馒头中金黄色葡萄球菌生长预测模型的建立

Establishment of Growth Model of Staphylococcus aureus in Steamed Buns

以传统面制品馒头作为研究对象,采用修正的Gompertz(SGompertz)和修正的Logistic(SLogistic)作为一级生长模型,应用Origin 9.0软件分别拟合馒头中金黄色葡萄球菌在10、15、25、30和37℃的生长情况,获得其最大比生长速率(μmax)和迟滞期(λ)。采用平方根模型和二次多项式模型建立馒头中金黄色葡萄球菌的二级生长模型,并对该模型进行验证。结果表明,SGompertz模型能较好地拟合馒头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0.931 5和0.932 0,偏差因子(Bf)分别为1.123 2和1.050 1,准确因子(Af)分别为1.221 0和1.190 2,表明采用μmax进行拟合时,二次多项式模型的拟合效果较好;以迟滞期λ建立的平方根和二次多项式模型,R2分别为0.948 4和0.969 6,Bf分别为0.890 1和0.912 2,Af分别为1.541 1和1.180 3,表明采用迟滞期λ进行拟合时,二次多项式模型的拟合效果较好。本研究可为馒头等传统面制品的定量风险评估提供参考。

Abstract Traditional flour product of steamed bun was chosen as the object of study. Using the revised Gompertz （SGompertz） and revised Logistic （Slogistic） as a primary growth model to describe growth of Staphylococcus aureus in steamed buns at different temperatures. In order to obtain the maximum specific growth rate （/xm,~） and lag phase （ k）, Origin 9.0 software was used to fit the growth curve of S. aureus with variable storage temperatures （ 10 ℃, 15 ℃, 25 ℃, 30 ℃, and 37 ℃ ） and the square root model combine with quadratic polynomial model was used as a secondary growth model of S. aureus and then the model was verified, The results showed that, SGompertz model can well＇ fit the growth of S. aureus in steamed buns. The/Xmax and k values obtained from the SGompertz model were used to establish the secondary growth models. When μmax was used as an argument to establish the square root models and quadratic polynomial models respectively, R2 values were 0. 931 5 and 0. 932 0 respectively; Bs, 1. 123 2 and 1. 050 1 respectively; Ai 1. 221 0 and 1. 190 2 respectively; suggested the quadratic polynomial model could better be employed to predict μmax When h was used as an argument to establish the square root models and quadratic polynomial models respectively, R2 values were 0. 948 4 and 0. 969 6 respectively; Bj.O. 890 1 and 0. 912 2 respectively; Ay 1. 541 1 and 1. 180 2 respectively; suggested the quadratic polynomial model could better be employed to predict k. This study can provide theoretical basis for quantitative risk assessment in steamed buns and other traditional flour products.