Journal article published in Food Research International, volume 143:110277, pp. 1–13.
Authors:
.Abstract
An extensive survey was conducted on 110 Italian monovarietal red wines from a single vintage to determine their standard compositional, color, and phenolic characteristics, analysing more than 35 parameters evaluated through methods commonly used in the wine industry. ‘Primitivo’ achieved the highest average alcohol strength (15.4% v/v) and dry extract values, while ‘Cannonau’ showed the lowest total acidity. ‘Corvina’ had the lowest phenolic content (1065 mg/L by Folin-Ciocalteu assay), remarkably different from the highest found in ‘Sagrantino’ (3578 mg/L), the latter being also the richest variety in both proanthocyanidins and vanillin-reactive flavanols. ‘Teroldego’ wines were the richest in both total and monomeric anthocyanins (702 and 315 mg/L, respectively), followed by ‘Aglianico’ and ‘Raboso Piave’, while ‘Corvina’, ‘Nebbiolo’, and ‘Nerello Mascalese’ were the poorest. ‘Montepulciano’ and ‘Sangiovese’ showed intermediate values for the majority of the parameters analyzed. A multivariate PCA-DA approach allowed achieving both a classification of the different wines as well as the discrimination of ‘Sangiovese’ wines produced in two regions (Emilia Romagna and Toscana) that returned a 42–66% success rate depending on the zone considered. Taking into account the number and diversity of the wines analyzed, a correlation study helped in better understanding the underlying relations between the most common and widespread analytical techniques for phenolic and color determinations.
Key words autochthonous grape varieties; phenolic compounds; tannins; antioxidant capacity; red wine; UV–Visible spectrophotometry; multivariate analysis; D-Wines collaboration
BibTeX entry: click to show
@article{ 2318_1782493, url = {https://hdl.handle.net/2318/1782493}, author = {Giacosa, Simone and Parpinello, Giuseppina Paola and Río Segade, Susana and Ricci, Arianna and Paissoni, Maria Alessandra and Curioni, Andrea and Marangon, Matteo and Mattivi, Fulvio and Arapitsas, Panagiotis and Moio, Luigi and Piombino, Paola and Ugliano, Maurizio and Slaghenaufi, Davide and Gerbi, Vincenzo and Rolle, Luca and Versari, Andrea}, title = {Diversity of Italian red wines: A study by enological parameters, color, and phenolic indices}, year = {2021}, journal = {Food Research International}, volume = {143:110277}, abstract = {An extensive survey was conducted on 110 Italian monovarietal red wines from a single vintage to determine their standard compositional, color, and phenolic characteristics, analysing more than 35 parameters evaluated through methods commonly used in the wine industry. ‘Primitivo’ achieved the highest average alcohol strength (15.4% v/v) and dry extract values, while ‘Cannonau’ showed the lowest total acidity. ‘Corvina’ had the lowest phenolic content (1065 mg/L by Folin-Ciocalteu assay), remarkably different from the highest found in ‘Sagrantino’ (3578 mg/L), the latter being also the richest variety in both proanthocyanidins and vanillin-reactive flavanols. ‘Teroldego’ wines were the richest in both total and monomeric anthocyanins (702 and 315 mg/L, respectively), followed by ‘Aglianico’ and ‘Raboso Piave’, while ‘Corvina’, ‘Nebbiolo’, and ‘Nerello Mascalese’ were the poorest. ‘Montepulciano’ and ‘Sangiovese’ showed intermediate values for the majority of the parameters analyzed. A multivariate PCA-DA approach allowed achieving both a classification of the different wines as well as the discrimination of ‘Sangiovese’ wines produced in two regions (Emilia Romagna and Toscana) that returned a 42–66% success rate depending on the zone considered. Taking into account the number and diversity of the wines analyzed, a correlation study helped in better understanding the underlying relations between the most common and widespread analytical techniques for phenolic and color determinations.}, keywords = {autochthonous grape varieties; phenolic compounds; tannins; antioxidant capacity; red wine; UV–Visible spectrophotometry; multivariate analysis; D-Wines collaboration}, doi = {10.1016/j.foodres.2021.110277}, pages = {1--13} }
Publication availability
Accepted manuscript
This file is available in an accepted manuscript version from the IRIS institutional repository.
This file is subjected to usage limitations according to its license.
Supplementary material (from IRIS): File 1
View or request this publication
You can find the postprint version of this article in the Open Access Repository of the University of Torino:
IRIS-AperTO record 2318/1782493
View the final version at publisher:
doi:10.1016/j.foodres.2021.110277
File not available? Do you need further information?
You can contact me and request this article through the following form: