Forensic Discrimination of Lipstick Stains Using Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy and Pattern Recognition Techniques
Mohd Afiq Mohd Azis(1), Naji Arafat Mahat(2*), Hasmerya Maarof(3), Sarah Aina Azman(4)
(1) Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia
(2) Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia; Investigative and Forensic Sciences Research Group, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia; Center for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial Research, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia; Center of Research for Fiqh Forensics and Judiciary, Universiti Sains Islam Malaysia, Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia
(3) Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia; Investigative and Forensic Sciences Research Group, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia
(4) Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia
(*) Corresponding Author
Abstract
Lipstick stains discovered on objects (such as drinking cups) may be utilized as evidence and/or lead in forensic investigations by chemical analysis. Hence, this study analyzed two brands of lipstick stains' organic composition on paper cups over 0, 24, and 48 h of exposure using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), coupled with pattern recognition techniques of principal component analysis (PCA) and linear discriminant analysis (LDA). Spectral analysis revealed several functional group differences between the two brands of lipstick, viz. Wardah (W) and Silkygirl (S) stains, particularly in the fingerprint region of 1800–650 cm−1. Application of PCA (variance of ≥ 70%) and LDA successfully provided the suitable means for categorically classifying (a) the different brands of lipstick, (b) the male and female volunteers, as well as (c) the different periods of exposure. The fact that the cross-validation correct classification rates for all the LDA models exceeded 90.0%, their suitability for forensic provenance application of lip stains appears statistically supported. Hence, such an approach to combine the non-destructive ATR-FTIR analysis with PCA and LDA is not only easy and cost-effective but also forensically relevant for enabling the data mining process for forensic intelligence.
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DOI: https://doi.org/10.22146/ijc.97097
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