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Temperature effect on bacterial growth rate: quantitative microbiology approach including cardinal values and variability estimates to perform growth simulations on/in food
Authors:Membré Jeanne-Marie  Leporq Benoît  Vialette Michèle  Mettler Eric  Perrier Louise  Thuault Dominique  Zwietering Marcel
Affiliation:

aLGPTA-INRA, 369, Rue Jules Guesde, BP 39, 59651 Villeneuve d'Ascq Cédex, France

bInstitut Pasteur de Lille, BP 245, 59019 Lille Cédex, France

cSOREDAB, La Tremblaye, 78125 La Boissière-Ecole, France

dDanone Vitapole, route départementale 128, 91767 Palaiseau Cédex, France

eADRIA, Z.A. de Créac'h Gwen, 29196 Quimper Cédex, France

Abstract:Temperature effect on growth rates of Listeria monocytogenes, Salmonella, Escherichia coli, Clostridium perfringens and Bacillus cereus, was studied. Growth rates were obtained in laboratory medium by using a binary dilutions method in which 15 optical density curves were generated to determine one μ value. The temperature was in the range from 2 to 48 °C, depending on the bacterial species. Data were analysed after a square root transformation. No large difference between the strains of a same species was observed, and therefore all the strains of a same species were analysed together with the same secondary model. The variability of the residual error, including both measurements errors and biological strain difference, was homogenous for sub-optimal temperature values. To represent this variability in bacterial kinetic simulation, the 95% confidence interval based on an asymptotic Normal distribution, around the growth rate value was determined. With this modelling approach, the behaviour of bacterial species on food, irrespective of the strain or the laboratory, was described. This growth simulation with confidence limits has several applications, such as to facilitate comparisons between a challenge-test and simulation results, and, to appreciate if the temperature change has or has not a significant effect on a bacterial growth profile, with regard to the uncontrolled factors. The integration of this piece of work in the Sym'Previus software is now in process. Results obtained in five French laboratories will be extended by working on new food and new microbial species and improved by further work on variability estimation.
Keywords:Temperature effect  Predictive microbiology  Confidence limits  Strain variability
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