Chemometrics-driven discrimination of flue-cured tobacco aroma types via GC-MS/MS and multivariate analysis
Hongjing Yang, Jiandong Zhang, Chen Liu, Kai Song, Yunzhen Gao, Jinbin Wei, Yanling Liu, Zhipeng Zang, Zhen Wang

TL;DR
This study uses chemometrics and GC-MS/MS to classify flue-cured tobacco aroma types based on 31 identified aroma components.
Contribution
A novel chemometrics model is introduced for accurate classification of flue-cured tobacco aroma types.
Findings
31 aroma components were identified using GC-MS/MS in flue-cured tobacco samples.
Cluster analysis successfully grouped samples into three distinct aroma types.
The discriminant model showed high reliability and accuracy through internal and cross-validation.
Abstract
In this work, a novel classification model for flue-cured tobacco aroma types is presented by integrating chemometric modeling with quantitative aroma component analysis. Three representative types of flue-cured tobacco samples were selected for their distinct flavor profiles and commercial importance. Sensory characteristics were quantified by descriptive analysis of a trained panel. Gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS) was employed to rapidly identify the aroma components. The aroma types of flue-cured tobacco were studied using correlation analysis, hierarchical clustering, principal component analysis (PCA), and discriminant analysis. In total, 31 aroma components of flue-cured tobacco were identified by GC-MS/MS. Each flue-cured tobacco sample was first assigned an aroma style based on geographical origin and subsequently corroborated by the…
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Taxonomy
TopicsFermentation and Sensory Analysis · GABA and Rice Research · Advanced Chemical Sensor Technologies
