DESIGN OF DYNAMIC EXPERIMENTS FOR DISCRIMINATION BETWEEN MODELS FOR MICROBIAL GROWTH KINETICS AS A FUNCTION OF TEMPERATURE.

In the field of predictive microbiology, mathematical models play an important role for describing the microbial growth, survival and inactivation. Often different models are available for describing the microbial dynamics in a similar way. However, the model that describes the system in the best way is desired. Optimal experiment design for model discrimination (OED-MD) is an efficient tool for discriminating among rival models. In this work the OED-MD method proposed by Schwaab et al. (2008) and Donckels et al. (2010) will be used for discriminating among dynamic models of microbial growth rate as a function of temperature. This method provides experiments with an increased discriminatory potential and better estimates of the uncertainties. Results from a simulation study indicate that it is possible to validate the case that one of the proposed models is more accurate for describing the temperature effect on the microbial growth rate.