raises new opportunities to analyse and experimentally challenge the meaning of the V h parameter. Particularly interesting would be to assess to which extent V h constitutes an intrinsic trait of the microbial culture, or if extrinsic attributes associated to the culture conditions (such as agitation, viscosity or ionic force) could also significantly influence its value. Such questions remain open and obviously await further studies.
From genetic sequencing, dry biomass, and metabolites measurements, the assignment of functions to the species present in chemostat experiments was solved by merging chemostat modelling and quadratic mixed integer programming. The method was tested on a nitrification bioprocess where two functions are known to drive the system. Sensitivity of the method, its advantages, and limitations are discussed.
This article deals with the inclusion of microbial ecology measurements such as abundances of operational taxonomic units in bioprocess modelling. The first part presents the mathematical analysis of a model that may be framed within the class of Lotka–Volterra models fitted to experimental data in a chemostat setting where a nitrification process was operated for over 500 days. The limitations and the insights of such an approach are discussed. In the second part, the use of an optimal tracking technique (developed within the framework of control theory) for the integration of data from genetic sequencing in chemostat models is presented. The optimal tracking revisits the data used in the aforementioned chemostat setting. The resulting model is an explanatory model, not a predictive one, it is able to reconstruct the different forms of nitrogen in the reactor by using the abundances of the operational taxonomic units, providing some insights into the growth rate of microbes in a complex community.
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