Chemometric Models Applied to Raman Spectroscopy for Bioprocess Monitoring

Abstract

This work investigates the development of a Raman spectroscopy-based sensor for the quantitative analysis of products obtained from the fermentation to ethanol of the hydrolyzed product of brewer’s spent grain. Partial least squares (PLS) and variable importance in projection (VIP) methods were applied in order to correlate the information contained in the Raman spectra to the concentration of the compounds investigated. Results showed good prediction capabilities of the developed models when analyzing standard solutions containing ethanol and glucose. On the other hand, when analyzing samples obtained from the fermentation process, turbidity, caused by suspended particles in the solution, made analyzing spectra more difficult, leading to a decrease of the validation determination coefficient from 0.9374 to 0.7913 for ethanol and from 0.6237 to 0.4783 for glucose.