Applied Microbiology and Biotechnology

, Volume 88, Issue 1, pp 11–22 | Cite as

On-line infrared spectroscopy for bioprocess monitoring

  • Daniel Landgrebe
  • Claas Haake
  • Tim Höpfner
  • Sascha Beutel
  • Bernd Hitzmann
  • Thomas ScheperEmail author
  • Martin Rhiel
  • Kenneth F. Reardon


One of the major aims of bioprocess engineering is the real-time monitoring of important process variables. This is the basis of precise process control and is essential for high productivity as well as the exact documentation of the overall production process. Infrared spectroscopy is a powerful analytical technique to analyze a wide variety of organic compounds. Thus, infrared sensors are ideal instruments for bioprocess monitoring. The sensors are non-invasive, have no time delay due to sensor response times, and have no influence on the bioprocess itself. No sampling is necessary, and several components can be analyzed simultaneously. In general, the direct monitoring of substrates, products, metabolites, as well as the biomass itself is possible. In this review article, insights are provided into the different applications of infrared spectroscopy for bioprocess monitoring and the complex data interpretation. Different analytical techniques are presented as well as example applications in different areas.


Infrared spectroscopy Bioprocess On-line measurement On-line monitoring Sensor 


  1. Acha V, Meurens M, Naveau H, Agathos S (2000) ATR-FTIR sensor development for continuous on-line monitoring of chlorinated aliphatic hydrocarbons in a fixed-bed bioreactor. Biotechnol Bioeng 68:473–487CrossRefGoogle Scholar
  2. American Society for Testing and Materials (1997) PA and note for guidance on the use of near infrared spectroscopy by the pharmaceutical industry and the date requirements for new submissions and variations, Method E 1655-97: Standard practices for infrared, multivariate, quantitative analysis, West Conshohocken, PMP/QWP/3309/01 and EMEA/CVMP/961/01Google Scholar
  3. Arnold S, Gaensakoo R, Harvey L, McNeil B (2002) Use of at-line and in-situ near-infrared spectroscopy to monitor biomass in an industrial fed-batch Escherichia coli process. Biotechnol Bioeng 80:405–413CrossRefGoogle Scholar
  4. Arnold S, Crowley S, Woods N, Harvey L, McNeil B (2003) In-situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation. Biotechnol Bioeng 84:13–19CrossRefGoogle Scholar
  5. Bras L, Lopes M, Ferreira A, Menezes J (2008) A bootstrap-based strategy for spectral interval selection in PLS regression. J Chemom 22:695–700CrossRefGoogle Scholar
  6. Brown P (1992) Wavelength selection in multicomponent near-infrared calibration. J Chemometr 6:151–161CrossRefGoogle Scholar
  7. Cervera A, Petersen N, Lantz A, Larson A, Gernaey K (2009) Application of near-infrared spectroscopy for monitoring and control of cell culture and fermentation. Am Inst Chem Eng. doi:10.1002/btpr.280
  8. Coen T, Saeys W, Ramon H, De Baerdemaeker J (2006) Optimizing the tuning parameters of least squares support vector machines regression for NIR spectra. J Chemom 20:184–192CrossRefGoogle Scholar
  9. Crowley J, Arnold S, Wood N, Harvey L, McNeil B (2005) Monitoring a high cell density recombinant Pichia pastoris fed-batch bioprocess using transmission and reflectance near infrared spectroscopy. Enzyme Microbiol Tech 36:621–628CrossRefGoogle Scholar
  10. Ferreira A, Menezes J (2006) Monitoring a complex medium fermentation with sample-sample two-dimensional FT-NIR correlation spectroscopy. Biotechnol Prog 22:866–872CrossRefGoogle Scholar
  11. Franco V, Perin J, Mantovani V, Goiceoechea H (2006) Monitoring substrate and products in a bioprocess with FTIR spectroscopy coupled to artificial neural networks enhanced with a genetic-algorithm-based method for wavelength selection. Talanta 68:1005–1012CrossRefGoogle Scholar
  12. Ge Z, Cavinato A, Callis J (1994) Non-invasive spectroscopy for monitoring cell density in a fermentation process. Anal Chem 66:1354–1362CrossRefGoogle Scholar
  13. Giavasis I, Robertson I, McNeill B, Harvey L (2003) Simultaneous and rapid monitoring of biomass and biopolymer production by Sphingomonas paucimobilis using Fourier transform-near infrared spectroscopy. Biotechnol Lett 25:975–979CrossRefGoogle Scholar
  14. Goicoechea H, Olivieri A (2003) A new family of genetic algorithms for wavelength interval selection in multivariate analytical spectroscopy. J Chemom 17:338–345CrossRefGoogle Scholar
