Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods

• Published in: Journal of AOAC International Vol. 100; no. 2; pp. 345 - 350
• Main Authors: Jiménez-Carvelo, Ana M, González-Casado, Antonio, Pérez-Castaño, Estefanía, Cuadros-Rodríguez, Luis
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.03.2017
• Subjects: Algorithms; Chemical properties; Chromatography, High Pressure Liquid - methods; High performance liquid chromatography; Identification and classification; Methods; Models, Chemical; Multivariate Analysis; Olive oil; Olive Oil - analysis; Plant Oils - analysis; Plant Oils - classification; Principal Component Analysis
• ISSN: 1060-3271; 1944-7922
• DOI: 10.5740/jaoacint.16-0411

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.