Near-infrared spectroscopy combined with chemometrics to classify cosmetic foundations from a crime scene

Cosmetic smears are a form of trace evidence that can link the crime scene, suspects, and victims. Foundation and lipstick are the most common sources of cosmetics that can easily smear, with most current research focused on the evidential analysis of lipsticks. This research aims to create a database of cosmetic foundations on different materials and to access the robustness of using Near-infrared with chemometrics as a non-destructive technique to identify unknown samples collected from a crime scene. Small amounts of six shades of three brands of foundations were smeared on clothing materials, which were then analysed with a combination of Near-infrared with chemometric analysis. Principle component analysis (PCA) was used to reduce data dimensionality and explore potential patterns in sample separation and Linear Discriminant Analysis (LDA) was utilised to assign unknown samples to one of the established classes. The selected techniques proved to be promising for database construction and as a preliminary method of analysis, with 93% of the spectra being correctly classified. Notably, darker foundation shades were less likely to be correctly classified (90% classified correctly) compared to lighter ones (96.7% classified correctly). This could not be improved with Standard Normal Variate (SNV) data pre-treatment or selecting specific NIR regions. This finding is of particular importance; according to the Crime Survey for England and Wales (year ending March 2020) police recorded sexual offences demonstrated that those in Mixed and Black or Black British ethnic groups were significantly more likely to be a victim of sexual assault compared to White, Asian or Other ethnic groups. It is, therefore, crucial to add a wide range of foundation shades, particularly of darker tones, to the future database.