Stochastic, Compartmental, and Dynamic Modeling of Cross-Contamination During Mechanical Smearing of Cheeses

Authors

  • Fanny Aziza,

    Corresponding author
      *Address correspondence to Fanny Aziza, Ecole Nationale Vétérinaire d'Alfort, Unité Epidémiologie et Analyse des Risques, Pôle HQSA, 7, av. du général de Gaulle, 94 704 Maison Alfort Cedex, France; tel: 00 33 143 96 7033; faziza@vet-alfort.fr.
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      Ecole Nationale Vétérinaire d'Alfort, Unité Epidémiologie et Analyse des Risques, Pôle HQSA, 7, av. du général de Gaulle, 94 704 Maison Alfort Cedex, France. SOREDAB S.A.S., La Tremblaye, 78 125 La Boissière Ecole, France.
  • Eric Mettler,

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      SOREDAB S.A.S., La Tremblaye, 78 125 La Boissière Ecole, France.
  • Jean-Jacques Daudin,

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      Institut National Agronomique Paris-Grignon, Organisation et Modélisation de l'Information et des Processus, 16 rue Claude Bernard, 75 231 Paris Cedex 05, France.
  • Moez Sanaa

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      Ecole Nationale Vétérinaire d'Alfort, Unité Epidémiologie et Analyse des Risques, Pôle HQSA, 7, av. du général de Gaulle, 94 704 Maison Alfort Cedex, France.

*Address correspondence to Fanny Aziza, Ecole Nationale Vétérinaire d'Alfort, Unité Epidémiologie et Analyse des Risques, Pôle HQSA, 7, av. du général de Gaulle, 94 704 Maison Alfort Cedex, France; tel: 00 33 143 96 7033; faziza@vet-alfort.fr.

Abstract

Cheese smearing is a complex process and the potential for cross-contamination with pathogenic or undesirable microorganisms is critical. During ripening, cheeses are salted and washed with brine to develop flavor and remove molds that could develop on the surfaces. Considering the potential for cross-contamination of this process in quantitative risk assessments could contribute to a better understanding of this phenomenon and, eventually, improve its control. The purpose of this article is to model the cross-contamination of smear-ripened cheeses due to the smearing operation under industrial conditions. A compartmental, dynamic, and stochastic model is proposed for mechanical brush smearing. This model has been developed to describe the exchange of microorganisms between compartments. Based on the analytical solution of the model equations and on experimental data collected with an industrial smearing machine, we assessed the values of the transfer parameters of the model. Monte Carlo simulations, using the distributions of transfer parameters, provide the final number of contaminated products in a batch and their final level of contamination for a given scenario taking into account the initial number of contaminated cheeses of the batch and their contaminant load. Based on analytical results, the model provides indicators for smearing efficiency and propensity of the process for cross-contamination. Unlike traditional approaches in mechanistic models, our approach captures the variability and uncertainty inherent in the process and the experimental data. More generally, this model could represent a generic base to use in modeling similar processes prone to cross-contamination.

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