Electronic senses and UPLC-Q-TOF/MS combined with chemometrics analyses of Cynanchum species (Baishouwu).

IF 3 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2024-09-29 DOI:10.1002/pca.3453

Junjie Tang, Man Luo, Xiaomeng Fei, Rongli Qiu, Mei Wang, Yifu Gan, Xudong Qian, Daoguo Zhang, Wei Gu

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Abstract

Introduction: Baishouwu, derived from Cynanchum auriculatum (CA) Royle ex Wight, Cynanchum bungei (CB) Decne., and Cynanchum wilfordii (CW) (Maxim.) Hemsl., is a valuable traditional Chinese medicine. CA is also recognized as a new food resource by China's National Health Commission. Given the considerable variations in flavor and chemical composition among these species and lack of their qualitative assessments, accurately differentiating between the species constituting Baishouwu is essential.

Objective: To develop a method combining electronic tongue (E-tongue), electronic nose (E-nose), and ultra-performance liquid chromatography-quadrupole-time of flight/mass spectrometry (UPLC-Q-TOF/MS) to differentiate between Baishouwu samples.

Material and methods: Fifteen batches of Baishouwu samples were analyzed using E-tongue, E-nose, and UPLC-Q-TOF/MS. Flavor differences and key differential metabolites were determined through principal component analysis and orthogonal partial least squares discriminant analysis.

Results: E-tongue results revealed umami, sweetness, and richness as the predominant flavors of Baishouwu, with CA having the highest umami response, CW exhibiting the highest bitterness, and CB the highest sweetness. E-nose sensors showed consistent responses across species, with variations in signal strength; W1W and W2W sensors showed the highest response values. A total of 158 and 41 characteristic variables in the positive and negative ion modes, respectively, were selected as candidate differential metabolites, of which 29 and 14 were confirmed through database comparison. Eight critical differential metabolites, including C₂₁ steroids and acetophenone compounds, were identified.

Conclusion: This study presents a strategy for differentiating among the species constituting Baishouwu, providing a basis for broader application and establishing quality standards for these medicinal compounds.

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电子感官和 UPLC-Q-TOF/MS 结合化学计量学分析萱草属植物（白首乌）。

介绍：白首乌是一种名贵的中药材，由浙贝母（Cynanchum auriculatum (CA) Royle ex Wight)、川贝母（Cynanchum bungei (CB) Decne.)和威灵仙（Cynanchum wilfordii (CW) (Maxim.) Hemsl.)提炼而成。CA 也被中国国家卫生委员会认定为新的食品资源。由于这些品种的风味和化学成分差异较大，且缺乏定性评估，因此准确区分白首乌的品种至关重要：开发一种结合电子舌（E-tongue）、电子鼻（E-nose）和超高效液相色谱-四极杆飞行时间/质谱（UPLC-Q-TOF/MS）的方法来区分白首乌样品：使用电子舌、电子鼻和 UPLC-Q-TOF/MS 分析了 15 个批次的白首乌样品。通过主成分分析和正交偏最小二乘法判别分析确定了风味差异和主要差异代谢物：电子舌的结果显示，鲜味、甜味和浓味是白首乌的主要风味，其中 CA 的鲜味反应最高，CW 的苦味最高，CB 的甜味最高。电子鼻传感器对不同物种的反应一致，但信号强度有所不同；W1W 和 W2W 传感器的反应值最高。在正离子和负离子模式下，分别有 158 个和 41 个特征变量被选为候选差异代谢物，其中 29 个和 14 个通过数据库比对得到确认。最后确定了 8 个关键的差异代谢物，包括 C21 类固醇和苯乙酮化合物：本研究提出了一种区分白首乌品种的策略，为这些药用化合物更广泛的应用和建立质量标准提供了依据。

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来源期刊

Phytochemical Analysis 生物-分析化学

CiteScore

6.00

自引率

6.10%

发文量

审稿时长

1.7 months

期刊介绍： Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.