Abstract

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 (2mm) soil samples taken from the top soil layer (about 10cm) that were then analysed using mid infrared spectroscopy. The spectra obtained were pre-treated 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