INQUISAL   20936
INSTITUTO DE QUIMICA DE SAN LUIS "DR. ROBERTO ANTONIO OLSINA"
Unidad Ejecutora - UE
artículos
Título:
Classification of organic olives based on chemometric analysis of elemental data
Autor/es:
FURLONG, OCTAVIO J.; HIDALGO, MELISA J.; MARCHEVSKY, EDUARDO J.; HIDALGO, MELISA J.; MARCHEVSKY, EDUARDO J.; POZZI, MARÍA T.; PELLERANO, ROBERTO G.; POZZI, MARÍA T.; PELLERANO, ROBERTO G.; FURLONG, OCTAVIO J.
Revista:
MICROCHEMICAL JOURNAL
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Año: 2018 vol. 142 p. 30 - 35
ISSN:
0026-265X
Resumen:
The aim of this study was to discriminate organic from conventional olive samples based on the levels of macro and trace elements, combined with chemometric techniques. Ten elements (Na, K, Ca, Fe, Mg, Cu, Zn, Se, S and P) were determined in organic (n = 30) and conventional (n = 30) olive samples by inductively coupled plasma optical emission spectrometry analysis (ICP-OES). The classification of samples was performed by using a well-known chemometric techniques, linear discriminant analysis (LDA), partial least square-discriminant analysis (PLS-DA), support vector machine-discriminant analysis (SVM-DA), k-nearest neighbors (k-NN) and random forest (RF). The k-NN technique showed the best performance in discriminating organic from conventional samples (Accuracy: 94%) using all chemical variables. After variable reduction, an accuracy of 83% was found by using only the elements K and P. The use of a fingerprint based on multielemental levels associated with classification chemometric techniques may be used as a simple method to authenticate organic olive samples.