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

Lingxia Wang, Siying Li, Xuejun Zhou, Yang Lu, Xiaoqing Wang, Zhenbo Wei

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Lingxia WangZhejiang Institute of Quality Science, 398 Jianshesan Road, Hangzhou 311202, China.

Siying LiDepartment of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.

Xuejun ZhouZhejiang Institute of Quality Science, 398 Jianshesan Road, Hangzhou 311202, China.

Yang LuZhejiang Institute of Quality Science, 398 Jianshesan Road, Hangzhou 311202, China.

Xiaoqing WangZhejiang Institute of Quality Science, 398 Jianshesan Road, Hangzhou 311202, China.

Zhenbo WeiDepartment of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.ORCID 0000-0002-4603-1422

Funding

The work was funded by the National Natural Science Foundation of China 31972200

6 · The paper itself

Abstract

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) (R

Indexed as

Gas Chromatography–Ion Mobility Spectrometryleather authenticationmultivariate statistical analysisspecies discriminationvolatile organic compounds

Identifiers

PMID41600182

DOI10.3390/s26020382

PMCPMC12845869

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