title: Near infrared reflectance spectrometry classification of cigarettes using the successive projections algorithm for variable selection.
abstract: This paper proposes a methodology for cigarette classification employing Near Infrared Reflectance spectrometry and variable selection. For this purpose, the Successive Projections Algorithm (SPA) is employed to choose an appropriate subset of wavenumbers for a Linear Discriminant Analysis (LDA) model. The proposed methodology is applied to a set of 210 cigarettes of four different brands. For comparison, Soft Independent Modelling of Class Analogy (SIMCA) is also employed for full-spectrum classification. The resulting SPA-LDA model successfully classified all test samples with respect to their brands using only two wavenumbers (5058 and 4903 cm(-1)). In contrast, the SIMCA models were not able to achieve 100% of classification accuracy, regardless of the significance level adopted for the F-test. The results obtained in this investigation suggest that the proposed methodology is a promising alternative for assessment of cigarette authenticity.
authors.affiliation: Universidade Federal da Paraíba, Departamento de Química, João Pessoa, PB, Brazil.
authors.forename: Edilene Dantas Teles
authors.initials: ED
authors.lastname: Moreira
authors.forename: Márcio José Coelho
authors.initials: MJ
authors.lastname: Pontes
authors.forename: Roberto Kawakami Harrop
authors.initials: RK
authors.lastname: Galvão
authors.forename: Mário César Ugulino
authors.initials: MC
authors.lastname: Araújo
mesh_terms: D000465:Algorithms; D016002:Discriminant Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014026:Nicotiana / Q000145:classification*