Citation: WANG Li-Xue,  TIAN Shi-Si,  SONG Xi-Lin,  LI Wen-Jie,  LI Hui-Min,  ZHAO Ya-Bin. Analysis of Fatty Acid Components in Fingerprint Residues by Gas Chromatography-Mass Spectrometry[J]. Chinese Journal of Analytical Chemistry, ;2022, 50(10): 1542-1550. doi: 10.19756/j.issn.0253-3820.221246 shu

Analysis of Fatty Acid Components in Fingerprint Residues by Gas Chromatography-Mass Spectrometry

  • Corresponding author: ZHAO Ya-Bin, zhaoyb04@gmail.com
  • Received Date: 17 May 2022
    Revised Date: 15 July 2022

    Fund Project: Supported by the Science and Technology Foundation of Ministry of Public Security of China (No.2021JSM01) and the Basic Research Project of People's Public Security University of China (No.2021JKF219).

  • As an important trace evidence, fingerprints are widely used in personal identification and disclosure of criminal acts at the crime scene. Traditional fingerprint studies mainly focus on morphological analysis, while the in-depth exploration of its chemical constituents has always been neglected. In comparison, the chemical analysis of fingerprint substances can better improve the sensitivity and scientificity of fingerprint inspection technique. In this work, by taking the fatty acid in the fingerprint substance as the target, a new method was explored to measure the fatty acid by gas chromatography-mass spectrometry and applied to the analysis of real fingerprint samples. Experiment results showed that when the concentration of hydrochloric acid/methanol solution was 5% (V/V), the derivative temperature was 50℃, the derivative time was 20 min, and the derivative reagent amount was 400 μL, the fatty acid components in fingerprint residues could be detected more accurately. On this basis, the method was applied to the detection of lipid composition in real fingerprint samples, which identified the standard detection process for fingerprint samples and proved a quite obvious individual difference in lipid composition in fingerprint residues. The lipid composition of four fingerprints left by 2 volunteers on the same day was analyzed and the main components with 99.7% of the cumulative variance contribution rate by employing the principal component analysis method was retained, which demonstrated a strong correlation between the lipid composition of these fingerprints, further proving the stability and reproducibility of the fingerprint lipid composition detection method. This work might lay a research foundation for further exploration of employing fingerprint substances to identify individuals.
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