Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors
| Autor: | Thomas Beuermann, Annabell Heintz, Norbert Gretz, Robert Schalk, Frank Braun, Frank-Jürgen Methner, Giuseppe Iacono, Matthias Rädle |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
multiple linear regression Analyte Absorption spectroscopy mid-infrared spectroscopy Analytical chemistry multi-channel photometric sensors 01 natural sciences fermentation of Saccharomyces cerevisiae lcsh:Technology lcsh:Chemistry symbols.namesake 010608 biotechnology Partial least squares regression Linear regression General Materials Science monitoring of glucose Spectroscopy Instrumentation lcsh:QH301-705.5 Fluid Flow and Transfer Processes Spectrometer biomass Chemistry lcsh:T Process Chemistry and Technology 010401 analytical chemistry General Engineering partial least squares regression real-time monitoring lcsh:QC1-999 0104 chemical sciences Computer Science Applications Diauxic growth lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 Raman spectroscopy symbols ddc:660 ethanol lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
| Zdroj: | Applied Sciences, Vol 9, Iss 12, p 2472 (2019) Applied Sciences Volume 9 Issue 12 |
| ISSN: | 2076-3417 |
| Popis: | Raman and mid-infrared (MIR) spectroscopy are useful tools for the specific detection of molecules, since both methods are based on the excitation of fundamental vibration modes. In this study, Raman and MIR spectroscopy were applied simultaneously during aerobic yeast fermentations of Saccharomyces cerevisiae. Based on the recorded Raman intensities and MIR absorption spectra, respectively, temporal concentration courses of glucose, ethanol, and biomass were determined. The chemometric methods used to evaluate the analyte concentrations were partial least squares (PLS) regression and multiple linear regression (MLR). In view of potential photometric sensors, MLR models based on two (2D) and four (4D) analyte-specific optical channels were developed. All chemometric models were tested to predict glucose concentrations between 0 and 30 g L&minus 1, ethanol concentrations between 0 and 10 g L&minus 1, and biomass concentrations up to 15 g L&minus 1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L&minus 1, 0.48 g L&minus 1, and 0.37 g L&minus 1 for glucose, ethanol, and biomass were achieved using the MIR setup combined with a PLS model. In the case of Raman spectroscopy, the corresponding RMSEP values were 0.92 g L&minus 1, 0.39 g L&minus 1, and 0.29 g L&minus 1. Nevertheless, the simple 4D MLR models could reach the performance of the more complex PLS evaluation. Consequently, the replacement of spectrometer setups by four-channel sensors were discussed. Moreover, the advantages and disadvantages of Raman and MIR setups are demonstrated with regard to process implementation. |
| Databáze: | OpenAIRE |
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