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Chemometric Study on the Forensic Discrimination of Soil Types Using Their Infrared Spectral Characteristics
Author(s) -
Mark Baron,
José González-Rodrı́guez,
Ruth Croxton,
Rafael González,
R. Pérez
Publication year - 2011
Publication title -
applied spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.415
H-Index - 110
eISSN - 1943-3530
pISSN - 0003-7028
DOI - 10.1366/10-06197
Subject(s) - linear discriminant analysis , partial least squares regression , transferability , chemometrics , soil test , forensic science , pattern recognition (psychology) , infrared spectroscopy , mathematics , statistics , artificial intelligence , analytical chemistry (journal) , soil science , environmental science , chemistry , environmental chemistry , computer science , soil water , chromatography , veterinary medicine , medicine , logit , organic chemistry
Soil has been utilized in criminal investigations for some time because of its prevalence and transferability. It is usually the physical characteristics that are studied; however, the research carried out here aims to make use of the chemical profile of soil samples. The research we are presenting in this work used sieved (2 mm) soil samples taken from the top soil layer (about 10 cm) that were then analyzed using mid-infrared spectroscopy. The spectra obtained were pretreated and then input into two chemometric classification tools: nonlinear iterative partial least squares followed by linear discriminant analysis (NIPALS-LDA) and partial least squares discriminant analysis (PLS-DA). The models produced show that it is possible to discriminate between soil samples from different land use types and both approaches are comparable in performance. NIPALS-LDA performs much better than PLS-DA in classifying samples to location.

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