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Classification of edible vegetable oils using square wave voltammetry with multivariate data analysis

2008; Elsevier BV; Volume: 77; Issue: 5 Linguagem: Inglês

10.1016/j.talanta.2008.10.003

1873-3573

Francisco Gambarra-Neto, Glimaldo Marino, Mário César Ugulino de Araújo, Roberto Kawakami Harrop Galvão, Márcio José Coelho Pontes, EVELINY DIAS DE MEDEIROS, Ricardo A. C. Lima,

Electrochemical Analysis and Applications

This paper proposes a simple and non-expensive electroanalytical methodology for classification of edible vegetable oils with respect to type (canola, sunflower, corn and soybean) and conservation state (expired and non-expired shelf life). The proposed methodology employs an alcoholic extraction procedure followed by square wave voltammetry (SWV). Two chemometric methods were compared for classification of the resulting voltammograms, namely Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) with variable selection by the Successive Projections Algorithm (SPA). The results were evaluated in terms of errors in a set of samples not included in the modelling process. The best results were obtained with the SPA-LDA method, which correctly classified all samples in terms of type and conservation state.