화학공학소재연구정보센터
Journal of Applied Microbiology, Vol.88, No.6, 938-951, 2000
Stepwise quantitative risk assessment as a tool for characterization of microbiological food safety
This paper describes a system for the microbiological quantitative risk assessment for food products and their production processes. The system applies a stepwise risk assessment, allowing the main problems to be addressed before focusing on less important problems. First, risks are assessed broadly, using order of magnitude estimates. Characteristic numbers are used to quantitatively characterize microbial behaviour during the production process. These numbers help to highlight the major risk-determining phenomena, and to find negligible aspects. Second, the risk-determining phenomena are studied in more detail. Both general and/or specific models can be used for this and varying situations can be simulated to quantitatively describe the risk-determining phenomena. Third, even more detailed studies can be performed where necessary, for instance by using stochastic variables. The system for quantitative risk assessment has been implemented as a decision supporting expert system called SIEFE: Stepwise and Interactive Evaluation of Food safety by an Expert System. SIEFE performs bacterial risk assessments in a structured manner, using various information sources. Because all steps are transparent, every step can easily be scrutinized. In the current study the effectiveness of SIEFE is shown for a cheese spread. With this product, quantitative data concerning the major risk-determining factors were not completely available to carry out a full detailed assessment. However, this did not necessarily hamper adequate risk estimation. Using ranges of values instead helped identifying the quantitatively most important parameters and the magnitude of their impact. This example shows that SIEFE provides quantitative insights into production processes and their risk-determining factors to both risk assessors and decision makers, and highlights critical gaps in knowledge.