Bioprocess and Biosystems Engineering

, Volume 40, Issue 10, pp 1519–1527 | Cite as

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

  • Robert SchalkEmail author
  • Frank Braun
  • Rudolf Frank
  • Matthias Rädle
  • Norbert Gretz
  • Frank-Jürgen Methner
  • Thomas Beuermann
Research Paper


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.


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



We gratefully acknowledge the support from the Albert and Anneliese Konanz-Foundation of the Mannheim University of Applied Sciences. We would also like to thank the Institute for Technical Microbiology (Mannheim University of Applied Sciences, Germany), especially Kerstin Schlosser, for providing the HPLC system. Furthermore, the authors would like to thank Dr. Hanns Simon Eckhardt (tec5 AG, Germany) for technical support. This work was funded by the German Federation of Industrial Research Associations (AiF Project GmbH, Funding Code 2035756LW3).

Compliance with ethical standards

Conflict of interest

The authors declare no financial or commercial conflict of interest.


  1. 1.
    Geörg D, Schalk R, Methner F-J, Beuermann T (2015) MIR-ATR sensor for process monitoring. Meas Sci Technol 26:065501. doi: 10.1088/0957-0233/26/6/065501 CrossRefGoogle Scholar
  2. 2.
    Kessler RW (2013) Perspectives in process analysis: process analysis and technology. J Chemom 27:369–378. doi: 10.1002/cem.2549 CrossRefGoogle Scholar
  3. 3.
    Braun F, Schwolow S, Seltenreich J et al (2016) Highly sensitive Raman spectroscopy with low laser power for fast in-line reaction and multiphase flow monitoring. Anal Chem 88:9368–9374. doi: 10.1021/acs.analchem.6b01509 CrossRefGoogle Scholar
  4. 4.
    Brun N, Youssef I, Chevrel M-C et al (2013) In situ monitoring of styrene polymerization using Raman spectroscopy. Multi-scale approach of homogeneous and heterogeneous polymerization processes: in situ monitoring of styrene polymerization using Raman spectroscopy. J Raman Spectrosc 44:909–915. doi: 10.1002/jrs.4279 CrossRefGoogle Scholar
  5. 5.
    De Beer TRM, Allesø M, Goethals F et al (2007) Implementation of a process analytical technology system in a freeze-drying process using Raman spectroscopy for in-line process monitoring. Anal Chem 79:7992–8003. doi: 10.1021/ac070549h CrossRefGoogle Scholar
  6. 6.
    Romero-Torres S, Pérez-Ramos JD, Morris KR, Grant ER (2006) Raman spectroscopy for tablet coating thickness quantification and coating characterization in the presence of strong fluorescent interference. J Pharm Biomed Anal 41:811–819. doi: 10.1016/j.jpba.2006.01.033 CrossRefGoogle Scholar
  7. 7.
    Saerens L, Vervaet C, Remon J-P, De Beer T (2013) Visualization and process understanding of material behavior in the extrusion barrel during a hot-melt extrusion process using raman spectroscopy. Anal Chem 85:5420–5429. doi: 10.1021/ac400097t CrossRefGoogle Scholar
  8. 8.
    Vankeirsbilck T, Vercauteren A, Baeyens W et al (2002) Applications of Raman spectroscopy in pharmaceutical analysis. TrAC Trends Anal Chem 21:869–877. doi: 10.1016/S0165-9936(02)01208-6 CrossRefGoogle Scholar
  9. 9.
    De Beer TRM, Bodson C, Dejaegher B et al (2008) Raman spectroscopy as a process analytical technology (PAT) tool for the in-line monitoring and understanding of a powder blending process. J Pharm Biomed Anal 48:772–779. doi: 10.1016/j.jpba.2008.07.023 CrossRefGoogle Scholar
  10. 10.
    Chevrel M-C, Hoppe S, Meimaroglou D et al (2016) Application of Raman spectroscopy to characterization of residence time distribution and online monitoring of a pilot-scale tubular reactor for acrylic acid solution polymerization. Macromol React Eng 10:406–414. doi: 10.1002/mren.201500055 CrossRefGoogle Scholar
  11. 11.
    Cornel J, Mazzotti M (2008) Calibration-Free quantitative application of in situ raman spectroscopy to a crystallization process. Anal Chem 80:9240–9249. doi: 10.1021/ac801606z CrossRefGoogle Scholar
