Teagasc Food Research Centre, Moorepark, Fermoy, Co Cork, Ireland.
Int J Food Microbiol. 2011 Mar 1;145 Suppl 1:S31-8. doi: 10.1016/j.ijfoodmicro.2010.11.032. Epub 2010 Dec 1.
The dynamics of the physicochemical characteristics of foods help to determine the fate of pathogens throughout processing. The aim of this study was to assess the behaviour of Listeria monocytogenes during cheesesmaking and ripening and to model the growth observed under the dynamic conditions of the cheese. A laboratory scale cheese was made in 4 independent replicates from pasteurised or raw cow's milk, artificially contaminated with L. monocytogenes. No growth of L. monocytogenes occurred during raw milk cheese-making, whereas growth did occur in pasteurised milk. During ripening, growth occurred in raw milk cheese, but inactivation occurred in pasteurised milk cheese. The behaviour observed for L. monocytogenes was modelled using a logistic primary model coupled with a secondary cardinal model, taking into account the effect of physicochemical conditions (temperature, pH, water activity and lactate). A novel statistical approach was proposed to assess the optimal growth rate of a microorganism from experiments performed in dynamic conditions. This complex model had an acceptable quality of fit on the experimental data. The estimated optimum growth rates can be used to predict the fate of L. monocytogenes during cheese manufacture in raw or pasteurized milk in different physicochemical conditions. The data obtained contributes to a better understanding of the potential risk that L. monocytogenes presents to cheese producers (growth on the product, if it is contaminated) and consumers (the presence of high numbers) and constitutes a very useful set of data for the completion of chain-based modelling studies.
食品物理化学特性的变化有助于确定病原体在整个加工过程中的命运。本研究的目的是评估单核细胞增生李斯特菌在奶酪制作和成熟过程中的行为，并对奶酪动态条件下观察到的生长进行建模。在 4 个独立重复的实验中，使用巴氏杀菌或生牛乳制作了实验室规模的奶酪，并用单核细胞增生李斯特菌进行了人工污染。生牛乳奶酪制作过程中单核细胞增生李斯特菌没有生长，而巴氏杀菌乳中则有生长。在成熟过程中，生牛乳奶酪中发生了生长，但巴氏杀菌乳奶酪中发生了失活。使用逻辑主模型与二级基数模型相结合的方法对单核细胞增生李斯特菌的行为进行建模，同时考虑了物理化学条件（温度、pH 值、水活度和乳酸盐）的影响。提出了一种新的统计方法来评估从动态条件下进行的实验中获得的微生物最佳生长速率。该复杂模型对实验数据具有良好的拟合质量。估计的最佳生长速率可用于预测生牛乳或巴氏杀菌牛乳中单核细胞增生李斯特菌在奶酪生产过程中的命运，在不同的物理化学条件下。所获得的数据有助于更好地了解单核细胞增生李斯特菌对奶酪生产者（如果产品受到污染，就会生长）和消费者（数量高）的潜在风险，并为基于链的建模研究提供了非常有用的数据集。
