清蛋糕中金黄色葡萄球菌生长预测模型的建立

Establishment of growth prediction models for Staphylococcus aureus in plain cakes

中文关键词:  清蛋糕  金黄色葡萄球菌  预测模型

英文关键词:plain cakes  Staphylococcus aureus  prediction model

中文摘要:

      目的 建立清蛋糕中金黄色葡萄球菌生长预测模型。方法 选用清蛋糕和金黄色葡萄球菌作为研究对象, 比较了6、15、25、35 ℃条件下金黄色葡萄球菌在糕点中生长情况, 分别采用修正Gompertz模型(SGompertz)和修正Logistic模型(SLogistic)进行拟合, 建立清蛋糕中金黄色葡萄球菌一级生长动力学模型, 采用平方根模型和二次多项式模型描述温度与最大比生长速率(μmax)及延滞期(λ)的关系, 并进行验证。结果 SLogistic模型作为一级模型, 能更好描述6~35 ℃条件下清蛋糕中金黄色葡萄球菌生长变化; 平方根模型是拟合温度与最大比生长速率的最适二级模型; 二次多项式模型是拟合温度与延滞期的最适二级模型。结论 本研究建立的生长预测模型能够有效预测金黄色葡萄球菌在清蛋糕中的生长情况, 为清蛋糕的定量风险评估提供参考。

英文摘要:

      Objective To establish the growth prediction model of Staphylococcus aureus in plain cake. Methods The plain cake and Staphylococcus aureus were selected as the research objects, and the growth of Staphylococcus aureus in the pastry was compared at 6, 15, 25 and 35 ℃. The growth data were fitted into the SGompertz model and the SLogistic model as primary models. The square root model combined with quadratic polynomial model was used as a secondary growth model to describe the relation between temperature and maximum specific growth rate (μmax) and the lag time (λ), and then the model was verified. Results As a first-level model, the SLogistic model could better describe the growth of Staphylococcus aureus in plain cakes at 6~35 ℃. The square root model was the optimal secondary model for fitting temperature and maximum specific growth rate. The quadratic polynomial model was an optimal secondary model for fitting temperature and lag period. Conclusion The established model could be applied to predict the growth of Staphylococcus aureus in plain cakes, which provide reference for quantitative risk assessment of plain cakes.