  15. Gorry P (1990) General least-squares smoothing and differentiation by the convolution (Savitzky–Golay) method. Anal Chem 62:570–573CrossRefGoogle Scholar
  16. Hantelmann K, Kollecker M, Huell D, Hitzmann B, Scheper T (2005) Two-dimensional fluorescence spectroscopy: a novel approach for controlling fed-batch cultivations. J Biotechnol 121:410–417CrossRefGoogle Scholar
  17. Heise H, Müller U, Gärtner A, Hölscher N (2001) Improved chemometric strategies for quantitative FTIR spectral analysis and applications in atmospheric open-path monitoring. Field Anal Chem Technol 5:13–28CrossRefGoogle Scholar
  18. Henriques J, Buziol S, Stocker E, Voogd A, Menezes J (2009) Monitoring mammalian cell cultivations for monoclonal antibody production using near-infrared spectroscopy. Adv Biochem Engin/Biotechnol 116:73–97CrossRefGoogle Scholar
  19. Holm-Nielsen J, Lomborg C, Oleskowicz-Popiel P, Esbensen K (2008) On-line near infrared monitoring of glycerol-boosted anaerobic digestion processes: evaluation of process analytical technologies. Biotechnol Bioeng 99:302–313CrossRefGoogle Scholar
  20. Hongqiang L, Hongzhang C (2008) Near-infrared spectroscopy with a fiber-optic probe for state variables determination in solid-state fermentation. Process Biochem 43:511–516CrossRefGoogle Scholar
  21. Kiviharju K, Salonen K, Moilanen U, Meskanen E, Leisola M, Eerikäinen T (2007) On-line biomass measurements in bioreactor cultivations: comparison study of two on-line probes. J Ind Microbiol Biotechnol 34:561–566CrossRefGoogle Scholar
  22. Knuettel T, Meyer H, Scheper T (2006) The application of two-dimensional fluorescence spectroscopy for the on-line evaluation of modified enzymatic enantioselectivities in organic solvents by forming substrate salts. Enz Microb Technol 39:607–611CrossRefGoogle Scholar
  23. Kornmann H, Rhiel M, Cannizzaro C, Marison I, von Stockar U (2003) Methodology for real-time, multianalyte monitoring of fermentations using an in-situ mid-infrared sensor. Biotechnol Bioeng 82:702–709CrossRefGoogle Scholar
  24. Kornmann H, Valentinotti S, Duboc P, Marison I, von Stockar U (2004) Monitoring and control of Gluconacetobacter xylinus fed-batch cultures using in situ mid-IR spectroscopy. J Biotechnol 113:231–245CrossRefGoogle Scholar
  25. Lavine B (2000) Fundamental reviews: chemometrics. Anal Chem 72:91–98CrossRefGoogle Scholar
  26. Leardi R (1994) Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection. J Chemometr 8:65–79CrossRefGoogle Scholar
  27. Marose S, Lindemann C, Ulber R, Scheper T (1999) Optical sensor systems for bioprocess monitoring. TIBTECH 17:30–34Google Scholar
  28. Mazarevica G, Diewok J, Baena J, Lendl J (2004) On-line fermentation monitoring by mid-IR spectroscopy. Appl Spectrosc 58:804–810CrossRefGoogle Scholar
  29. Miller C (2000) Chemometrics for on-line spectroscopy applications—theory and practice. J Chemom 14:513–528CrossRefGoogle Scholar
  30. Navrátil M, Norberg A, Lembrén L, Mandenius C (2005) On-line multi-analyzer monitoring of biomass, glucose and acetate for growth rate control of a Vibrio cholerae fed-batch cultivation. J Biotechnol 115:67–79CrossRefGoogle Scholar
  31. Nordon A, Littlejohn D, Dann A, Jeffkins P, Richardson M, Simpson S (2008) In situ monitoring of a seed stage of a fermentation process using non-invasive NIR spectrometry. Analyst 133:660–666CrossRefGoogle Scholar
  32. Petersen N, Ödman P, Padrell A, Stocks S, Lantz A, Gernaey K (2009) In situ near infrared spectroscopy for analyte-specific monitoring of glucose and ammonium in Streptomyces coelicolor fermentations. Am Inst Chem Eng. doi:10.1002/btpr.288
  33. Rhiel M, Ducommun P, Bolzonella I, Marison I, von Stockar U (2001) Real-time in situ monitoring of freely suspended and immobilized cell cultures based on mid-infrared spectroscopic measurements. Biotechnol Bioeng 77:174–185CrossRefGoogle Scholar
  34. Rhiel M, Amrhein M, Marison I, von Stockar U (2002) The influence of correlated calibration samples on the prediction performance of multivariate models based on mid-infrared spectra of animal cell cultures. Anal Chem 74:5227–5236CrossRefGoogle Scholar
  35. Rhiel M, Cohen M, Arnold M, Murhammer D (2004) On-line monitoring of human prostate cancer cells in a perfusion rotating wall vessel by near-infrared spectroscopy. Biotechnol Bioeng 86:852–861CrossRefGoogle Scholar
  36. Riley M, Rhiel M, Zhou X, Arnold M, Murhammer D (1997) Simultaneous monitoring of glucose and glutamine in insect cell cultures by NIR spectroscopy. Biotechnol Bioeng 55:11–15CrossRefGoogle Scholar
