Modélisation de la contamination par Listeria monocytogenes pour l'amélioration de la surveillance dans les industries agro-alimentaires

Abstract : Food business operators are responsible for the quality of the products they sell. A way to assess the safety of food is to determine the contamination distribution. During my PhD thesis, we used data about L. monocytogenes during the process of diced bacon and of cold smoked salmon. Then, we constructed several hierarchical models to describe contamination taking or not into account several kinds of variability such as between batches variability. We compared the capacity of each model to simulate data close to the observed ones. We also compared the parameters assessment by frequentist inference using raw data (the results of the microbiological analyses) and concentration-like data. In addition to the models describing the contamination at one step of the process, we improved an existing model describing the fate of L. monocytogenes throughout the diced bacon process. A tool to assess the quality of a product is the sampling plan. We applied the Bayesian theory of decision to the pairs L. monocytogenes/diced bacon and L. monocytogenes/cold smoked salmon at the end of the process to determine the optimal size of a sample analysed per batch so that the average cost for the manufacturer is as los as possible. We also compared several sampling plans of temperature measurement of a meal cooked in an institutional food service facility and put in a blast-chiller just after cooking. The aim was to select the best sampling plan regarding the risk of C. perfringens growth that the manager is ready to take.
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Natalie Commeau. Modélisation de la contamination par Listeria monocytogenes pour l'amélioration de la surveillance dans les industries agro-alimentaires. Alimentation et Nutrition. AgroParisTech, 2012. Français. ⟨NNT : 2012AGPT0043⟩. ⟨pastel-00770790⟩

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