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Growth limits of Listeria monocytogenes as a function of temperature, pH, NaCl, and lactic acid
Models describing the limits of growth of pathogens under multiple constraints will aid management of the safety of foods which are sporadically contaminated with pathogens and for which subsequent growth of the pathogen would significantly increase the risk of food-borne illness. We modeled the eff...
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Published in: | Applied and environmental microbiology 2000-11, Vol.66 (11), p.4979-4987 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Models describing the limits of growth of pathogens under multiple constraints will aid management of the safety of foods which are sporadically contaminated with pathogens and for which subsequent growth of the pathogen would significantly increase the risk of food-borne illness. We modeled the effects of temperature, water activity, pH, and lactic acid levels on the growth of two strains of Listeria monocytogenes in tryptone soya yeast extract broth. The results could be divided unambiguously into "growth is possible" or "growth is not possible" classes. We observed minor differences in growth characteristics of the two L. monocytogenes strains. The data follow a binomial probability distribution and may be modeled using logistic regression. The model used is derived from a growth rate model in a manner similar to that described in a previously published work (K. A. Presser, T. Ross, and D. A. Ratkowsky, Appl. Environ. Microbiol. 64:1773-1779, 1998). We used "nonlinear logistic regression" to estimate the model parameters and developed a relatively simple model that describes our experimental data well. The fitted equations also described well the growth limits of all strains of L. monocytogenes reported in the literature, except at temperatures beyond the limits of the experimental data used to develop the model (3 to 35 degrees C). The models developed will improve the rigor of microbial food safety risk assessment and provide quantitative data in a concise form for the development of safer food products and processes. |
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ISSN: | 0099-2240 1098-5336 |
DOI: | 10.1128/AEM.66.11.4979-4987.2000 |