The research in Monitoring and Control of Bioprocesses includes:
Monitoring of activated sludge using quantitative image analysis (correlation with settleability, SVI, detection of bulking events): data from morphological sludge characterization (microbial aggregates and protruding filaments) is treated using chemometrics techniques (PLS).
Also, an activated sludge reactor has been surveyed using online UV-visible and NIR spectroscopy and chemometrics.
QIA is being used in automatic recognition of protozoa and metazoa populations most frequently found in wastewater treatment plants. Image analysis procedures were developed for determining the geometrical, morphological and signature data and subsequent processing by discriminant analysis and neural network techniques.
Image analysis is also used in the determination of the movement changes of ciliates exposed to toxics.
QIA of granular sludge and multivariate statistical analysis have been used for monitoring high-rate anaerobic reactors.
Image Analysis is being used to characterize granular anaerobic sludge from EGSB Reactors fed with oleic acid. QIA allows for automatic detection of granules disintegration constituting a tool to recognize anaerobic granulation time.
The research carried out in Modelling, Monitoring, and Control of Bioprocesses by the BIOSYSTEMS group has been focused in the development of mathematical and computational tools aiming the optimization of the operational conditions of relevant bioprocesses like recombinant proteins production with E. coli, baker's yeast fermentation, production of prebiotics with yeast and fungi, production of phages and animal cell culture. The main areas of activities are the following:
Design and implementation of algorithms for estimating on-line state variables like biomass concentration from common bioreactor measurements like dissolved and exhausted oxygen concentrations.
Observer based estimators for on-line measurement of specific growth rates.
Applications: estimation of biomass concentration and specific growth rates in high cell density fed-batch culture of E. coli.
Model-based adaptive linearizing control for the regulation of substrates/products during the fed-batch fermentations.
Development and implementation of control laws for the specific growth rate in fed-batch fermentation (PI like feedforward/feedback controllers).
Applications: recombinant proteins production in high cell density culture of E. coli; baker's yeast production.