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Analysis of fingermark constituents: a systematic review of quantitative studies.

Robson, R., Ginige, T. A., Mansour, S., Khan, I. and Assi, S., 2022. Analysis of fingermark constituents: a systematic review of quantitative studies. Chemical Papers, 76, 4645-4667.

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DOI: 10.1007/s11696-022-02232-x

Abstract

Fingermark identification has significance in forensic science, particularly in the processing of crime scene evidence. The majority of literature focused on physical interpretation of fingermarks with limited studies relating to chemical analysis. This systematic review investigated prospective studies dealing with the analysis of latent fingermark constituents. Studies included were those concerned with the analysis of intrinsic organic constituents present in latent fingerprints. Studies with no clear procedure were excluded. Data from the studies were exported into SPSS v22 (IBM, Armonk, NY, USA) where descriptive statistics were applied. The data extraction yielded 19 studies related to identification of lipids (n = 66) and/or amino acids (n =27) in latent fingermarks. The primary lipid identified was squalene and the major amino acids included: alanine, glycine, leucine, lysine, and serine. For identification of the aforementioned constituents both chromatographic and spectroscopic techniques of which the main technique was gas chromatography-mass spectrometry. Prior to analysis, the majority of studies involved collection of fingermarks from both hands at room temperature. Deposition was done on different substrates of which the main were glass, Mylar strips, aluminium sheets or paper. In conclusion, chemical analysis of latent fingermarks enabled identifying key biomarkers of individual that could serve as complementary evidence in crime scene investigation.

Item Type:Article
ISSN:0366-6352
Uncontrolled Keywords:Fingermark analysis; Fingermark components; Fingermark constituents; Fingermarks; Classification; Regression; Extraction techniques
Group:Faculty of Science & Technology
ID Code:36974
Deposited By: Symplectic RT2
Deposited On:23 May 2022 11:12
Last Modified:01 Sep 2022 12:29

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