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Risk‐Based Approach for Microbiological Food Safety Management in the Dairy Industry: The Case of Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk
Author(s) -
TenenhausAziza Fanny,
Daudin JeanJacques,
Maffre Alexandre,
Sanaa Moez
Publication year - 2014
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.12074
Subject(s) - pasteurization , food safety , risk analysis (engineering) , risk management , listeria monocytogenes , risk assessment , silo , hazard analysis and critical control points , business , food science , engineering , computer science , computer security , mechanical engineering , chemistry , finance , biology , bacteria , genetics
According to Codex Alimentarius Commission recommendations, management options applied at the process production level should be based on good hygiene practices, HACCP system, and new risk management metrics such as the food safety objective. To follow this last recommendation, the use of quantitative microbiological risk assessment is an appealing approach to link new risk‐based metrics to management options that may be applied by food operators. Through a specific case study, Listeria monocytogenes in soft cheese made from pasteurized milk, the objective of the present article is to practically show how quantitative risk assessment could be used to direct potential intervention strategies at different food processing steps. Based on many assumptions, the model developed estimates the risk of listeriosis at the moment of consumption taking into account the entire manufacturing process and potential sources of contamination. From pasteurization to consumption, the amplification of a primo‐contamination event of the milk, the fresh cheese or the process environment is simulated, over time, space, and between products, accounting for the impact of management options, such as hygienic operations and sampling plans. A sensitivity analysis of the model will help orientating data to be collected prioritarily for the improvement and the validation of the model. What‐if scenarios were simulated and allowed for the identification of major parameters contributing to the risk of listeriosis and the optimization of preventive and corrective measures.