Characterization of Sparkling Wine Based on Polyphenolic Profiling by Liquid Chromatography Coupled to Mass Spectrometry

Author:

Oliva Eleonora12,Mir-Cerdà Aina13ORCID,Sergi Manuel4,Sentellas Sònia135ORCID,Saurina Javier13ORCID

Affiliation:

1. Department of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, E08028 Barcelona, Spain

2. Faculty of Bioscience and Technology for Food, Agriculture and Environment, 64100 Teramo, Italy

3. Research Institute in Food Nutrition and Food Safety, Universitat de Barcelona, Recinte Torribera, E08921 Santa Coloma de Gramenet, Spain

4. Chemistry Department, University La Sapienza, 00185 Rome, Italy

5. Serra Húnter Fellow, Generalitat de Catalunya, E08007 Barcelona, Spain

Abstract

Polyphenols are phytochemicals naturally present in wines that arouse much interest in the scientific community due to their healthy properties. In addition, their role as descriptors of various wine qualities, such as the geographical origin or the grape variety, cannot be underestimated. Here, Pinot Noir and Xarel·lo monovarietal samples belonging to the sparkling wine production process have been studied, corresponding to base wines from a first alcoholic fermentation (plus malolactic in some cases), base wines resulting from tartaric stabilization, and sparkling wines from a second alcoholic fermentation aged for 3 and 7 months. One of the objectives of this paper is to obtain valuable chemical and oenological information by processing a huge amount of data with suitable chemometric methods. High-performance liquid chromatography coupled with ultraviolet spectroscopy and tandem mass spectrometry (HPLC-UV-MS/MS) has been used for the determination of polyphenols in wines and related samples. The method relies on reversed-phase mode and further detection by multiple reaction monitoring. Concentrations of relevant phenolic compounds have been determined, and the resulting compositional data have been used for characterization purposes. Exploratory studies by principal component analysis have shown that samples can be discriminated according to varietal and quality issues. Further classification models have been established to assign unknown samples to their corresponding classes. For this purpose, a sequential classification tree has been designed involving both variety and quality classes, and an excellent classification rate has been achieved.

Funder

Agencia Estatal de Investigación. Ministerio de Ciencia e Innovación. Gobierno de España

Publisher

MDPI AG

Subject

Plant Science,Biochemistry, Genetics and Molecular Biology (miscellaneous),Food Science

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3