INQUISAL   20936
INSTITUTO DE QUIMICA DE SAN LUIS "DR. ROBERTO ANTONIO OLSINA"
Unidad Ejecutora - UE
artículos
Título:
Non-essential element concentrations in brown grain rice: Assessment by advanced data mining techniques
Autor/es:
PELLERANO, ROBERTO GERARDO; PICCOLI, ANALÍA; HIDALGO, MELISA JAZMÍN; MARCHEVSKY, EDUARDO JORGE; PELLERANO, ROBERTO GERARDO; MARCHEVSKY, EDUARDO JORGE; VILLAFAÑE, ROXANA NOELIA; HIDALGO, MELISA JAZMÍN; VILLAFAÑE, ROXANA NOELIA; PICCOLI, ANALÍA
Revista:
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Editorial:
SPRINGER HEIDELBERG
Referencias:
Año: 2017 vol. 25 p. 21362 - 21367
ISSN:
0944-1344
Resumen:
The concentrations of 17non-essential elements (Al, As, Ba, Be, Cd, Ce, Cr, Hg, La, Li, Pb, Sb, Sn, Sr,Th, Ti and Tl) were determined in brown grain rice samples of two varieties:Fortuna and Largo Fino. The samples were collected from four main producingregions of Corrientes province (Argentina). Quantitative determinations wereperformed by inductively coupled plasma mass spectrometry (ICP-MS), using avalidated method. The contents of As, Be, Cd, Ce, Cr, Hg, Pb, Sb, Sn, Th and Tlwere very low or not detected in most samples. The non-essential element levelsdetected were in line with studies conducted in rice from different parts ofthe world. In order to characterize the influence of geographical origin in thesamples, the following classification methods were carried out: lineardiscriminant analysis (LDA), k-nearest neighbors (k-NN), partial least squaresdiscriminant analysis (PLS-DA), support vector machine (SVM) and random forests(RF). The best performance was obtained by using RF (96%) and SVM (96%). The resultshere reported showed the variation in the non-essential element profiles in ricegrain depending on the geographical origin.