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.

Non-destructive forensic identification and quantification of cocaine through sealed packaging using FT-NIR spectroscopy and hyperspectral imaging / Spinelli, Elena; Casamassima, Rosario; Marini, Federico. - In: ANALYTICA CHIMICA ACTA. - ISSN 0003-2670. - 1414:(2026). [10.1016/j.aca.2026.345679]

Non-destructive forensic identification and quantification of cocaine through sealed packaging using FT-NIR spectroscopy and hyperspectral imaging

Spinelli, Elena
Primo
;
Casamassima, Rosario;Marini, Federico
Ultimo
2026

Abstract

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.
2026
Fourier transform near-infrared spectroscopy (FT-NIR); Hyperspectral imaging (HSI); Chemometrics; Non-destructive analysis; Multivariate classification; Partial least squares regression (PLS-R); Illicit drug analysisCocaine
01 Pubblicazione su rivista::01a Articolo in rivista
Non-destructive forensic identification and quantification of cocaine through sealed packaging using FT-NIR spectroscopy and hyperspectral imaging / Spinelli, Elena; Casamassima, Rosario; Marini, Federico. - In: ANALYTICA CHIMICA ACTA. - ISSN 0003-2670. - 1414:(2026). [10.1016/j.aca.2026.345679]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1768710
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