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Status: Bibliographieeintrag

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Verfasst von:Schalk, Robert [VerfasserIn]   i
 Heintz, Annabell [VerfasserIn]   i
 Braun, Frank [VerfasserIn]   i
 Iacono, Giuseppe [VerfasserIn]   i
 Rädle, Matthias [VerfasserIn]   i
 Gretz, Norbert [VerfasserIn]   i
 Methner, Frank-Jürgen [VerfasserIn]   i
 Beuermann, Thomas [VerfasserIn]   i
Titel:Comparison of raman and mid-infrared spectroscopy for real-time monitoring of yeast fermentations
Titelzusatz:a proof-of-concept for multi-channel photometric sensors
Verf.angabe:Robert Schalk, Annabell Heintz, Frank Braun, Giuseppe Iacono, Matthias Raedle, Norbert Gretz, Frank-Juergen Methner and Thomas Beuermann
E-Jahr:2019
Jahr:17 June 2019
Umfang:18 S.
Fussnoten:Gesehen am 11.09.2019
Titel Quelle:Enthalten in: Applied Sciences
Ort Quelle:Basel : MDPI, 2011
Jahr Quelle:2019
Band/Heft Quelle:9(2019,12), Artikel-Nummer 2472, 18 Seiten
ISSN Quelle:2076-3417
Abstract: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-1, ethanol concentrations between 0 and 10 g L-1, and biomass concentrations up to 15 g L-1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L-1, 0.48 g L-1, and 0.37 g L-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-1, 0.39 g L-1, and 0.29 g L-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.
DOI:doi:10.3390/app9122472
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

kostenfrei: Volltext: https://doi.org/10.3390/app9122472
 kostenfrei: Volltext: https://www.mdpi.com/2076-3417/9/12/2472
 DOI: https://doi.org/10.3390/app9122472
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:biomass
 bioprocess
 ethanol
 fermentation of Saccharomyces cerevisiae
 in-line reaction
 mid-infrared spectroscopy
 monitoring of glucose
 multi-channel photometric sensors
 multiple linear regression
 partial least squares regression
 prediction
 probe
 Raman spectroscopy
 real-time monitoring
 saccharomyces-cerevisiae
 systems
K10plus-PPN:1676501894
Verknüpfungen:→ Zeitschrift

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