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Updated: Jun 30, 2025

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry
Published on: October 2, 2016
A compact Fourier-transform near-infrared spectrophotometer and chemometrics for characterizing a comprehensive set
Jennifer A Cavalcante1, Jamille C Souza2, Jarbas J R Rohwedder1
1Chemistry Institute, State University of Campinas - UNICAMP, Rua Monteiro Lobato, 290, Campinas, SP, 13083-862, Brazil.
Abstract:
A comprehensive data set of ecstasy samples containing MDMA (N-methyl-3,4-methylenedioxyamphetamine) and MDA (3,4-methylenedioxyamphetamine) seized by the Brazilian Federal Police was characterized using spectral data obtained by a compact, low-cost, near-infrared Fourier-transform based spectrophotometer. Qualitative and quantitative characterization was accomplished using soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA) classification, discriminating partial least square (PLS-DA), and regression models based on partial least square (PLS). By applying chemometric analysis, a protocol can be proposed for the in-field screening of seized ecstasy samples. The validation led to an efficiency superior to 96 % for ecstasy classification and estimating total actives, MDMA, and MDA content in the samples with a root mean square error of validation of 4.4, 4.2, and 2.7 % (m/m), respectively. The feasibility and drawbacks of the NIR technology applied to ecstasy characterization and the compromise between false positives and false negatives rate achieved by the classification models are discussed and a new approach to improve the classification robustness was proposed considering the forensic context.
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