Exploratory Study on Distinguishing Dendrobium Stem and Five Species of Dendrobium Using Heracles Neo Ultra-Fast Gas Phase Electronic Nose

IF 2.5 4区 工程技术 Q3 CHEMISTRY, ANALYTICAL
Yuping Dai, Dan Huang, Ye He, Yun Xiang, Shunxiang Li
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引用次数: 0

Abstract

Dendrobium stem is a valuable food with medicinal and edible properties. Due to its high medicinal value and price, closely related Dendrobium varieties are often sold as imitations on the market. Therefore, there is an urgent need to develop new methods that can quickly identify Dendrobium stem and its closely related species. The Heracles Neo ultra-fast gas phase electronic nose was used in this study to determine and analyze the composition and contents of volatile organic compounds (VOCs) in Dendrobium stem and samples of five other species closely related to it. A total of 20 VOCs were identified, and a fingerprint map of the VOCs was constructed. Principal component analysis (PCA), Euclidean distance, and other methods were used to comprehensively process and analyze the obtained VOC information. The AroChemBase database was also used for qualitative analysis of the compounds. The results showed that there are significant differences in the odor fingerprint spectra of Dendrobium stem and the five other closely related species. The main types of compounds in Dendrobium stem and its five closely related species were organic esters, aldehydes, ketones, and olefins. Among them, 3-methylbutanal and n-butanol were characteristic compounds of the Dendrobium stem sample, while the VOCs acetonitrile and trometamol were present in the five related Dendrobium species samples. The Heracles Neo ultra-fast gas phase electronic nose can quickly and accurately identify Dendrobium stem and its five closely related species. It can also be used for the quality evaluation of Dendrobium stem, providing a theoretical reference for reducing the phenomenon of medicinal confusion in the Dendrobium stem market.
使用 Heracles Neo 超快气相电子鼻区分铁皮石斛茎干和五个铁皮石斛品种的探索性研究
铁皮石斛的茎是一种珍贵的食品,具有药用和食用特性。由于其药用价值高且价格昂贵,市场上经常有近缘石斛品种作为仿制品出售。因此,迫切需要开发能够快速鉴定石斛茎及其近缘品种的新方法。本研究采用 Heracles Neo 超快速气相电子鼻测定和分析了铁皮石斛茎叶及其他五个近缘品种样品中挥发性有机化合物(VOCs)的成分和含量。共鉴定出 20 种挥发性有机化合物,并构建了挥发性有机化合物指纹图谱。利用主成分分析(PCA)、欧氏距离等方法对所获得的挥发性有机化合物信息进行了综合处理和分析。此外,还利用 AroChemBase 数据库对化合物进行了定性分析。结果表明,铁皮石斛茎干的气味指纹谱与其他五个近缘物种存在显著差异。铁皮石斛茎叶及其五个近缘物种的主要化合物类型为有机酯类、醛类、酮类和烯烃类。其中,3-甲基丁醛和正丁醇是石斛茎样本的特征化合物,而乙腈和曲美醇这两种挥发性有机化合物则存在于五个近缘石斛品种的样本中。Heracles Neo 超快速气相电子鼻可以快速准确地鉴定铁皮石斛茎叶及其五个近缘品种。它还可用于铁皮石斛茎叶的质量评价,为减少铁皮石斛茎叶市场的药用混淆现象提供理论参考。
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来源期刊
Separations
Separations Chemistry-Analytical Chemistry
CiteScore
3.00
自引率
15.40%
发文量
342
审稿时长
12 weeks
期刊介绍: Separations (formerly Chromatography, ISSN 2227-9075, CODEN: CHROBV) provides an advanced forum for separation and purification science and technology in all areas of chemical, biological and physical science. It publishes reviews, regular research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: Manuscripts regarding research proposals and research ideas will be particularly welcomed. Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. Manuscripts concerning summaries and surveys on research cooperation and projects (that are funded by national governments) to give information for a broad field of users. The scope of the journal includes but is not limited to: Theory and methodology (theory of separation methods, sample preparation, instrumental and column developments, new separation methodologies, etc.) Equipment and techniques, novel hyphenated analytical solutions (significantly extended by their combination with spectroscopic methods and in particular, mass spectrometry) Novel analysis approaches and applications to solve analytical challenges which utilize chromatographic separations as a key step in the overall solution Computational modelling of separations for the purpose of fundamental understanding and/or chromatographic optimization
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