title: Management of Listeria monocytogenes in fermented sausages using the Food Safety Objective concept underpinned by stochastic modeling and meta-analysis.
abstract: In the present work, a demonstration is made on how the risk from the presence of Listeria monocytogenes in fermented sausages can be managed using the concept of Food Safety Objective (FSO) aided by stochastic modeling (Bayesian analysis and Monte Carlo simulation) and meta-analysis. For this purpose, the ICMSF equation was used, which combines the initial level (H0) of the hazard and its subsequent reduction (ΣR) and/or increase (ΣI) along the production chain. Each element of the equation was described by a distribution to investigate the effect not only of the level of the hazard, but also the effect of the accompanying variability. The distribution of each element was determined by Bayesian modeling (H0) and meta-analysis (ΣR and ΣI). The output was a normal distribution N(-5.36, 2.56) (log cfu/g) from which the percentage of the non-conforming products, i.e. the fraction above the FSO of 2 log cfu/g, was estimated at 0.202%. Different control measures were examined such as lowering initial L. monocytogenes level and inclusion of an additional killing step along the process resulting in reduction of the non-conforming products from 0.195% to 0.003% based on the mean and/or square-root change of the normal distribution, and 0.001%, respectively.
authors.affiliation: Università di Torino, Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, Grugliasco, 10095 Turin, Italy; Agriculture University of Athens, Department of Food Science and Technology, Laboratory of Food Quality Control and Hygiene, Iera Odos 75, 11855, Athens, Greece. Electronic address: mmat@aua.gr.
authors.forename: M
authors.initials: M
authors.lastname: Mataragas
authors.affiliation: Università di Torino, Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, Grugliasco, 10095 Turin, Italy.
authors.forename: V
authors.initials: V
authors.lastname: Alessandria
authors.affiliation: Università di Torino, Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, Grugliasco, 10095 Turin, Italy.
authors.forename: K
authors.initials: K
authors.lastname: Rantsiou
authors.affiliation: Università di Torino, Dipartimento di Scienze Agrarie, Forestali e Alimentari, Via Leonardo da Vinci 44, Grugliasco, 10095 Turin, Italy.
authors.forename: L
authors.initials: L
authors.lastname: Cocolin
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D005285:Fermentation; D005506:Food Contamination / Q000517:prevention & control / Q000706:statistics & numerical data; D059022:Food Safety; D008089:Listeria monocytogenes / Q000254:growth & development / Q000378:metabolism*; D008461:Meat Products / Q000382:microbiology*; D015233:Models, Statistical; D013552:Swine
keywords: Bayesian modeling; Fermented meats; Food safety objective; Foodborne pathogens; HACCP; meta-Analysis