Predictive microbiology is a recent area within food microbiology which studies the responses
of microorganisms in foods to environmental factors (e.g. temperature pH) through
mathematical functions. These functions enable scientists to predict the behavior of pathogens
and spoilage microorganisms under different combinations of factors. The main goal of
predictive models in food science is to assure both food safety and food quality. Predictive
models in foods have developed significantly in the last 20 years due to the emergence of
powerful computational resources and sophisticated statistical packages. This book presents the
concepts models most significant advances and future trends in predictive microbiology. It
will discuss the history and basic concepts of predictive microbiology. The most frequently
used models will be explained and the most significant software and databases (e.g. Combase
Sym'Previus) will be reviewed. Quantitative Risk Assessment which uses predictive modeling to
account for the transmission of foodborne pathogens across the food chain will also be
covered.
