ABSTRACT
A model has been described as “a system of postulates, data, and inferences presented as a mathematical description of an entity, or state of affairs” (Webster, 1989). Predictive modeling offers food safety microbiologists a means to describe the survival, growth, and production of toxins by bacterial pathogens in substrates controlled by preservation factors, such as temperature, pH, water activity, oxidation-reduction potential (Eh), various additives, and their interactions. Acquisition of bacterial growth or toxigenesis data is labor-intensive, especially in the study of Clostridium botulinum. Thus, individual researchers have concentrated their studies on variables affecting specific media or food systems. The analysis of these separate studies has led to many modeling techniques, which may confuse readers, depending on their individual working knowledge of advanced statistics, calculus, solution of engineering problems, or use of computer applications. The future of food preservation science will most likely use models to reduce and correlate data from related factorial research designs. The best modeling approaches will incorporate terms that are consistent with the principles of microbial physiology, robust enough to be applicable to food product design, and offer a basis for risk assessment and the establishment of safety margins.
