Lipid composition of fingermark residue and donor classification using GC/MS

Details

Ressource 1Download: BIB_1A13FBB48B91.P001.pdf (1016.63 [Ko])
State: Public
Version: Final published version
Serval ID
serval:BIB_1A13FBB48B91
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Lipid composition of fingermark residue and donor classification using GC/MS
Journal
Forensic Science International
Author(s)
Girod A., Weyermann C.
ISSN
1872-6283
ISSN-L
0379-0738
Publication state
Published
Issued date
05/2014
Peer-reviewed
Oui
Pages
68-82
Language
english
Abstract
Lipids available in fingermark residue represent important targets for enhancement and dating techniques. While it is well known that lipid composition varies among fingermarks of the same donor (intra-variability) and between fingermarks of different donors (inter-variability), the extent of this variability remains uncharacterised. Thus, this worked aimed at studying qualitatively and quantitatively the initial lipid composition of fingermark residue of 25 different donors. Among the 104 detected lipids, 43 were reported for the first time in the literature. Furthermore, palmitic acid, squalene, cholesterol, myristyl myristate and myristyl myristoleate were quantified and their correlation within fingermark residue was highlighted. Ten compounds were then selected and further studied as potential targets for dating or enhancement techniques. It was shown that their relative standard deviation was significantly lower for the intra-variability than for the inter-variability. Moreover, the use of data pretreatments could significantly reduce this variability. Based on these observations, an objective donor classification model was proposed. Hierarchical cluster analysis was conducted on the pre-treated data and the fingermarks of the 25 donors were classified into two main groups, corresponding to "poor" and "rich" lipid donors. The robustness of this classification was tested using fingermark replicates of selected donors. 86% of these replicates were correctly classified, showing the potential of such a donor classification model for research purposes in order to select representative donors based on compounds of interest.
Keywords
fingerprints, sebaceous compounds, variability, chemometrics, hierarchical cluster analysis
Open Access
Yes
Create date
06/03/2014 11:50
Last modification date
20/08/2019 12:51
Usage data