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http://dx.doi.org/10.5851/kosfa.2010.30.5.730

Development of Predictive Growth Models for Staphylococcus aureus and Bacillus cereus on Various Food Matrices Consisting of Ready-to-Eat (RTE) Foods  

Kang, Kyung-Ah (Department of Food and Nutrition, Research Institute of Human Ecology, Kyung Hee University)
Kim, Yoo-Won (Department of Food and Nutrition, Research Institute of Human Ecology, Kyung Hee University)
Yoon, Ki-Sun (Department of Food and Nutrition, Research Institute of Human Ecology, Kyung Hee University)
Publication Information
Food Science of Animal Resources / v.30, no.5, 2010 , pp. 730-738 More about this Journal
Abstract
We developed predictive growth models for Staphylococcus aureus and Bacillus cereus on various food matrices consisting primarily of ready-to-eat (RTE) foods. A cocktail of three S. aureus strains, producing enterotoxins A, C, and D, or a B. cereus strain, were inoculated on sliced bread, cooked rice, boiled Chinese noodles, boiled bean sprouts, tofu, baked fish, smoked chicken, and baked hamburger patties at an initial concentration of 3 log CFU/g and stored at 8, 10, 13, 17, 24, and $30^{\circ}C$. Growth kinetic parameters were determined by the Gompertz equation. The square-root and Davey models were used to determine specific growth rate and lag time values, respectively, as a function of temperature. Model performance was evaluated based on bias and accuracy factors. S. aureus and B. cereus growth were most delayed on sliced bread. Overall, S. aureus growth was significantly (p<0.05) more rapid on animal protein foods than carbohydrate-based foods and vegetable protein foods. The fastest growth of S. aureus was observed on smoked chicken. B. cereus growth was not observed at 8 and $10^{\circ}C$. B. cereus growth was significantly (p<0.05) more rapid on vegetable protein foods than on carbohydrate-based foods. The secondary models developed in this study showed suitable performance for predicting the growth of S. aureus and B. cereus on various food matrices consisting of RTE foods.
Keywords
S. aureus; B. cereus; animal protein foods; food matrices; predictive modeling;
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