Discrimination and screening of volatile metabolites in atractylodis rhizoma from different varieties using headspace solid-phase microextraction-gas chromatography-mass spectrometry and headspace gas chromatography-ion mobility spectrometry, and ultra-fast gas chromatography electronic nose

离子迁移光谱法 色谱法 质谱法 气相色谱-质谱法 气相色谱法 固相微萃取 化学计量学 电子鼻 化学 芳香 食品科学 神经科学 生物
作者
Le Peng,Xi Wang,Mulan He,Xin Sha,Zhiying Dou,Ling Xiao,Wenlong Li
出处
期刊:Journal of Chromatography A [Elsevier BV]
卷期号:1725: 464931-464931 被引量:5
标识
DOI:10.1016/j.chroma.2024.464931
摘要

Atractylodis rhizoma is a common bulk medicinal material with multiple species. Although different varieties of atractylodis rhizoma exhibit variations in their chemical constituents and pharmacological activities, they have not been adequately distinguished due to their similar morphological features. Hence, the purpose of this research is to analyze and characterize the volatile organic compounds (VOCs) in samples of atractylodis rhizoma using multiple techniques and to identify the key differential VOCs among different varieties of atractylodis rhizoma for effective discrimination. The identification of VOCs was carried out using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), resulting in the identification of 60 and 53 VOCs, respectively. The orthogonal partial least squares discriminant analysis (OPLS-DA) model was employed to screen potential biomarkers and based on the variable importance in projection (VIP≥1.2), 24 VOCs were identified as critical differential compounds. Random forest (RF), K-nearest neighbor (KNN) and back propagation neural network based on genetic algorithm (GA-BPNN) models based on potential volatile markers realized the greater than 90% discriminant accuracies, which indicates that the obtained key differential VOCs are reliable. At the same time, the aroma characteristics of atractylodis rhizoma were also analyzed by ultra-fast gas chromatography electronic nose (Ultra-fast GC E-nose). This study indicated that the integration of HS-SPME-GC-MS, HS-GC-IMS and ultra-fast GC E-nose with chemometrics can comprehensively reflect the differences of VOCs in atractylodis rhizoma samples from different varieties, which will be a prospective tool for variety discrimination of atractylodis rhizoma.
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