| This thesis presents a technique for the classification and profiling of illicit heroin samples using GC-MS and chemometric, pattern recognition methods based on principal component analysis. Random heroin samples were collected and analyzed at the Detroit Police Forensic Services Chemistry Unit over a nine-month period. Mass spectral detection supported with gas chromatographic retention indices allowed for the detection of selected opium alkaloids, impurities, diluents, and adulterants commonly found in illicit heroin samples while principal component analysis allowed for data reduction and classification of illicit heroin samples. |
