Development Of Growth Model And Thermal Inactivation Model Of Salmonella In Chilled Beef

Salmonella,a genus of the family Enterobacteriaceae,is gram-negative and widely exists in the nature.Since it is asymptomatically carried by cattle and related with the contamination of beef and responding beef products closely,so it does harm to the quality safety of beef products seriously;what is more,Salmonella is a zoonotic pathogen and one of main foodborne pathogens,which is a leading cause of bacterial foodborne disease outbreaks in the whole world and continues to be a concern of public health significance to food processors,regulatory agencies and consumers.Traditional tests of microorganisms are laborious and time-consuming,so the results are too late to predict andtake precautions in advance.Microbiological predictive models can control the survival and growth of pathogen and grasp the growth rules of microbial organisms during different temperatures,and therefore mathematical models can ensure the safety of products through inspecting the actual process,distribution,storage and so on.Salmonella strains were inoculated to the surface of contamination-free chilled beef,then samples were placed at the followed storage conditions: 0,4,7,10,15 and 20℃,and Salmonella kinetic growth curves were monitored during different storage periods.The primary predictive model of Salmonella was developed by the modified Gompertz equation or Linear equation.The secondary predictive model was established by the Ratkowsy-square root model.At last,validating model effectiveness under constant temperature and variable temperature conditions were established,respectively.In an effort to control the salmonella,the thermal inactivation of Salmonella in beef was developed: 4 strains of Salmonella were inoculated and meat samples were heated at 55,57.5,60,62.5 and 65℃ respectively.The survival curves were fitted with Linear model,Logistic model,modified Gompertz model and Weibull model,and then the most suitable model was choosen by comprehensive analysis and comparision.After these,the secondary model was developed and validated.The results showed that:1.Linear model could well describe the growth of Salmonella at 0℃,and the modified Gompertz model could well describe the growth of Salmonella under 4-20℃;the square root model was used to describe the relation between the maximum specific growth rate and lag phase of Salmonella and temperature,and the secondary model of Salmonella were obtained: μ1/2=0.025[T-1.14],λ-1/2=0.024[T-1.08],R2 were 0.965 and 0.986.The Modified models were validated at constant temperatures(9℃and 12℃)and fluctuant temperatures,bias factor(Bf)were 0.913,0.997,0.889,and the differences between predicted and observed values(Af)were1.118,1.019,1.147,respectively.So the predict model can predict the growth of Salmonella in chilled beef during storage well.2.In order to set up suitable kinetic models for the evaluation of heat inactivation rate of Salmonella in beef,four kinetic models(Linear model,Logistic model,modified Gompertz model and Weibull model)were used to fit the survivals datas,and then three statistical parameters(RMSE,R2 and RSS)were adopted to compare and evaluate the goodness of fitness.Analytical results showed that RMSE and RSS of Weibull model was lowest,and(R2)was larger,so Weibull model was the most suitable thermal-inactivation-kinetic model.3.Linear model was used to fit the survival curves of Salmonella,and results showed that: as the heating temperature increased,the inactivation rate of Salmonella was bigger gradually and D value decreased,with Z value 5.88℃.The secondary-level model to predict the effect of temperature on the first-level model parameters was lnb=0.47T-28.07.The Weibull model established was validated at 58.5℃ and 64℃,the bias factor(Bf)and accuracy factor(Af)were all acceptable.The results above showed that Weibull model could predict the thermal inactivation of Salmonella in beef reliably and quickly.4.The software predicting the growth of salmonella in beef was developed base on the growth model and inactivation model.C++ programming language combined with MATLAB were used to predict the growth and inactivation of Salmonella.