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-HRMS-QTOF-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
Authors: Panagiotis Arapitsas, Maurizio Ugliano, Matteo Marangon, Luigi Moio, Luca Rolle, Andrea Versari, Fulvio Mattivi
Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige (Italy)
Department of Biotechnology, University of Verona (Italy)
Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova (Italy)
Department of Agricultural Sciences, University of Naples Federico II, Avellino (Italy); Dipartimento di Scienze Agrarie, Forestali e Alimentari, Universitàdi Torino (Italy)
Department of Agricultural and Food Sciences, University of Bologna (Italy); Centre Agriculture Food Environment, University of Trento (Italy)
Keywords: mass spectrometry, wine authenticity, bioinformatics, metabolomics