Raman-based estimation of glucose concentration for on-line monitoring of biological process

In biological process, it not simple to analyze concentrations of a mixture in bioreactor because pre-processing is required for analyzing bio-product. Also, on-line monitoring of biological processes is essential for maximizing productivity because reactions are very slow. The Raman spectroscopy is...

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Bibliographic Details
Published in2012 12th International Conference on Control, Automation and Systems pp. 845 - 850
Main Authors Se-Kyu Oh, Sung Jin Yoo, Shin Je Lee, Jong Min Lee
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Biology
Monitoring
Noise
On-line monitoring
Partial Least Square
Predictive models
Raman scattering
Raman spectroscopy
Rolling-Circle Filter
Savitzky-Golay smoothing filter
Smoothing methods
Sugar
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Summary:In biological process, it not simple to analyze concentrations of a mixture in bioreactor because pre-processing is required for analyzing bio-product. Also, on-line monitoring of biological processes is essential for maximizing productivity because reactions are very slow. The Raman spectroscopy is suitable for on-line monitoring of bioprocess with proper analysis algorithms. This work proposes a prediction technique based on Raman spectra. It first removes the background effect and further reduces noise using the Rolling-Circle Filter (RCF) and Savitzky-Golay smoothing filter, respectively. Then Partial Least Square (PLS) is used to reduce the dimension of spectra and predict the concentrations based on latent variables. The prediction performance of glucose concentration was improved by 30% by applying the proposed methods.
ISBN:9781467322478
1467322474