  12. 12.
    Šašić S, Ozaki Y (2010) Raman, infrared, and near-infrared chemical imaging. Wiley, HobokenGoogle Scholar
  13. 13.
    Salzer R, Siesler HW (2014) Infrared and Raman spectroscopic imaging. Wiley-VCH, Weinheim (2., completely rev. and updated ed.) CrossRefGoogle Scholar
  14. 14.
    Schwolow S, Braun F, Rädle M et al (2015) Fast and efficient acquisition of kinetic data in microreactors using in-line Raman analysis. Org Process Res Dev 19:1286–1292. doi: 10.1021/acs.oprd.5b00184 CrossRefGoogle Scholar
  15. 15.
    Shope TB, Vickers TJ, Mann CK (1987) The direct analysis of fermentation products by raman spectroscopy. Appl Spectrosc 41:908–912CrossRefGoogle Scholar
  16. 16.
    Shaw AD, Kaderbhai N, Jones A et al (1999) Noninvasive, on-line monitoring of the biotransformation by yeast of glucose to ethanol using dispersive raman spectroscopy and chemometrics. Appl Spectrosc 53:1419–1428. doi: 10.1366/0003702991945777 CrossRefGoogle Scholar
  17. 17.
    Sivakesava S, Irudayaraj J, Demirci A (2001) Monitoring a bioprocess for ethanol production using FT-MIR and FT-Raman spectroscopy. J Ind Microbiol Biotechnol 26:185–190CrossRefGoogle Scholar
  18. 18.
    Aarnoutse PJ, Westerhuis JA (2005) Quantitative raman reaction monitoring using the solvent as internal standard. Anal Chem 77:1228–1236. doi: 10.1021/ac0401523 CrossRefGoogle Scholar
  19. 19.
    Picard A, Daniel I, Montagnac G, Oger P (2007) In situ monitoring by quantitative Raman spectroscopy of alcoholic fermentation by Saccharomyces cerevisiae under high pressure. Extremophiles 11:445–452. doi: 10.1007/s00792-006-0054-x CrossRefGoogle Scholar
  20. 20.
    Iversen JA, Berg RW, Ahring BK (2014) Quantitative monitoring of yeast fermentation using Raman spectroscopy. Anal Bioanal Chem 406:4911–4919. doi: 10.1007/s00216-014-7897-2 CrossRefGoogle Scholar
  21. 21.
    Berger AJ, Itzkan I, Feld MS (1997) Feasibility of measuring blood glucose concentration by near-infrared Raman spectroscopy. Spectrochim Acta Part A 53:287–292Google Scholar
  22. 22.
    Enejder AMK, Scecina TG, Oh J et al (2005) Raman spectroscopy for noninvasive glucose measurements. J Biomed Opt 10:031114. doi: 10.1117/1.1920212 CrossRefGoogle Scholar
  23. 23.
    Bechtel KL, Shih W-C, Feld MS (2008) Intrinsic Raman spectroscopy for quantitative biological spectroscopy part II: experimental applications. Opt Express 16:12737–12745CrossRefGoogle Scholar
  24. 24.
    Braun F, Schalk R, Brunner J et al (2016) Nicht-invasive Prozesssonde zur Inline-Ramananalyse durch optische Schaugläser. Tm Tech Mess. doi: 10.1515/teme-2016-0011 Google Scholar
  25. 25.
    Schalk R, Geoerg D, Staubach J et al (2016) Evaluation of a newly developed mid-infrared sensor for real-time monitoring of yeast fermentations. J Biosci Bioeng. doi: 10.1016/j.jbiosc.2016.12.005 Google Scholar
  26. 26.
    Beuermann T, Egly D, Geoerg D et al (2012) On-line carbon balance of yeast fermentations using miniaturized optical sensors. J Biosci Bioeng 113:399–405. doi: 10.1016/j.jbiosc.2011.10.016 CrossRefGoogle Scholar
  27. 27.
    Carey WP, Beebe KR, Sanchez E et al (1986) Chemometric analysis of multisensor arrays. Sens Actuators 9:223–234. doi: 10.1016/0250-6874(86)80023-3 CrossRefGoogle Scholar
  28. 28.
    Preacher KJ, Curran PJ, Bauer DJ (2006) Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. J Educ Behav Stat 31:437–448. doi: 10.3102/10769986031004437 CrossRefGoogle Scholar
  29. 29.
    Bellon V, Vigneau JL, Sévila F (1994) Infrared and near-infrared technology for the food industry and agricultural uses: on-line applications. Food Control 5:21–27. doi: 10.1016/0956-7135(94)90129-5 CrossRefGoogle Scholar
  30. 30.
