Real-time estimation of glucose concentration in algae cultivation system using Raman spectroscopy
•We propose a framework for estimation of glucose concentration.•Prediction performance is improved by applying pre- and post-processing steps.•Prediction performance was evaluated using samples of two different experiments.•The background effect has the greatest impact on prediction performance. Th...
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Published in | Bioresource technology Vol. 142; pp. 131 - 137 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier Ltd
01.08.2013
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | •We propose a framework for estimation of glucose concentration.•Prediction performance is improved by applying pre- and post-processing steps.•Prediction performance was evaluated using samples of two different experiments.•The background effect has the greatest impact on prediction performance.
This work proposes a soft-sensor design for real-time estimation of glucose concentration under mixotrophic conditions using Raman spectroscopy. The suggested approach applies a Rolling-Circle Filter (RCF), Partial Least Squares (PLS), and a successive Savitzky–Golay (SG) smoothing filter. RCF is used to remove the background effects of Raman spectrum in the pre-processing step. PLS is used to reduce the dimensionality of spectrum data and relate them to the concentration. The SG filter is further employed as a post-processing step in a successive manner to adjust predicted glucose concentrations. Two sets of experiments using artificial assays and samples from a microalgae cultivation system were performed for verification. The proposed approach showed improved prediction performances compared to other data processing and regression techniques. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0960-8524 1873-2976 |
DOI: | 10.1016/j.biortech.2013.05.008 |