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首页> 外文期刊>Food Control >A dynamic predictive model for the growth of Salmonella spp. and Staphylococcus aureus in fresh egg yolk and scenario-based risk estimation
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A dynamic predictive model for the growth of Salmonella spp. and Staphylococcus aureus in fresh egg yolk and scenario-based risk estimation

机译：沙门氏菌生长的动态预测模型。 在新鲜蛋黄和情景的风险估计中，金黄色葡萄球菌和基于场景的风险估算

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摘要

The present study aimed to develop and validate a predictive model of Salmonella spp. and Staphylococcus aureus growth in fresh egg under isothermal and non-isothermal (fluctuating temperature) conditions and also estimate infection probability based on Monte Carlo simulation and scenario analysis. Egg yolk and egg white were inoculated with six serovars of Salmonella and three strains of S. aureus and stored at 5, 10, 20, 30, and 37 degrees C. No growth of Salmonella spp. and S. aureus was observed at all temperatures in egg white. However, growth of both strains was observed at above 10 degrees C in egg yolk. Primary growth models for both strains in egg yolk were developed based on the Baranyi model. Secondary models were developed as a function of temperature for lag phase duration (LPD) and maximum specific growth rate (mu(max)) using Davey and second-order polynomial, and square root models, respectively. The primary and secondary models for both strains were fitted well with a high degree of goodness-of-fit (R-2 >= 0.99). Bias factor (Bf) was 0.96-1.08, and root mean square error (RMSE) was 0.04-0.15 log CFU/mL. The model was validated and found to be applicable to a scenario involving the consumption of an egg omelet, and other strains of S. aureus, including food isolates. As the results of validation, the developed model was conservatively applicable to other strains (Bf: 0.88-1.07, RMSE: 0.05-0.23 log CFU/mL) and egg products (Bf: 0.94-1.09, RMSE: 0.04-0.06 log CFU/mL of mu(max)). The dynamic model was validated for 3 temperature profiles: 1) rapidly changing and 2) slowly changing at 10-25 degrees C, and 3) 2-h cycles change at 15-30 degrees C with corresponding RMSE values less than 0.5 log CFU/mL. Using a baseline simulation model, the probability of infection for Salmonella spp. and S. aureus from the consumption of ready-to-eat egg products (e.g., rolled omelet) was estimated as zero. However, scenario analysis that factored for possible initial contamination by pathogens in egg products suggested that the probability of infection has a positive relationship with initial contamination level. The developed growth model can provide useful data for quantitative microbial risk assessment and risk management options of Salmonella spp. and S. aureus during the consumption of egg-related foods.
机译：本研究旨在开发和验证沙门氏菌SPP的预测模型。等温和非等温（波动温度）条件下新鲜蛋的金黄色葡萄球菌生长，以及基于蒙特卡罗模拟的感染概率和情景分析。蛋黄和蛋白接种六种沙门氏菌和金黄色葡萄球菌菌株，并储存在5,10,20,30和37摄氏度下。没有沙门氏菌SPP的生长。在蛋清的所有温度下观察到金黄色葡萄球菌。然而，在蛋黄中的10℃以上观察到两种菌株的生长。基于Baranyi模型开发了蛋黄中蛋黄中菌株的主要生长模型。通过分别使用Davey和二阶多项式和平方根模型的延迟阶段持续时间（LPD）和最大特异性生长速率（MU（MU（MU（MU））和平方根模型的函数开发了二次模型。两种菌株的初级和二级模型均匀，具有高度的拟合度（R-2> = 0.99）。偏置因子（BF）为0.96-1.08，均均方误差（RMSE）为0.04-0.15 log CFU / ml。该模型被验证，发现适用于涉及蛋煎蛋卷消耗的情况，以及包括食物分离物的其他菌株的情况。作为验证结果，开发的模型保守适用于其他菌株（BF：0.88-1.07，RMSE：0.05-0.23 Log CFU / ML）和蛋产品（BF：0.94-1.09，RMSE：0.04-0.06 log CFU / ml mu（max））。动态模型被验证为3个温度曲线：1）快速改变，2）在10-25摄氏度下缓慢变化，3）2-H周期在15-30摄氏度下，相应的RMSE值少于0.5 LOG CFU / ml。使用基线仿真模型，对沙门氏菌SPP感染的概率。来自现成蛋产品的消耗（例如轧制煎蛋卷）的消耗量，估计为零。然而，蛋产病病原体可能初始污染的情景分析表明，感染的概率与初始污染水平具有正关系。开发的生长模型可以为大鼠SPP的定量微生物风险评估和风险管理选择提供有用的数据。和金黄色葡萄球菌在消耗鸡蛋相关食品期间。

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