Volatile Profiling and Variety Discrimination of Leather Using GC-IMS Coupled with Chemometric Analysis

Volatile fingerprint analysis using Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) was applied to differentiate cowhide (22 samples), sheepskin (6 samples), and pigskin (6 samples). A total of 126 signal peaks were detected from the whole GC-IMS dataset, with 96 volatile compounds identified. Principal Component Analysis (PCA) revealed distinct clustering: cowhide exhibited unique volatile profiles, separating itself clearly from sheepskin and pigskin, which showed significant similarity. This was confirmed by Hierarchical clustering, K-means clustering (optimal k = 2), and Partial Least Squares Discriminant Analysis (PLS-DA) (R² = 0.9836, Q² = 0.9040). Cowhide was characterized by exclusive compounds (2-Hexanone, alpha-Thujene, Butyl acetate, 3-Methyl-2-butanol, 2-Heptanone, Hexyl methyl ether-monomer, Diethyl disulfide). Sheepskin and pigskin shared exclusive compounds (2-Methyl propanol, Isobutyl acetate, 2-Pentyl acetate, 3-Penten-2-one, 2,5-Dimethylfuran). Orthogonal PLS-DA (OPLS-DA) further differentiated sheepskin (Ethyl isobutanoate-dimer, Pentyl acetate-dimer, 3-Methyl-2-butanol, 2-Pentanone, 2-Methylbutanol-dimer, 3-Methyl-1-butanol, 2,5-Dimethylfuran, Propan-2-ol, Ethanol-dimer, and alpha-Thujene) and pigskin (Butan-2-one, Pentanal-dimer, 1-Pentanal-monomer, Ethyl vinyl ether, Z-2-Heptene, and Butyronitrile), identifying alpha-Thujene, 3-Methyl-2-butanol, and 2,5-Dimethylfuran as universal discriminatory markers. GC-IMS coupled with chemometric analysis provides a robust approach for leather authentication.