Application of Bayesian Belief Network models to food-safety science

Abstract

We describe the use of Bayesian Belief Network methods for the representation of complex systems and indicate their role in analyses of food-borne hazards. We illustrate the method with two applications (i) an exposure assessment for nonproteolytic Clostridium botulinum in a minimally processed food product (ii) an analysis of the variability associated with the spore germination and growth lag times