Academic Journal
Non-destructive forensic identification and quantification of cocaine through sealed packaging using FT-NIR spectroscopy and hyperspectral imaging.
| Τίτλος: | Non-destructive forensic identification and quantification of cocaine through sealed packaging using FT-NIR spectroscopy and hyperspectral imaging. |
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| Συγγραφείς: | Spinelli E; Dept. of Chemistry, University of Rome 'La Sapienza', Rome, 00185, Italy., Casamassima R; Dept. of Chemistry, University of Rome 'La Sapienza', Rome, 00185, Italy; Raggruppamento Carabinieri Investigazioni Scientifiche, Rome, 00191, Italy., Marini F; Dept. of Chemistry, University of Rome 'La Sapienza', Rome, 00185, Italy. Electronic address: federico.marini@uniroma1.it. |
| Πηγή: | Analytica chimica acta [Anal Chim Acta] 2026 Sep 08; Vol. 1414, pp. 345679. Date of Electronic Publication: 2026 May 19. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0370534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4324 (Electronic) Linking ISSN: 00032670 NLM ISO Abbreviation: Anal Chim Acta Subsets: MEDLINE |
| Imprint Name(s): | Publication: Amsterdam : Elsevier Original Publication: Amsterdam. |
| Ιατρικοί όροι (MeSH): | Cocaine*/analysis , Illicit Drugs*/analysis , Hyperspectral Imaging* , Forensic Sciences* , Product Packaging*, Spectroscopy, Near-Infrared ; Spectroscopy, Fourier Transform Infrared ; Least-Squares Analysis ; Principal Component Analysis ; Drug Contamination |
| Περίληψη: | The forensic analysis of illicit drugs requires analytical methods that are rapid, reliable, and compliant with legal constraints concerning sample integrity. In this study, Fourier Transform Near-Infrared (FT-NIR) spectroscopy and hyperspectral imaging (HSI) were evaluated as non-destructive tools for the identification, classification, and quantification of cocaine and its most common cutting agents, directly through sealed polyethylene packaging. Real samples of cocaine seized in four independent operations, together with six typical adulterants (creatine, caffeine, levamisole, lidocaine, lactose, and mannitol), were analyzed without opening the evidence, ensuring operator safety and full compliance with Article 360 of the Italian Code of Criminal Procedure. FT-NIR spectroscopy combined with chemometric techniques enabled a clear differentiation between cocaine and adulterants through exploratory Principal Component Analysis (PCA) and supervised Soft Independent Modeling of Class Analogy (SIMCA), achieving 100% sensitivity and specificity in cocaine identification. Partial Least Squares (PLS) regression further allowed accurate prediction of cocaine content in seized samples (R2 = 0.95, RMSEP = 2.40%). NIR hyperspectral imaging provided additional advantages by integrating spatial and spectral information, enabling pixel-level classification and visualization of chemical distribution within the samples. Pixel-based SIMCA models applied to NIR-HSI data showed excellent classification performance, selectively identifying cocaine and adulterants while rejecting background and packaging materials without the need for prior masking. Beyond analytical performance, the proposed approach is designed to support green, non-destructive, and operationally safe forensic workflows, enabling rapid screening while minimizing sample handling and operator exposure. Overall, the results demonstrate that FT-NIR spectroscopy and NIR hyperspectral imaging represent powerful, rapid, and legally robust alternatives to conventional destructive techniques for forensic drug analysis, with significant advantages in terms of safety, repeatability, and preservation of evidentiary integrity. (Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Chemometrics; Cocaine; Fourier transform near-infrared spectroscopy (FT-NIR); Hyperspectral imaging (HSI); Illicit drug analysis; Multivariate classification; Non-destructive analysis; Partial least squares regression (PLS-R) |
| Substance Nomenclature: | I5Y540LHVR (Cocaine) 0 (Illicit Drugs) |
| Entry Date(s): | Date Created: 20260604 Date Completed: 20260610 Latest Revision: 20260707 |
| Update Code: | 20260707 |
| DOI: | 10.1016/j.aca.2026.345679 |
| PMID: | 42242816 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1873-4324 |
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| DOI: | 10.1016/j.aca.2026.345679 |