Literature DB >> 19201963

Dynamic model of heat inactivation kinetics for bacterial adaptation.

Maria G Corradini1, Micha Peleg.   

Abstract

The Weibullian-log logistic (WeLL) inactivation model was modified to account for heat adaptation by introducing a logistic adaptation factor, which rendered its "rate parameter" a function of both temperature and heating rate. The resulting model is consistent with the observation that adaptation is primarily noticeable in slow heat processes in which the cells are exposed to sublethal temperatures for a sufficiently long time. Dynamic survival patterns generated with the proposed model were in general agreement with those of Escherichia coli and Listeria monocytogenes as reported in the literature. Although the modified model's rate equation has a cumbersome appearance, especially for thermal processes having a variable heating rate, it can be solved numerically with commercial mathematical software. The dynamic model has five survival/adaptation parameters whose determination will require a large experimental database. However, with assumed or estimated parameter values, the model can simulate survival patterns of adapting pathogens in cooked foods that can be used in risk assessment and the establishment of safe preparation conditions.

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Year:  2009        PMID: 19201963      PMCID: PMC2675227          DOI: 10.1128/AEM.02167-08

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  22 in total

Review 1.  Modeling microbial survival during exposure to a lethal agent with varying intensity.

Authors:  M Peleg; C M Penchina
Journal:  Crit Rev Food Sci Nutr       Date:  2000-03       Impact factor: 11.176

2.  Structural model requirements to describe microbial inactivation during a mild heat treatment.

Authors:  A H Geeraerd; C H Herremans; J F Van Impe
Journal:  Int J Food Microbiol       Date:  2000-09-10       Impact factor: 5.277

3.  On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells.

Authors:  Martinus A J S van Boekel
Journal:  Int J Food Microbiol       Date:  2002-03-25       Impact factor: 5.277

4.  On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model.

Authors:  P Mafart; O Couvert; S Gaillard; I Leguerinel
Journal:  Int J Food Microbiol       Date:  2002-01-30       Impact factor: 5.277

5.  Calculating Salmonella inactivation in nonisothermal heat treatments from isothermal nonlinear survival curves.

Authors:  K L Mattick; J D Legan; T J Humphrey; M Peleg
Journal:  J Food Prot       Date:  2001-05       Impact factor: 2.077

6.  Prediction of an organism's inactivation patterns from three single survival ratios determined at the end of three non-isothermal heat treatments.

Authors:  Maria G Corradini; Mark D Normand; Micha Peleg
Journal:  Int J Food Microbiol       Date:  2008-05-15       Impact factor: 5.277

7.  Mathematical modelling of the heat resistance of Listeria monocytogenes.

Authors:  J C Augustin; V Carlier; J Rozier
Journal:  J Appl Microbiol       Date:  1998-02       Impact factor: 3.772

Review 8.  Tailing of survival curves of bacterial spores.

Authors:  O Cerf
Journal:  J Appl Bacteriol       Date:  1977-02

9.  Estimation of the non-isothermal inactivation patterns of Bacillus sporothermodurans IC4 spores in soups from their isothermal survival data.

Authors:  P M Periago; A van Zuijlen; P S Fernandez; P M Klapwijk; P F ter Steeg; M G Corradini; M Peleg
Journal:  Int J Food Microbiol       Date:  2004-09-01       Impact factor: 5.277

10.  A low-pH-inducible, stationary-phase acid tolerance response in Salmonella typhimurium.

Authors:  I S Lee; J L Slonczewski; J W Foster
Journal:  J Bacteriol       Date:  1994-03       Impact factor: 3.490

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  2 in total

1.  Relevance of the Induced Stress Resistance When Identifying the Critical Microorganism for Microbial Risk Assessment.

Authors:  Alberto Garre; Jose A Egea; Asunción Iguaz; Alfredo Palop; Pablo S Fernandez
Journal:  Front Microbiol       Date:  2018-07-24       Impact factor: 5.640

2.  Explicit numerical solutions of a microbial survival model under nonisothermal conditions.

Authors:  Si Zhu; Guibing Chen
Journal:  Food Sci Nutr       Date:  2015-11-14       Impact factor: 2.863

  2 in total

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