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| Author: | M. Cornu |
| Keywords: | microbial interactions, predictive microbiology |
Abstract:
Current models used in predictive microbiology take into account a precise description of the effect of environmental conditions, but often neglect the effect of the background microflora, i.e. microbial interactions.
Different approaches have been recently proposed to model these interactions, but few are applicable for integration into simple predictive modelling.
We propose a differential model based on a simple competition hypothesis.
This model could satisfactorily describe most growth curves extracted from the literature, proving that this simple competition hypothesis is in most cases adequate to describe the interactions between natural food flora and L. monocytogenes. This model could provide a simple way to predict growth of a foodborne pathogen in different naturally contaminated media or foods, providing that the growth characteristics of this pathogen and those of the background flora are known.
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