Title: Optimal Experimental Design for Discriminating between Microbial Growth Models as a Function of Suboptimal Temperature
Other Titles: Optimaal experimentontwerp voor model discriminatie tussen microbiële kinetische modellen in in functie van het suboptimale temperatuurgebied,,
Authors: Stamati, Ioanna
Issue Date: 9-Dec-2016
Abstract: In the field of predictive microbiology, mathematical models play an important role for describing microbial growth, survival and inactivation. Microbial dynamics are often described likewise by different models. However, the model that describes the system in the best way is desired. Optimal experimental design for model discrimination (OED/MD) is an efficient tool for discriminating among rival models.
This dissertation focuses on the use of methods for optimal experiment design for model discrimination between microbial kinetic models, with particular emphasis to secondary models describing microbial kinetics in the suboptimal temperature range.
On the one hand, different methods have been considered and tested for their applicability on the current application domain, i.e., secondary models describing microbial kinetics in the suboptimal temperature range. It appears that the method proposed by Schwaab et al. (2008) and Donckels et al. (2009) would behave better in a real life application. On the other hand, a thorough study has been performed as to define the possibilities of this particular selected method and get an indication of the expected experimental burden, when applied on the discrimination between the models under interest. Given the above aspects the last step includes the smooth and efficient transition from the in silico to the in vivo environment.
Publication status: published
KU Leuven publication type: TH
Appears in Collections:UC Limburg - miscellaneous
Sustainable Chemical Process Technology TC, Technology Campus Diepenbeek
Sustainable Chemical Process Technology TC
Sustainable Chemical Process Technology TC, Technology Campuses Ghent and Aalst
Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics

Files in This Item:
File Status SizeFormat
IoannaPhD_FINAL.pdf Published 2817KbAdobe PDFView/Open Request a copy

These files are only available to some KU Leuven Association staff members


All items in Lirias are protected by copyright, with all rights reserved.