Literature DB >> 15615424

Calculating microbial survival parameters and predicting survival curves from non-isothermal inactivation data.

Micha Peleg1, Mark D Normand.   

Abstract

Irrespective of whether the isothermal semi-logarithmic survival curves of heat inactivated microbial cells or spores are linear or nonlinear, it is theoretically possible to numerically calculate their survival parameters from inactivation data obtained under non-isothermal conditions. A method to do the calculation, when the temperature history ('profile') is expressed algebraically, is demonstrated with simulated survival curves. It has been tested with the published survival data of Salmonella, whose nonlinear semi-logarithmic isothermal survival curves can be described by a power law model. The reported survival ratios of Salmonella, determined during non-isothermal heat treatments in a broth and in ground chicken breast, were used to estimate its isothermal survival parameters in the two media and their temperature dependence. These, in turn, were used to predict the cells' survival curves under different temperature 'profiles.' There was a good agreement between the predicted and the reported experimental survival curves in the broth case and reasonable agreement in the ground chicken breasts, where the database was considerably smaller The development of a mathematical method to calculate survival parameters from non-isothermal inactivation data will eliminate the need to determine these parameters under isothermal conditions, which can only be approximated and are technically difficult to perform. In many cases, the proposed method will also enable the determination of the survival parameters in the actual food or medium of interest, which may contain particles, or is too viscous to be heated and cooled effectively using the currently available experimental procedures. In principle, the described mathematical method can also be used to assess organisms' survival parameters in nonthermal inactivation processes, such as exposure to a dissipating chemical agent or the application of ultra high-pressure.

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Year:  2004        PMID: 15615424     DOI: 10.1080/10408690490489297

Source DB:  PubMed          Journal:  Crit Rev Food Sci Nutr        ISSN: 1040-8398            Impact factor:   11.176


  6 in total

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2.  Modeling of pathogen survival during simulated gastric digestion.

Authors:  Shige Koseki; Yasuko Mizuno; Itaru Sotome
Journal:  Appl Environ Microbiol       Date:  2010-12-03       Impact factor: 4.792

3.  Dynamic model of heat inactivation kinetics for bacterial adaptation.

Authors:  Maria G Corradini; Micha Peleg
Journal:  Appl Environ Microbiol       Date:  2009-02-06       Impact factor: 4.792

4.  Evaluation of Strain Variability in Inactivation of Campylobacter jejuni in Simulated Gastric Fluid by Using Hierarchical Bayesian Modeling.

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Journal:  Appl Environ Microbiol       Date:  2021-07-13       Impact factor: 4.792

5.  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

6.  Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment.

Authors:  Kento Koyama; Hidekazu Hokunan; Mayumi Hasegawa; Shuso Kawamura; Shigenobu Koseki
Journal:  Appl Environ Microbiol       Date:  2017-02-01       Impact factor: 4.792

  6 in total

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