Development and validation of experimental protocols for use of cardinal models for prediction of microorganisms growth in food products

A. Pinon, M.H. Zwietering, L. Perrier, J.M. Membré, B. Leporq, E. Mettler, D. Thuault, L. Coroller, V. Stahl, M. Vialette

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49 Citations (Scopus)


An experimental protocol to validate secondary-model application to foods was suggested. Escherichia coli, Listeria monocytogenes, Bacillus cereus, Clostridium perfringens, and Salmonella were observed in various food categories, such as meat, dairy, egg, or seafood products. The secondary model validated in this study was based on the gamma concept, in which the environmental factors temperature, pH, and water activity (alpha(w)) were introduced as individual terms with microbe-dependent parameters, and the effect of foodstuffs on the growth rates of these species was described with a food- and microbe-dependent parameter. This food-oriented approach was carried out by challenge testing, generally at 15 and 10degreesC for L. monocytogenes, E. coli, B. cereus, and Salmonella and at 25 and 20degreesC for C. perfringens. About 222 kinetics in foods were generated. The results were compared to simulations generated by existing software, such as PMP. The bias factor was also calculated. The methodology to obtain a food-dependent parameter (fitting step) and therefore to compare results given by models with new independent data (validation step) is discussed in regard to its food safety application. The proposed methods were used within the French national program of predictive microbiology, Sym'Previus, to include challenge test results in the database and to obtain predictive models designed for microbial growth in food products.
Original languageEnglish
Pages (from-to)1081-1087
JournalApplied and Environmental Microbiology
Issue number2
Publication statusPublished - 2004


  • escherichia-coli o157-h7
  • listeria-monocytogenes
  • sodium-chloride
  • water activity
  • brochothrix-thermosphacta
  • thermal inactivation
  • combined temperature
  • mathematical-models
  • storage-temperature
  • microbial-growth

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