Aging of target lipid parameters in fingermark residue using GC/MS: Effects of influence factors and perspectives for dating purposes.

Despite the recurrence of fingermark dating issues and the research conducted on fingermark composition and aging, no dating methodology has yet been developed and validated. In order to further evaluate the possibility of developing dating methodologies based on the fingermark composition, this research proposed an in-depth study of the aging of target lipid parameters found in fingermark residue and exposed to different influence factors. The selected analytical technique was gas chromatography coupled with mass spectrometry (GC/MS). The effects of donor, substrate and enhancement techniques on the selected parameters were firstly evaluated. These factors were called known factors, as their value could be obtained in real caseworks. Using principal component analysis (PCA) and univariate exponential regression, this study highlighted the fact that the effects of these factors were larger than the aging effects, thus preventing the observation of relevant aging patterns. From a fingermark dating perspective, the specific value of these known factors should thus be included in aging models newly built for each case. Then, the effects of deposition moment, pressure, temperature and lighting were also evaluated. These factors were called unknown factors, as their specific value would never be precisely obtained in caseworks. Aging models should thus be particularly robust to their effects and for this reason, different chemometric tools were tested: PCA, univariate exponential regression and partial least square regression (PLSR). While the first two models allowed observing interesting aging patterns regardless of the value of the applied influence factors, PLSR gave poorer results, as large deviations were obtained. Finally, in order to evaluate the potential of such modelling in realistic situations, blind analyses were carried out on eight test fingermarks. The age of five of them was correctly estimated using soft independent modelling of class analogy analysis (SIMCA) based on PCA classes, univariate exponential linear regression and PLSR. Furthermore, a probabilistic approach using the calculation of likelihood ratios (LR) through the construction of a Bayesian network was also tested. While the age of all test fingermarks were correctly evaluated when the storage conditions were known, the results were not significant when these conditions were unknown. Thus, this model clearly highlighted the impact of storage conditions on correct age evaluation. This research showed that reproducible aging modelling could be obtained based on fingermark residue exposed to influence factors, as well as promising age estimations. However, the proposed models are still not applicable in practice. Further studies should be conducted concerning the impact of influence factors (in particular, storage conditions) in order to precisely evaluate in which conditions significant evaluations could be obtained. Furthermore, these models should be properly validated before any application in real caseworks could be envisaged.

Fingermark initial composition and aging using Fourier transform infrared microscopy (µ-FTIR).

This study investigated fingermark residues using Fourier transform infrared microscopy (µ-FTIR) in order to obtain fundamental information about the marks' initial composition and aging kinetics. This knowledge would be an asset for fundamental research on fingermarks, such as for dating purposes. Attenuated total reflection (ATR) and single-point reflection modes were tested on fresh fingermarks. ATR proved to be better suited and this mode was subsequently selected for further aging studies. Eccrine and sebaceous material was found in fresh and aged fingermarks and the spectral regions 1000-1850cm(-1) and 2700-3600cm(-1) were identified as the most informative. The impact of substrates (aluminium and glass slides) and storage conditions (storage in the light and in the dark) on fingermark aging was also studied. Chemometric analyses showed that fingermarks could be grouped according to their age regardless of the substrate when they were stored in an open box kept in an air-conditioned laboratory at around 20°C next to a window. On the contrary, when fingermarks were stored in the dark, only specimens deposited on the same substrate could be grouped by age. Thus, the substrate appeared to influence aging of fingermarks in the dark. Furthermore, PLS regression analyses were conducted in order to study the possibility of modelling fingermark aging for potential fingermark dating applications. The resulting models showed an overall precision of ±3 days and clearly demonstrated their capability to differentiate older fingermarks (20 and 34 days old) from newer ones (1, 3, 7 and 9 days old) regardless of the substrate and lighting conditions. These results are promising from a fingermark dating perspective. Further research is required to fully validate such models and assess their robustness and limitations in uncontrolled casework conditions.

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

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 uncharacterized. Thus, this work 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 pre-treatments 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.

Composition of fingermark residue: a qualitative and quantitative review.

This article describes the composition of fingermark residue as being a complex system with numerous compounds coming from different sources and evolving over time from the initial composition (corresponding to the composition right after deposition) to the aged composition (corresponding to the evolution of the initial composition over time). This complex system will additionally vary due to effects of numerous influence factors grouped in five different classes: the donor characteristics, the deposition conditions, the substrate nature, the environmental conditions and the applied enhancement techniques. The initial and aged compositions as well as the influence factors are thus considered in this article to provide a qualitative and quantitative review of all compounds identified in fingermark residue up to now. The analytical techniques used to obtain these data are also enumerated. This review highlights the fact that despite the numerous analytical processes that have already been proposed and tested to elucidate fingermark composition, advanced knowledge is still missing. Thus, there is a real need to conduct future research on the composition of fingermark residue, focusing particularly on quantitative measurements, aging kinetics and effects of influence factors. The results of future research are particularly important for advances in fingermark enhancement and dating technique developments.