  Short-chain fatty acids (SCFAs), including acetate, propionate and butyrate,
are organic fatty-acids that are produced when indigested carbohydrates are
fermented in the colon by gut-bacteria. Butyrate is especially considered a
beneficial compound in relation to gut health and the maintenance of colonic
homeostasis. Little is known about butyrate production and the current
measurement methods of fecal samples are not representative and there is a
strong unmet need to measure SCFAs in-vivo to further understand their role and
effect on colonic function in human gut health and disease. The general aim of
the project is to develop a novel sensor based on infrared technology that is
capable of online detecting short chain fatty acids (SCFA; e.g. acetate,
propionate and butyrate) and other small biomolecules (e.g. ammonium) produced
in bioreactors. Whereas currently such levels of small biomolecules are usually
not detected online due to practical constraints (sampling-analysis-processing
of data), reliable online detection could significantly decrease analysis
costs. Further, it would allow to perform online quality control of the
bioreactors and allow to e.g. detect deviating values at an early stage. Hence,
one can react much faster tackling certain problems which will further improve
the quality of each experiment. Using machine learning algorithms to process
the sensor signals, the results from testing in a so-called artificial gut
setup are described in this technical report.
