On-line infrared spectroscopy for bioprocess monitoring
Abstract
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.
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Currently, there are few reviews of vibrational spectroscopy as it pertains to the microalgae industry, and these reviews do not take into account the technological progress and development of on-line/in-line vibrational spectroscopy implemented in bioprocess, pharmaceutical, and liquid and solid food industries.
“Currently, there are few reviews of vibrational spectroscopy as it pertains to the microalgae industry [9,17-19]; however, these reviews do not take into account the technological progress and development of on-line/in-line vibrational spectroscopy implemented in bioprocess, pharmaceutical, and liquid and solid food industries [20-28]”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
NIR spectroscopy is used to analyze vibrational spectra produced from the overtones of fundamental vibrations occurring in the 12 500 cm-1 to 4000 cm-1 MIR range and from stretch vibrations of hydrogen bonds (3600 - 2400 cm-1); effectively, the range is between 13 000 and 4000 cm-1.
“NIR spectroscopy is used to analyze vibrational spectra produced from the overtones of fundamental vibrations occurring in the 12 500 cm -1 to 4000 cm -1 MIR range and from stretch vibrations of hydrogen bonds (3600 - 2400 cm -1 ); effectively, the range is between 13 000 and 4000 cm -1 [20].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
The monitoring of intracellular and extracellular macromolecules in bioprocesses shares many intrinsic similarities to yeast and bacteria bioprocesses.
“the monitoring of intracellular and extracellular macromolecules in bioprocesses share many intrinsic similarities to yeast and bacteria bioprocesses, which have been extensively reviewed together due to these similarities [20,21,29].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
There are numerous cases of in situ MIR applications, all of which use ATR-FTIR probes to acquire quantitative MIR spectra of a multitude of media components and bioproducts.
“There are numerous cases of in situ MIR applications, all of which use ATR-FTIR probes to acquire quantitative MIR spectra of a multitude of media components and bioproducts [20,21].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
MIR spectra relevant to the microalgal industry obtained in situ in yeast and bacterial bioreaction suspensions in 5 L to 15 L reactors include optical density, ammonium, phosphates, acetate, glucose, fructose, organic acids as well as several bioproducts.
“MIR spectra relevant to the microalgal industry obtained in situ in yeast and bacterial bioreaction suspensions in 5 L to 15 L reactors include optical density, ammonium, phosphates, acetate, glucose, fructose, organic acids as well as several bioproducts [20,21].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
NIR in vivo analysis of microalgae has only yet investigated biomass, lipids, and carotenoids, but the potential use of high-selectivity on-line/in-line NIR in microalgae bioreactions is evidenced by its prolific use in other bioprocesses.
“NIR in vivo analysis of microalgae has only yet investigated biomass, lipids, and carotenoids (Fig. 2) but the potential use of high-selectivity on-line/in-line NIR in microalgae bioreactions is evidenced by its prolific use in other bioprocesses [20,21].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
A promising mode of MIR for wet applications is attenuated total reflectance Fourier transform infrared (ATR-FTIR), which has had growing applications in pharmaceutical, agro-food, and environmental sectors and can be used on-line/in-line in liquid media.
“However, a promising mode of MIR for wet applications is attenuated total reflectance Fourier transform infrared (ATR-FTR), which has had growing applications in pharmaceutical, agro-food, and environmental sectors and can be used on-line/in-line in liquid media (see reviews by [20] and [21]).”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [20]
Cites
A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies
Roggo, Y., Chalus, P., Maurer, L., Lema-Martinez, C., Edmond, A., & Jent, N. (2007) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2007.03.023 · Cited by 1,136 · see citing works
General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method
