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Individual-based modelling: a mechanistic complement underpinning macroscopic models in predictive microbiology
Abstract:
In the field of predictive microbiology, mathematical models are developed to describe and predict the behaviour and possible outgrowth of spoilage and pathogenic microorganisms in food products. Research has mainly focused on the development of macroscopic models, describing the evolution of macroscopical quantities like the total cell number N. This macroscopic approach has a number of inherent disadvantages. This paper proposes the individual-based modelling methodology as a complement to macroscopic models to overcome some of these issues. As a case study, the paper proposes a new bacterial growth model to describe the stationary phase of bacterial growth. The new model is implemented in an individual-based framework and exploratory results are presented.
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