Literature DB >> 19787698

Application of near-infrared spectroscopy for monitoring and control of cell culture and fermentation.

Albert E Cervera1, Nanna Petersen, Anna Eliasson Lantz, Anders Larsen, Krist V Gernaey.   

Abstract

Near-infrared (NIR) spectroscopy can potentially provide on-line information on substrate, biomass, product, and metabolite concentrations in fermentation processes, which could be useful for improved monitoring or control. However, several factors can negatively influence the quality of chemometric models built for interpretation of the spectra, thus impairing the analyte concentration predictions. The aim of this review was to provide an overview of necessary conditions and challenges that one has to face when developing a NIR application for monitoring of cell culture or fermentation processes. Important practical aspects are introduced, such as sampling, modeling of biomass concentration, influence of microorganism morphology on the spectra, effects of the hydrodynamic conditions in the fermenter, temperature influence, instrument settings, and signal optimization. Several examples from the literature are provided, which will hopefully guide the reader interested in the topic. Furthermore, the general procedure used for the development of calibration models is presented, and the influence of microorganism metabolism-potential source of correlation between analytes-is commented. Other important issues such as wavelength selection and evaluation of robustness are shortly introduced. Finally, some examples of potential applications of NIR monitoring are provided, including the implementation of control strategies, the combination with other monitoring tools (the so-called sensor fusion), and the description of process trajectories. On the basis of the review, we conclude that acceptance of NIR spectroscopy as a standard monitoring tool by the fermentation industry will necessitate considerably more on-line studies using industrially relevant-and highly challenging-fermentation conditions (high aeration intensity, high biomass concentration and viscosity, and filamentous production strain). (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.

Mesh:

Year:  2009        PMID: 19787698     DOI: 10.1002/btpr.280

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  12 in total

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10.  Transforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentation.

Authors:  Pau Cabaneros Lopez; Isuru A Udugama; Sune T Thomsen; Christian Roslander; Helena Junicke; Miguel M Iglesias; Krist V Gernaey
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