凉拌面中金黄色葡萄球菌生长预测模型的建立

摘要

Establishment of Growth Model of Staphylococcus aureus in Cold Noodles. Cold noodles was chosen as the object of study. Using the modified Gompertz(SGompertz) and modified Logistic(Slogistic) as the primary growth model to describe growth of Staphylococcus aureus in cold noodles at different temperatures. In order to obtain the maximum specific growth rate(μmax) and lag phase (λ), Origin 9.0 was used to fit the growth curve of Staphylococ cus aureus with variable storage temperatures (10℃, 15℃, 20℃, 25℃, 30℃ and 37℃) and the Square Root model combine with Quadratic Polynomial model was used as secondary growth model of Staphylococcus aureus and then the model was validated. The results showed that, Slogistic model can well fit the growth of Staphylococcus aureus in cold noodles. The μmax and λ values obtained from the Slogistic model were used to establish the secondary growth models. When we used μmax as an argument to establish the Square Root model and Quadratic Polynomial model respectively, R2 values were 0.9180 and 0.8810; Bf 1.0403 and 1.1381; Af 1.2226 and 1.2613; suggested the Square Root model could better be employed to predict μmax. When we used λ as an argument to establish the Square Root model and Quadratic Polynomial model respectively, R2 values were 0.9412 and 0.9587; Bf 0.9655 and 1.0881; Af 1.1869 and 1.3766; suggested the Square Root model could better be employed to predict λ. This study can pro-vide theoretical basis for quantitative risk assessment in cold noodles and other traditional flour products.%建立凉拌面中金黄色葡萄球菌的生长预测模型.采用修正的Gompertz(SGompertz)和修正的Logistic(Slogistic)作为一级生长模型,选用即食面制品凉拌面作为研究对象,应用Origin 9.0软件分别拟合凉拌面中金黄色葡萄球菌在10℃、15℃、20℃、25℃、30℃、37℃的生长情况,并以此获得最大比生长速率(μmax)和迟滞期(λ).采用平方根模型和二次多项式模型建立凉拌面中金黄色葡萄球菌的二级生长模型,并对该模型进行了验证.Slogistic模型能较好的拟合凉拌面中金黄色葡萄球菌的生长.以μmax建立的平方根和二次多项式模型,R2分别为0.9180和0.8810,偏差因子(Bf)分别为1.0403和1.1381,准确因子(Af)分别为1.2226和1.2613,表明采用μmax进行拟合时,平方根模型的预测效果较好;以迟滞期λ建立的平方根和二次多项式模型,R2分别为0.9412和0.9587,Bf分别为0.9655和1.0881,Af分别为1.1869和1.3766,表明采用迟滞期λ进行拟合时,平方根模型的预测效果较好.本研究可为凉拌面等传统即食面制品的的定量风险评估提供理论依据.