Negative effects on wine quality and productivity caused by stuck and sluggish fermentations can be reduced significantly, if such problems are detected early through periodic chemical analysis. Infrared spectroscopy (IR) has been used successfully for monitoring fermentations, since many compounds can be measured quickly from a single sample without prior treatment. Nevertheless, few applications of this technology in large scale winemaking have been reported, and these do not cover the entire fermentation from must to finished wine. In this work, we developed IR calibrations for analyzing the fermenting must at any stage of fermentation. The calibration model was obtained with multivariable partial least squares and proved effective for analyzing Cabernet Sauvignon fermentations for glucose, fructose, glycerol, ethanol, and the organic acids; malic, tartaric, succinic, lactic, acetic, and citric. Upon external validation we found an average relative predictive error of 4.8%. Malic acid showed the largest relative predictive error (8.7%). In addition, external validation found that insufficient data for these calibrations made the analysis of fermenting musts using other grape varieties less reliable. (C) 2004 Elsevier B.V. All rights reserved.
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Autor | Urtubia, A Perez Correa, JR Meurens, M Agosin, E |
Título | Monitoring large scale wine fermentations with infrared spectroscopy |
Revista | TALANTA |
ISSN | 0039-9140 |
ISSN electrónico | 1873-3573 |
Volumen | 64 |
Número de publicación | 3 |
Página inicio | 778 |
Página final | 784 |
Fecha de publicación | 2004 |
Resumen | Negative effects on wine quality and productivity caused by stuck and sluggish fermentations can be reduced significantly, if such problems are detected early through periodic chemical analysis. Infrared spectroscopy (IR) has been used successfully for monitoring fermentations, since many compounds can be measured quickly from a single sample without prior treatment. Nevertheless, few applications of this technology in large scale winemaking have been reported, and these do not cover the entire fermentation from must to finished wine. In this work, we developed IR calibrations for analyzing the fermenting must at any stage of fermentation. The calibration model was obtained with multivariable partial least squares and proved effective for analyzing Cabernet Sauvignon fermentations for glucose, fructose, glycerol, ethanol, and the organic acids; malic, tartaric, succinic, lactic, acetic, and citric. Upon external validation we found an average relative predictive error of 4.8%. Malic acid showed the largest relative predictive error (8.7%). In addition, external validation found that insufficient data for these calibrations made the analysis of fermenting musts using other grape varieties less reliable. (C) 2004 Elsevier B.V. All rights reserved. |
Derechos | acceso restringido |
DOI | 10.1016/j.talanta.2004.04.005 |
Editorial | ELSEVIER |
Enlace | |
Id de publicación en Pubmed | MEDLINE:18969672 |
Id de publicación en WoS | WOS:000224285300030 |
Paginación | 7 páginas |
Palabra clave | Cabernet Sauvignon winemaking sugars organic acids glycerol PLS CALIBRATION CLASSIFICATION |
Tema ODS | 02 Zero Hunger |
Tema ODS español | 02 Hambre cero |
Tipo de documento | artículo |