Literature DB >> 15854693

Germination and growth from spores: variability and uncertainty in the assessment of food borne hazards.

G C Barker1, P K Malakar, M W Peck.   

Abstract

We have developed a model for the variability of spore lag times and shown that variability has an important role in the quantitative assessment of risks associated with spore forming bacteria in food. The model includes two sequential independent delay times that contribute to the lag time for a single spore. We have shown that a population of variable spores also has a variable lag time, and we have emphasised the significance of this variability in quantitative representations of population dynamics for small populations. We have made a Bayesian estimate for the extent of the variability in spore lag times and made a comparison with direct microscopic observations of individual spores of nonproteolytic Clostridium botulinum. We conclude that Bayesian inference is a practical method for quantifying variability and hence a significant element in the development of quantitative risk assessments for hazards associated with spore forming bacteria.

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Mesh:

Year:  2004        PMID: 15854693     DOI: 10.1016/j.ijfoodmicro.2004.10.020

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


  6 in total

1.  Heterogeneity of times required for germination and outgrowth from single spores of nonproteolytic Clostridium botulinum.

Authors:  Sandra C Stringer; Martin D Webb; Susan M George; Carmen Pin; Michael W Peck
Journal:  Appl Environ Microbiol       Date:  2005-09       Impact factor: 4.792

2.  Historical and contemporary NaCl concentrations affect the duration and distribution of lag times from individual spores of nonproteolytic clostridium botulinum.

Authors:  Martin D Webb; Carmen Pin; Michael W Peck; Sandra C Stringer
Journal:  Appl Environ Microbiol       Date:  2007-02-02       Impact factor: 4.792

3.  Estimating risk from small inocula by using population growth parameters.

Authors:  P K Malakar; G C Barker
Journal:  Appl Environ Microbiol       Date:  2009-07-31       Impact factor: 4.792

4.  Analysis of the variability in the number of viable bacteria after mild heat treatment of food.

Authors:  J S Aguirre; C Pin; M R Rodríguez; G D García de Fernando
Journal:  Appl Environ Microbiol       Date:  2009-10-02       Impact factor: 4.792

5.  Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling.

Authors:  Kento Koyama; Zafiro Aspridou; Shige Koseki; Konstantinos Koutsoumanis
Journal:  Front Microbiol       Date:  2019-09-25       Impact factor: 5.640

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

Authors:  Kento Koyama; Jukka Ranta; Kohei Takeoka; Hiroki Abe; Shige Koseki
Journal:  Appl Environ Microbiol       Date:  2021-07-13       Impact factor: 4.792

  6 in total

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