Monitoring a bioprocess for ethanol production using FT-MIR and FT-Raman spectroscopy |
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Authors: | S Sivakesava J Irudayaraj A Demirci |
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Affiliation: | (1) Department of Agricultural and Biological Engineering, Pennsylvania State University, 249, Agricultural Engineering Building, University Park, PA 16802, USA, US |
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Abstract: | The application of Fourier transform mid-infrared (FT-MIR) spectroscopy and Fourier transform Raman (FT-Raman) spectroscopy for process and quality control of fermentative production of ethanol was investigated. FT-MIR and FT-Raman spectroscopy along with multivariate techniques were used to determine simultaneously glucose, ethanol, and optical cell density of Saccharomyces cerevisiae during ethanol fermentation. Spectroscopic measurement of glucose and ethanol were compared and validated with the high-performance liquid chromatography (HPLC) method. Spectral wave number regions were selected for partial least-squares (PLS) regression and principal component regression (PCR) and calibration models for glucose, ethanol, and optical cell density were developed for culture samples. Correlation coefficient (R 2) value for the prediction for glucose and ethanol was more than 0.9 using various calibration methods. The standard error of prediction for the PLS first-derivative calibration models for glucose, ethanol, and optical cell density were 1.938 g/l, 1.150 g/l, and 0.507, respectively. Prediction errors were high with FT-Raman because the Raman scattering of the cultures was weak. Results indicated that FT-MIR spectroscopy could be used for rapid detection of glucose, ethanol, and optical cell density in S. cerevisiae culture during ethanol fermentation. Journal of Industrial Microbiology & Biotechnology (2001) 26, 185–190. Received 16 November 2000/ Accepted in revised form 12 January 2001 |
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Keywords: | : Fourier transform midinfrared spectroscopy Fourier transform Raman spectroscopy multivariate analysis principal component regression partial least-squares regression |
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