A novel headspace solid-phase microextraction arrow method employing comprehensive two-dimensional gas chromatography–mass spectrometry combined with chemometric tools for the investigation of wine aging

葡萄酒 酿造的 化学 固相微萃取 主成分分析 色谱法 质谱法 化学计量学 气相色谱-质谱法 萃取(化学) 指纹(计算) 食品科学 人工智能 计算机科学 生物化学
作者
Natasa P. Kalogiouri,Natalia Manousi,Antonio Ferracane,George A. Zachariadis,Stéfanos Koundouras,Victoria Samanidou,Peter Q. Tranchida,Luigi Mondello,Erwin Rosenberg
出处
期刊:Analytica Chimica Acta [Elsevier BV]
卷期号:1304: 342555-342555 被引量:10
标识
DOI:10.1016/j.aca.2024.342555
摘要

Omics is used as an analytical tool to investigate wine authenticity issues. Aging authentication ensures that the wine has undergone the necessary maturation and developed its desired organoleptic characteristics. Considering that aged wines constitute valuable commodities, the development of advanced omics techniques that guarantee aging authenticity and prevent fraud is essential. Α solid phase microextraction Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry was developed to identify volatiles in red wines and investigate how aging affects their volatile fingerprint. The method was optimized by examining the critical parameters that affect the solid phase microextraction Arrow extraction (stirring rate, extraction time) process. Under optimized conditions, extraction took place within 45 min under stirring at 1000 rpm. In all, 24 monovarietal red wine samples belonging to the Xinomavro variety from Naoussa (Imathia regional unit of Macedonia, Greece) produced during four different vintage years (1998, 2005, 2008 and 2015) were analyzed. Overall, 237 volatile compounds were tentatively-identified that were treated with chemometric tools. Four major groups, one for each vintage year were revealed from the Hierarchical Clustering Analysis. The first two Principal Components of Principal Component Analysis explained 86.1% of the total variance, showing appropriate grouping of the wine samples produced in the same crop year. A two-way orthogonal partial least square – discriminant analysis model was developed and successfully classified all the samples to the proper class according to the vintage age, establishing 17 volatile markers as the most important features responsible for the classification, with an explained total variance of 88.5%. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, based on their volatile fingerprint. The developed methodology in combination with chemometric techniques allows to trace back and confirm the vintage year, and is proposed as a novel authenticity tool which opens completely new and hitherto unexplored possibilities for wine authenticity testing and confirmation.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
林钰浩发布了新的文献求助10
刚刚
刚刚
完美世界应助XX采纳,获得10
刚刚
ww发布了新的文献求助10
1秒前
tjr8910发布了新的文献求助10
1秒前
王帅崽完成签到 ,获得积分10
1秒前
2秒前
2秒前
2秒前
2秒前
2秒前
wek完成签到,获得积分10
3秒前
二个完成签到,获得积分10
3秒前
3秒前
羽毛发布了新的文献求助10
3秒前
4秒前
善良的人发布了新的文献求助10
4秒前
5秒前
5秒前
烟花应助活力皮皮虾采纳,获得10
5秒前
5秒前
6秒前
尺素寸心发布了新的文献求助10
6秒前
清风发布了新的文献求助10
6秒前
LmyHusband发布了新的文献求助10
6秒前
阳光的雯发布了新的文献求助10
7秒前
没有答案发布了新的文献求助10
8秒前
8秒前
8秒前
二个发布了新的文献求助10
9秒前
科研通AI2S应助tsuki采纳,获得10
9秒前
机灵书易发布了新的文献求助10
9秒前
9秒前
嘟噜完成签到 ,获得积分10
9秒前
9秒前
9秒前
小铁匠发布了新的文献求助10
10秒前
活力青槐发布了新的文献求助10
10秒前
10秒前
欢呼妙菱发布了新的文献求助10
10秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Materials selection in mechanical design 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6479469
求助须知:如何正确求助?哪些是违规求助? 8280603
关于积分的说明 17661739
捐赠科研通 5562111
什么是DOI,文献DOI怎么找? 2911422
邀请新用户注册赠送积分活动 1888488
关于科研通互助平台的介绍 1742583