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.

Discrimination and quantification of cocaine and adulterants in seized drug samples by infrared spectroscopy and PLSR

“…Recent studies using this technique for the analysis of cocaine have been presented [10][11][12]. The combination of vibrational spectroscopy and chemometric methods has been considered a promising and simple alternative to extract information directly from the sample.…”

Automated Fast Screening Method for Cocaine Identification in Seized Drug Samples Using a Portable Fourier Transform Infrared (FT-IR) Instrument

“…1,12 Small shifts in peak position and intensity have been observed for the two cocaine forms when the infrared ATR spectra are compared with the transmission mode spectra. 5,17 In ATR spectra, the strong characteristic wavenumber values for the standard cocaine salt sample are 1728, 1712, 1265, 1230, 1105, 1071, 1026, and 729 cm À1 . For standard cocaine base, the peaks are at 1734, 1707, 1273, 1227, 1107, 1068, 1035, and 712 cm À1 (Table 1).…”

“…5 Principal component analysis (PCA) and PLS-DA were utilized for the classification of seized samples based on the purity, chemical form, and the cocaine content. Even though the PLS-DA classification showed rates of true positive between 95 and 97% in separating cocaine with different chemical form and content, the training set samples had only four adulterants and hence limited the models use for unknown samples that contain other adulterants.…”

Assessing the effect of data pretreatment procedures for principal components analysis of chromatographic data

“…Global optimized alignment algorithms are the most dynamic and robust methods of alignment as they maximize a local, as well as a global, measure of similarity [23, 30-A c c e p t e d M a n u s c r i p t 9 32]. In this work, a correlation optimized warping (COW) algorithm was investigated, which optimizes the Pearson product-moment correlation (PPMC) coefficient between a sample and target chromatogram [30].…”

“…[1] Since publication of this report, there has been increasing interest in applying multivariate statistical procedures to forensically relevant chromatographic and spectral data. For example, principal components analysis (PCA), cluster analysis, and discriminant analysis have been applied in the analysis of fire debris [2][3][4][5], explosives [6], controlled substances [7][8][9], and various trace evidence types including hair [10], soil [11], electrical tape [12], and paint [13][14][15]. Forensic research in this area has conclusively demonstrated the potential of these procedures for case work.…”