Literature DB >> 17140686

Modeling the growth of Listeria monocytogenes based on a time to detect model in culture media and frankfurters.

Francisco Diez-Gonzalez1, Daniel Belina, Theodore P Labuza, Amit Pal.   

Abstract

In the current study, temperature dependent growth of Listeria monocytogenes strain H7776, with an initial inoculum level of approximately 0.1 CFU/mL or g, was modeled based on "time to detect" (TTD) using the Arrhenius equation. The activation energies (E(a)) obtained from specific growth rate and lag phase duration in tryptic soy broth (TSB) and frankfurters were compared. At 4 degrees C, the TTD for L. monocytogenes was 217 h in TSB and 48 h in portions of frankfurters. The TTD decreased as temperature increased from 4 to 36 degrees C in both culture media and frankfurters, and this relationship was modeled using the Arrhenius equation. Based on this model, the E(a) values for the TTD in TSB and frankfurters averaged 22.7 and 18.7 kcal/mol, respectively, and were not significantly different (p<0.05). Linear regression was performed on the exponential part of the growth curve to evaluate specific growth rate constants at each temperature using the Monod model. The E(a) values were also calculated based on the specific growth rate and the lag phase of L. monocytogenes in TSB and frankfurters incubated in the same range of temperatures. The average E(a) values for the specific growth rates and the lag phase durations in TSB cultures were 19 and 21 kcal/mol, respectively. In frankfurters, the average E(a) values were slightly greater for both specific growth rate and lag phase duration (29 and 35 kcal/mol, respectively), but these values were not significantly different from the E(a) calculated for the TTD in each medium. These results indicate that the TTD concept can be used to develop and validate safety-based shelf life models.

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Year:  2006        PMID: 17140686     DOI: 10.1016/j.ijfoodmicro.2006.08.011

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  2 in total

1.  A random effect multiplicative heteroscedastic model for bacterial growth.

Authors:  Ricardo Cao; Mario Francisco-Fernández; Emiliano J Quinto
Journal:  BMC Bioinformatics       Date:  2010-02-08       Impact factor: 3.169

2.  Development of a microbial time/temperature indicator prototype for monitoring the microbiological quality of chilled foods.

Authors:  Hariklia Vaikousi; Costas G Biliaderis; Konstantinos P Koutsoumanis
Journal:  Appl Environ Microbiol       Date:  2008-03-07       Impact factor: 4.792

  2 in total

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