Research On Bacillus Cereus In The Process Of Sofu And Its Prohibition

Sufu, a kind of Chinese traditional fermented soybean food, is rich of nutrition. It has some disadvantages in competition at modern market due to the number of Bacillus cereus excessive levels. In this context, this paper studied the distribution of Bacillus cereus through the sufu processing period, and predictive modeling of Bacillus cereus in tofu was established to effectively control the content of Bacillus cereus.The distribution of Bacillus cereus were studied through the sufu processing period in different seasons:air in workshop of tofu and phetze, the surface of the tools which storage and transport tofu, the trunks of phetze and salted phetze, toufu, phetze, salted phetze and soup bases. The critical control point were the tools which storage and transport tofu, the trunks of phetze and salted phetze, toufu.Predictive models were established to predict the mixed growth kinetics of Bacillus cereus, using Gompertz equation as primary model and Ratkowsky model as secondary model. The growth curves at15℃、18℃、21℃、24℃、28℃、32℃were measured and fitted with Gompertz model, from which the growth rates and lag times under each temperature were calculated. The growth rates and lag times of Bacillus cereus were0.3161g cfu/g/h、0.3941g cfu/g/h、0.4671g cfu/g/h、0.5961g cfu/g/h、0.7251g cfu/g/h.0.933lg cfu/g/h and23.250h、13.190h、8.496h、5.628h、4.205h、3.517h, respectively. The statistical validation of primary models showed that, correlation coefficients of all fitted growth curves were larger than0.99, indicating a good fitting degree of the models. The secondary model, which described the change of growth rate with temperature, was obtained by incorporating the growth parameters of primary model into Ratkowsky equation with linear regression technique. The correlation coefficient of linear models was0.996. The standard errors was0.010710and the regression equation showed a significant different at the level of a=0.05. The secondary models were validated through plotting method and statistical method. The result showed that, the models were statistically reliable at a=0.05for residues of√μm fell within the range of±0.05. The bias factor and accuracy factor of Bacillus cereus were1.0113and1.0725, respectively. The values of bias factor and accuracy factor agreed with those in literature and were acceptable statistically. As a result, the primary models and secondary models established in this paper could effectively predict the growth kinetics of Bacillus cereus at15℃-32℃and provide quantitative data for evaluating the safety and quality of tofu.Quantitative germicidal test was used to observe experimentally its disinfection efficacy. Results:The average killing rates of Bacillus cereus exposed to the disinfectant containing peracetic acid2000mg/L and chlorine dioxide200mg/L for10min respectively attained100%. The average eradicating rate of Bacillus cereus on simulated on-the-spot object surface exposed to the disinfectant containing chlorine dioxide200mg/L for30min was over99.9%.In conclusion, on the basis of predictive models and sanitizer, we could effectively prevent and control the Bacillus cereus during sufu processing, provided the basis for the production.