Two-dimensional fluorescence spectroscopy: A novel approach for controlling fed-batch cultivations
Abstract
In industrial fed-batch cultivations it is often necessary to control substrate concentrations at a low level to prevent the production of overflow metabolites and thus optimize the biomass yield. A new method for on-line monitoring and fed-batch control based on fluorescence measurements has been developed. Via instantaneous in situ measurements and multivariate data analysis a chemometric model has been established, which enables the rapid detection of ethanol production at aerobic Saccharomyces cerevisiae fed-batch cultivations. The glucose feed rate is controlled by predicting the metabolic state directly from the fluorescence intensities. Thus, ethanol production could be avoided completely while increasing the biomass yield accordingly. The robust instrumentation is suitable for industrial applications.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Spectroscopic sensors do not interfere with biological material, allowing monitoring of in vivo cells and obtaining information on their intracellular state, in addition to information on extracellular media.
“Also, as non‐invasive techniques, spectroscopic sensors do not interfere with the biological material, allowing to monitor in vivo cells and obtain information on their intracellular state, in addition to information on extracellular media (Marose et al., 1999; Ulber et al., 2003; Hantelmann et al., 2006; Glindkamp et al., 2009).”
From Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry (2022) · cites this paper as Hantelmann et al., 2006
Fluorescence spectroscopy is flexible for monitoring a number of analytes via direct or indirect correlations.
“The flexibility of fluorescence spectroscopy is well‐reported for the monitoring of a number of analytes, via direct or indirect correlations, such as proteins, vitamins, co‐enzymes, glucose, ethanol, ATP, pyruvate, nitrate, or succinate (Shaw et al., 1999; Ulber et al., 2003; Hantelmann et al., 2006; Glindkamp et al., 2009; Ranzan et al., 2012).”
From Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry (2022) · cites this paper as Hantelmann et al., 2006
Fluorescence spectroscopy has been used to track physiological changes such as the transition between bacterial aerobic and anaerobic metabolisms and the change between oxidative and oxidoreductive metabolism in yeasts.
“For that reason, fluorescence spectroscopy has been used to track physiological changes, such as the transition between bacterial aerobic and anerobic metabolisms (Glindkamp et al., 2009), and the change between oxidative and oxidoreductive metabolism in yeasts (Hantelmann et al., 2006).”
From Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry (2022) · cites this paper as Hantelmann et al., 2006
Cites
Effect of Specific Growth Rate on Fermentative Capacity of Baker’s Yeast
Van Hoek, P., Van Dijken, J. P., & Pronk, J. T. (1998) · Applied and Environmental Microbiology · doi:10.1128/aem.64.11.4226-4233.1998 · Cited by 316 · see citing works
Two-Dimensional Fluorescence Spectroscopy: A New Tool for On-Line Bioprocess Monitoring
Marose, S., Lindemann, C., & Scheper, T. (1998) · Biotechnology Progress · doi:10.1021/bp970124o · Cited by 190 · see citing works
Self-citationShaw, A. D., Kaderbhai, N., Jones, A., Woodward, A. M., Goodacre, R., Rowland, J. J., & Kell, D. B. (1999) · Applied Spectroscopy · doi:10.1366/0003702991945777 · Cited by 84 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Bioreactor monitoring with spectroscopy and chemometrics: a review
Lourenço, N. D., Lopes, J. A., Almeida, C. F., Sarraguça, M. C., & Pinheiro, H. M. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6073-9 · Cited by 275 · see citing works
Sensor systems for bioprocess monitoring
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-citationClaßen, J., Aupert, F., Reardon, K. F., Solle, D., & Scheper, T. (2017) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-016-0068-x · Cited by 176 · see citing works
Self-citationOn-line infrared spectroscopy for bioprocess monitoring
Landgrebe, D., Haake, C., Höpfner, T., Beutel, S., Hitzmann, B., Scheper, T., Rhiel, M., & Reardon, K. F. (2010) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-010-2743-8 · Cited by 134 · see citing works
Self-citationOn-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-citationFluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring
Faassen, S., & Hitzmann, B. (2015) · Sensors · doi:10.3390/s150510271 · Cited by 120 · see citing works
Self-citationOn-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
Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry
Sá, M., Ferrer‐Ledo, N., Gao, F., Bertinetto, C. G., Jansen, J., Crespo, J. G., Wijffels, R. H., Barbosa, M., & Galinha, C. F. (2022) · Microbial Biotechnology · doi:10.1111/1751-7915.14013 · Cited by 29 · see citing works
A comparison of analytical techniques for evaluating food waste degradation by anaerobic digestion
Gómez, X., Cuetos, M. J., Tartakovsky, B., Martínez-Núñez, M. F., & Morán, A. (2010) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-009-0343-8 · Cited by 22 · see citing works
Karakach, T. K., McGinn, P. J., Choi, J., MacQuarrie, S. P., & Tartakovsky, B. (2015) · Journal of Applied Phycology · doi:10.1007/s10811-014-0494-0 · Cited by 14 · see citing works
- Authors
- Hantelmann, K., Kollecker, M., Hüll, D., Hitzmann, B., & Scheper, T.
- Affiliations
- Leibniz University Hannover (DE)
- Corresponding author
- Scheper, T.
- Venue
- Journal of Biotechnology
- Publisher
- Elsevier BV
- Published
- 2006-02
- Volume
- 121
- Issue
- 3
- Pages
- 410-417
- ISSN
- 0168-1656 (ISSN-L)
- OpenAlex
- W2155306850
- Cited by
- 80
- References
- 3
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 6 · 2018: 5 · 2017: 5 · 2016: 6 · 2015: 4 · 2014: 2 · 2013: 5 · 2012: 4
- FWCI
- 3.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- two-dimensional fluorescence spectroscopy, fed-batch fermentation, real-time process monitoring, Saccharomyces cerevisiae, biomass yield, chemometric models, multivariate analysis
- MeSH terms
- Aerobiosis, Ethanol, Carbon Dioxide, Feedback, Fermentation, Glucose, Industrial Microbiology, Kinetics, Online Systems, Oxidation-Reduction, Saccharomyces cerevisiae, Sensitivity and Specificity, Spectrometry, Fluorescence, Linear Models, Biomass, Cell Culture Techniques, Bioreactors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
