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Probeless non-invasive near-infrared spectroscopic bioprocess monitoring using microspectrometer technology.
Zimmerleiter, Robert; Kager, Julian; Nikzad-Langerodi, Ramin; Berezhinskiy, Vladimir; Westad, Frank; Herwig, Christoph; Brandstetter, Markus.
Afiliação
  • Zimmerleiter R; RECENDT - Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040, Linz, Austria.
  • Kager J; Institute of Chemical, Environmental and Bioscience Engineering, TU Wien, Getreidemarkt 9/166, 1060, Vienna, Austria.
  • Nikzad-Langerodi R; RECENDT - Research Center for Non-Destructive Testing GmbH, Altenberger Straße 69, 4040, Linz, Austria.
  • Berezhinskiy V; Institute of Chemical, Environmental and Bioscience Engineering, TU Wien, Getreidemarkt 9/166, 1060, Vienna, Austria.
  • Westad F; Camo Analytics, Gaustadalléen 21, 0349, Oslo, Norway.
  • Herwig C; Department of Engineering Cybernetics, Norwegian University of Science and Technology, O. S. Bragstads Plass 2D, 7034, Trondheim, Norway.
  • Brandstetter M; Institute of Chemical, Environmental and Bioscience Engineering, TU Wien, Getreidemarkt 9/166, 1060, Vienna, Austria.
Anal Bioanal Chem ; 412(9): 2103-2109, 2020 Apr.
Article em En | MEDLINE | ID: mdl-31802180
Real-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 Penicilliumchrysogenum 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 applications. Graphical abstract.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Penicilinas / Penicillium chrysogenum / Espectroscopia de Luz Próxima ao Infravermelho / Acetatos Tipo de estudo: Prognostic_studies Idioma: En Revista: Anal Bioanal Chem Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Penicilinas / Penicillium chrysogenum / Espectroscopia de Luz Próxima ao Infravermelho / Acetatos Tipo de estudo: Prognostic_studies Idioma: En Revista: Anal Bioanal Chem Ano de publicação: 2020 Tipo de documento: Article