Infrared Spectroscopy of Aqueous Antibiotic Solutions

Wong, Judith Ju‐Ming; Rein, Alan J.; Wilks, Donald K.; Wilks, Paul A.

doi:10.1366/0003702844554350

Cited by 39 publications

(8 citation statements)

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“…For simple solutions, where the analyzed absorbance peaks are clearly separated, classical analysis using peak height can be used for quantitative analysis (Dadd et al, 2000;White and Roberts, 1985;Wong et al, 1983). Most fermentation media, however, have a complex composition.…”

Section: Introductionmentioning

confidence: 99%

Methodology for real‐time, multianalyte monitoring of fermentations using an in‐situ mid‐infrared sensor

Kornmann

Rhiel²,

Cannizzaro³

et al. 2003

Biotech & Bioengineering

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An in-situ, mid-infrared sensor was used to monitor the major analyte concentrations involved in the cultivation of Gluconacetobacter xylinus and the production of gluconacetan, a food-grade exopolysaccharide. To predict the analyte concentrations, three different sets of standard spectra were used to develop calibration models, applying partial least-squares regression. It was possible to build a valid calibration model to predict the 700 spectra collected during the complete time course of the cultivation, using only 12 spectra collected every 10 h as standards. This model was used to reprocess the concentration profiles from 0 to 15 g/L of nine different analytes with a mean standard error of validation of 0.23 g/L. However, this calibration model was not suitable for real-time monitoring as it was probably based on non-specific spectral features, which were correlated only with the measured analyte concentrations. Valid calibration models capable of real-time monitoring could be established by supplementing the set of 12 fermentation spectra with 42 standards of measured analytes. A pulse of 5 g/L ethanol showed the robustness of the model to sudden disturbances. The prediction of the models drifted, however, toward the end of the fermentation. The most robust calibration model was finally obtained by the addition of 34 standard spectra of non-measured analytes. Although the spectra did not contain analyte-specific information, it was believed that this addition would increase the variability space of the calibration model. Therefore, an expanded calibration model containing 88 spectra was used to monitor, in real time, the concentration profiles of fructose, acetic acid, ethanol and gluconacetan and allowed standard errors of prediction of 1.11, 0.37, 0.22, and 0.79 g/L, respectively.

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Section: Introductionmentioning

confidence: 99%

Methodology for real‐time, multianalyte monitoring of fermentations using an in‐situ mid‐infrared sensor

Kornmann

Rhiel²,

Cannizzaro³

et al. 2003

Biotech & Bioengineering

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“…In recording the spectra in Fig. 1 , the advantages of the ATR FT-IR technique (i.e., simplicity in liquid handling and ability to optimize the pathlength for measurements on aqueous solutions 15 , 39 ) made it possible to detect vibrations of the ionomer dispersed down to a few weight percent in water.…”

Section: Resultsmentioning

confidence: 99%

Vibrational Spectroscopic Monitoring of the Gelation Transition in Nafion Ionomer Dispersions

et al. 2020

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“…Infrared (IR) spectroscopy has been used in the context of measurements on fermentation systems since the eighties, when Wong et al (1984) accounted for measurements on aqueous antibiotic solutions. Since that time the hardware has developed, and the combination of Fourier transform infrared (FT-IR) spectroscopy and an in situ sterilisable attenuated total reflection (ATR) probe, which was used in this work, should be a perfect tool for bioprocess monitoring.…”

Section: Introductionmentioning

confidence: 99%

On-line measurement of the substrate concentrations in Pichia pastoris fermentations using FT-IR/ATR

et al. 2012

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The glycerol and methanol concentrations in Pichia pastoris fermentations were measured on-line using Fourier transform infrared spectroscopy and an attenuated total reflection probe. Partial least squares regression was used to obtain calibration models. The models were regressed on synthetic multi-component spectra and semi-synthetic fermentation broth spectra. These were obtained by spectral addition. The accuracy for the on-line measurement of glycerol, given as standard error of prediction (SEP), was determined to 0.68 g/l, and the SEP of methanol was 0.13 g/l. We show how reliable calibration models are obtained relatively effortlessly by replacing extensive sampling from the reactor with simple mathematical manipulations of the model regression spectra.

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Infrared Spectroscopy of Aqueous Antibiotic Solutions

Cited by 39 publications

References 0 publications

Methodology for real‐time, multianalyte monitoring of fermentations using an in‐situ mid‐infrared sensor

Methodology for real‐time, multianalyte monitoring of fermentations using an in‐situ mid‐infrared sensor

Vibrational Spectroscopic Monitoring of the Gelation Transition in Nafion Ionomer Dispersions

On-line measurement of the substrate concentrations in Pichia pastoris fermentations using FT-IR/ATR

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