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Mathematical modeling of growth of Salmonella spp. and spoilage microorganisms in raw oysters
Affiliation:1. Program of Biomedical Science, School of Diagnostic and Applied Health Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia;2. School of Chemical Sciences and Food Technology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia;3. Drug and Herbal Research Center, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia
Abstract:The main objective of this study was to develop the primary and secondary models to describe the growth kinetics of Salmonella as well as background microorganisms in raw, shucked oysters. Samples, inoculated with a cocktail of two Salmonella serotypes, S. Typhimurium (CICC22956) and S. Enteritidis (CICC21482), were incubated at 4, 8, 12, 16, 20, 25, 30, 33, 37, 40, and 43 °C. Growth of Salmonella was observed at all temperatures, except at 4 °C. The background microorganisms grew at all temperatures. All growth curves clearly exhibited lag, exponential and stationary phases, and were analyzed using the Huang growth model. Three secondary models (Ratkowsky square-root, Huang square-root, and Cardinal parameter models) were compared for evaluating the effect of temperature on bacterial growth rates. Data analysis was performed using IPMP 2013, a free predictive microbiology software tool developed by the USDA ARS.The Cardinal parameters model underestimated the specific rates of the microorganisms at low temperatures. The Huang square-root model was more suitable than the Ratkowsky square-root model for describing the effect of temperature on growth of Salmonella, while the Ratkowsky square-root model, on the other hand, was more suitable for background microorganisms. For both Salmonella and background microorganisms, the logarithms of the lag phase were expressed as linear functions of the logarithms of specific growth rates. The results of this study can be used by the food retailers and regulatory agencies to estimate the microbial shelf-life of raw, shucked oysters.
Keywords:Mathematical model  Spoilage microorganisms  Oysters
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