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New mathematical modeling approach for predicting microbial inactivation by high hydrostatic pressure

Klotz, B., Pyle, D.L. and Mackey, B.M. (2007) New mathematical modeling approach for predicting microbial inactivation by high hydrostatic pressure. Applied and Environmental Microbiology, 73 (8). pp. 2468-2478. ISSN 0099-2240

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To link to this item DOI: 10.1128/AEM.02211-06


A new primary model based on a thermodynamically consistent first-order kinetic approach was constructed to describe non-log-linear inactivation kinetics of pressure-treated bacteria. The model assumes a first-order process in which the specific inactivation rate changes inversely with the square root of time. The model gave reasonable fits to experimental data over six to seven orders of magnitude. It was also tested on 138 published data sets and provided good fits in about 70% of cases in which the shape of the curve followed the typical convex upward form. In the remainder of published examples, curves contained additional shoulder regions or extended tail regions. Curves with shoulders could be accommodated by including an additional time delay parameter and curves with tails shoulders could be accommodated by omitting points in the tail beyond the point at which survival levels remained more or less constant. The model parameters varied regularly with pressure, which may reflect a genuine mechanistic basis for the model. This property also allowed the calculation of (a) parameters analogous to the decimal reduction time D and z, the temperature increase needed to change the D value by a factor of 10, in thermal processing, and hence the processing conditions needed to attain a desired level of inactivation; and (b) the apparent thermodynamic volumes of activation associated with the lethal events. The hypothesis that inactivation rates changed as a function of the square root of time would be consistent with a diffusion-limited process.

Item Type:Article
Divisions:Life Sciences > School of Chemistry, Food and Pharmacy > Department of Food and Nutritional Sciences
ID Code:13247

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