info:eu-repo/semantics/article
Brown rice authenticity evaluation by spark discharge-laser-induced breakdown spectroscopy
Fecha
2019-11Registro en:
Pérez Rodríguez, Michael; Dirchwolf, Pamela Maia; Silva, Tiago Varão; Villafañe, Roxana Noelia; Neto, José Anchieta Gomes; et al.; Brown rice authenticity evaluation by spark discharge-laser-induced breakdown spectroscopy; Elsevier; Food Chemistry; 297; 11-2019; 1-6
0308-8146
CONICET Digital
CONICET
Autor
Pérez Rodríguez, Michael
Dirchwolf, Pamela Maia
Silva, Tiago Varão
Villafañe, Roxana Noelia
Neto, José Anchieta Gomes
Pellerano, Roberto Gerardo
Ferreira, Edilene Cristina
Resumen
Rice is the most consumed food worldwide, therefore its designation of origin (PDO) is very useful. Laserinduced breakdown spectroscopy (LIBS) is an interesting analytical technique for PDO certification, since it provides fast multielemental analysis requiring minimal sample treatment. In this work LIBS spectral data from rice analysis were evaluated for PDO certification of Argentine brown rice. Samples from two PDOs were analyzed by LIBS coupled to spark discharge. The selection of spectral data was accomplished by extreme gradient boosting (XGBoost), an algorithm currently used in machine learning, but rarely applied in chemical issues. Emission lines of C, Ca, Fe, Mg and Na were selected, and the best performance of classification were obtained using k-nearest neighbor (k-NN) algorithm. The developed method provided 84% of accuracy, 100% of sensitivity and 78% of specificity in classification of test samples. Furthermore, it is simple, clean and can be easily applied for rice certification.