A near‐infrarod spectroscopy technique for the control of fermentation processes: An application to lactic acid fermentation

Vaccari, G.; Dosi, E.; Campi, A.L.; Mantovani, G.; Matteuzzi, Diego

doi:10.1002/bit.260431003

Cited by 88 publications

(64 citation statements)

References 9 publications

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“…A number of on-line studies using NIRS as applied to microbial bioprocesses have been carried out (Brookes et al, 1996;Cavinato et al, 1990;Ge et al, 1994;Hammond, 1992;Vaccari et al, 1994) but not using a steam-sterilisable fibre optic probe inserted directly into the reaction vessel itself. As discussed previously, in the past on-line studies have been carried out using flow-through cells (Brookes et al, 1996;Hammond, 1992;Vaccari et al, 1994) or fibre optic probes scanning through the glass window of the reactor wall (Brookes et al, 1996;Cavinato et al, 1990;Ge et al, 1994;Hammond, 1992).…”

Section: Transfer From At-line To On-linementioning

confidence: 99%

“…There have been some previous studies carried out on-line but none have fully exploited the potential of in-situ NIRS. Many studies have been carried out ex-situ using either flow-through cells (Brookes et al, 1996;Hammond, 1992;Vaccari et al, 1994) or placing the fibre optic probe on fermenter windows (Brookes et al, 1996;Cavinato et al, 1990;Ge et al, 1994;Hammond, 1992). Most of the previous work did not give details on either the nature of the models subsequently developed or any detailed process (fermentation) data (Hammond, 1992).…”

Section: Introductionmentioning

confidence: 99%

“…The same group went on to monitor cell density in a fermentation process (S. cerevisiae), again using a fibre optic probe on a glass wall (Ge et al, 1994). Vaccari et al (1994) also looked at on-line NIRS using a flow-through cell (ex-situ). Once again it was an anaerobic process and the agitation was even lower, at only 120 rpm.…”

Section: Introductionmentioning

confidence: 99%

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Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process

Arnold

Gaensakoo²,

Harvey

et al. 2002

Biotech & Bioengineering

125

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One of the key goals in bioprocess monitoring is to achieve real-time knowledge of conditions within the bioreactor, i.e., in-situ. Near-infrared spectroscopy (NIRS), with its ability to carry out multi-analyte quantification rapidly with little sample presentation, is potentially applicable in this role. In the present study, the application of NIRS to a complex, fed-batch industrial E. coli (RV308/PHKY531) process was investigated. This process undergoes a series of temperature changes and is vigorously agitated and aerated. These conditions can pose added challenges to in-situ NIRS. Using the measurement of a key analyte (biomass) as an illustration, the details of the relationship between the at-line and in-situ use of NIRS are considered from the viewpoint of both theory and practical application. This study shows that NIRS can be used both at-line and in-situ in order to achieve good predictive models for biomass. There are particular challenges imposed by in-situ operation (loss of wavelength regions and noise) which meant the need for signal optimisation studies. This showed that whilst the at-line modelling process may provide some useful information for the in-situ process, there were distinct differences. This study shows that the in-situ use of NIRS in a highly challenging matrix (similar to those encountered in current industrial practice) is possible, and thus extends previous works in the area.

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Section: Transfer From At-line To On-linementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process

Arnold

Gaensakoo²,

Harvey

et al. 2002

Biotech & Bioengineering

125

View full text Add to dashboard Cite

show abstract

“…Monitoring errors over large concentration ranges were approximately 7 mM for each analyte with an MPE of 1-3%. Vaccari et al 11 measured the concentrations of lactate, glucose, and biomass in bacterial cell fermentations with similar levels of error. We have pre-…”

Section: %mentioning

confidence: 99%

Matrix-Enhanced Calibration Procedure for Multivariate Calibration Models with Near-Infrared Spectra

1998

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A novel method is introduced for developing calibration models for the spectroscopic measurement of chemical concentrations in an aqueous environment. To demonstrate this matrix-enhanced calibration procedure, we developed calibration models to quantitate glucose and glutamine concentrations in an insect cell culture medium that is a complex mixture of more than 20 components, with three components that manifest significant concentration changes. Accurate calibration models were generated for glucose and glutamine by using a calibration data set composed of 60 samples containing the analytes dissolved in an aqueous buffer along with as few as two samples of the analytes dissolved in culture medium. Standard errors of prediction were 1.0 mM for glucose and 0.35 mM for glutamine. The matrix-enhanced method was also applied to culture medium samples collected during the course of a second bioreactor run. Addition of three culture medium samples to a buffer calibration reduced glucose prediction errors from 3.8 mM to 1.0 mM; addition of two culture medium samples reduced glutamine prediction errors from 1.6 mM to 0.76 mM. Results from this study suggest that spectroscopic calibration models can be developed from a relatively simple set of samples provided that some account for variations in the sample matrix.

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“…Thus, at present, despite considerable advances in control, such assessments/decisions are typically based on process data produced by infrequent sampling which often has a significant time delay built in, and may, in many cases, be an inferential measurement. Conversely, near-infrared spectroscopy (NIRS) has features that are attractive for real-time process monitoring (Vaidyanathan and McNeil, 1998) and is progressively being investigated for this purpose (Hall et al, 1996;Riley et al, 1998;Vaccari et al, 1994;Vaidyanathan et al, 1999b;Yeung et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Assessment of near‐infrared spectral information for rapid monitoring of bioprocess quality

Vaidyanathan

Arnold

Matheson

et al. 2001

Biotech & Bioengineering

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Access to real-time process information is desirable for consistent and efficient operation of bioprocesses. Near-infrared spectroscopy (NIRS) is known to have potential for providing real-time information on the quantitative levels of important bioprocess variables. However, given the fact that a typical NIR spectrum encompasses information regarding almost all the constituents of the sample matrix, there are few case studies that have investigated the spectral details for applications in bioprocess quality assessment or qualitative bioprocess monitoring. Such information would be invaluable in providing operator-level assistance on the progress of a bioprocess in industrial-scale productions. We investigated this aspect and report the results of our investigation. Near-infrared spectral information derived from scanning unprocessed culture fluid (broth) samples from a complex antibiotic production process was assessed for a data set that incorporated bioprocess variations. Principal component analysis was applied to the spectral data and the loadings and scores of the principal components studied. Changes in the spectral information that corresponded to variations in the bioprocess could be deciphered. Despite the complexity of the matrix, near-infrared spectra of the culture broth are shown to have valuable information that can be deconvoluted with the help of factor analysis techniques such as principal component analysis (PCA). Although complex to interpret, the loadings and score plots are shown to offer potential in process diagnosis that could be of value in the rapid assessment of process quality, and in data assessment prior to quantitative model development.

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A near‐infrarod spectroscopy technique for the control of fermentation processes: An application to lactic acid fermentation

Cited by 88 publications

References 9 publications

Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process

Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process

Matrix-Enhanced Calibration Procedure for Multivariate Calibration Models with Near-Infrared Spectra

Assessment of near‐infrared spectral information for rapid monitoring of bioprocess quality

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