【目的】研究不同浓度和不同温度条件下金黄色葡萄球菌接种在熟鸡肉中的生长情况,比较3种常见预测模型拟合的准确性,选择最适合的预测模型建立一级和二级模型,为进一步探讨建立三级模型提供数据基础。【方法】测定浓度为102、103和104 CFU/g的金黄色葡萄球菌接种在15-36°C熟鸡肉中的生长数据,使用Matlab软件分别建立修正的Gompertz、Logistic和Baranyi模型,通过比较残差和拟合度(RSS、AIC、RSE)选择最优模型,并且拟合出生长参数(迟滞期、最大比生长速率和最大细胞密度),在此基础上通过响应面方程建立二级模型。最后对模型的可靠性进行了内部和外部实验验证。【结果】36°C和29°C条件下,修正的Gompertz模型最适合;22°C和15°C条件下,最适合模型按接种浓度依次为修正的Gompertz、Logistic和Baranyi模型,综合考虑,最优模型选择修正的Gompertz模型。通过计算预测标准差(%SEP)、平方根误差(RMSE)、准确性因子(Af)和偏差因子(Bf)对建立的二级模型进行数学检验,检验结果均在可接受范围内。【结论】用修正的Gompertz方程和响应面方程建立的一、二级预测模型可以为建立三级模型提供有效、精确的基础。
[Objective] To investigate the growth of Staphylococcus aureus in cooked chicken at different incubation temperature and initial inoculating level, three common predictive models were compared and the best-fit one was chosen to build the primary and secondary model, the result of this study could be applied to develop the tertiary model, from which the density of the S. aureus at any time in cooked chicken can be calculated from any combination of temperature and initial inoculating level. [Methods] The S. aureus strain was inoculated into cooked chicken under various initial concentrations of 102, 103, 104 CFU/g and stored at 15, 22, 29, 36 °C. The number of colonies was counted by 3M Petrifilm? Staph Express Count Plate. The modified Gompertz model, modified Logistic model and Baranyi model for describing the growth of S. aureus were established by using Matlab software. The best model was chosen by comparing the residuals and the goodness-of-fit [Residual Sum of Squares(RSS), Akallke Information Crlterlon(AIC), Residual Standard Error(RSE)]. The growth parameter(lag phase, maximum specific growth rate and maximum population density) were then obtained from the best model. The secondary model was set up by using response surface equation. Finally, the reliability of the model was verified by internal and external validation. [Results] At 36 and 29 °C, the best choice to describe the growth of S. aureus was modified Gompertz model at all initial inoculating level. At 22 and 15 °C, the most suitable model is modified Gompertz model, modified Logistic model and Baranyi model successively according to the initial inoculation level. By comprehensive considerations, the modified Gompertz model was thought of the optimal primary model. The secondary model was verified by calculating the standard error of prediction(%SEP), Root-Mean-Squares(RMSE), Accuracy factor(Af) and Bias factor(Bf), the results of verification were all within acceptable range. [Conclusion] The modified Gompertz