In-depth analysis of the characteristics of volatile organic compounds in wines: a systematic study integrating intelligent sensory and metabolomics techniques with chemometrics and machine learning models

IF 8.2 1区农林科学 Q1 CHEMISTRY, APPLIED

Food Chemistry: X Pub Date : 2025-10-01 DOI:10.1016/j.fochx.2025.103082

Rui Xie , Jiawen Liu , Yutao Li , Yong Chen , Tian Shen , Meilong Xu , Yanlun Ju , Yulin Fang , Zhenwen Zhang

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引用次数: 0

Abstract

The volatile organic compounds (VOCs) in wines of ‘Dornfelder’ (DF), ‘Petit Verdot’ (PV), ‘Pinot Noir’ (PN), ‘Sangiovese’ (SV) and ‘Malbec’ (MB) were analyzed using an E-nose, HS-SPME-GC–MS and HS-GC-IMS. A total of 94 VOCs were identified by two techniques. Specifically, HS-SPME-GC–MS identified 70 compounds (alcohols' concentration accounting for 52.56%–68.75 %), and HS-GC-IMS identified 36 compounds (esters' concentration accounting for 35.58 %–42.05 %), with 12 compounds were identified by both methods. 15 key differential VOCs identified through chemometrics and machine learning analysis. Additionally, correlation analysis of E-nose sensor responses with key differential VOCs indicated that W2S, W2W, and W5S may be more suitable for predicting levels of 2-methylbutyl acetate, 3-methyl-butanoic acid, and isoamyl acetate, which can thus help to quickly identify PV wine. These results help to understand the flavor differences between different varieties of wines and provide a theoretical basis for wine flavor differentiation, quality control and product development.

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深入分析葡萄酒中挥发性有机化合物的特征：将智能感官和代谢组学技术与化学计量学和机器学习模型相结合的系统研究

采用电子鼻、HS-SPME-GC-MS和HS-GC-IMS分析了‘Dornfelder’（DF）、‘Petit Verdot’（PV）、‘Pinot Noir’（PN）、‘Sangiovese’（SV）和‘Malbec’（MB）葡萄酒中的挥发性有机化合物（VOCs）。两种技术共鉴定出94种挥发性有机化合物。其中，HS-SPME-GC-MS鉴定出70个化合物（醇类浓度占52.56% ~ 68.75%），HS-GC-IMS鉴定出36个化合物（酯类浓度占35.58% ~ 42.05%），两种方法共鉴定出12个化合物。通过化学计量学和机器学习分析确定了15种关键的差异VOCs。此外，电子鼻传感器响应与关键差异VOCs的相关性分析表明，W2S、W2W和W5S可能更适合预测2-甲基乙酸丁酯、3-甲基丁酸和乙酸异戊酯的水平，从而有助于快速识别PV酒。这些结果有助于了解不同品种葡萄酒的风味差异，为葡萄酒风味区分、质量控制和产品开发提供理论依据。

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来源期刊

Food Chemistry: X CHEMISTRY, APPLIED-

CiteScore

4.90

自引率

6.60%

发文量

315

审稿时长

55 days

期刊介绍： Food Chemistry: X, one of three Open Access companion journals to Food Chemistry, follows the same aims, scope, and peer-review process. It focuses on papers advancing food and biochemistry or analytical methods, prioritizing research novelty. Manuscript evaluation considers novelty, scientific rigor, field advancement, and reader interest. Excluded are studies on food molecular sciences or disease cure/prevention. Topics include food component chemistry, bioactives, processing effects, additives, contaminants, and analytical methods. The journal welcome Analytical Papers addressing food microbiology, sensory aspects, and more, emphasizing new methods with robust validation and applicability to diverse foods or regions.