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首页> 美国卫生研究院文献>Applied and Environmental Microbiology >Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese
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Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese

机译：结合基于个体的建模和食物微环境描述来预测涂片软奶酪上李斯特菌的生长

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An individual-based modeling (IBM) approach was developed to describe the behavior of a few Listeria monocytogenes cells contaminating smear soft cheese surface. The IBM approach consisted of assessing the stochastic individual behaviors of cells on cheese surfaces and knowing the characteristics of their surrounding microenvironments. We used a microelectrode for pH measurements and micro-osmolality to assess the water activity of cheese microsamples. These measurements revealed a high variability of microscale pH compared to that of macroscale pH. A model describing the increase in pH from approximately 5.0 to more than 7.0 during ripening was developed. The spatial variability of the cheese surface characterized by an increasing pH with radius and higher pH on crests compared to that of hollows on cheese rind was also modeled. The microscale water activity ranged from approximately 0.96 to 0.98 and was stable during ripening. The spatial variability on cheese surfaces was low compared to between-cheese variability. Models describing the microscale variability of cheese characteristics were combined with the IBM approach to simulate the stochastic growth of L. monocytogenes on cheese, and these simulations were compared to bacterial counts obtained from irradiated cheeses artificially contaminated at different ripening stages. The simulated variability of L. monocytogenes counts with the IBM/microenvironmental approach was consistent with the observed one. Contrasting situations corresponding to no growth or highly contaminated foods could be deduced from these models. Moreover, the IBM approach was more effective than the traditional population/macroenvironmental approach to describe the actual bacterial behavior variability.
机译：开发了一种基于个体的建模（IBM）方法来描述少数污染涂片软干酪表面的单核细胞增生李斯特菌细胞的行为。 IBM的方法包括评估干酪表面上细胞的随机个体行为，并了解其周围微环境的特征。我们使用微电极进行pH测量和微摩尔渗透压浓度，以评估奶酪微样品的水活度。这些测量结果显示，与大型pH值相比，微型pH值具有较高的可变性。建立了一个模型，描述了在成熟过程中pH从约5.0升高到7.0以上的模型。还对奶酪表面的空间变异性进行了建模，其特征是随着半径的增加pH值的升高以及与奶酪果皮上的凹陷相比，c的pH值更高。微观水活度在大约0.96至0.98的范围内，并且在成熟期间稳定。与奶酪之间的差异相比，奶酪表面的空间差异较小。将描述奶酪特征的微观变化的模型与IBM方法结合，以模拟单核细胞增生李斯特氏菌在奶酪上的随机生长，并将这些模拟结果与从在成熟阶段被人工污染的辐照奶酪获得的细菌数进行比较。用IBM /微环境方法对单核细胞增生李斯特菌计数的模拟变异与观察到的一致。可以从这些模型中得出与没有生长或高污染食品相对应的相反情况。而且，IBM方法比传统的种群/宏观环境方法更有效地描述了实际的细菌行为变异性。

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