Biological systems
are commonly controlled and monitored
through
offline and time-consuming tools, which often impairs an effective
and real-time response to counteract system disturbances. The feasibility
of using two-dimensional (2D) fluorescence spectroscopy as a non-invasive,
non-destructive, and real-time procedure to monitor the acidogenic
fermentation of brewer’s spent grain (BSG) in a granular sludge
reactor was evaluated. For that, the effect of pH fluctuations on
the system response was used as a model to ascertain the 2D fluorescence
spectroscopy applicability to monitor the process performance, namely,
to predict the fermentation products (FP) and the soluble protein
(SProt) concentrations in the effluent stream through mathematical
analysis. The pH fluctuations over the course of the reactor’s
operation altered the granules’ microbiome composition, leading
to different effluent FP profiles. Fluorescence excitation–emission
matrices (EEMs) were used with projection to latent structures (PLS)
modeling to predict the FP and SProt concentrations in the effluent
with average errors below 0.75 and 0.43 g L–1, respectively.
Both models were able to capture the tendency of the data even when
the accuracy of prediction was not so high. The combined approach
of using 2D fluorescence spectroscopy and mathematical analysis seemed
promising for real-time monitoring of the acidogenic fermentation
of complex substrates.