A probabilistic approach towards source level inquiries for forensic soil examination based on mineral counts

Details

Serval ID
serval:BIB_25FA5D080364
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A probabilistic approach towards source level inquiries for forensic soil examination based on mineral counts
Journal
Forensic Science International
Author(s)
Lim Yu Chen, Marolf André, Estoppey Nicolas, Massonnet Geneviève
ISSN
0379-0738
Publication state
Published
Issued date
11/2021
Volume
328
Pages
111035
Language
english
Abstract
Forensic soil examination has a well-established foundation in forensic science, this is in part due to the widely varied and complex nature of soil. Within this domain, mineral suite studies are a commonly utilized tool in soil examination. However, statistical or probabilistic approaches towards the interpretation of results from such analysis are lacking and this study aims to fill that gap. Soil samples from four different locations in the city of Lausanne, Switzerland were sampled and their mineral fractions, light and heavy of size between 90 and 180 µm, were studied utilizing microscopical methods. First, the light minerals were identified and counted by employing scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Second, the heavy minerals were identified and counted manually under a polarized light microscope (PLM). The resulting count data were subjected to various multivariate statistical treatments such as principal components analysis (PCA), hierarchical clustering analysis (HCA), and linear discriminant analysis (LDA). These methods assist in identifying pertinent variables and subsequently in building various classification models. The validities of these models were then tested and evaluated using blind tests. Finally, these methods demonstrate how a probabilistic approach can be taken in the interpretation of the results to answer source level questions.
Keywords
Forensic geology, Bayesian approach, Heavy mineral fraction, Light mineral fraction, Polarized light microscopy, Scanning electron microscopy, Multivariate statistics, Inter-variability, Intra-variability, Blind tests
Pubmed
Open Access
Yes
Create date
18/10/2021 10:43
Last modification date
19/10/2021 6:39
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