    Via B, Shupe T, Groom L et al (2003) Multivariate modelling of density, strength and stiffness from near infrared spectra for mature, juvenile and pith wood of longleaf pine (Pinus palustris). J Infrared Spectrosc 11:365. doi: 10.1255/jnirs.388 CrossRefGoogle Scholar
  31. 31.
    Livingstone D (2009) A practical guide to scientific data analysis. Wiley, ChichesterCrossRefGoogle Scholar
  32. 32.
    Hidalgo B, Goodman M (2013) Multivariate or multivariable regression? Am J Public Health 103:39–40. doi: 10.2105/AJPH.2012.300897 CrossRefGoogle Scholar
  33. 33.
    Hejazi L, Mohammadi DE, Yamini Y, Brereton RG (2004) Solid-phase extraction and simultaneous spectrophotometric determination of trace amounts of Co, Ni and Cu using partial least squares regression. Talanta 62:183–189. doi: 10.1016/S0039-9140(03)00412-0 CrossRefGoogle Scholar
  34. 34.
    Rohleder D, Kiefer W, Petrich W (2004) Quantitative analysis of serum and serum ultrafiltrate by means of Raman spectroscopy. Analyst 129:906. doi: 10.1039/b408927h CrossRefGoogle Scholar
  35. 35.
    Sivakesava S, Irudayaraj J, Ali D (2001) Simultaneous determination of multiple components in lactic acid fermentation using FT-MIR, NIR, and FT-Raman spectroscopic techniques. Process Biochem 37:371–378. doi: 10.1016/S0032-9592(01)00223-0 CrossRefGoogle Scholar
  36. 36.
    Söderholm S, Roos YH, Meinander N, Hotokka M (1999) Raman spectra of fructose and glucose in the amorphous and crystalline states. J Raman Spectrosc 30:1009–1018CrossRefGoogle Scholar
  37. 37.
    Vasko PD, Blackwell J, Koenig JL (1972) Infrared and raman spectroscopy of carbohydrates.: part II: normal coordinate analysis of α-d-glucose. Carbohydr Res 23:407–416CrossRefGoogle Scholar
  38. 38.
    Mazarevica G, Diewok J, Baena JR et al (2004) On-line fermentation monitoring by mid-infrared spectroscopy. Appl Spectrosc 58:804–810. doi: 10.1366/0003702041389229 CrossRefGoogle Scholar
  39. 39.
    Ibrahim M, Alaam M, El-Haes H et al (2006) Analysis of the structure and vibrational spectra of glucose and fructose. Eclética Quím 31:15–21. doi: 10.1590/S0100-46702006000300002 CrossRefGoogle Scholar
  40. 40.
    Günzler H (2002) IR spectroscopy: an introduction. Wiley-VCH, WeinheimGoogle Scholar
  41. 41.
    Gan W, Zhang Z, Feng R, Wang H (2006) Identification of overlapping features in the sum frequency generation vibrational spectra of air/ethanol interface. Chem Phys Lett 423:261–265. doi: 10.1016/j.cplett.2006.03.084 CrossRefGoogle Scholar
  42. 42.
    Ávila TC, Poppi RJ, Lunardi I et al (2012) Raman spectroscopy and chemometrics for on-line control of glucose fermentation by Saccharomyces cerevisiae. Biotechnol Prog 28:1598–1604. doi: 10.1002/btpr.1615 CrossRefGoogle Scholar
  43. 43.
    Wang Q, Li Z, Ma Z, Liang L (2014) Real time monitoring of multiple components in wine fermentation using an on-line auto-calibration Raman spectroscopy. Sens Actuators B Chem 202:426–432. doi: 10.1016/j.snb.2014.05.109 CrossRefGoogle Scholar
  44. 44.
    Berry B, Moretto J, Matthews T et al (2015) Cross-scale predictive modeling of CHO cell culture growth and metabolites using Raman spectroscopy and multivariate analysis. Biotechnol Prog 31:566–577. doi: 10.1002/btpr.2035 CrossRefGoogle Scholar
  45. 45.
    André S, Cristau LS, Gaillard S et al (2015) In-line and real-time prediction of recombinant antibody titer by in situ Raman spectroscopy. Anal Chim Acta 892:148–152. doi: 10.1016/j.aca.2015.08.050 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Robert Schalk
    • 1
    Email author
  • Frank Braun
    • 1
  • Rudolf Frank
    • 1
  • Matthias Rädle
    • 1
  • Norbert Gretz
    • 2
  • Frank-Jürgen Methner
    • 3
  • Thomas Beuermann
    • 1
  1. 1.Institute for Process ControlMannheim University of Applied SciencesMannheimGermany
  2. 2.Medical Research CenterUniversity of HeidelbergMannheimGermany
  3. 3.Institute of BiotechnologyTechnical University of Berlin, Chair of Brewing ScienceBerlinGermany

Personalised recommendations