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Article

Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach

1
Faculty of Science and Technology, Free University of Bozen-Bolzano, Piazza Università 5, 39100 Bolzano, Italy
2
Oenolab, NOI Techpark, Via Alessandro Volta 13, 39100 Bolzano, Italy
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Food Experience and Sensory Testing (Feast) Lab, Massey University, Palmerston North 4410, New Zealand
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Riddet Institute, Massey University, Palmerston North 4410, New Zealand
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Laimburg Research Centre, Laimburg 6, Pfatten (Vadena), 39040 Auer, Italy
*
Author to whom correspondence should be addressed.
Academic Editors: Tristan Richard and Encarna Gómez-Plaza
Molecules 2021, 26(20), 6245; https://doi.org/10.3390/molecules26206245
Received: 27 August 2021 / Revised: 28 September 2021 / Accepted: 13 October 2021 / Published: 15 October 2021
(This article belongs to the Special Issue 25th Anniversary of Molecules—Recent Advances in Applied Chemistry)
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. View Full-Text
Keywords: pinot blanc; sensory analysis; volatile profile; phenolic profile; multivariate regression; winemaking pinot blanc; sensory analysis; volatile profile; phenolic profile; multivariate regression; winemaking
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MDPI and ACS Style

Poggesi, S.; Dupas de Matos, A.; Longo, E.; Chiotti, D.; Pedri, U.; Eisenstecken, D.; Robatscher, P.; Boselli, E. Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach. Molecules 2021, 26, 6245. https://doi.org/10.3390/molecules26206245

AMA Style

Poggesi S, Dupas de Matos A, Longo E, Chiotti D, Pedri U, Eisenstecken D, Robatscher P, Boselli E. Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach. Molecules. 2021; 26(20):6245. https://doi.org/10.3390/molecules26206245

Chicago/Turabian Style

Poggesi, Simone, Amanda Dupas de Matos, Edoardo Longo, Danila Chiotti, Ulrich Pedri, Daniela Eisenstecken, Peter Robatscher, and Emanuele Boselli. 2021. "Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach" Molecules 26, no. 20: 6245. https://doi.org/10.3390/molecules26206245

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