Modelling the growth boundaries of Listeria monocytogenes: focus on strain variability and organic acids.

Authors

Yvan Le Marc, Elena Cosciani-Cunico, Marie-Laure Le Cardunier, Elena Dalzini, Nicolas Nguyen Van Long

Published in

Journal of food protection. Pages 100890. Aug 11, 2026. Epub Aug 11, 2026.

Abstract

Listeria monocytogenes is a major food safety concern, notably because of its ability to grow in a wide range of environmental conditions. Since this pathogen generally requires high infectious doses to cause illness, reliable models describing its growth boundaries as a function of temperature, pH, water activity (a_w), but also preservatives (e.g., organic acids) are essential for accurate risk assessment. This study proposes a growth/ no growth model, based on an 'interaction term', for the effects of eight environmental factors (temperature, pH, a_w, lactic, acetic, sorbic, propionic and citric acids). In that model, single values for strain-dependent model parameters were replaced, wherever possible, with statistical distributions, making it possible to describe the intra-species variability in the growth capabilities of L. monocytogenes. The distributions of the Minimum Inhibitory Concentrations (MIC) of lactic, acetic, propionic and citric acids are based on values for 33, 14, 9, 8 different Listeria strains, respectively. The information available on sorbic acid is limited, and the distribution has been derived from two MIC values retrieved from the literature. For model evaluation, a literature review was conducted to compile growth/no growth data for L. monocytogenes primarily in culture media, but also in model food matrices and food products (dairy, seafood, and meat-based products). In total, 3060 growth/no growth data were compiled in culture media and 622 in model foods and food products. The model predictions for the transition from "no growth" to "possible growth" usually provided correct or fail-safe predictions. Some "fail-safe" predictions in food products are associated with curing or the presence of high concentrations of lactic acid bacteria. Further model validation will be necessary, especially for citric and propionic acids, where data gaps have been acknowledged.

PMID:
42580634
Bibliographic data and abstract were imported from PubMed on 12 Aug 2026.

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