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Probabilistic Modeling of the Fate of Listeria Monocytogenes in Diced Bacon During the Manufacturing Process
Author(s) -
Billoir Elise,
Denis JeanBaptiste,
Commeau Natalie,
Cornu Marie,
Zuliani Véronique
Publication year - 2011
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/j.1539-6924.2010.01494.x
Subject(s) - process (computing) , probabilistic logic , computer science , calibration , product (mathematics) , reliability engineering , process validation , risk analysis (engineering) , biochemical engineering , engineering , statistics , mathematics , operations management , artificial intelligence , verification and validation , medicine , geometry , operating system
To assess the impact of the manufacturing process on the fate of Listeria monocytogenes , we built a generic probabilistic model intended to simulate the successive steps in the process. Contamination evolution was modeled in the appropriate units (breasts, dice, and then packaging units through the successive steps in the process). To calibrate the model, parameter values were estimated from industrial data, from the literature, and based on expert opinion. By means of simulations, the model was explored using a baseline calibration and alternative scenarios, in order to assess the impact of changes in the process and of accidental events. The results are reported as contamination distributions and as the probability that the product will be acceptable with regards to the European regulatory safety criterion. Our results are consistent with data provided by industrial partners and highlight that tumbling is a key step for the distribution of the contamination at the end of the process. Process chain models could provide an important added value for risk assessment models that basically consider only the outputs of the process in their risk mitigation strategies. Moreover, a model calibrated to correspond to a specific plant could be used to optimize surveillance.