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Modeling Growth of Clostridium perfringens in Pea Soup During CoolingModeling Growth of Clostridium perfringens in Pea Soup During Cooling

机译:冷却期间豌豆汤中产气荚膜梭菌的生长模拟冷却期间豌豆汤中产气荚膜梭菌的生长模拟

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摘要

Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth rate model based on interpretable parameters was used to predict growth during linear cooling of pea soup. Second, a temperature model for cooling pea soup was constructed by fitting the model to experimental data published earlier. This cooling model was used to estimate the effect of various cooling environments on average cooling times, taking into account the effect of stirring and product volume. The growth model systematically overestimated growth of C. perfringens during cooling in air, but this effect was limited to less than 0.5 1og N/ml and this was considered to be acceptable for practical purposes. It was demonstrated that the growth model for C. perfringens combined with the cooling model for pea soup could be used to sufficiently predict growth of C. perfringens in different volume sizes of pea soup during cooling in air as well as the effect of stirring, different cooling temperatures, and various cooling environments on the growth of C. perfringens in pea soup. Although fine-tuning may be needed to eliminate inaccuracies, it was concluded that the combined model could be a useful tool for designing good manufacturing practices (GMP) procedures.
机译:产气荚膜梭状芽胞杆菌是一种病原体,在准备大量食物时主要引起食物中毒暴发。因此,开发了一个模型来预测食品冷却过程中不同冷却程序对这种病原体生长的影响:荷兰豌豆汤。首先,基于可解释参数的生长速率模型用于预测豌豆汤线性冷却期间的生长。其次,通过将豌豆汤冷却模型与先前发布的实验数据进行拟合,构建了该模型。考虑到搅拌和产品体积的影响,该冷却模型用于估计各种冷却环境对平均冷却时间的影响。生长模型系统地高估了空气中冷却过程中产气荚膜梭菌的生长,但是这种影响仅限于小于0.5 1og N / ml,并且在实际应用中被认为是可以接受的。结果表明,产气荚膜梭菌的生长模型与豌豆汤的冷却模型相结合,可以充分预测不同体积的豌豆汤在空气中冷却过程中产气荚膜梭菌的生长以及搅拌的效果,不同冷却温度以及各种冷却环境对豌豆汤中产气荚膜梭菌的生长的影响。尽管可能需要进行微调以消除不准确之处,但结论是,组合模型可能是设计良好生产规范(GMP)程序的有用工具。

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