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Artículo

Brown rice authenticity evaluation by spark discharge-laser-induced breakdown spectroscopy

Pérez Rodríguez, MichaelIcon ; Dirchwolf, Pamela MaiaIcon ; Silva, Tiago Varão; Villafañe, Roxana NoeliaIcon ; Neto, José Anchieta Gomes; Pellerano, Roberto GerardoIcon ; Ferreira, Edilene Cristina
Fecha de publicación: 11/2019
Editorial: Elsevier
Revista: Food Chemistry
ISSN: 0308-8146
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Química Analítica

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.
Palabras clave: BROWN RICE , FOOD AUTHENTICITY , PATTERN RECOGNITION , PDO , SD-LIBS
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info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/110600
DOI: https://doi.org/10.1016/j.foodchem.2019.124960
URL: https://www.sciencedirect.com/science/article/abs/pii/S0308814619310623
Colecciones
Articulos(IQUIBA-NEA)
Articulos de INSTITUTO DE QUIMICA BASICA Y APLICADA DEL NORDESTE ARGENTINO
Citación
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
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