DISCRIMINATION BETWEEN SIMILAR WOODS BY MOLECULAR FLUORESCENCE AND PARTIAL LEAST SQUARES
Author(s) -
Elian Meneses Oliveira,
Jez Willian Batista Braga,
Alexandre Florian da Costa
Publication year - 2015
Publication title -
química nova
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.214
H-Index - 73
eISSN - 1678-7064
pISSN - 0100-4042
DOI - 10.5935/0100-4042.20150127
Subject(s) - partial least squares regression , fluorescence , least squares function approximation , mathematics , statistics , chemistry , physics , optics , estimator
Wood is an extremely complex biological material, which can show macroscopic similarities that make it difficult to discriminate between species. Discrimination between similar wood species can be achieved by either anatomic or instrumental methods, such as near infrared spectroscopy (NIR). Although different spectroscopy methods are currently available, few studies have applied them to discriminate between wood species. In this study, we applied a partial least squares-discriminant analysis (PLS-DA) model to evaluate the viability of using direct fluorescence measurements for discriminating between Eucalyptus grandis, Eucalyptus urograndis, and Cedrela odorata. The results show that molecular fluorescence is an efficient technique for discriminating between these visually similar wood species. With respect to calibration and the validation samples, we observed no misclassifications or outliers
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