Molecular structural discrimination of chemical compounds in body odor using their GC–MS chromatogram and clustering methods

Sunil Kr Jha, Kenshi Hayashi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In the present study, body odor samples have been collected according to different sampling protocols and characterized using the gas chromatography (GC)–mass spectrometry (MS) technique with the objective to investigate the existence of different volatile organic compounds (VOCs) belonging to several chemical classes in body odor composition. Moreover, the characterization outcomes have been validated by analyzing spectral information using substantial clustering methods. Specifically, the data matrix based on peak height of chemical compounds in each experiment has been analyzed by using six clustering methods, including principal component analysis (PCA), k-means clustering, fuzzy c-means clustering, hierarchical cluster analysis, fuzzy clustering, and k-medoids clustering. Chemical compounds were well clustered into several groups with each of the implemented clustering methods which endorse the experimental characterization outcomes and establishes the existence of VOCs from multiple chemical classes in body odor composition.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalInternational Journal of Mass Spectrometry
Volume423
DOIs
Publication statusPublished - Dec 1 2017

Fingerprint

odors
chemical compounds
Chemical compounds
Odors
discrimination
Volatile Organic Compounds
Fuzzy clustering
volatile organic compounds
Volatile organic compounds
cluster analysis
Cluster analysis
gas chromatography
principal components analysis
Chemical analysis
Gas chromatography
Principal component analysis
Mass spectrometry
mass spectroscopy
sampling
Sampling

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Condensed Matter Physics
  • Spectroscopy
  • Physical and Theoretical Chemistry

Cite this

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abstract = "In the present study, body odor samples have been collected according to different sampling protocols and characterized using the gas chromatography (GC)–mass spectrometry (MS) technique with the objective to investigate the existence of different volatile organic compounds (VOCs) belonging to several chemical classes in body odor composition. Moreover, the characterization outcomes have been validated by analyzing spectral information using substantial clustering methods. Specifically, the data matrix based on peak height of chemical compounds in each experiment has been analyzed by using six clustering methods, including principal component analysis (PCA), k-means clustering, fuzzy c-means clustering, hierarchical cluster analysis, fuzzy clustering, and k-medoids clustering. Chemical compounds were well clustered into several groups with each of the implemented clustering methods which endorse the experimental characterization outcomes and establishes the existence of VOCs from multiple chemical classes in body odor composition.",
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