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

Détails

Ressource 1Télécharger: BIB_1A13FBB48B91.P001.pdf (1016.63 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_1A13FBB48B91
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Lipid composition of fingermark residue and donor classification using GC/MS
Périodique
Forensic Science International
Auteur⸱e⸱s
Girod A., Weyermann C.
ISSN
1872-6283
ISSN-L
0379-0738
Statut éditorial
Publié
Date de publication
05/2014
Peer-reviewed
Oui
Pages
68-82
Langue
anglais
Résumé
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.
Mots-clé
fingerprints, sebaceous compounds, variability, chemometrics, hierarchical cluster analysis
Open Access
Oui
Création de la notice
06/03/2014 12:50
Dernière modification de la notice
20/08/2019 13:51
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