E.J Dens

On the need for another type of predictive model in structured foods

Most of the models discussed up till now in predictive microbiology do not 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 homogeneity 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.

Concepts and tools for predictive modeling of microbial dynamics

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

On the importance of taking space into account when modeling microbial competition in structured food products

Most of the models discussed up till now in predictive microbiology do not 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 homogeneity can thus, not be accepted: space must be considered as an additional independent variable. In the current paper, a continuous time — two species competition model (proposed in previous work by the authors) is extended to take space into account. The spatio-temporal behavior of the spatially extended model is observed on a coupled map lattice. The smaller motility 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, which is very important in the field of predictive microbiology, where microbial safety is of major interest.