Comparison of Primary Models to Predict Microbial Growth by the Plate Count and Absorbance Methods

The selection of a primary model to describe microbial growth in predictive food microbiology often appears to be subjective. The objective of this research was to check the performance of different mathematical models in predicting growth parameters, both by absorbance and plate count methods. For...

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Bibliographic Details
Published inBioMed research international Vol. 2015; no. 2015; pp. 1 - 14
Main Authors Andreu, Santiago, Esteban, María-Dolores, Oltra, Sandra, Pla, María-Leonor, Palop, Alfredo
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2015
John Wiley & Sons, Inc
Hindawi Limited
Subjects
Bacillus cereus - growth & development
Biomedical research
Escherichia coli - growth & development
Food
Food Microbiology
Growth
Growth rate
Health aspects
Humans
Kinetics
Listeria monocytogenes - growth & development
Mathematical models
Mean square errors
Methods
Microbial colonies
Microorganisms
Models, Theoretical
Physiology
Population
Studies
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Summary:The selection of a primary model to describe microbial growth in predictive food microbiology often appears to be subjective. The objective of this research was to check the performance of different mathematical models in predicting growth parameters, both by absorbance and plate count methods. For this purpose, growth curves of three different microorganisms (Bacillus cereus, Listeria monocytogenes, and Escherichia coli) grown under the same conditions, but with different initial concentrations each, were analysed. When measuring the microbial growth of each microorganism by optical density, almost all models provided quite high goodness of fit (r2>0.93) for all growth curves. The growth rate remained approximately constant for all growth curves of each microorganism, when considering one growth model, but differences were found among models. Three-phase linear model provided the lowest variation for growth rate values for all three microorganisms. Baranyi model gave a variation marginally higher, despite a much better overall fitting. When measuring the microbial growth by plate count, similar results were obtained. These results provide insight into predictive microbiology and will help food microbiologists and researchers to choose the proper primary growth predictive model.
Bibliography:Academic Editor: Avelino Alvarez-Ordóñez
ISSN:2314-6133
2314-6141
DOI:10.1155/2015/365025