Gorry, P. A. (1990) · Analytical Chemistry · doi:10.1021/ac00205a007 · Cited by 693 · see citing works
Application of genetic algorithm-PLS for feature selection in spectral data sets
Leardi, R. (2000) · Journal of Chemometrics · doi:10.1002/1099-128x(200009/12)14:5/6 · Cited by 564 · see citing works
Bidirectional reaction steps in metabolic networks: II. Flux estimation and statistical analysis
Wiechert, W., Siefke, C., de Graaf, A. A., & Marx, A. (1997) · Biotechnology and Bioengineering · doi:10.1002/(sici)1097-0290(19970705)55:1 · Cited by 239 · see citing works
Leardi, R. (1994) · Journal of Chemometrics · doi:10.1002/cem.1180080107 · Cited by 202 · see citing works
Diogo, M. M., Queiroz, J. A., Monteiro, G. A., Martins, S. A. M., Ferreira, G. N. M., & Prazeres, D. M. F. (2000) · Biotechnology and Bioengineering · doi:10.1002/(sici)1097-0290(20000605)68:5 · Cited by 196 · see citing works
Cervera-Padrell, A. E., Petersen, N., Lantz, A. E., Larsen, A., & Gernaey, K. V. (2009) · Biotechnology Progress · doi:10.1002/btpr.280 · Cited by 176 · see citing works
In‐situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation
Arnold, S. A., Crowley, J. N., Woods, N., Harvey, L. M., & McNeil, B. W. J. (2003) · Biotechnology and Bioengineering · doi:10.1002/bit.10738 · Cited by 149 · see citing works
Arnold, S. A., ., R. G., Harvey, L. M., & McNeil, B. W. J. (2002) · Biotechnology and Bioengineering · doi:10.1002/bit.10383 · Cited by 126 · see citing works
On-Line Fermentation Monitoring by Mid-Infrared Spectroscopy
Mazarevica, G., Diewok, J., Baena, J. R., Rosenberg, E., & Lendl, B. (2004) · Applied Spectroscopy · doi:10.1366/0003702041389229 · Cited by 121 · see citing works
Sivakesava, S., Irudayaraj, J., & Demırcı, A. (2001) · Process Biochemistry · doi:10.1016/s0032-9592(01)00223-0 · Cited by 115 · see citing works
Holm‐Nielsen, J. B., Lomborg, C. J., Oleśkowicz-Popiel, P., & Esbensen, K. H. (2007) · Biotechnology and Bioengineering · doi:10.1002/bit.21571 · Cited by 114 · see citing works
Optical sensor systems for bioprocess monitoring
Marose, S. (1999) · Trends in biotechnology · doi:10.1016/s0167-7799(98)01247-5 · Cited by 102 · see citing works
Ant colony optimisation: a powerful tool for wavelength selection
Shamsipur, M., Zare-Shahabadi, V., Hemmateenejad, B., et al. (2006) · Journal of Chemometrics · doi:10.1002/cem.1002 · Cited by 102 · see citing works
Lavine, B. K. (2000) · Analytical Chemistry · doi:10.1021/a1000016x · Cited by 96 · see citing works
Wavelength selection in multicomponent near‐infrared calibration
Brown, P. J. (1992) · Journal of Chemometrics · doi:10.1002/cem.1180060306 · Cited by 87 · see citing works
Navrátil, M., Norberg, A., Lembrén, L., & Mandenius, C. (2004) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2004.07.013 · Cited by 86 · see citing works
Rhiel, M. H., Ducommun, P., Bolzonella, I., Marison, I. W., & von Stockar, U. (2001) · Biotechnology and Bioengineering · doi:10.1002/bit.10134 · Cited by 83 · see citing works
Self-citationTwo-dimensional fluorescence spectroscopy: A novel approach for controlling fed-batch cultivations
Hantelmann, K., Kollecker, M., Hüll, D., Hitzmann, B., & Scheper, T. (2006) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2005.07.016 · Cited by 80 · see citing works
Self-citationNoninvasive Spectroscopy for Monitoring Cell Density in a Fermentation Process
Ge, Z., Cavinato, A. G., & Callis, J. B. (1994) · Analytical Chemistry · doi:10.1021/ac00080a023 · Cited by 78 · see citing works
Roychoudhury, P., O’Kennedy, R. D., McNeil, B. W. J., & Harvey, L. M. (2007) · Analytica Chimica Acta · doi:10.1016/j.aca.2007.03.011 · Cited by 77 · see citing works
Tosi, S., Rossi, M., Tamburini, E., Vaccari, G., Amaretti, A., & Matteuzzi, D. (2003) · Biotechnology Progress · doi:10.1021/bp034101n · Cited by 77 · see citing works
Roychoudhury, P., Harvey, L. M., & McNeil, B. W. J. (2006) · Analytica Chimica Acta · doi:10.1016/j.aca.2006.01.037 · Cited by 75 · see citing works
On-line biomass measurements in bioreactor cultivations: comparison study of two on-line probes
Kiviharju, K., Salonen, K., Moilanen, U., Meskanen, E., LEISOLA, M. S. A., & Eerikäinen, T. (2007) · Journal of Industrial Microbiology & Biotechnology · doi:10.1007/s10295-007-0233-5 · Cited by 66 · see citing works
Goicoechea, H. C., & Olivieri, A. C. (2003) · Journal of Chemometrics · doi:10.1002/cem.812 · Cited by 66 · see citing works
