.ru
ORCID iD: 0000-0003-0583-4277

кандидат ветеринарных наук, начальник Управления государственного ветеринарного надзора

1/11 Orlikov per., Moscow, 107996, Russian Federation

Olga I. Lavrukhina

Vladimir State University named after A.G. and N.G. Stoletov

Author for correspondence.
Email: hamsster@mail.ru
ORCID iD: 0000-0001-6248-5726

кандидат химических наук, доцент кафедры химии

87 Gor’kogo St, Vladimir, 600026, Russian Federation

Leonid A. Shirkin

Vladimir State University named after A.G. and N.G. Stoletov

Email: hamsster@mail.ru
ORCID iD: 0000-0003-1622-9574

кандидат химических наук, доцент, доцент кафедры экологии

87 Gor’kogo St, Vladimir, 600026, Russian Federation

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Copyright (c) 2022 Makarov D.A., Balagula T.V., Lavrukhina O.I., Shirkin L.A.

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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