Ryder Alan G
Department of Physics, National University of Ireland, Galway.
J Forensic Sci. 2002 Mar;47(2):275-84.
Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.
采用近红外（785 nm激发）拉曼光谱法对85个由非法麻醉品与几种不同材料稀释而成的固体样品进行了分析。主成分分析（PCA）用于根据麻醉品类型对样品进行分类。通过使用拉曼光谱的一阶导数获得了最佳的样品区分效果。此外，根据纯麻醉品拉曼光谱中最强峰将PCA的光谱变量限制为原始光谱数据的2%或3%，从而得到了一种根据麻醉品类型对样品进行分类的快速判别方法。即使拉曼光谱复杂或非常相似，该方法也能轻松区分可卡因、海洛因和摇头丸混合物。这种限制光谱变量的方法还将计算时间减少了30倍（与全光谱相比），使得该方法对于可疑材料的快速自动分类和识别具有吸引力。