Schenk, J., Marison, I. W., & VONSTOCKAR, U. (2006) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2006.09.015 · Cited by 65 · see citing works
Bioanalytics: detailed insight into bioprocesses
Scheper, T. H., Hitzmann, B., Stärk, E., Ulber, R., Faurie, R., Sosnitza, P., & Reardon, K. F. (1999) · Analytica Chimica Acta · doi:10.1016/s0003-2670(99)00612-1 · Cited by 60 · see citing works
Self-citationSellick, C. A., Hansen, R., Jarvis, R. M., Maqsood, A. R., Stephens, G., Dickson, A. J., & Goodacre, R. (2010) · Biotechnology and Bioengineering · doi:10.1002/bit.22707 · Cited by 60 · see citing works
Kornmann, H., Rhiel, M. H., Cannizzaro, C., et al. (2003) · Biotechnology and Bioengineering · doi:10.1002/bit.10618 · Cited by 56 · see citing works
Self-citationCrowley, J. N., Arnold, S. A., Wood, N., Harvey, L. M., & McNeil, B. W. J. (2005) · Enzyme and Microbial Technology · doi:10.1016/j.enzmictec.2003.12.016 · Cited by 54 · see citing works
Biosensors in bioprocess monitoring
Scheper, T. H., Hilmer, J., Lammers, F., et al. (1996) · Journal of Chromatography A · doi:10.1016/0021-9673(95)00998-1 · Cited by 54 · see citing works
Self-citationA bootstrap‐based strategy for spectral interval selection in PLS regression
Brás, L. P., Lopes, M. B., Ferreira, A. P., et al. (2008) · Journal of Chemometrics · doi:10.1002/cem.1153 · Cited by 51 · see citing works
Petersen, N., Ödman, P., Cervera-Padrell, A. E., Stocks, S. M., Lantz, A. E., & Gernaey, K. V. (2009) · Biotechnology Progress · doi:10.1002/btpr.288 · Cited by 48 · see citing works
Franco, V. G., Perin, J. C., Mantovani, V. E., & Goicoechea, H. C. (2005) · Talanta · doi:10.1016/j.talanta.2005.07.003 · Cited by 47 · see citing works
Kornmann, H., Valentinotti, S., Duboc, P., Marison, I. W., & von Stockar, U. (2004) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2004.03.029 · Cited by 45 · see citing works
Measurement of biological parameters during fermentation processes
Scheper, T. H., Gebauer, A., Sauerbrei, A., et al. (1984) · Analytica Chimica Acta · doi:10.1016/s0003-2670(00)81499-3 · Cited by 43 · see citing works
Self-citationHenriques, J. G., Buziol, S., Stocker, E., Voogd, A., & de Menezes, J. C. (2009) · Advances in biochemical engineering, biotechnology · doi:10.1007/10_2009_11 · Cited by 40 · see citing works
Optimizing the tuning parameters of least squares support vector machines regression for NIR spectra
Coen, T., Saeys, W., Ramón, H., et al. (2006) · Journal of Chemometrics · doi:10.1002/cem.989 · Cited by 37 · see citing works
Assessment of near infrared and “software sensor” for biomass monitoring and control
Soons, Z. I. T. A., Streefland, M., Straten, G. V., & van Boxtel, A. J. B. (2008) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2008.07.009 · Cited by 35 · see citing works
Rodrigues, L. M., VIEIRA, L., CARDOSO, J., & de Menezes, J. C. (2008) · Talanta · doi:10.1016/j.talanta.2008.01.048 · Cited by 34 · see citing works
Rhiel, M. H., Amrhein, M., Marison, I. W., & von Stockar, U. (2002) · Analytical Chemistry · doi:10.1021/ac020165l · Cited by 33 · see citing works
Self-citationRhiel, M. H., Cohen, M. B., Arnold, M. A., et al. (2004) · Biotechnology and Bioengineering · doi:10.1002/bit.10834 · Cited by 33 · see citing works
Self-citationUdelhoven, T., & Schütt, B. (2000) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(99)00069-6 · Cited by 32 · see citing works
Li, H., & Hongzhang, C. (2008) · Process Biochemistry · doi:10.1016/j.procbio.2008.01.012 · Cited by 31 · see citing works
pH prediction and control in bioprocesses using mid‐infrared spectroscopy
Schenk, J., Marison, I. W., & von Stockar, U. (2007) · Biotechnology and Bioengineering · doi:10.1002/bit.21719 · Cited by 29 · see citing works
Ferreira, A., & de Menezes, J. C. (2006) · Biotechnology Progress · doi:10.1021/bp0503991 · Cited by 26 · see citing works
In situ monitoring of the seed stage of a fermentation process using non-invasive NIR spectrometry
Nordon, A., Littlejohn, D., Dann, A. S., Jeffkins, P. A., Richardson, M. D., & Stimpson, S. L. (2008) · The Analyst · doi:10.1039/b719318a · Cited by 26 · see citing works
Vaidyanathan, S., White, S., Harvey, L. M., & McNeil, B. W. J. (2003) · Biotechnology and Bioengineering · doi:10.1002/bit.10621 · Cited by 23 · see citing works
Heise, H. M., Müller, U., Gärtner, A., et al. (2001) · Field Analytical Chemistry & Technology · doi:10.1002/fact.1002 · Cited by 22 · see citing works
