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Effect of temperature, water-phase salt and phenolic contents on Listeria monocytogenes growth rates on cold-smoked salmon and evaluation of secondary models

Author:
Cornu, M., Beaufort, A., Rudelle, S., Laloux, L., Bergis, H., Miconnet, N., Serot, T., Delignette-Muller, M.L.
Source:
International journal of food microbiology 2006 v.106 no.2 pp. 159-168
ISSN:
0168-1605
Subject:
salmon, smoked fish, cured foods, salted fish, salting, smoking (food products), smoke, phenolic compounds, food preservation, food storage, cold storage, storage temperature, water activity, salt concentration, food contamination, food spoilage, Listeria monocytogenes, food pathogens, viability, predictive microbiology, mathematical models, model validation, pH, lactates, dissolved organic carbon, quantitative risk assessment
Abstract:
Salting and smoking are ancient processes for fish preservation. The effects of salt and phenolic smoke compounds on the growth rate of L. monocytogenes in cold-smoked salmon were investigated through physico-chemical analyses, challenge tests on surface of cold-smoked salmon at 4 °C and 8 °C, and a survey of the literature. Estimated growth rates were compared to predictions of existing secondary models, taking into account the effects of temperature, water phase salt content, phenolic content, and additional factors (e.g. pH, lactate, dissolved CO2). The secondary model proposed by Devlieghere et al. [Devlieghere, F., Geeraerd, A.H., Versyck, K.J., Vandewaetere, B., van Impe, J., Debevere, J., 2001. Growth of Listeria monocytogenes in modified atmosphere packed cooked meat products: a predictive model. Food Microbiology 18, 53-66.] and modified by Giménez and Dalgaard [Giménez, B., Dalgaard, P., 2004. Modelling and predicting the simultaneous growth of Listeria monocytogenes and spoilage micro-organisms in cold-smoked salmon. Journal of Applied Microbiology 96, 96-109.] appears appropriate. However, further research is needed to understand all effects affecting growth of L. monocytogenes in cold-smoked salmon and to obtain fully validated predictive models for use in quantitative risk assessment.
Agid:
684703