作 者：
李苗云;张佳烨;朱瑶迪;王小慧;赵改名;柳艳霞
关键词：
精油;菌;模型;香辛料精油;熟制鸡胸肉;产气荚膜梭菌
摘 要：
为研究不同香辛料精油对熟制鸡胸肉中产气荚膜梭菌(C.perfringens)的影响,该文以肉桂精油、艾草精油和茴香精油为研究对象,对C.perfringens标准株(ATCC13124)和分离株(C1)抑菌效果,筛选出抑制最佳浓度,采用BP神经网络构建C.perfringens的生长/残存动力学模型,并以相关系数(R~2)和均方根误差(RMSE)评价模型精度,以期快速预测不同精油浓度条件对C.perfringens影响.结果表明:经肉桂精油处理后的ATCC13124和C1浓度最低,抑制效果最强;采用BP神经网络模型构建不同精油对熟制鸡胸肉中C.perfringens的预测模型,肉桂精油对ATCC13124和C1的R~2分别为0.963和0.976,RMSE分别为0.327和0.271CFU/g,预测效果最佳;利用验证集对模型鲁棒性进行验证,结果表明R~2均在0.917以上,RMSE在0.200~0.640 CFU/g之间,结果表明,BP神经网络模型可以较好的预测熟制鸡胸肉中产气夹膜梭菌的生长/残存情况;为肉类加工过程中控制C.perfringens提供理论依据.
作 者：
Li Miaoyun;Zhang Jiaye;Zhu Yaodi;Wang Xiaohui;Zhao Gaiming;Liu Yanxia;College of Food Science and Technology, Henan Agricultural University;
单 位：
Li Miaoyun%Zhang Jiaye%Zhu Yaodi%Wang Xiaohui%Zhao Gaiming%Liu Yanxia%College of Food Science and Technology, Henan Agricultural University
关键词：
essential oil;;bacteria;;models;;spice essential oil;;cooked chicken breast;;Clostridium perfringens
摘 要：
Roasted chicken is an important commercial products widely distributed in China, and is consumed by many consumers. The products, prepared with different spices and other ingredients and different cooking methods, can be contaminated with C.perfringens. In order to better inhibit the growth/survival of C.perfringens in food and improve the scientific application of essential oils, in this paper, we studied the effects of various essential oils from spices on the growth of C.perfringens in cooked chicken breast were investigated. The Oxford cup method and two-fold dilution method were used to determine the in vitro inhibitory activities and minimum inhibitory concentrations(MIC) of cinnamon, black pepper, ginger, fennel and wormwood essential oils on C.perfringens. The essential oils of cinnamon, artemisia and fennel with good bacteriostatic activity were screened out and their inhibitory concentrations against(ATCC13124,C1) were obtained for construction of growth/residual kinetic model of C.perfringens in cooked chicken breast by BP neural network. In order to improve the accuracy of network training, data of including essential oil concentration, the number of strains and the types of essential oils were used as input parameters prior for training; the corresponding surviving counts of C.perfringens(C1 and ATCC13124) in cooked chicken breast were used as the target parameter. After the trained samples were normalized, he trainlm function was used in the network learning parameter, the maximum training times were 5 000, the training step was 0.1, the expected error was 1×10~(-7) and a feedforward and backpropagation BP-ANN model was constructed. By comparing the correlation coefficient(R~2) and the root mean square error of prediction(RMSE) values from the models.The prediction model accuracy and the accuracy index(Af) and bias factor(B f) of the inactivated growth curve of C.perfringens in cooked chicken breast meat with different essential oil concentrations were determined. The results showed that: As the concentration of essential oil increased, the growth/residual amount of C.perfringens gradually decreased. Among them, cinnamon oil had the lowest inhibitory concentration on ATCC13124 and C1, and the effect was the strongest. The calculated values of the Bf for the BP-ANN model were close to 1 indicating no systematic bias. The prediction accuracy of the BP-ANN model was greater than 0.917 and the degree of fitting was high. For strain ATCC13124, the prediction model worked best for wormwood essential oil, with R~2, RMSE, Af and B f of 0.992, 0.197 CFU/g, 1.015 and 1.000, respectively. In the case of the isolated strain C1, the prediction model performed best for cinnamon essential oil, with R~2 of 0.976, RMSE value of 0.271 CFU/g, A_f and B_f of 1.022 and 1.000, respectively. The robustness of the model was verified by the verification set. The results showed that R~2 is above 0.917, and the RMSE was between 0.200-0.640 CFU/g. The predicted value and the measured value were better. In summary, the BP-ANN model can be used to rapidly obtain the optimal inhibitory concentration for different essential oils and quantitatively predict the survival of C.perfringens. This work can be used to assess the food safety hazards of C.perfringens in cooked chicken breast and provides a theoretical basis for the control of C.perfringens during meat processing.
