At-line monitoring of ammonium, glucose, methyl oleate and biomass in a complex antibiotic fermentation process using attenuated total reflectance-mid-infrared (ATR-MIR) spectroscopy

P. Roychoudhury, L.M. Harvey, B. McNeil

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

The utility of attenuated total reflectance-mid-infrared spectroscopy (ATR-MIR) to monitor the concentrations of the key analytes ammonium, glucose, methyl oleate and biomass in a Streptomyces clavuligerus bioprocess for the synthesis of clavulanic acid was investigated. The cultivation medium was complex and the process fluid (matrix) underwent profound changes as culture growth proceeded, representing a considerable challenge from a spectroscopic viewpoint. Quantitative models were developed using the multivariate statistical technique, partial least square (PLS) for the key analytes over the entire time course of the bioprocess, which were validated externally using samples not incorporated in the original modelling exercise. The reasoning behind the choice of modelling strategy for each analyte is discussed, with particular focus on biomass modelling in order to generate clearer insight into the modelling process in this complex matrix. Despite the heterogeneous nature of the sample matrix, and the complexity of the spectral information arising, at-line models were developed giving low prediction error values for the analytes: ammonium 0.013 g/l; glucose 0.56 g/l; methyl oleate 0.38 g/l and biomass 0.39 g/l, respectively. These findings represent a considerable advance on previous studies using NIR in antibiotic processes, as all key analytes have been successfully modelled here, and the use of ATR-MIR in complex bioprocess fluids has been shown to be a viable method of near real-time monitoring.
Original languageEnglish
Pages (from-to)218-224
Number of pages7
JournalAnalytica Chimica Acta
Volume561
Issue number1-2
Early online date17 Feb 2006
DOIs
Publication statusPublished - 2 Mar 2006

Keywords

  • ATR-MIR
  • streptomyces
  • PLS
  • models

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