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Predictive food microbiology: A probabilistic approach

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  • Nicolaï, B.M.
  • Van Impe, J.F.

Abstract

An existing mathematical model for microbial growth and inactivation in dynamically changing temperature conditions has been modified to explain the experimentally observed variability between replicate growth curves. The model incorporates a random variable parameter representing the random physiological state of the inoculum. The model is validated using experimental growth data which were obtained in time-varying temperature conditions. It is shown by Monte Carlo analyses that broad confidence bands are associated with the model predictions.

Suggested Citation

  • Nicolaï, B.M. & Van Impe, J.F., 1996. "Predictive food microbiology: A probabilistic approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 42(2), pages 287-292.
    • Handle: RePEc:eee:matcom:v:42:y:1996:i:2:p:287-292
    DOI: 10.1016/0378-4754(95)00129-8
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    Cited by:

    1. Poschet, F. & Bernaerts, K. & Geeraerd, A.H. & Scheerlinck, N. & Nicolaı̈, B.M. & Van Impe, J.F., 2004. "Sensitivity analysis of microbial growth parameter distributions with respect to data quality and quantity by using Monte Carlo analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 65(3), pages 231-243.

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