Determination of Major Compounds of Alcoholic Fermentation by Middle-Infrared Spectroscopy: Study of Temperature Effects and Calibration Methods

Fayolle, Philippe; Picque, Daniel; Perret, Bruno; Latrille, Éric; Corrieu, Georges

doi:10.1366/0003702963904872

Cited by 39 publications

(28 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 1 shows the first and last spectra of honey must. The peaks at 1151 and 1109 cm −1 were correlated with sugar consumption (mainly glucose and fructose), whereas the growing peak at about 880 cm −1 was mainly correlated with the production of ethanol [26]. Although the substrates (glucose and fructose) and the fermentation product (ethanol) have mid-infrared spectra that overlap, the multivariate treatment of these spectra allows opening a window into the fermentation reaction-i.e.…”

Section: Monitoring Of Mead Fermentation By Ftir-atrmentioning

confidence: 99%

Mead fermentation monitoring by proton transfer reaction mass spectrometry and medium infrared probe

Cuenca

Ciesa²,

Romano

et al. 2016

Eur Food Res Technol

View full text Add to dashboard Cite

Section: Monitoring Of Mead Fermentation By Ftir-atrmentioning

confidence: 99%

Mead fermentation monitoring by proton transfer reaction mass spectrometry and medium infrared probe

Cuenca

Ciesa²,

Romano

et al. 2016

Eur Food Res Technol

View full text Add to dashboard Cite

“…The intensity of a near-IR absorption band is typically 10±100 times weaker than its comparable mid-IR band [17,18]. Until now applications of mid-IR have involved off-line measurement of carbohydrates for yeast fermentation [19], polysaccharide and lignin degradation during substrate composting system [20], and on-line monitoring of conversion of lactate to lactic acid from whey fermentation [21].…”

Section: Introductionmentioning

confidence: 99%

Real-time analyte monitoring of a fungal fermentation, at pilot scale, using in situ mid-infrared spectroscopy

Pollard

Buccino

Connors

et al. 2001

Bioprocess Biosyst Eng

View full text Add to dashboard Cite

Robust in situ biochemical monitoring is essential for the development of substrate feed control to optimize fermentation processes. The scale up of the fermentation for the fungus Glarea lozoyensis can bene®t from such technology to improve the yield of the pharmaceutically important pneumocandin of interest and control the levels of unwanted analogues. A new in situ probe, using a diamond attenuated total re¯ection element, was evaluated at pilot scale for the quantitative measurement of fermentation analytes using Fourier transform mid-IR spectrometry. The new technology was shown to be stable, unaffected by reactor operation conditions of agitation, air¯ow, and backpressure, but sensitive to temperature control. Both glucose and phosphate were simultaneously monitored during a seed fermentation at 280 L pilot scale using complex medium with detection to 0.1 g/L for both analytes. Fructose, glutamate, and proline were monitored at 75 L scale using production media with detection limits of 0.1, 0.5, and 0.5 g/L respectively. Partial least squares calibration/prediction models were created for analytes of interest using off-line reference measurements and speci®c spectral regions. Good ®ts were obtained between off-line measurements and those predicted by in situ mid-IR. Standard errors of prediction (SEP) for glucose (range 18±0.1 g/L) and phosphate (range 11±7.5 g/L) were 0.16 and 1.8 g/L respectively with mean percentage errors (MPEs) around 2.5%. SEP values for the production process: fructose (range 20±0.1 g/L), glutamate (8±0.5 g/L), and proline (12±0.5 g/L) were 0.44, 0.6, and 0.5 g/L respectively with MPEs of 2.2, 5.3, and 10.1%. The technology effectively demonstrates quantitative multicomponent analysis of fermentation processes using in situ monitoring.

show abstract

“…In addition to production or consumption of uncalibrated byproducts, physical properties of the media, such as pH, or temperatures, may also affect the prediction of concentration (Fayolle et al, 1996). To reduce this influence, variation in the physical properties of the culture medium should be calibrated.…”

Section: Discussionmentioning

confidence: 99%

Real‐time update of calibration model for better monitoring of batch processes using spectroscopy

Kornmann¹,

Valentinotti²,

Marison³

et al. 2004

Biotech & Bioengineering

View full text Add to dashboard Cite

In order to reduce the large calibration matrix usually required for calibrating multiwavelength optical sensors, a simple algorithm based on the addition in process of new standards is proposed. A small calibration model, based on 14 standards, is periodically updated by spectra collected on-line during fermentation operation. Concentrations related to these spectra are reconciled into best-estimated values, by considering carbon and oxygen balances. Using this method, fructose, acetate, and gluconacetan were monitored during batch fermentations of Gluconacetobacter xylinus 12281 using mid-infrared spectroscopy. It is shown that this algorithm compensates for noncalibrated events such as production or consumption of by-products. The standard error of prediction (SEP) values were 0.99, 0.10, and 0.90 g/L for fructose, acetate, and gluconacetan, respectively. By contrast, without an updating of the calibration model, the SEP values were 2.46, 0.92, and 1.04 g/L for fructose, acetate, and gluconacetan, respectively. Using only 14 standards, it was therefore possible to approach the performance of an 88-standard-based calibration model having SEP values of 1.11, 0.37, and 0.79 g/L for fructose, acetate, and gluconacetan, respectively. Therefore, the proposed algorithm is a valuable approach to reduce the calibration time of multiwavelength optical sensors.

show abstract

Determination of Major Compounds of Alcoholic Fermentation by Middle-Infrared Spectroscopy: Study of Temperature Effects and Calibration Methods

Cited by 39 publications

References 23 publications

Mead fermentation monitoring by proton transfer reaction mass spectrometry and medium infrared probe

Mead fermentation monitoring by proton transfer reaction mass spectrometry and medium infrared probe

Real-time analyte monitoring of a fungal fermentation, at pilot scale, using in situ mid-infrared spectroscopy

Real‐time update of calibration model for better monitoring of batch processes using spectroscopy

Contact Info

Product

Resources

About