Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling.

ABSTRACT: Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. In the context of microbial risk assessment, the uncertainty in the predicted microbial behavior can be an important component of the overall uncertainty. Conventional deterministic modeling approaches which provide point estimates of the pathogen's levels cannot quantify the uncertainty around the predictions. The objective of this study was to use Bayesian statistical modeling for describing uncertainty in predicted microbial thermal inactivation of Salmonella enterica Typhimurium DT104. A set of thermal inactivation data in broth with water activity adjusted to 0.75 at 9 different temperature conditions obtained from the ComBase database (w

SUBMITTER: Koyama K 

PROVIDER: S-EPMC6798057 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature