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A mathematical risk model for Escherichia coli O157:H7 cross-contamination of lettuce during processing

机译:加工过程中生菜大肠杆菌O157:H7交叉污染的数学风险模型

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摘要

A stochastic simulation modelling approach was taken to determine the extent of Escherichia coli O157:H7 contamination in fresh-cut bagged lettuce leaving the processing plant. A probabilistic model was constructed in Excel to account for E. coli O157:H7 cross contamination when contaminated lettuce enters the processing line. Simulation of the model was performed using@Risk Palisade© Software, providing an estimate of concentration and prevalence in the final bags of product. Three different scenarios, named S1, S2, and S3, were considered to represent the initial concentration on the contaminated batch entering the processing line which corresponded to 0.01,1 and 100 cfu/g, respec tively. The model was satisfactorily validated based on Standard Error of Prediction (SEP), which ranged from 0.00-35%. ANOVA analysis performed on simulated data revealed that the initial concentration in the contaminated batch (i.e., S1, S2, and S3) did not influence significantly (p= 0.4) the E. coli O157:H7 levels in bags derived from cross contamination. In addition, significantly different (p<0.001) prevalence was observed at the different levels simulated (S1; S2 and S3). At the lowest contamination level (0.01 cfu/g), bags were cross-contaminated sporadically, resulting in very low E. coli O157:H7 populations (mean: <2cfu/bag) and prevalence levels (<1%). In contrast, higher average prevalence levels were obtained for S2 and S3 corresponding to 3.05 and 13.39%, respectively. Furthermore, the impact of different interventions on E. coli O157:H7 cross-contamination (e.g., pathogen testing, chlorination, irradiation, and cleaning and disinfection procedures) was evaluated. Model showed that the pathogen was able to survive and be present in the final bags in all simulated interventions scenarios although irradiation (0.5 KGy) was a more effective decontamination step in reducing prevalence than chlorination or pathogen testing under the same simulated conditions.
机译:采用随机模拟建模方法确定离开加工工厂的鲜切袋装生菜中大肠杆菌O157:H7的污染程度。在Excel中构建了一个概率模型,以解释被污染的生菜进入加工线时大肠杆菌O157:H7的交叉污染。使用@Risk Palisade©软件进行了模型的仿真,提供了最终产品袋中浓度和流行程度的估计值。考虑了三种不同的情况,分别称为S1,S2和S3,它们代表进入加工线的受污染批次的初始浓度,分别对应于0.01、1和100 cfu / g。根据标准预测误差(SEP)对模型进行了令人满意的验证,其范围为0.00-35%。对模拟数据进行的方差分析表明,受污染批次(即S1,S2和S3)中的初始浓度不会显着(p = 0.4)影响交叉污染产生的包装袋中的O157:H7大肠杆菌水平。此外,在不同的模拟水平(S1,S2和S3)下,观察到的患病率也有显着差异(p <0.001)。在最低污染水平(0.01 cfu / g)下,袋子被零星地交叉污染,从而导致非常低的大肠杆菌O157:H7种群(平均:<2cfu /袋子)和患病率(<1%)。相反,S2和S3的平均患病率较高,分别对应于3.05%和13.39%。此外,评估了不同干预措施对大肠杆菌O157:H7交叉污染的影响(例如,病原体测试,氯化,辐照以及清洁和消毒程序)。模型显示,在相同的模拟条件下,辐射(0.5 KGy)比氯化法或病原体测试在降低流行率方面是更有效的净化步骤,尽管在模拟干预的所有情况下,病原体都能够生存并存在于最终包装袋中。

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