Modeling of microbial quality of food

<p>In this thesis it is shown that predictive modeling is a promising tool in food research, to be used to optimize food chains. Various models are developed and validated to be used to describe microbial growth in foods.<p>A tool is developed to discriminate between different models and to restrict the number of parameters in models. Models to describe a growth curve and to describe the effect of temperature, and the effect of shifts in temperatures, are developed and validated with a large amount of experimental data.<p>Furthermore, a procedure is developed to couple quantitative and qualitative information in a structured manner. Simple procedures to make (preliminary) shelf-life predictions are given, as are procedures to extend these (simple) models.<p>The most important advantage of modeling is that insight is gained in the progression of microbial growth within a product chain. Furthermore, these models are shown to be essential to calculate quality changes with the use of decision support systems (DSS)