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基于 UHPLC-QTOF-MS 的葡萄品种鉴别中国红葡萄酒的非靶向代谢组学分析。

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties.

机构信息

College of Life Sciences, College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434025, China.

Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China.

出版信息

Food Res Int. 2024 Feb;178:113923. doi: 10.1016/j.foodres.2023.113923. Epub 2023 Dec 23.

DOI:10.1016/j.foodres.2023.113923
PMID:38309902
Abstract

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

摘要

葡萄酒是一种非常受欢迎的酒精饮料,因为它具有抗氧化作用的健康益处。然而,由于利润的驱动,葡萄酒市场上经常出现欺诈行为,特别是品种的虚假声明。在这项工作中,建立了一种基于 UHPLC-QTOF-MS 的非靶向代谢组学方法,用于分析来自四个品种(赤霞珠、梅洛、品丽珠和黑皮诺)的 119 瓶中国红葡萄酒的代谢物图谱。使用正交偏最小二乘判别分析(OPLS-DA)评估不同品种红葡萄酒的代谢物,并使用 KEGG 代谢途径分析进行分析。结果表明,不同品种红葡萄酒之间的差异化合物主要是类黄酮、酚类、吲哚和氨基酸。KEGG 代谢途径分析表明,吲哚代谢和黄酮类代谢与葡萄酒品种密切相关。基于差异化合物,OPLS-DA 模型可以在正离子模式下正确识别 90.9%的外部验证酒样,在负离子模式下正确识别 100%的外部验证酒样。本研究表明,基于 UHPLC-QTOF-MS 的非靶向代谢组学方法是一种潜在的鉴定中国红葡萄酒品种的工具。

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