The objective of this research was to develop a new one-step methodology that uses a dynamic approach to directly
construct a tertiarymodel for prediction of the growth of Clostridiumperfringens in cooked beef. This methodologywas
based on simultaneous numerical analysis and optimization of both primary and secondary models
using multiple dynamic growth curves obtained under different conditions. Once the models were constructed,
the bootstrapmethod was used to calculate the 95% confidence intervals of kinetic parameters, and aMonte Carlo
simulation method was developed to validate the models using the growth curves not previously used in model
development. The results showed that the kinetic parameters obtained from this study accurately matched the
common characteristics of C. perfringens, with the optimum temperature being 45.3 °C. The results also showed
that the predicted growth curves matched accurately with experimental observations used in validation. The
mean of residuals of the predictions is −0.02 log CFU/g, with a standard deviation of only 0.23 log CFU/g. For
relative growths b1 log CFU/g, the residuals of predictions are b0.4 log CFU/g. Overall, 74% of the residuals of predictions
are b0.2 log CFU/g, 7.7% are N0.4 log CFU/g, while only 1.5% are N0.8 log CFU/g. In addition, the dynamic
model also accurately predicted four isothermal growth curves arbitrarily chosen fromthe literature. Finally, the
Monte Carlo simulation was used to provide the probability of N1 and 2 log CFU/g relative growths at the end of
cooling. The results of this study will provide a newand accurate tool to the food industry and regulatory agencies
to assess the safety of cooked beef in the event of cooling deviation.
The objective of this research was to develop a new one-step methodology that uses a dynamic approach to directlyconstruct a tertiarymodel for prediction of the growth of Clostridiumperfringens in cooked beef. This methodologywasbased on simultaneous numerical analysis and optimization of both primary and secondary modelsusing multiple dynamic growth curves obtained under different conditions. Once the models were constructed,the bootstrapmethod was used to calculate the 95% confidence intervals of kinetic parameters, and aMonte Carlosimulation method was developed to validate the models using the growth curves not previously used in modeldevelopment. The results showed that the kinetic parameters obtained from this study accurately matched thecommon characteristics of C. perfringens, with the optimum temperature being 45.3 °C. The results also showedthat the predicted growth curves matched accurately with experimental observations used in validation. Themean of residuals of the predictions is −0.02 log CFU/g, with a standard deviation of only 0.23 log CFU/g. Forrelative growths b1 log CFU/g, the residuals of predictions are b0.4 log CFU/g. Overall, 74% of the residuals of predictionsare b0.2 log CFU/g, 7.7% are N0.4 log CFU/g, while only 1.5% are N0.8 log CFU/g. In addition, the dynamicmodel also accurately predicted four isothermal growth curves arbitrarily chosen fromthe literature. Finally, theใช้การจำลอง Carlo มอนให้ล็อก 2 CFU/g ญาติเจริญเติบโตที่สุดของความน่าเป็นของ N1ระบายความร้อน ผลการศึกษานี้จะทำให้เครื่องมือถูกต้อง newand เพื่ออุตสาหกรรมอาหารและหน่วยงานกำกับดูแลการประเมินความปลอดภัยของเนื้อสุกในกรณีที่ทำความเย็นส่วนเบี่ยงเบน
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