Application of green analytical chemistry to a green chemistry process: Magnetic resonance and Raman spectroscopic process monitoring of continuous ethanolic fermentation. Issue 11 (21st July 2019)

• Record Type: Journal Article
• Authors: Legner, Robin; Wirtz, Alexander; Koza, Tim; Tetzlaff, Till; Nickisch‐Hartfiel, Anna; Jaeger, Martin
• Is Part Of: Biotechnology and bioengineering. Volume 116:Issue 11(2019)
• Page Start: 2874
• Page End: 2883
• Publication Date: 2019-07-21
• Subjects: bioprocess monitoring -- compact spectrometer -- immobilized yeast -- multivariate data analysis -- NMR and Raman spectroscopy -- PLS2; Biotechnology -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/bit.27112
• Languages: English
• ISSNs: 0006-3592

Abstract

Abstract: Compact 1 H NMR and Raman spectrometers were used for real‐time process monitoring of alcoholic fermentation in a continuous flow reactor. Yeast cells catalyzing the sucrose conversion were immobilized in alginate beads floating in the reactor. The spectrometers proved to be robust and could be easily attached to the reaction apparatus. As environmentally friendly analysis methods, 1 H NMR and Raman spectroscopy were selected to match the resource‐ and energy‐saving process. Analyses took only a few seconds to minutes compared to chromatographic procedures and were, therefore, suitable for real‐time control realized as a feedback loop. Both compact spectrometers were successfully implemented online. Raman spectroscopy allowed for faster spectral acquisition and higher quantitative precision, NMR yielded more resolved signals thus higher specificity. By using the software Matlab for automated data loading and processing, relevant parameters such as the ethanol, glycerol, and sugar content could be easily obtained. The subsequent multivariate data analysis using partial linear least‐squares regression type 2 enabled the quantitative monitoring of all reactants within a single model in real time. Abstract : Green chemistry was process‐monitored by Green Analytical Chemistry: Continuous one‐ and two‐stage alcoholic fermentation by immobilized yeast was followed in real time using compact NMR and Raman spectrometers. Process data were transformed into concentration–time diagrams. Process models were developed through multivariate chemometric methods. The models represent process understanding and might be used to optimize the fermentation, compare fermentations and to implement a feedback control loop for process automation.