OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 OENO IVAS 9 OENO IVAS 2019 9 Analytical developments from grape to wine, spirits : omics, chemometrics approaches… 9 D-wines: use of LC-MS metabolomic space to discriminate italian mono-varietal red wines

D-wines: use of LC-MS metabolomic space to discriminate italian mono-varietal red wines

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-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

DOI:

Publication date: June 19, 2020

Issue: OENO IVAS 2019

Type: Article

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)

Contact the author

Keywords

mass spectrometry, wine authenticity, bioinformatics, metabolomics 

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

Improvement of non-Saccharomyces yeast dominance during must fermentation by using spontaneous mutants resistant to SO2, EtOH and high pressure of CO2

AIM: A genetic study of four wine T. delbrueckii strains was done. Spore clones free of possible recessive growth‐retarding alleles with enhanced resistance to winemaking stressing conditions were obtained from these yeasts. METHODS: The genetic marker of resistance to cycloheximide (cyhR) allows easy monitoring of the new mutants obtained from these yeasts.

Illuminating vineyard management: Elevating operational efficiency through advanced sensing and data analytics

In this video recording of the IVES science meeting 2024, Luca Brillante (California State University, Fresno, USA) speaks about vineyard management, advanced sensing and data analytics. This presentation is based on an original article accessible for free on OENO One.

Tracking the origin of Tempranillo Tinto through whole genome resequencing and high-throughput genotyping  

Grapevine cultivars are vegetatively propagated to maintain their varietal characteristics. This process of multiplication leads to spontaneous somatic mutations that can eventually generate a variant phenotype, of potential interest for cultivar improvement and innovation. However, regardless their phenotypic effect, somatic mutations stack in the genome, and they can be used to reveal the origin and dissemination history of ancient cultivars. Here, a stringent somatic variant calling over whole genome resequencing data from 35 ‘Tempranillo Tinto’ clones or old vines from seven Iberian winemaking regions revealed 135 single nucleotide variations (SNVs) shared by some of the clonal lines.

Exploiting the diversity in spent yeast for its valorisation towards producing yeast-derived processing aids

In view of sustainability and zero-waste initiatives, the valorisation of sidestreams is a key emerging topic in the wine industry.

Learning from remote sensing data: a case study in the Trentino region 

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy.