Utilization of first-order mass action kinetic models to elucidate the mechanism of methane fermentation of glycerol

Abstract

Knowledge-driven models can aid in understanding the underlying mechanism of methane fermentation, however, these models are often too complex. We proposed to utilize first-order mass action kinetic models as a simpler alternative to conventional knowledge-driven models for gaining some insights on the mechanism of methane fermentation. The data used for model fitting were obtained from a methane fermentation experiment using anaerobic sequencing batch reactor (ASBR) with glycerol as a substrate. Incorporation of substrate feeding profile into the model improved fitness to the data especially during the early stage of the feeding cycle. Model with the assumption that glycerol was metabolized into both propionic and acetic acid and methane was produced via both propionic and acetic acid showed the best fit (root-mean square error = 0.0012), which suggested that the mechanism of the glycerol methane fermentation might follow that particular path. The difference in the applicability of the models on several feed profiles used in this experiment suggested that the mechanism can be different for each feed profile, which was supported by the microbial consortium data. These findings showed the possibility to use first-order mass action kinetic models as a simpler alternative to study the mechanism of methane fermentation of glycerol.