HS-GC-IMS Coupled With Chemometrics Analyzes Volatile Aroma Compounds in Steamed Polygonatum cyrtonema Hua at Different Production Stages.

IF 2.3 3区 化学 Q3 CHEMISTRY, ANALYTICAL
Journal of Analytical Methods in Chemistry Pub Date : 2025-03-10 eCollection Date: 2025-01-01 DOI:10.1155/jamc/5592877
Bingbing Shen, Rongrong Zhou, Jia Lao, Jian Jin, Wei He, Xin Zhou, Hao Liu, Jing Xie, Shuihan Zhang, Can Zhong
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Abstract

Headspace-gas chromatography-ion migration spectrometry (HS-GC-IMS) combined with chemometrics was used to analyze the changes in volatile aroma compounds (VOCs) at different production stages of steaming Polygonatum cyrtonema Hua. Fifty-seven representative compounds in the process of steaming were identified, including 17 aldehydes, 15 alcohols, 15 ketones, 5 esters, 3 furans, and 2 acids. After steaming, the content of 21 compounds decreased. Among them, 3 compounds gradually decreased along with an increase in steaming times; they were 1-hexanol dimer, 1-hexanol monomer, and 3-methylbutan-1-ol dimer. The content of 14 compounds increased than before, and that of three, 1-(2-furanyl)ethanone monomer, 2-furaldehyde, and 3-methyl butanal, increased significantly in the steaming times. The VOCs of the different samples can be classified by GC-IMS data combined with principal component analysis (PCA) and heatmap cluster analysis. A reliable prediction set was established by orthogonal partial least squares discriminant analysis (OPLS-DA), and 18 different VOCs with projected variable importance (VIP) greater than 1.0 were screened out, which could be used as differentiating markers. Therefore, HS-GC-IMS and PCA were used to rapidly identify and classify the VOCs in different production stages of steaming P. cyrtonema Hua.

HS-GC-IMS联合化学计量学分析了不同生产阶段蒸黄精的挥发性香气成分。
采用顶空-气相色谱-离子迁移光谱法(HS-GC-IMS)结合化学计量学分析了蒸黄精不同生产阶段挥发性香气物质(VOCs)的变化。在蒸煮过程中鉴定出57种具有代表性的化合物,包括17种醛类、15种醇类、15种酮类、5种酯类、3种呋喃类和2种酸类。经蒸煮后,其中21种化合物含量降低。其中3种化合物随蒸煮次数的增加而逐渐减少;它们分别是1-己醇二聚体、1-己醇单体和3-甲基丁醇二聚体。其中,1-(2-呋喃基)乙酮单体、2-呋喃醛和3-甲基丁醛的含量随着蒸煮时间的增加而显著增加。采用GC-IMS数据结合主成分分析(PCA)和热图聚类分析对不同样品的VOCs进行分类。通过正交偏最小二乘判别分析(OPLS-DA)建立了可靠的预测集,筛选出了18种预测变量重要度(VIP)大于1.0的VOCs作为区分指标。因此,采用HS-GC-IMS和PCA技术,对蒸制花青树不同生产阶段的挥发性有机化合物进行快速鉴定和分类。
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来源期刊
Journal of Analytical Methods in Chemistry
Journal of Analytical Methods in Chemistry CHEMISTRY, ANALYTICAL-ENGINEERING, CIVIL
CiteScore
4.80
自引率
3.80%
发文量
79
审稿时长
6-12 weeks
期刊介绍: Journal of Analytical Methods in Chemistry publishes papers reporting methods and instrumentation for chemical analysis, and their application to real-world problems. Articles may be either practical or theoretical. Subject areas include (but are by no means limited to): Separation Spectroscopy Mass spectrometry Chromatography Analytical Sample Preparation Electrochemical analysis Hyphenated techniques Data processing As well as original research, Journal of Analytical Methods in Chemistry also publishes focused review articles that examine the state of the art, identify emerging trends, and suggest future directions for developing fields.
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