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Field Validation Of Predictive Models For The Growth Of Lactic Acid Bacteria In Acidic Cheese-based Greek Appetizers

机译:酸性奶酪基希腊开胃菜中乳酸菌生长预测模型的现场验证

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摘要

A microbial model was developed for spoilage of two acidic Greek appetizers, namely, tyrosalata (TS) and tyrokafteri (TK), with pH values of 4.34 to 4.50 and 4.22 to 4.38, respectively. The specific spoilage organisms of these products were lactic acid bacteria (LAB), which dominated during storage, while yeasts, whenever present, remained at low levels (1 to 2 log CFU/g). Correlations of LAB populations with changes in pH and sensory characteristics indicated that the spoilage level of LAB ranged from 8.1 to 8.6 log CFU/g for both products. TK showed a relatively higher microbial stability than did TS. The growth of LAB was modeled with the Baranyi model, while their maximum specific growth rates were further modeled as a function of temperature with square-root model and Arrhenius equations for each appetizer. The validation of the model was performed under nonisothermal conditions in the laboratory and in a field validation trial with temperature logging during distribution of individual packages in the chill supply chain, including transportation from the plant to the distribution center, retail display, and household refrigerators. Models for both appetizers showed satisfactory agreement with data, with a slight tendency of overprediction of LAB in TS. The field validation process also confirmed the higher stability of TK over TS. The developed models may serve as a useful tool for monitoring the microbiological quality of such complex products and manage their distribution. Furthermore, depending on the seasonal variation of chill chain conditions, reassessment of shelf life may be performed.
机译:建立了一种微生物模型,用于破坏两种酸性希腊开胃菜,即tyrosalata(TS)和tyrokafteri(TK),其pH值分别为4.34至4.50和4.22至4.38。这些产品的特定腐败生物是乳酸菌(LAB),在存储过程中占主导地位,而酵母(无论何时存在)都保持较低水平(1-2 log CFU / g)。乳酸菌种群与pH值和感官特征变化的相关性表明,两种产品的乳酸菌腐败水平在8.1至8.6 log CFU / g之间。 TK显示出比TS更高的微生物稳定性。 LAB的生长用Baranyi模型进行建模,而每种开胃菜的最大比生长速率通过平方根模型和Arrhenius方程进一步建模为温度的函数。该模型的验证是在实验室的非等温条件下进行的,并且是在冷却包装供应链中各个包装的分发过程中进行温度记录的现场验证试验中进行的,包括从工厂到配送中心的运输,零售陈列和家用冰箱。两种开胃菜的模型与数据均显示出令人满意的一致性,但TS中LAB的预测值略有偏高的趋势。现场验证过程还证实了传统知识相对于传统知识的更高稳定性。开发的模型可以用作监测此类复杂产品的微生物质量并管理其分布的有用工具。此外,根据冷链条件的季节性变化,可以对保质期进行重新评估。

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