The Biological Characters Of C.sakazakii And Studies On Predictive Models Of C.sakazakii In Reconstituted Powdered Infant Formula

Cronobacter sakazakii(C.sakazakii)is an emerging foodborn pathogen which is parasitic on gut of human and animals.It can cause neonatal meningitis,septicemia and necrotizing enterocolitis.However infant formula milk powder(PIF)has been implicated as the source of transmission in neonatal infections.To solve the problem of PIF caused by C.sakazakii and estimate and control the survival condition of the microorganisms in PIF effectively and then found a safe and effective control method,this research studied the growth biological characteristics of C.sakazakii and develope predictive models for the growth of C.sakazakii in PIF,and then discussed the effect of cold shock treatment on C.sakazakii.The main results were shown as follows:(1)The influences of temperature,NaCl concentration and pH value on C.sakazakii have been studied,results showed that the optimum growth temperature for C.sakazakii was 35??40?,the optimum range of NaCl concentration for C.sakazakii was 1%?3%and the optimum range of pH value for C.sakazakii was 5?8.It also showed that the influences of temperature,NaCl concentration and pH value on C.sakakii is significant.(2)The growth data were fitted to four primary models(Baranyi model,Huang model,Gompertz model,and Three-Phase Linear)to describe the growth of C.sakazakii at each isothermal condition at 8?,10?,15?,20?,25?,30?,33?,37?,43?.Results showed that under 8?,the population of C.sakazakii increased firstly and then decreased gradually which were not accord with the rule of primary models,thus the data under 8? can not be fitted to primary models.However under other temperatures,Baranyi model was particularly suitable for describing the growth of C.sakazakii in PIF than Huang model,Gompertz model and Three-Phase Linear model.The growth curve of C.sakazakii in PIF presented as S that came through lag phase,logarithmic phase and stationary phase.The lag phase decreased with the temperature increased,however the growth rate increased with temperature increased.As for background microorganisms,Baranyi model also showed the fit indicators of the model are good.The population of background microorganisms increased slower at the beginning and then grew rapidly at exponential phases and ultimately the population were constant at stationary phases.The lag phase became shorter with the temperature increased,however the growth rate ? increased with temperature increased.(3)Four different secondary models(Ratkowsky models,Huang models,Cardinal models and Arrhenius-type models)were used to describe the effect of temperature on the growth rate of C.sakazakii for each product.Results showed that the secondary model of C.sakazakii in PIF was Huang square-root model,and the estimated minimum and maximum temperatures of the growth of Salmonella were 7.3? and 48.3?,the predictive a value and b value were 0.122 and 0.283,respectively.However the secondary model of background microorganisms in PIF was Cardinal model and the estimated minimum and maximum temperatures of the growth of background microorganisms were 5.990? and 48.191?,and Topt and ?opt were 40.665? and 2.239,respectively.The establishment of predictive models can be used to set critical limits and conduct risk assessment to prevent or reduce potential risk of C.sakazakii growth in PIF.The establishment of these models can help regulatory agencies and food retailers to develop safe storage temperatures for PIF and predict the microbial shelf-life of PIF.(4)The influences of cold shock on C.sakazakii in PIF under 37? were studied,and the growth data were fitted to Baranyi model,Huang model,Gompertz model,and Three-Phase Linear.The fitting curves and the fitting parameters of AIC and RMSE showed Baranyi model was particularly suitable for describing the growth of C.sakazakii after cold shock in PIF,and AIC was from-16.077 to-5.044,RMSE was from 0.272 to 0.431.The growth curve of C.sakazakii in PIF presented as S that come through lag phase,logarithmic phase and stationary phase.The lag phase increased with the time of cold shock extended.As for background microorganisms,Baranyi model also showed the fitting indicators of the model were good.The population of background microorganisms increased slower at the beginning and then grew rapidly at exponential phases and ultimately the population were constant at stationary phases.The lag phase became shorter with the temperature increased.The utility of these models can help regulatory agencies and food retailers to develop safe storage temperatures for PIF and predict the microbial shelf-life of PIF.