Browsing by Author "Robatscher P"

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    Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach
    (MDPI (Basel, Switzerland), 15/10/2021) Poggesi S; Dupas de Matos A; Longo E; Chiotti D; Pedri U; Eisenstecken D; Robatscher P; Boselli E
    A multivariate regression approach based on sensory data and chemical compositions has been applied to study the correlation between the sensory and chemical properties of Pinot Blanc wines from South Tyrol. The sensory properties were identified by descriptive analysis and the chemical profile was obtained by HS-SPME-GC/MS and HPLC. The profiles of the most influencing (positively or negatively) chemical components have been presented for each sensory descriptor. Partial Least Square Regression (PLS) and Principal Component Regression (PCR) models have been tested and applied. Visual (clarity, yellow colour), gustatory (sweetness, sourness, saltiness, bitterness, astringency, and warmness) and olfactory (overall intensity, floral, apple, pear, tropical fruit, dried fruit, fresh vegetative, spicy, cleanness, and off-odours) descriptors have been correlated with the volatile and phenolic profiles, respectively. Each olfactory descriptor was correlated via a PCR model to the volatile compounds, whereas a comprehensive PLS2 regression model was built for the correlation between visual/gustatory descriptors and the phenolic fingerprint. "Apple" was the olfactory descriptor best modelled by PCR, with an adjusted R2 of 0.72, with only 20% of the validation samples falling out of the confidence interval (α = 95%). A PLS2 with 6 factors was chosen as the best model for gustatory and visual descriptors related to the phenolic compounds. Finally, the overall quality judgment could be explained by a combination of the calibrated sensory descriptors through a PLS model. This allowed the identification of sensory descriptors such as "olfactory intensity", "warmness", "apple", "saltiness", "astringency", "cleanness", "clarity" and "pear", which relevantly contributed to the overall quality of Pinot Blanc wines from South Tyrol, obtained with two different winemaking processes and aged in bottle for 18 months.
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    Enantioselective-GCxGC determination of α-terpinyl ethyl ether in wine: Quantitative analysis and identification of main terpene precursors
    (Elsevier B.V., 2024-10-18) Darnal A; Ceccon A; Magni M; Robatscher P; Poggesi S; Boselli E; Longo E
    The present study investigates the presence of α-terpinyl ethyl ether in wine and gives insights on the chemical processes leading to its formation. The analytical determination of (S)-α-terpinyl ethyl ether and (R)-α-terpinyl ethyl ether enantiomers was obtained by enantioselective comprehensive two-dimensional gas chromatography. Applying the two isomers as variables in combination with closely related terpenes, an accurate classification model of wines for the grape variety was successfully applied to a representative set of single-variety wine samples. Although presenting relatively low absolute concentrations, α-terpinyl ethyl ether (along with α-terpineol) resulted to be an inevitable and irreversible degradation product of linalool. In fact, a conversion study from enantiomerically pure (R)-linalool showed a major loss of the initial chiral configuration, i.e. only a very small enantiomeric excess characterized the product. α-Terpineol itself was also confirmed to be a precursor of α-terpinyl ethyl ether, however this process showed a smaller conversion over two weeks than from linalool, and without losses of the initial chiral configuration. In the real samples, the concentration of α-terpinyl ethyl ether was found to be much lower than that of α-terpineol, regardless of the alcohol-to-water ratio. Finally, olfactory descriptors were qualitatively attributed to each α-terpinyl ethyl ether enantiomer.