Literature DB >> 27207811

Microbial variability in growth and heat resistance of a pathogen and a spoiler: All variabilities are equal but some are more equal than others.

Heidy M W den Besten1, Diah C Aryani2, Karin I Metselaar2, Marcel H Zwietering2.   

Abstract

Quantitative microbiology is used in risk assessment studies, microbial shelf life studies, product development, and experimental design. Realistic prediction is, however, complicated by different sources of variability. The final concentration of microorganisms at the moment of consumption is affected by different sources of variability: variability in the storage times and temperatures, variability in product characteristics, variability in process characteristics, variability in the initial contamination of the raw materials, and last but not least, microbiological variability. This article compares different sources of microbiological variability in growth and inactivation kinetics of a pathogen and a spoiler, namely experimental variability, reproduction variability (within strain variability), strain variability (between strain variability) and variability between individual cells within a population (population heterogeneity). Comparison of the different sources of microbiological variability also allows to prioritize their importance. In addition, the microbiological variability is compared to other variability factors encountered in a model food chain to evaluate the impact of different variability factors on the variability in microbial levels encountered in the final product. Copyright Â
© 2016 Elsevier B.V. All rights reserved.

Keywords:  Diversity; Heterogeneity; Prediction; Quantitative risk assessment; Sensitivity analysis

Mesh:

Year:  2016        PMID: 27207811     DOI: 10.1016/j.ijfoodmicro.2016.04.025

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


  8 in total

1.  Modeling Invasion of Campylobacter jejuni into Human Small Intestinal Epithelial-Like Cells by Bayesian Inference.

Authors:  Hiroki Abe; Kento Koyama; Shigenobu Koseki
Journal:  Appl Environ Microbiol       Date:  2020-12-17       Impact factor: 4.792

Review 2.  Underscoring interstrain variability and the impact of growth conditions on associated antimicrobial susceptibilities in preclinical testing of novel antimicrobial drugs.

Authors:  David A Sanchez; Luis R Martinez
Journal:  Crit Rev Microbiol       Date:  2018-12-06       Impact factor: 7.624

3.  Competitive growth kinetics of Campylobacter jejuni, Escherichia coli O157:H7 and Listeria monocytogenes with enteric microflora in a small-intestine model.

Authors:  Yuto Fuchisawa; Hiroki Abe; Kento Koyama; Shigenobu Koseki
Journal:  J Appl Microbiol       Date:  2021-09-23       Impact factor: 4.059

4.  Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples.

Authors:  Emilie Cauchie; Laurent Delhalle; Ghislain Baré; Assia Tahiri; Bernard Taminiau; Nicolas Korsak; Sophie Burteau; Papa Abdoulaye Fall; Frédéric Farnir; Georges Daube
Journal:  Front Microbiol       Date:  2020-04-09       Impact factor: 5.640

5.  Assessment of Spoilage Bacterial Communities in Food Wrap and Modified Atmospheres-Packed Minced Pork Meat Samples by 16S rDNA Metagenetic Analysis.

Authors:  Emilie Cauchie; Laurent Delhalle; Bernard Taminiau; Assia Tahiri; Nicolas Korsak; Sophie Burteau; Papa Abdoulaye Fall; Frédéric Farnir; Ghislain Baré; Georges Daube
Journal:  Front Microbiol       Date:  2020-01-21       Impact factor: 5.640

6.  Quantifying the Responses of Three Bacillus cereus Strains in Isothermal Conditions and During Spray Drying of Different Carrier Agents.

Authors:  Verônica O Alvarenga; Fernanda B Campagnollo; Arthur K R Pia; Deborah A Conceição; Yuri Abud; Celso Sant'Anna; Miriam D Hubinger; Anderson S Sant'Ana
Journal:  Front Microbiol       Date:  2018-05-29       Impact factor: 5.640

7.  From Culture-Medium-Based Models to Applications to Food: Predicting the Growth of B. cereus in Reconstituted Infant Formulae.

Authors:  Nathália Buss da Silva; József Baranyi; Bruno A M Carciofi; Mariem Ellouze
Journal:  Front Microbiol       Date:  2017-09-21       Impact factor: 5.640

8.  A quantitative study on growth variability and production of ochratoxin A and its derivatives by A. carbonarius and A. niger in grape-based medium.

Authors:  Luísa Freire; Tatiane M Guerreiro; Arthur K R Pia; Estela O Lima; Diogo N Oliveira; Carlos F O R Melo; Rodrigo R Catharino; Anderson S Sant'Ana
Journal:  Sci Rep       Date:  2018-10-01       Impact factor: 4.379

  8 in total

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