Analysis of seized cocaine samples by using chemometric methods and FTIR spectroscopy

Abstract

O objetivo deste trabalho foi desenvolver uma metodologia quimiométrica para descrever o perfil químico de amostras de cocaína apreendidas no estado de Minas Gerais (Brasil). A identificação de adulterantes e a quantificação do teor de cocaína foram feitas por cromatografia gasosa acoplada à espectrometria de massa (GC-MS). Espectros de 91 amostras foram obtidos por espectroscopia no infravermelho usando refletância total atenuada (ATR-FTIR), e utilizados na construção de um modelo de análise de componentes principais (PCA). A primeira componente principal (PC1) discriminou as amostras de maior pureza das mais diluídas/adulteradas, nas quais foram identificadas lidocaína, cafeína e benzocaína. PC2 discriminou a forma química da cocaína, cloridrato ou base. Além disso, dois modelos supervisionados discriminantes (mínimos quadrados parciais para análise discriminante, PLS-DA) foram desenvolvidos para classificar as amostras em função de sua diluição (abaixo e acima de 15% m/m) e de sua forma química, apresentando taxas de acerto que variaram entre 83 e 97%. Os modelos de classificação constituem uma ferramenta simples, rápida e não destrutiva, de grande valor para peritos forenses e investigadores criminais.The aim of this article was to develop a chemometric methodology for determining the chemical profile of cocaine samples seized in Minas Gerais State, Brazil. The adulterant detection and the cocaine determination were performed by gas chromatography-mass spectrometry (GC-MS). Spectra of 91 samples were obtained by attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) and used to build an exploratory principal component analysis (PCA) model. The first principal component (PC1) discriminated samples of more purity from the more diluted/adulterated ones, which were characterized by the presence of lidocaine, caffeine and benzocaine. PC2 discriminated the two chemical forms of cocaine, hydrochloride and base. In addition, two supervised discriminant partial least-squares models (partial least-squares discriminant analysis, PLS-DA) were developed for classifying the samples according to dilution (above and below 15% m/m) and chemical form, with a rate of success that varied between 83 and 97%. The classification models constitute a simple, rapid and non-destructive tool, of great value for both forensic experts and criminal investigators. Keywords: illicit drugs, MID infrared, principal component analysis, cocaine, chemometrics IntroductionCocaine is an alkaloid extracted from plants of the genera Erythroxylum (E. novagranatense and E. coca). United Nations Office on Drugs and Crime (UNODC) considers cocaine, after heroin, the second most problematic drug worldwide in terms of negative health consequences and probably the most problematic drug in terms of trafficking-related violence. Estimates suggest that 440 t of pure cocaine were consumed in the world in 2009, which would be in line with a total production estimate of 1,111 t, wholesale purity-adjusted seizures Analysis of Seized Cocain...

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