Literature DB >> 28656375

Non-contact Raman spectroscopy for in-line monitoring of glucose and ethanol during yeast fermentations.

Robert Schalk1, Frank Braun2, Rudolf Frank2, Matthias Rädle2, Norbert Gretz3, Frank-Jürgen Methner4, Thomas Beuermann2.   

Abstract

The monitoring of microbiological processes using Raman spectroscopy has gained in importance over the past few years. Commercial Raman spectroscopic equipment consists of a laser, spectrometer, and fiberoptic immersion probe in direct contact with the fermentation medium. To avoid possible sterilization problems and biofilm formation on the probe tip, a large-aperture Raman probe was developed. The design of the probe enables non-contact in-line measurements through glass vessels or inspection glasses of bioreactors and chemical reactors. The practical applicability of the probe was tested during yeast fermentations by monitoring the consumption of substrate glucose and the formation of ethanol as the product. Multiple linear regression models were applied to evaluate the Raman spectra. Reference values were determined by high-performance liquid chromatography. The relative errors of prediction for glucose and ethanol were 5 and 3%, respectively. The presented Raman probe allows simple adaption to a wide range of processes in the chemical, pharmaceutical, and biotechnological industries.

Entities:  

Keywords:  Glucose and ethanol; In-line reaction monitoring; Multiple linear regression; Non-contact Raman spectroscopy; Saccharomyces cerevisiae

Mesh:

Substances:

Year:  2017        PMID: 28656375     DOI: 10.1007/s00449-017-1808-9

Source DB:  PubMed          Journal:  Bioprocess Biosyst Eng        ISSN: 1615-7591            Impact factor:   3.210


  4 in total

1.  Label-free enzymatic reaction monitoring in water-in-oil microdroplets using ultra-broadband multiplex coherent anti-Stokes Raman scattering spectroscopy.

Authors:  Ryo Imai; Hideaki Kano
Journal:  Biomed Opt Express       Date:  2022-02-15       Impact factor: 3.732

2.  Non-invasive Raman spectroscopy for time-resolved in-line lipidomics.

Authors:  Karin Wieland; Mahmoud Masri; Jeremy von Poschinger; Thomas Brück; Christoph Haisch
Journal:  RSC Adv       Date:  2021-08-24       Impact factor: 4.036

3.  Incremental Learning in Modelling Process Analysis Technology (PAT)-An Important Tool in the Measuring and Control Circuit on the Way to the Smart Factory.

Authors:  Shivani Choudhary; Deborah Herdt; Erik Spoor; José Fernando García Molina; Marcel Nachtmann; Matthias Rädle
Journal:  Sensors (Basel)       Date:  2021-05-01       Impact factor: 3.576

4.  Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy.

Authors:  Simona Dzurendová; Volha Shapaval; Valeria Tafintseva; Achim Kohler; Dana Byrtusová; Martin Szotkowski; Ivana Márová; Boris Zimmermann
Journal:  Int J Mol Sci       Date:  2021-06-23       Impact factor: 5.923

  4 in total

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