National Research Council of Canada. NRC Biotechnology Research Institute
environmental; multi-wavelength fluorometry; process monitoring; regression; PLS; anaerobic digestion; Bacteria, Anaerobic; biotechnology; cheese; fatty acids; fluorometry; least-squares analysis; multivariate analysis; oxygen; predictive value of tests; regression analysis; reproducibility of results; time factors; volatilization; waste disposal; fluid
This work examined the use of multi-wavelength fluorometry for on-line monitoring of an anaerobic digestion process. Experiments were carried out in a laboratory-scale anaerobic digestor fed with either synthetic or agricultural (cheese factory) wastewater. An in-line fiber optic probe installed in the external recirculation loop of the reactor was used to acquire fluorescence spectra with an interval of 5-10 min. The spectra were compared with analytical measurements taken at the same time to develop regression models, which were then used to predict concentrations of chemical oxygen demand, volatile fatty acids, and other key process parameters. A comparison of partial least squares (PLS), nonlinear principal components regression, and step-wise regression models on an independent set of data showed that the PLS model gave the best prediction accuracy.
Water Research38, no. 14-15 (2 July 2004): 3287–3296.