Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.talanta.2013.12.026
Title: Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring
Authors: Chen, B.
Wu, H. 
Li, S.F.Y. 
Keywords: Chemical oxygen demand (COD)
Data fusion
Partial-least-squares regression (PLSR)
Slope-derived spectroscopy
Wastewater quality monitoring
Issue Date: Mar-2014
Citation: Chen, B., Wu, H., Li, S.F.Y. (2014-03). Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring. Talanta 120 : 325-330. ScholarBank@NUS Repository. https://doi.org/10.1016/j.talanta.2013.12.026
Abstract: To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R2 of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring. © 2013 Elsevier B.V.
Source Title: Talanta
URI: http://scholarbank.nus.edu.sg/handle/10635/113242
ISSN: 00399140
DOI: 10.1016/j.talanta.2013.12.026
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