Flavor components detection and discrimination of isomers in Huaguo tea using headspace-gas chromatography-ion mobility spectrometry and multivariate statistical analysis

Abstract

Aroma components are one of the crucial factors in dynamic processes analysis, quality control, and origin traceability. Various categories of Huaguo Tea possessed different taste due to the generation of aroma. In this study, a comprehensive analysis of volatiles was conducted for five popular Huaguo Tea samples (Lemon Slices, Bitter Gourd Slices, Citri Reticulatae Pericarpium, Red Lycium Barbarum, and Black Lycium Barbarum) via gas chromatography-ion mobility spectrometry (GC-IMS) combining with multivariate statistical strategies. Comparison analysis was achieved with the properties of visually and intuitively by drawing of topography plots. A total of one hundred and eighty volatiles were distinguished. Aliphatic isomers were identified simultaneously by fingerprint spectra. Alcohols, aldehydes, esters, and ketones were the most abundant volatiles in Huaguo Tea samples. To characterize the Huaguo Tea precisely and establish an analysis model for their classification, multivariate statistical analysis was applied to distinguish different Huaguo Tea. Satisfied discrimination was obtained by principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) based on the HS-GC-IMS results with the robustness parameter (R2Y) of 99.4%, and prediction ability parameter (Q2) of 98.6%, respectively. The results provide a theoretical basis for aroma discrimination, isomer identification, and categories analysis of Huaguo Tea.