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利用气相色谱 - 质谱联用指纹图谱的化学计量学分析对伊朗红茶中的挥发性化合物进行全面表征。

Comprehensive characterization of volatile compounds in Iranian black teas using chemometric analysis of GC-MS fingerprints.

作者信息

Aminianfar Adineh, Fatemi Mohammad Hossein, Azimi Fatemeh

机构信息

Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.

Gilan Province Water and Wastewater Quality Monitoring and Supervision Center, National Water and Wastewater Engineering Company (NWWEC), Ministry of Energy, Iran.

出版信息

Food Chem X. 2024 Sep 28;24:101859. doi: 10.1016/j.fochx.2024.101859. eCollection 2024 Dec 30.

Abstract

Black tea, a widely popular non-alcoholic beverage, is renowned for its unique aroma and has attracted significant attention due to its complex composition. However, the chemical profile of Iranian tea remains largely unexplored. In this research, black tea samples from key tea cultivation regions in four geographical areas in northern Iran were firstly analyzed using headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (HS-SPME-GC-MS) to separate, identify, and quantify their volatile organic compounds. Subsequently, employing a robust investigative strategy, we utilized for the first time the well-known multivariate curve resolution-alternating least square (MCR-ALS) method as a deconvolution technique to analyze the complex GC-MS peak clusters of tea samples. This approach effectively addressed challenges such as severe baseline drifts, overlapping peaks, and background noise, enabling the identification of minor components responsible for the distinct flavors and tastes across various samples. The MCR-ALS technique significantly improved the resolution of spectral and elution profiles, enabling both qualitative and semi-quantitative analysis of tea constituents. Qualitative analysis involved comparing resolved peak profiles to theoretical spectra, along with retention indices, while semi-quantification was conducted using the overall volume integration (OVI) approach for volatile compounds, providing a more accurate correlation between peak areas and concentrations. The application of chemometric tools in GC-MS analysis increased the number of recognized components in four tea samples, expanding from 54 to 256 components, all with concentrations exceeding 0.1 %. Among them, 32 volatile compounds were present in every tea sample. Hydrocarbons (including alkenes, alkanes, cycloalkanes, monoterpenes and sesquiterpenes), esters and alcohols were the three major chemical classes, comprising 78 % of the total relative content of volatile compounds. Analyzing black teas from four distinct regions revealed variations not only in their volatile components but also in their relative proportions. This integrated approach provides a comprehensive understanding of the volatile chemical profiles in Iranian black teas, enhances knowledge about their unique characteristics across diverse geographical origin, and lays the groundwork for quality improvement.

摘要

红茶是一种广受欢迎的非酒精饮料,以其独特的香气而闻名,因其成分复杂而备受关注。然而,伊朗茶叶的化学特征在很大程度上仍未得到探索。在本研究中,首先使用顶空固相微萃取结合气相色谱 - 质谱联用(HS-SPME-GC-MS)对伊朗北部四个地理区域主要茶叶种植区的红茶样品进行分析,以分离、鉴定和定量其挥发性有机化合物。随后,采用一种强有力的研究策略,我们首次使用著名的多元曲线分辨 - 交替最小二乘法(MCR-ALS)作为去卷积技术来分析茶叶样品复杂的气相色谱 - 质谱峰簇。这种方法有效地解决了诸如严重基线漂移、峰重叠和背景噪声等挑战,能够识别出导致不同样品独特风味和口感的微量成分。MCR-ALS技术显著提高了光谱和洗脱图谱的分辨率,实现了对茶叶成分的定性和半定量分析。定性分析包括将解析后的峰谱与理论光谱以及保留指数进行比较,而半定量则使用挥发性化合物的总体积积分(OVI)方法进行,从而在峰面积和浓度之间提供更准确的相关性。化学计量工具在气相色谱 - 质谱分析中的应用增加了四个茶叶样品中已识别成分的数量,从54种增加到256种,所有成分的浓度均超过0.1%。其中,每个茶叶样品中都含有32种挥发性化合物。烃类(包括烯烃、烷烃、环烷烃、单萜和倍半萜)、酯类和醇类是三大主要化学类别,占挥发性化合物总相对含量的78%。对来自四个不同地区的红茶进行分析发现,不仅其挥发性成分存在差异,而且其相对比例也有所不同。这种综合方法全面了解了伊朗红茶的挥发性化学特征,增强了对其不同地理来源独特特性的认识,并为质量改进奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/479a/11471522/1bd79c87b30d/ga1.jpg

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