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dc.contributor.authorZimmerleiter, Robert
dc.contributor.authorKager, Julian
dc.contributor.authorNikzad-Langerodi, Ramin
dc.contributor.authorBerezhinskiy, Vladimir
dc.contributor.authorWestad, Frank Ove
dc.contributor.authorHerwig, Christoph
dc.contributor.authorBrandstetter, Markus
dc.date.accessioned2020-02-13T11:57:01Z
dc.date.available2020-02-13T11:57:01Z
dc.date.created2020-02-02T20:23:59Z
dc.date.issued2019
dc.identifier.citationAnalytical and Bioanalytical Chemistry. 2019, .nb_NO
dc.identifier.issn1618-2642
dc.identifier.urihttp://hdl.handle.net/11250/2641530
dc.description.abstractReal-time measurements and adjustments of critical process parameters are essential for the precise control of fermentation processes and thus for increasing both quality and yield of the desired product. However, the measurement of some crucial process parameters such as biomass, product, and product precursor concentrations usually requires time-consuming offline laboratory analysis. In this work, we demonstrate the in-line monitoring of biomass, penicillin (PEN), and phenoxyacetic acid (POX) in a Penicillium chrysogenum fed-batch fermentation process using low-cost microspectrometer technology operating in the near-infrared (NIR). In particular, NIR reflection spectra were taken directly through the glass wall of the bioreactor, which eliminates the need for an expensive NIR immersion probe. Furthermore, the risk of contaminations in the reactor is significantly reduced, as no direct contact with the investigated medium is required. NIR spectra were acquired using two sensor modules covering the spectral ranges 1350–1650 nm and 1550–1950 nm. Based on offline reference analytics, partial least squares (PLS) regression models were established for biomass, PEN, and POX either using data from both sensors separately or jointly. The established PLS models were tested on an independent validation fed-batch experiment. Root mean squared errors of prediction (RMSEP) were 1.61 g/L, 1.66 g/L, and 0.67 g/L for biomass, PEN, and POX, respectively, which can be considered an acceptable accuracy comparable with previously published results using standard process spectrometers with immersion probes. Altogether, the presented results underpin the potential of low-cost microspectrometer technology in real-time bioprocess monitoring applicationsnb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleProbeless non-invasive near-infrared spectroscopic bioprocess monitoring using microspectrometer technologynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber7nb_NO
dc.source.journalAnalytical and Bioanalytical Chemistrynb_NO
dc.identifier.doi10.1007/s00216-019-02227-w
dc.identifier.cristin1789944
dc.description.localcodeThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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