Fast spark discharge-laser-induced breakdown spectroscopy method for rice botanic origin determination

PÉREZ-RODRÍGUEZ, MICHAEL; DIRCHWOLF, PAMELA MAIA; SILVA, TIAGO VARÃO; VIEIRA, ALAN LIMA; NETO, JOSÉ ANCHIETA GOMES; PELLERANO, ROBERTO GERARDO; FERREIRA, EDILENE CRISTINA

FOOD CHEMISTRY

ELSEVIER SCI LTD

Año: 2020 vol. 331 p. 127051 - 127051

0308-8146

A simple, fast, and efficient spark discharge-laser-induced breakdown spectroscopy (SD-LIBS) method was developed for determining rice botanic origin using predictive modeling based on support vector machine (SVM). Seventy-two samples from four rice varieties (Guri, Irga 424, Puitá, and Taim) were analyzed by SD-LIBS. Spectral lines of C, Ca, Fe, Mg, N and Na were selected as input variables for prediction model fitting. The SVM algorithm parameters were optimized using a central composite design (CCD) to find the better classification performance. The optimum model for discriminating rice samples according to their botanical variety was obtained using C=5.25 and γ=0.119. This model achieved 96.4% of correct predictions in test samples and showed sensitivities and specificities per class within the range of 92?100%. The developed method is robust and eco-friendly for rice botanic identification since its prediction results are consistent and reproducible and its application does not generate chemical waste.