ArticleMolecules (Basel, Switzerland)2021
Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach.
Article in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- South-Tyrolean pinot blanc identity: Exploration of chemical and sensory profile changes ascribed to vineyard locations and winemaking variables.Food chemistry: X · 2024Article
- Decoding the Identity of Pinot Gris and Pinot Noir Wines: A Comprehensive Chemometric Fusion of Sensory (from Dual Panel) and Chemical Analysis.Foods (Basel, Switzerland) · 2023Article
- Effects of pre- and post-fermentative practices on oligomeric cyclic and non-cyclic condensed tannins in wine from Schiava grapes.Current research in food science · 2023Article
- Fusion of 2DGC-MS, HPLC-MS and Sensory Data to Assist Decision-Making in the Marketing of International Monovarietal Chardonnay and Sauvignon Blanc Wines.Foods (Basel, Switzerland) · 2022Article
- Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS.Foods (Basel, Switzerland) · 2022Review
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Authors and funding
8 authors.
Funding
Abstract
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 R
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