SECALIM, INRA, Oniris, Université Bretagne Loire, 44307 Nantes, France.
SECALIM, INRA, Oniris, Université Bretagne Loire, 44307 Nantes, France.
Food Res Int. 2018 Apr;106:1132-1139. doi: 10.1016/j.foodres.2017.11.025. Epub 2017 Nov 22.
The objective of this article is to bring scientific background as well as practical hints and tips to guide risk assessors and modelers who want to develop a quantitative Microbiological Risk Assessment (MRA) in an industrial context. MRA aims at determining the public health risk associated with biological hazards in a food. Its implementation in industry enables to compare the efficiency of different risk reduction measures, and more precisely different operational settings, by predicting their effect on the final model output. The first stage in MRA is to clearly define the purpose and scope with stakeholders, risk assessors and modelers. Then, a probabilistic model is developed; this includes schematically three important phases. Firstly, the model structure has to be defined, i.e. the connections between different operational processing steps. An important step in food industry is the thermal processing leading to microbial inactivation. Growth of heat-treated surviving microorganisms and/or post-process contamination during storage phase is also important to take into account. Secondly, mathematical equations are determined to estimate the change of microbial load after each processing step. This phase includes the construction of model inputs by collecting data or eliciting experts. Finally, the model outputs are obtained by simulation procedures, they have to be interpreted and communicated to targeted stakeholders. In this latter phase, tools such as what-if scenarios provide an essential added value. These different MRA phases are illustrated through two examples covering important issues in industry. The first one covers process optimization in a food safety context, the second one covers shelf-life determination in a food quality context. Although both contexts required the same methodology, they do not have the same endpoint: up to the human health in the foie gras case-study illustrating here a safety application, up to the food portion in the brioche case-study illustrating here a quality application.
本文的目的是为希望在工业环境中开发定量微生物学风险评估(MRA)的风险评估人员和建模人员提供科学背景以及实用的提示和技巧。MRA 的目的是确定食品中与生物危害相关的公共卫生风险。在工业中的实施使人们能够通过预测不同减少风险措施(更确切地说是不同操作设置)对最终模型输出的影响来比较其效率。MRA 的第一阶段是与利益相关者、风险评估人员和建模人员明确界定目的和范围。然后,开发概率模型;这包括三个重要阶段。首先,必须定义模型结构,即不同操作处理步骤之间的连接。食品工业中的一个重要步骤是导致微生物失活的热处理。还需要考虑热处理后存活微生物的生长和/或储存阶段的后续过程污染。其次,确定数学方程来估计每个处理步骤后微生物负荷的变化。这一阶段包括通过收集数据或征求专家意见来构建模型输入。最后,通过模拟程序获得模型输出,必须对其进行解释并与目标利益相关者进行沟通。在最后阶段,情景分析等工具提供了重要的附加值。通过涵盖工业中重要问题的两个示例来说明不同的 MRA 阶段。第一个示例涵盖食品安全背景下的工艺优化,第二个示例涵盖食品质量背景下的保质期确定。尽管这两个背景都需要相同的方法,但它们的终点不同:在本文中,鹅肝案例研究中的终点是人类健康,用于说明安全应用,而面包案例研究中的终点是食品部分,用于说明质量应用。