Studying wine metabolome through multiple targeted methods is complicated and limitative; since grapes, yeasts, bacteria, oxygen, enological techniques and wine aging collaborate to deliver one of the richest metabolomic fingerprint. Therefore, untargeted metabolomics, that developed and evolved as a consequence of the need to obtain a comprehensive characterization of the organic molecules in any biological sample, is the current methodology offering the best coverage of wine metabolome. Taking into account the large genetic diversity, the diversity of the climate and of the agronomical practices, and the wide winemaking culture characterizing the Italian wines, the metabolomic untargeted approach appears as an appropriate analytical tool to study such metabolic space. According to the national project D-Wines, 110 single-cultivar red wines from the 2016 vintage were collected directly from wineries across different regions of Italy: Sangiovese from Tuscany and Romagna, Nebbiolo from Piemont, Aglianico from Campania, Nerello Mascalese from Sicily, Primitivo from Apulia, Raboso and Corvina from Veneto, Cannonau from Sardinia, Teroldego from Trentino, Sagrantino from Umbria, and Montepulciano from Abruzzo. The wines were analyzed according to a well-defined RP-UPLC-HRMSQTOF-MS protocol. The results of the data analysis, after their validation: a) confirmed untargeted LC-MS-based metabolomics as a powerful authenticity tool; b) provided indications about the similarity between the cultivars, clustering the wines in three major groups (Primitivo – Nebbiolo, Corvina, Raboso, Sangiovese – Teroldego, Sagrantino, Cannonau, Nerello, Aglianico, Montepulciano); c) furnished a rich list of putative markers characterizing each cultivar, where Primitivo, Teroldego and Nebbiolo had the maximum number of unique putative markers; d) revealed that the putative markers were not only phenolic metabolites; and e) pointed out rt/mz chromatographic sections helpful to distinguish each cultivar from the others. This study, together with other D-Wines analytical results, is directed to understand the diversity of Italian red wines and to characterize them in term of metabolic space coverage/variability and taste and in consequence comprehend better their quality. Acknowledgements: MIUR project N. 20157RN44Y. A. Curioni, A. Gambuti, V. Gerbi, S. Giacosa, G.P. Parpinello, D. Perenzoni, P. Piombino, A. Rinaldi, S. Río Segade, B. Simonato, G. Tornielli, S. Vincenzi
Arapitsas, P.; Ugliano, U.; Marangon, M.; Moio, L.; Rolle, L.; Versari, A.; Mattivi, F. (2019). D-wines: use of LC-MS metabolomic space to discriminate Italian mono-varietal red wines. In: ŒnoIVAS 2019: 11th International Symposium of Oenology of Bordeaux and 11th edition of the symposium In Vino Analytica Scientia, Bordeaux, France, June 25-28, 2019: 108. url: http://isvv-events.com/oeno2019-ivas2019/ handle: http://hdl.handle.net/10449/56548
D-wines: use of LC-MS metabolomic space to discriminate Italian mono-varietal red wines
Arapitsas, P
Primo
;Mattivi, F.Ultimo
2019-01-01
Abstract
Studying wine metabolome through multiple targeted methods is complicated and limitative; since grapes, yeasts, bacteria, oxygen, enological techniques and wine aging collaborate to deliver one of the richest metabolomic fingerprint. Therefore, untargeted metabolomics, that developed and evolved as a consequence of the need to obtain a comprehensive characterization of the organic molecules in any biological sample, is the current methodology offering the best coverage of wine metabolome. Taking into account the large genetic diversity, the diversity of the climate and of the agronomical practices, and the wide winemaking culture characterizing the Italian wines, the metabolomic untargeted approach appears as an appropriate analytical tool to study such metabolic space. According to the national project D-Wines, 110 single-cultivar red wines from the 2016 vintage were collected directly from wineries across different regions of Italy: Sangiovese from Tuscany and Romagna, Nebbiolo from Piemont, Aglianico from Campania, Nerello Mascalese from Sicily, Primitivo from Apulia, Raboso and Corvina from Veneto, Cannonau from Sardinia, Teroldego from Trentino, Sagrantino from Umbria, and Montepulciano from Abruzzo. The wines were analyzed according to a well-defined RP-UPLC-HRMSQTOF-MS protocol. The results of the data analysis, after their validation: a) confirmed untargeted LC-MS-based metabolomics as a powerful authenticity tool; b) provided indications about the similarity between the cultivars, clustering the wines in three major groups (Primitivo – Nebbiolo, Corvina, Raboso, Sangiovese – Teroldego, Sagrantino, Cannonau, Nerello, Aglianico, Montepulciano); c) furnished a rich list of putative markers characterizing each cultivar, where Primitivo, Teroldego and Nebbiolo had the maximum number of unique putative markers; d) revealed that the putative markers were not only phenolic metabolites; and e) pointed out rt/mz chromatographic sections helpful to distinguish each cultivar from the others. This study, together with other D-Wines analytical results, is directed to understand the diversity of Italian red wines and to characterize them in term of metabolic space coverage/variability and taste and in consequence comprehend better their quality. Acknowledgements: MIUR project N. 20157RN44Y. A. Curioni, A. Gambuti, V. Gerbi, S. Giacosa, G.P. Parpinello, D. Perenzoni, P. Piombino, A. Rinaldi, S. Río Segade, B. Simonato, G. Tornielli, S. VincenziFile | Dimensione | Formato | |
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