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Autor:
Giorgio S. Senesi, Jader Cabral, Matheus C. S. Ribeiro, Gustavo Nicolodelli, Cícero Cena, Bruno S. Marangoni, Charles Kiefer
Publikováno v:
Applied optics (2004) 59 (2020): 10043–10048. doi:10.1364/AO.409029
info:cnr-pdr/source/autori:Ribeiro, Matheus C. S.; Senesi, Giorgio S.; Cabral, Jader S.; Cena, Cicero; Marangoni, Bruno S.; Kiefer, Charles; Nicolodelli, Gustavo/titolo:Evaluation of rice varieties using LIBS and FTIR techniques associated with PCA and machine learning algorithms/doi:10.1364%2FAO.409029/rivista:Applied optics (2004)/anno:2020/pagina_da:10043/pagina_a:10048/intervallo_pagine:10043–10048/volume:59
info:cnr-pdr/source/autori:Ribeiro, Matheus C. S.; Senesi, Giorgio S.; Cabral, Jader S.; Cena, Cicero; Marangoni, Bruno S.; Kiefer, Charles; Nicolodelli, Gustavo/titolo:Evaluation of rice varieties using LIBS and FTIR techniques associated with PCA and machine learning algorithms/doi:10.1364%2FAO.409029/rivista:Applied optics (2004)/anno:2020/pagina_da:10043/pagina_a:10048/intervallo_pagine:10043–10048/volume:59
Laser-induced breakdown spectroscopy (LIBS) for atomic multi-elementary analyses, and Fourier transform infrared spectroscopy (FTIR) for molecular identification, are often suggested as the most versatile spectroscopic techniques. The present work ai