細菌の死滅予測モデルに おける最近の進展

抄録

Stochastic approaches for describing microbial death responses in foods have gained increased attention in the field of predictive microbiology and quantitative microbial risk assessment. Particularly, recent studies have focused on describing variability and uncertainty of microbial responses. Although variability due to individual cell heterogeneity is inherent in a small number of bacteria during the inactivation process, an appropriate theoretical stochastic description for the variability in individual cell heterogeneity has not been achieved. This article reviews recent advances in the development of models for describing the variability in individual cell heterogeneity from the perspective of bacterial inactivation, as a stochastic process of bacterial cell numbers. Large numbers of replicated experiments, computer simulations, and mathematical formulations have led to novel techniques for describing variability in individual cell heterogeneity during the microbial survival process. The proposed stochastic theory will enable reinterpretation of conventional bacterial behavior based on the average bacterial numbers. Advances in the modeling procedures described in this article will support the further development of predictive microbiology studies and their practical use in food processing and distribution environments.