Giavasis, I., Robertson, I., McNeil, B., & Harvey, L. M. (2003) · Biotechnology Letters · doi:10.1023/a:1024040420799 · Cited by 18 · see citing works
Trevisan, M. G., & Poppi, R. J. (2008) · Talanta · doi:10.1016/j.talanta.2007.12.050 · Cited by 17 · see citing works
Optical Inline Measurement Procedures for Counting and Sizing Cells in Bioprocess Technology
Rudolph, G., Lindner, P., Bluma, A., Joeris, K., Martínez, G., Hitzmann, B., & Scheper, T. H. (2009) · Advances in biochemical engineering, biotechnology · doi:10.1007/10_2009_12 · Cited by 14 · see citing works
Self-citationRoychoudhury, P., McNeil, B. W. J., & Harvey, L. M. (2007) · Analytica Chimica Acta · doi:10.1016/j.aca.2006.12.051 · Cited by 14 · see citing works
Yamane, Y.-I., Mikami, T., Higashida, K., Kakizono, T., & Nishio, N. (1996) · Biotechnology Techniques · doi:10.1007/bf00159519 · Cited by 14 · see citing works
Knüttel, T., Meyer, H., & Scheper, T. H. (2006) · Enzyme and Microbial Technology · doi:10.1016/j.enzmictec.2005.11.026 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
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Biechele, P., Busse, C., Solle, D., Scheper, T., & Reardon, K. (2015) · Engineering in Life Sciences · doi:10.1002/elsc.201500014 · Cited by 224 · see citing works
Self-citationWhelan, J., Craven, S., & Glennon, B. (2012) · Biotechnology Progress · doi:10.1002/btpr.1590 · Cited by 159 · see citing works
On-Line Monitoring of Large Cultivations of Microalgae and Cyanobacteria
Havlik, I., Lindner, P., Scheper, T., & Reardon, K. F. (2013) · Trends in Biotechnology · doi:10.1016/j.tibtech.2013.04.005 · Cited by 131 · see citing works
Self-citationModern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes
Reyes, S. J., Durocher, Y., Pham, P. L., & Henry, O. (2022) · Processes · doi:10.3390/pr10020189 · Cited by 130 · see citing works
On-line soft sensing in upstream bioprocessing
Randek, J., & Mandenius, C.-F. (2018) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2017.1312271 · Cited by 86 · see citing works
Mini‐review: soft sensors as means for <scp>PAT</scp> in the manufacture of bio‐therapeutics
Mandenius, C., & Gustavsson, R. (2015) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.4477 · Cited by 84 · see citing works
Kozma, B., Hirsch, E., Gergely, S., Párta, L., Pataki, H., & Salgó, A. (2017) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2017.06.070 · Cited by 41 · see citing works
Sensors and Techniques for On-Line Determination of Cell Viability in Bioprocess Monitoring
Rösner, L., Walter, F., Ude, C., John, G., & Beutel, S. (2022) · Bioengineering · doi:10.3390/bioengineering9120762 · Cited by 42 · see citing works
Self-citationKoch, C., Brandstetter, M., Wechselberger, P., Lorantfy, B., Plata, M. R., Radel, S., Herwig, C., & Lendl, B. (2015) · Analytical Chemistry · doi:10.1021/ac504126v · Cited by 35 · see citing works
Podevin, M., Fotidis, I. A., & Angelidaki, I. (2018) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2017.1398132 · Cited by 34 · see citing works
- Authors
- Landgrebe, D., Haake, C., Höpfner, T., Beutel, S., Hitzmann, B., Scheper, T., Rhiel, M., & Reardon, K. F.
- Affiliations
- Leibniz University Hannover (DE)
- Novartis (Switzerland) (CH)
- Colorado State University (US)
- Corresponding author
- Scheper, Thomas
- Venue
- Applied Microbiology and Biotechnology
- Published
- 2010-07-22
- Volume
- 88
- Issue
- 1
- Pages
- 11-22
- ISSN
- 0175-7598 (ISSN-L)
- 1432-0614
- OpenAlex
- W2075435986
- Cited by
- 134
- References
- 55
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 4 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 9 · 2019: 8 · 2018: 6 · 2017: 18 · 2016: 9 · 2015: 15 · 2014: 8 · 2013: 12 · 2012: 12
- FWCI
- 1.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Applied Microbiology and Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Physical Sciences › Environmental Science › Waste Management and Disposal › Water Quality Monitoring and Analysis
- Keywords
- infrared spectroscopy, bioprocess monitoring, real-time process monitoring, infrared sensors, process control, biomass monitoring, metabolite analysis, spectral interpretation
- MeSH terms
- Biotechnology, Culture Media, Organic Chemicals, Spectrophotometry, Infrared, Biomass, Bioreactors
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