Direct Classification of Seized Heroin Samples with FT-ATR Spectroscopy and Multivariate Discriminant Analysis

Chemical profiles play a very critical role in the clustering\classification of heroin confiscated samples. Classification of heroin helps in the accurate and reliable tactical and strategic investigation on the transit route, geographic origins, and manufacturing process, which are important for forensic and judicial purposes[1,2]. To the customary classification of drugs, a non-destructive, fast, direct, simple, cheap, safe, and free sample preparation steps like attenuated total reflection fourier transform infrared spectroscopy (ATR-FTIR) is proposed. Hence, ATR-FTIR spectra of 69 seized heroin samples were used to build a PLS-DA model. Calibration heroin samples consist of samples from four different seized heroin classes. Each class has its own specific adulterants[3]. One vs. all classification approach was used in this contribution. Additionally, PLS-DA resulted in appropriate modeling of each classes while miss classification rate is acceptable for each of classes. Optimizing PLS-DA model parameters including latent variable resulted in a predictive model not only from internal validation but also from external validation perspective[4,5]. This strategy showed significant potential for exploring adulterants features involved in heroin samples. Finally, this contribution may contribute to paving the way for future studies aiming at identifying heroin networks. These data types are useful as the basis for providing the courts with information concerning the possible links between samples in cases where the charges include supplying and to provide intelligence information to assist in the elucidation of drug-dealing networks. Chemical profiling using ATR-FTIR spectroscopy and chemometrics analyses proved to be an innovative strategy to distinguish adulterants according to treatment.