Title: On the need for another type of predictive model in structured foods
Authors: Dens, EJ ×
Van Impe, Jan #
Issue Date: 2001
Series Title: International journal of food microbiology vol:64 issue:3 pages:247-260
Conference: date:Katholieke Univ Leuven, Dept Food & Microbial Technol, B-3001 Louvain, Belgium
Abstract: Most of the models discussed up till now in predictive microbiology do nor take into account the variability of microbial growth with respect to space. In structured (solid) foods, microbial growth can strongly depend on the position in the food and the assumption of humogeneity can thus not be accepted: space must be considered as an independent variable. Indeed, experimental evidence exists of bacteria competition on agar not showing the same behavior as the competition in a well-mixed liquid culture system. It is conjectured that this is due to the spatially structured habitat. Therefore, in the current paper, a prototype two species competition model proposed in previous work by the authors is extended to take space into account. The extended model describes two phenomena: (i) local evolution of biomass and (ii) transfer of biomass through the medium. The structure of the food product is taken into account by limiting the diffusion through the medium. The smaller mobility of the micro-organisms in solid foods allows spatial segregation which causes pattern formation. Evidence is given for the fact that taking space into account indeed has an influence on the behavior (coexistence/extinction) of the populations. Although the reported simulations are by no means to be interpreted as accurate predictions, the proposed model structure allows one to highlight (i) important characteristics of microbial growth in structured foods and (ii) future research trends in predictive microbiology. (C) 2001 Elsevier Science B.V. All rights reserved.
ISSN: 0168-1605
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
× corresponding author
# (joint) last author

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