Browsing by Author "Fernandez, Katherina"

Now showing 1 - 3 of 3
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    Characterization of Vitis vinifera L. cv. Carmenere grape and wine proanthocyanidins
    (AMER CHEMICAL SOC, 2007) Fernandez, Katherina; Kennedy, James A.; Agosin, Eduardo
    A formal compositional study of the proanthocyanidins of Vitis vinifera L. cv. Carmenere was conducted in this work. We first characterized the polymeric proanthocyanidins of Carmenere skins, seeds, and wines. In addition, the wine astringency was analyzed and compared with Cabernet Sauvignon. Although Carmenere wines had a higher proanthocyanidin concentration and mean degree of polymerization than Cabernet Sauvignon wines, the former wines were perceived as less astringent. The low seed/skin proportion in Carmenere wines as compared to other varieties, as evidenced by the reduced number of seeds per berry and the higher amount of epigallocatechin subunits of Carmenere wine proanthocyanidins, could explain this apparent paradox.
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    Comparative study of wine tannin classification using Fourier transform mid-infrared spectrometry and sensory analysis
    (SOC APPLIED SPECTROSCOPY, 2007) Fernandez, Katherina; Labarca, Ximena; Bordeu, Edmundo; Guesalaga, Andres; Agosin, Eduardo
    Wine tannins are fundamental to the determination of wine quality. However, the chemical and sensorial analysis of these compounds is not straightforward and a simple and rapid technique is necessary. We analyzed the mid-infrared spectra of white, red, and model wines spiked with known amounts of skin or seed tannins, collected using Fourier transform mid-infrared (FT-MIR) transmission spectroscopy (400-4000 cm(-1)). The spectral data were classified according to their tannin source, skin or seed, and tannin concentration by means of discriminant analysis (DA) and soft independent modeling of class analogy (SIMCA) to obtain a probabilistic classification. Wines were also classified sensorially by a trained panel and compared with FT-MIR. SIMCA models gave the most accurate classification (over 97%) and prediction (over 60%) among the wine samples. The prediction was increased (over 73%) using the leave-one-out cross-validation technique. Sensory classification of the wines was less accurate than that obtained with FT-MIR and SINICA. Overall, these results show the potential of FT-MIR spectroscopy, in combination with adequate statistical tools, to discriminate wines with different tannin levels.
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    Quantitative analysis of red wine tannins using Fourier-transform mid-infrared spectrometry
    (AMER CHEMICAL SOC, 2007) Fernandez, Katherina; Agosin, Eduardo
    Tannin content and composition are critical quality components of red wines. No spectroscopic method assessing these phenols in wine has been described so far. We report here a new method using Fourier transform mid-infrared (FT-MIR) spectroscopy and chemometric techniques for the quantitative analysis of red wine tannins. Calibration models were developed using protein precipitation and phloroglucinolysis as analytical reference methods. After spectra preprocessing, six different predictive partial least-squares (PLS) models were evaluated, including the use of interval selection procedures such as iPLS and CSMWPLS. PLS regression with full-range (650-4000 cm(-1)), second derivative of the spectra and phloroglucinolysis as the reference method gave the most accurate determination for tannin concentration (RMSEC = 2.6%, RMSEP = 9.4%, r = 0.995). The prediction of the mean degree of polymerization (mDP) of the tannins also gave a reasonable prediction (RMSEC = 6.7%, RMSEP = 10.3%, r = 0.958). These results represent the first step in the development of a spectroscopic methodology for the quantification of several phenolic compounds that are critical for wine quality.