Data from: A mathematical model of cocoa bean fermentation

Cocoa bean fermentation relies on the sequential activation of several
microbial populations, triggering a temporal pattern of biochemical
transformations. Understanding this complex process is of tremendous
importance as it is known to form the precursors of the resulting
chocolate's flavor and taste. At the same time, cocoa bean
fermentation is one of the least controlled processes in the food
industry. Here, a quantitative model of cocoa bean fermentation is
constructed based on available microbiological and biochemical knowledge.
The model is formulated as a system of coupled ordinary differential
equations with two distinct types of state variables: (1) Metabolite
concentrations of glucose, fructose, ethanol, lactic acid and acetic acid,
and (2) Population sizes of yeast, lactic acid bacteria and acetic acid
bacteria. We demonstrate that the model can quantitatively describe
existing fermentation time series and that the estimated parameters,
obtained by a Bayesian framework, can be used to extract and interpret
differences in environmental conditions. The proposed model is a valuable
tool towards a mechanistic understanding of this complex biochemical
process, and can serve as a starting point for hypothesis testing of new
systemic adjustments. In addition to providing the first quantitative
mathematical model of cocoa bean fermentation, the purpose of our
investigation is to show how differences in estimated parameter values for
two experiments allow us to deduce differences in experimental conditions.