The Development Of Detection Method By Real-time PCR And Predictive Model Of Salmonella Spp. On Surimi

Salmonella spp. is the most common pathogenic bacteria that cause bacterial food poisoning. In this paper, a selective enrichment broth was obtained to allow rapid growth of Salmonella spp. by the study about basal medium, growth promoters, inhibitors and so on. Based on this, A method was developed for the detection of Salmonella spp. by conventional PCR and real-time fluorescent PCR. According to invA gene, a set of primers were designed to perform standard curve, specificity, sensitivity and simulation sample tests by real-time PCR. The results indicated that the developed method by real-time PCR can detect Salmonella spp. rapidly and accurately. It is of great significance for diagnosis and control of Salmonella spp. in food. The growth of Salmonella Typhimurium. in different temperatures (at 4,10,20,28℃ and 37℃) was compared on fresh surimi and the primary model was developed by Huang model, Baranyi model and modified Gompertz model. The square root model was selected as the secondary model to describe the relationship between temperature and specific growth rate or lag time. The results indicated that the modified Gompertz model may describe the growth of S. Typhimurium. better than Huang model and Baranyi model on surimi. The Polynomial equation model can be used to describe the growth parameters of S. Typhimurium. on surimi. In addition, the influence of variables, namely citric acid concentration (0.5%,1% and 2%), process temperature (4 and 25℃) and time (1-15 min) on the inactivation of S. Typhimurium. were also investigated. In order to describe the kinetics of 5. Typhimurium., BP-ANN and PSO BP-ANN was used to develop predictive models for simulation the dynamic of amount of S. Typhimurium. A comparison between the results of the proposed new model with PSO algorithm shows that the predictive model is more accurate.