Department of Veterinary Disease Biology, University of Copenhagen, Frederiksberg, Denmark.
Appl Environ Microbiol. 2012 Dec;78(24):8508-14. doi: 10.1128/AEM.01865-12. Epub 2012 Sep 14.
The aim of this study was to develop a predictive model simulating growth over time of the pathogenic bacterium Listeria monocytogenes in a soft blue-white cheese. The physicochemical properties in a matrix such as cheese are essential controlling factors influencing the growth of L. monocytogenes. We developed a predictive tertiary model of the bacterial growth of L. monocytogenes as a function of temperature, pH, NaCl, and lactic acid. We measured the variations over time of the physicochemical properties in the cheese. Our predictive model was developed based on broth data produced in previous studies. New growth data sets were produced to independently calibrate and validate the developed model. A characteristic of this tertiary model is that it handles dynamic growth conditions described in time series of temperature, pH, NaCl, and lactic acid. Supplying the model with realistic production and retail conditions showed that the number of L. monocytogenes cells increases 3 to 3.5 log within the shelf life of the cheese.
本研究旨在开发一个预测模型，模拟软质蓝纹干酪中病原菌李斯特菌随时间的生长情况。奶酪等基质中的理化特性是影响李斯特菌生长的重要控制因素。我们开发了一个预测性的三级模型，用于描述李斯特菌的细菌生长情况，作为温度、pH 值、NaCl 和乳酸的函数。我们测量了奶酪中理化特性随时间的变化。我们的预测模型是基于以前研究中产生的肉汤数据开发的。新的生长数据集用于独立校准和验证所开发的模型。这个三级模型的一个特点是，它可以处理以温度、pH 值、NaCl 和乳酸的时间序列形式描述的动态生长条件。根据实际的生产和零售条件为模型提供数据表明，在奶酪的保质期内，李斯特菌细胞的数量增加了 3 到 3.5 个对数级。
