Xanthiakos K, Simos D, Angelidis A S, Nychas G J-E, Koutsoumanis K
Department of Food Science and Technology, Faculty of Agriculture, Aristotle University of Thessaloniki, Thessaloniki, Greece.
J Appl Microbiol. 2006 Jun;100(6):1289-98. doi: 10.1111/j.1365-2672.2006.02854.x.
The development and validation of a dynamic model for predicting Listeria monocytogenes growth in pasteurized milk stored at both static and dynamic temperature conditions.
Growth of inoculated L. monocytogenes in a commercial pasteurized whole milk product was monitored at various isothermal conditions from 1.5 to 16 degrees C. The kinetic parameters of the pathogen were modelled as a function of temperature using a square root type model, which was further validated using data from 92 published growth curves from eight different milk products. Compared to four published models for L. monocytogenes growth, the model developed in this study performed better, with a per cent discrepancy and bias of 49.1 and -1.01%, respectively. The performance of the model in predicting growth at dynamic temperature conditions was evaluated at four different fluctuating temperature scenarios with periodic temperature changes from -2 to 16 degrees C. The prediction of growth at dynamic storage temperature was based on the square root model in conjunction with the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. The per cent relative errors between the observed and the predicted growth of L. monocytogenes were less than 10% for all temperature scenarios tested.
Available models from experiments conducted in laboratory media may result in significant overestimation of L. monocytogenes growth in pasteurized milk because they do not take into account factors such as milk composition (e.g. natural antimicrobial compounds present in milk) and the interactions of the pathogen with the natural microflora. The product-targeted model developed in the present study showed a high performance in predicting growth of L. monocytogenes in pasteurized milk under both static and dynamic temperature conditions.
Temperature fluctuations often occur during the transportation and storage of pasteurized milk. A high performance, dynamic model for the growth of L. monocytogenes can be a useful tool for effective management and optimization of product safety and can lead to more realistic estimations of pasteurized-milk related safety risks.
建立并验证一个动态模型，用于预测在静态和动态温度条件下储存的巴氏杀菌乳中单核细胞增生李斯特菌的生长情况。
在1.5至16摄氏度的各种等温条件下，监测商业巴氏杀菌全脂乳产品中接种的单核细胞增生李斯特菌的生长情况。使用平方根型模型将病原体的动力学参数建模为温度的函数，并使用来自八种不同乳制品的92条已发表生长曲线的数据进行进一步验证。与四个已发表的单核细胞增生李斯特菌生长模型相比，本研究开发的模型表现更好，百分比差异和偏差分别为49.1%和-1.01%。在四种不同的波动温度场景下评估该模型在动态温度条件下预测生长的性能，温度在-2至16摄氏度之间周期性变化。动态储存温度下的生长预测基于平方根模型以及Baranyi和Roberts模型的微分方程，并对时间进行数值积分。在所有测试的温度场景下，观察到的和预测的单核细胞增生李斯特菌生长之间的相对误差百分比均小于10%。
在实验室培养基中进行实验得到的现有模型可能会显著高估巴氏杀菌乳中单核细胞增生李斯特菌的生长，因为它们没有考虑牛奶成分（例如牛奶中存在的天然抗菌化合物）以及病原体与天然微生物群落的相互作用等因素。本研究开发的针对产品的模型在预测静态和动态温度条件下巴氏杀菌乳中单核细胞增生李斯特菌的生长方面表现出高性能。
在巴氏杀菌乳的运输和储存过程中经常会出现温度波动。一个高性能的单核细胞增生李斯特菌生长动态模型可以成为有效管理和优化产品安全的有用工具，并能更实际地估计与巴氏杀菌乳相关的安全风险。