  37. Rodrigues L, Vieira L, Cardoso J, Menezes J (2008) The use of NIR as a multi-parametric in situ monitoring technique in filamentous fermentation systems. Talanta 75:1356–1361CrossRefGoogle Scholar
  38. Roggo Y, Chalus P, Maurer L, Lema-Martinez C, Edmond A, Jent N (2007) A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies. J Pharm Biomed Anal 44:683–700CrossRefGoogle Scholar
  39. Roychoudhury P, Harvey L, McNeil B (2006) At-line monitoring of ammonium, glucose, methyl oleate and biomass in a complex antibiotic fermentation process using attenuated total reflectance-mid-infrared (ATR-MIR) spectroscopy. Anal Chim Acta 561:218–224CrossRefGoogle Scholar
  40. Roychoudhury P, Harvey L, McNeil B (2007a) Simultaneous determination of glycerol and clavulanic acid in an antibiotic bioprocess using attenuated total reflectance mid infrared spectroscopy. Anal Chim Acta 585:246–252CrossRefGoogle Scholar
  41. Roychoudhury P, O’Kennedy R, McNeil B, Harvey L (2007b) Multiplexing fibre optic near infrared (NIR) spectroscopy as an emerging technology to monitor industrial bioprocesses. Anal Chim Acta 590:110–117CrossRefGoogle Scholar
  42. Schenk J, Marison I, von Stockar U (2006) A simple method to monitor and control methanol feeding of Pichia pastoris fermentations using mid-IR. J Biotechnol 128(344):353Google Scholar
  43. Schenk J, Marison I, von Stockarl U (2008) pH prediction and control in bioprocesses using mid-infrared spectroscopy. Biotechnol Bioeng 100:82–93CrossRefGoogle Scholar
  44. Scheper T, Gebauer A, Sauerbrei A, Niehoff A, Schügerl K (1984) Measurement of biological parameters during fermentation processes. Anal Chim Acta 163:111–118CrossRefGoogle Scholar
  45. Scheper T, Hilmer J, Lammers F, Mueller C, Reinecke M (1996) Biosensors in bioprocess monitoring. J Chromat 725:3–12CrossRefGoogle Scholar
  46. Scheper T, Hitzmann B, Staerk E, Ulber R, Faurie R, Sosnitza P, Reardon K (1999) Bioanalytics: detailed insight into bioprocesses. Anal Chim Acta 400:121–143CrossRefGoogle Scholar
  47. Sellick C, Hansen R, Jarvis R, Maqsood A, Stephens G, Dickson A, Goodacre R (2010) Rapid monitoring of recombinant antibody production by mammalian cell cultures using Fourier transform infrared spectroscopy and chemometrics. Biotechnol Bioeng 106:432–442Google Scholar
  48. Shamsipur M, Zare-Shahabadi V, Hemmateenejad B, Akhond M (2006) Ant colony optimisation: a powerful tool for wavelength selection. J Chemom 20:146–157CrossRefGoogle Scholar
  49. 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 37:371–78CrossRefGoogle Scholar
  50. Soons Z, Streefland M, van Straten G, van Boxtel A (2008) Assessment of near infrared and “software sensor” for biomass monitoring and control. Chemometr Intell Lab Sys 94:166–174CrossRefGoogle Scholar
  51. Tosi S, Rossi M, Tamburini E, Vaccari G, Amaretti A, Matteuzzi D (2003) Assessment of in-line near-infrared spectroscopy for continuous monitoring of fermentation processes. Biotechnol Prog 19:1816–1821CrossRefGoogle Scholar
  52. Trevisan M, Poppi R (2008) Direct determination of ephedrine intermediate in a biotransformation reaction using infrared spectroscopy and PLS. Talanta 75:1021–1027CrossRefGoogle Scholar
  53. Udelhoven T, Schütt B (2000) Capability of feed-forward neural networks for a chemical evaluation of sediments with diffuse reflectance spectroscopy. Chemom Intell Lab Syst 51:9–22CrossRefGoogle Scholar
  54. Vaidyanathan S, White S, Harvey L, McNeil B (2003) Influence of morphology on the near-infrared spectra of mycelial biomass and its implications in bioprocess monitoring. Biotechnol Bioeng 82:715–724CrossRefGoogle Scholar
  55. Yamane Y, Mikami K, Higshida K, Kakizano T, Nishio N (1996) Estimation of the concentrations of cells, astaxanthin and glucose in a culture of Phaffia rhodozyma by near infrared reflectance spectroscopy. Biotechnol Tech 10:529–534CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Daniel Landgrebe
    • 1
  • Claas Haake
    • 1
  • Tim Höpfner
    • 1
  • Sascha Beutel
    • 1
  • Bernd Hitzmann
    • 1
  • Thomas Scheper
    • 1
    Email author
  • Martin Rhiel
    • 2
  • Kenneth F. Reardon
    • 3
  1. 1.Institut für Technische ChemieLeibniz Universität HannoverHannoverGermany
  2. 2.Process Sciences & ProductionNovartis BiologicsBaselSwitzerland
  3. 3.Department of Chemical and Biological EngineeringColorado State UniversityFort CollinsUSA

Personalised recommendations