Abstract
The Salmonella growth was monitored in pasteurized and non- pasteurized milk using real-time PCR, and growth prediction model was constructed based on the results. Pasteurized and non- pasteurized milk were inoculated with Salmonella to a concentration of 104 CFU/ml, and the Salmonella growth was monitored for 168 hours at 4℃ to 35℃ using traditional culture method and real-time PCR. With real-time PCR, total-DNA was directly extracted from 1 ml of pasteurized and non- pasteurized milk, and the copy number of Salmonella invA was quantified and converted to the Salmonella cell count. The Salmonella cell counts estimated by traditional culture method and real-time PCR in pasteurized milk were very similar, and these results were reflecting the MRV predictive model. A predictive growth curve was constructed from the Salmonella cell count estimated using real-time PCR, and a relational expression for the maximum growth rate (μmax) and incubation temperature was derived using the square-root model. Comparison of μmax between pasteurized and non-pasteurized milk showed a slightly lower μmax of Salmonella for non- pasteurized milk compared to pasteurized milk, and the maximum cell concentration also tended to be lower for non- pasteurized milk. Application of the real-time PCR monitoring and predictive microbiological analysis enables rapid provision of a growth prediction formula that includes the effects of microbacterial flora and food matrices.
