A new logistic model for Escherichia coli growth at constant and dynamic temperatures |
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| Affiliation: | 1. Department of Horticulture and Crop Science, California Polytechnic State University, 1 Grand Ave, San Luis Obispo, CA 93405, USA;2. Department of Food Science and Human Nutrition, Iowa State University, 2312 Food Sciences Building, Ames, IA 50011, USA;3. Finance Department, California Polytechnic State University, 1 Grand Ave, San Luis Obispo, CA 93405, USA;4. Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI 48865, USA;1. Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece;2. Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Iera Odos 75, Athens 11855, Greece;3. Department of Food Science and Technology, Perrotis College, American Farm School, Thessaloniki 55102, Greece;1. Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, 14469 Potsdam, Germany;2. Institute of Animal Hygiene and Environmental Health, Department of Veterinary Medicine, Free University Berlin, Robert-von-Ostertag-Str. 7-13, 14163 Berlin, Germany;1. Institute of Food Science and Nutrition, Faculty of Chemical and Food Technology, Slovak University of Technology Bratislava, Slovakia;2. Institute of Chemical and Environmental Engineering, Faculty of Chemical and Food Technology, Slovak University of Technology Bratislava, Slovakia |
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| Abstract: | A new logistic model for bacterial growth was developed in this study. The model, which is based on the logistic model, contains an additional term for expression of the very low rate of growth during a lag phase, in its differential equation. The model successfully described sigmoidal growth curves of Escherichia coli at various initial cell concentrations and constant temperatures. The model predicted well the bacterial growth curves, similar to the Baranyi model and better than the modified Gompertz model, especially in terms of the rate constant and the lag period of the growth curves. Using the experimental data obtained at the constant temperatures, the new logistic model was studied for growth prediction at a dynamic temperature. The model accurately described E. coli growth curves at various patterns of dynamic temperature. It also well described other bacterial growth curves reported by other investigators. These results showed that this model could be a useful tool for bacterial growth prediction from the temperature history of a tested food. |
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