Thomas, J, Rowlands, S, Al-Jumeily OBE, D, Ginige, T and Assi, S (2025) Identification of Cosmetics Using Near-Infrared Spectroscopy. In: 2024 17th International Conference on Development in eSystem Engineering (DeSE) . pp. 305-309. (2024 17th International Conference on Development in eSystem Engineering (DeSE), 6th - 8th Nov 2024, Khorfakkan, United Arab Emirates).

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Abstract

Non-destructive identification of cosmetics is essential to confirm their identity and purity. Near-infrared (NIR) spectroscopy provides a fast and non-destructive method for cosmetic identification. For this study, 99 raw materials and 30 products were measured using a palm sized NIR spectrometer. Spectral pre-treatment and analysis involved techniques such as multiplicative scatter correction-first derivative (MSC-D1), correlation in wavelength space (CWS), and Principal Component Analysis (PCA) respectively. Among the raw materials, 66 exhibited strong NIR activity, 25 showed medium NIR activity, and eight had weak NIR activity, while all 30 samples were found to be NIR active. The CWS method revealed a high frequency of Type II errors, with 81 out of 99 raw materials mismatching. All 30 of the products also resulted in mismatches. PCA proved to be the more accurate of the data analysis techniques with creams 97% of variance was accounted for in PC1, and PC scores demonstrating strong differentiation among seven of the eight cream products. In contrast, the perfume products displayed 84% variance in PC1 and 13% in PC2, with two of the seven products showing significant discrimination from the others. This study confirmed that NIR spectroscopy is well-suited for this application as it provides a quick analysis time, no sample preparation and allows for sample preservation.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects:	Q Science > Q Science (General)
Divisions:	Computer Science and Mathematics Pharmacy and Biomolecular Sciences
Publisher:	IEEE
SWORD Depositor:	A Symplectic
Date Deposited:	13 Mar 2025 13:43
Last Modified:	13 Mar 2025 13:43
DOI or ID number:	10.1109/dese63988.2024.10911935
URI:	https://researchonline.ljmu.ac.uk/id/eprint/25867

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