Department of Agronomical Engineering & Institute of Plant Biotechnology, Universidad Politécnica de Cartagena, Murcia, Paseo Alfonso XIII, 48, 30203, Spain.
Laboratory of Clinical Microbiology and Microbial Pathogenesis, School of Medicine, University of Crete, Heraklion, Crete, 71100, Greece.
Food Res Int. 2022 Aug;158:111477. doi: 10.1016/j.foodres.2022.111477. Epub 2022 Jun 7.
In this article, the thermal inactivation of two Salmonella strains (Salmonella Enteritidis CECT4300 and Salmonella Senftenberg CECT4565) was studied under both isothermal and dynamic conditions. We observed large differences between these two strains, with S. Senftenberg being much more resistant than S. Enteritidis. Under isothermal conditions, S. Senftenberg had non-linear survivor curves, whereas the response of S. Enteritidis was log-linear. Therefore, weibullian inactivation models were used to describe the response of S. Senftenberg, with the Mafart model being the more suitable one. For S. Enteritidis, the Bigelow (log-linear) inactivation model was successful at describing the isothermal response. Under dynamic conditions, a combination of the Peleg and Mafart models (secondary model of Mafart; t* of Peleg) fitted to the isothermal data could predict the response of S. Senftenberg to the dynamic treatments tested (heating rates between 0.5 and 10 °C/min). This was not the case for S. Enteritidis, where the model predictions based on isothermal data underestimated the microbial concentrations. Therefore, a dynamic model that considers stress acclimation to one of the dynamic profiles was fitted, using the remaining profiles as validation. In light of this, besides its quantitative impact, variability between strains of bacterial species can also cause qualitative differences in microbial inactivation. This is demonstrated by S. Enteritidis being able to develop stress acclimation where S. Senftenbenberg could not. This has important implications for the development of microbial inactivation models to support process design, as every industrial treatment is dynamic. Consequently, it is crucial to consider different model hypotheses, and how they affect the model predictions both under isothermal and dynamic conditions.
本文研究了两种沙门氏菌菌株（肠炎沙门氏菌 CECT4300 和 森夫滕贝格沙门氏菌 CECT4565）在等温条件和动态条件下的热失活动力学。我们观察到这两种菌株之间存在很大差异，森夫滕贝格沙门氏菌比肠炎沙门氏菌具有更强的抗性。在等温条件下，森夫滕贝格沙门氏菌的存活曲线是非线性的，而肠炎沙门氏菌的响应是对数线性的。因此，我们使用 Weibull 失活动力学模型来描述森夫滕贝格沙门氏菌的响应，其中 Mafart 模型更适用。对于肠炎沙门氏菌，Bigelow（对数线性）失活动力学模型成功地描述了等温响应。在动态条件下，Peleg 和 Mafart 模型的组合（Mafart 的二次模型；Peleg 的 t*）可以拟合等温数据，从而预测森夫滕贝格沙门氏菌对测试的动态处理（加热速率在 0.5 和 10°C/min 之间）的响应。对于肠炎沙门氏菌来说，这种情况并非如此，基于等温数据的模型预测低估了微生物浓度。因此，拟合了一个考虑到对动态曲线之一的应激适应的动态模型，并用剩余的曲线作为验证。鉴于此，除了定量影响外，细菌菌株之间的可变性还可能导致微生物失活动力学的定性差异。肠炎沙门氏菌能够适应应激而森夫滕贝格沙门氏菌不能适应应激，这就证明了这一点。这对开发支持工艺设计的微生物失活动力学模型具有重要意义，因为每个工业处理都是动态的。因此，考虑不同的模型假设及其如何在等温条件和动态条件下影响模型预测非常重要。
