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致病微生物和腐败微生物的联合随机建模

Combined stochastic modelling of pathogenic and spoilage microorganisms.

作者信息

Maciejewska Nikola, Stefanou Constantine-Richard, Stathas Leonardos, Koutsoumanis Konstantinos

机构信息

Department of Food Quality, Prof. Waclaw Dabrowski Institute of Agriculture and Food Biotechnology State Research Institute Lodz Poland.

Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece.

出版信息

EFSA J. 2024 Dec 20;22(Suppl 1):e221112. doi: 10.2903/j.efsa.2024.e221112. eCollection 2024 Dec.

Abstract

Quantitative microbiological risk assessment (QMRA) of pathogens in food safety is well established, but steps are being taken to expand this methodology to food spoilage. Parallels can be drawn between the steps involved in a QMRA for pathogens and its application to specific spoilage organisms (SSO). During hazard characterisation for pathogens, the appropriate dose-response model is used to link the hazard level to the health outcome by estimating the probability of illness, resulting from the ingestion of a certain dose of the hazard. The dose-response model, in the case of food spoilage, may be translated into a spoilage-response relationship linking the spoilage-level with the probability the consumer will discard the food and not consume it. Such models are developed with sensory testing, assessing consumers sensitivity to microbial spoilage quality defects and correlating them to the SSO concentration. Ignoring food spoilage before the stated expiration date can lead to the final health risk being overestimated, since cases in which the food item poses a real risk to the consumer but is not consumed due to perceived spoilage are not excluded. Plenty of risk assessments have been carried out for pathogens in different RTE foods. What is missing is the integration of the two approaches into a single model that can estimate the risk of illness, factoring in the variability of consumer responses to spoilage. The spoilage-response relationship was combined with a stochastic modelling approach for lactic acid bacteria (LAB) and growth, also taking into account microbial interaction between LAB and (Jameson effect) to increase accuracy. The comparison of results between the 'Baseline' and the 'Spoilage-informed' approach showed significant difference in listeriosis cases, both for consumers under and over 65 years old. These results may suggest, that the hypothesis about overestimation of listeriosis risk in case of not taking into account product spoilage is correct. The combined QMRA model developed in the present study can be a useful tool for risk management decisions in the meat industry.

摘要

食品安全中病原体的定量微生物风险评估(QMRA)已得到广泛认可,但目前正在采取措施将该方法扩展到食品变质领域。在针对病原体的QMRA所涉及的步骤与其应用于特定腐败菌(SSO)之间可以找到相似之处。在病原体的危害特征描述过程中,通过估计摄入一定剂量危害导致疾病的概率,使用适当的剂量反应模型将危害水平与健康结果联系起来。在食品变质的情况下,剂量反应模型可以转化为腐败反应关系,将腐败水平与消费者丢弃食品而不食用的概率联系起来。此类模型通过感官测试来开发,评估消费者对微生物腐败质量缺陷的敏感性,并将其与SSO浓度相关联。忽略在规定保质期之前的食品变质可能导致最终健康风险被高估,因为未排除食品对消费者构成真正风险但因感觉变质而未被食用的情况。已经针对不同即食食品中的病原体进行了大量风险评估。所缺少的是将这两种方法整合到一个单一模型中,该模型可以估计疾病风险,同时考虑消费者对变质反应的变异性。将腐败反应关系与乳酸菌(LAB)生长的随机建模方法相结合,同时也考虑了LAB与[此处原文缺失相关内容]之间的微生物相互作用(詹姆森效应)以提高准确性。“基线”方法和“考虑变质”方法之间的结果比较显示,无论是65岁以下还是65岁以上的消费者,李斯特菌病病例都存在显著差异。这些结果可能表明,关于在不考虑产品变质情况下高估李斯特菌病风险的假设是正确的。本研究中开发的综合QMRA模型可以成为肉类行业风险管理决策的有用工具。

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