Development of FTIR partial least squares models for polyphenol quantification in red wine during fermentation
Polyphenolic compounds are considered to have a major impact on the quality of red wines. Sensory impact, such as astringency and bitterness, stems directly from tannin composition. Thenceforth, quick analytical measurement of phenolic compounds appears to be a real challenge for winemaking monitoring and process control.
Many methods were developed to analyzed polyphenols in wine, but they are time-consuming and require chemistry skills and equipment, not suitable for a rapid routine analysis. A reliable and rapid method to obtain this kind of measurement is Fourier Transform Infrared (FTIR) spectroscopy.
Thus, in order to develop new methods based on FTIR spectroscopy, this work first sought to follow polyphenols during winemaking in a vineyard of Bordeaux area, through two different vintages, different type of winemaking and grape varieties. For this purpose, tannin concentration was analysed by precipitation with Bovine Serum Albumin assay and Methylcellulose assay. In order to obtain the most complete information, the samples were also analyzed by HPLC, using the phloroglucinolysis reaction to obtain the mean degree of polymerization and indication on galloylation, procyanidin and prodelphinidin ratio.
The data collected were statistically analyzed by Partial Least Squares regression method for quantification of laboratory-determined polyphenols from FTIR spectra. Cross validation was used to validate the predictive performance of the models.
Correlations obtained show good results for all parameters studied, with coefficient of determination (r2) for both calibration and cross validation larger than 0.8. This work is the first step for the construction of robust models to quantify different polyphenols parameters during winemaking by FTIR spectroscopy.
Issue: OENO IVAS 2019
Unité de recherche Oenologie, EA 4577, USC 1366 INRA, ISVV, Université de Bordeaux, Bordeaux INP, F33882 Villenave d’Ornon France
USC 1366 INRA, IPB, INRA, ISVV, F-33140 Villenave d’Ornon, France
FOSS Analytical A/S, DK-3400 Hillerød, Denmark
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Polyphenol, Fourier Transform Infrared, Partial Least Squares regression, Spectroscopy