Heo Sun-Kyung, Lee Ji-Young, Baek Seung-Bum, Ha Sang-Do
Department of Food Science and Technology, Chung-Ang University, 72-1 Nae-ri, Ansung-si, Gyunggi-do 456-756, Republic of Korea.
J Food Prot. 2009 Jun;72(6):1296-300. doi: 10.4315/0362-028x-72.6.1296.
This study was performed to develop a predictive model for the growth rate of Bacillus cereus in cooked rice. A response surface methodology (RSM) was used with a combination of storage temperature (10 to 40 degrees C) and pH value (5.4 to 6.8). The growth curves generated under different conditions were fitted using a modified Gompertz equation, and the relationship of the growth rate to the growth curves was modeled using an RSM quadratic polynomial equation. The predictive model was significant (P < 0.01), and the predicted values of the growth parameters obtained using the model equations were in close agreement with experimental values (R2 = 0.9864). The RSM evaluation for describing the growth rate of B. cereus involved both a bias factor (Bf) and an accuracy factor (Af). Both the Bf value (1.006) and the Af value (1.011) approached 1.0 and were within acceptable ranges. Therefore, the adequacy of the predictive model for B. cereus in cooked rice was verified by the validation data.
本研究旨在建立一个预测米饭中蜡样芽孢杆菌生长速率的模型。采用响应面法(RSM),结合储存温度(10至40摄氏度)和pH值(5.4至6.8)进行研究。使用修正的Gompertz方程拟合不同条件下生成的生长曲线,并使用RSM二次多项式方程对生长速率与生长曲线的关系进行建模。该预测模型具有显著性(P < 0.01),使用模型方程获得的生长参数预测值与实验值高度吻合(R2 = 0.9864)。用于描述蜡样芽孢杆菌生长速率的RSM评估涉及偏差因子(Bf)和准确度因子(Af)。Bf值(1.006)和Af值(1.011)均接近1.0且在可接受范围内。因此,验证数据证实了该预测模型对米饭中蜡样芽孢杆菌的适用性。