DEVELOPING NEAR INFRARED SPECTROSCOPIC MODELS FOR PREDICTING DENSITY OF Eucalyptus WOOD BASED ON INDIRECT MEASUREMENT

Main Article Content

Taiana Guimaraes Arriel http://orcid.org/0000-0002-3801-1878 Fernanda Maria Guedes Ramalho http://orcid.org/0000-0001-5701-4479 Rebeca Alves Barreto Lima http://orcid.org/0000-0001-9657-8349 Kelly Iapuque Rodrigues Souza http://orcid.org/0000-0003-4234-1631 Paulo Ricardo Gheradi Hein http://orcid.org/0000-0002-9152-6803 Paulo Fernando Trugilho http://orcid.org/0000-0002-6230-5462

Abstract

Basic density has been considered a wood quality index because it has a relationship with other properties and affects its industrial application. Several studies have shown that near infrared spectroscopy (NIRS) is able to estimate wood density quickly and reliably. The objective of this study was to develop calibrations for the prediction of basic wood density using the mean values of the trees and spectra measured in wood disks and sawdust as references. The wood basic density of 39 Eucalyptus clones was determined in the laboratory by means of the mean longitudinal positions of 0%, 2%, 10%, 30%, 50% and 75% of the commercial height of the tree by the gravimetric method. NIR spectra were recorded using a spectrometer using optical fiber and integrating sphere directly on the transverse plane of the solid wood in disks collected from diameter et breast height and later in the sawdust. The performance of the NIR based models was evaluated according to the spectral acquisition method and sample preparation. The results showed that the best model for basic density estimation using indirect measurements was developed from the average spectra per clone measured in solid wood disks (R2cv of 0.77 and RMSEcv of 15 kg.m-³).

Article Details

How to Cite
ARRIEL, Taiana Guimaraes et al. DEVELOPING NEAR INFRARED SPECTROSCOPIC MODELS FOR PREDICTING DENSITY OF Eucalyptus WOOD BASED ON INDIRECT MEASUREMENT. CERNE, [S.l.], v. 25, n. 3, p. 294-300, nov. 2019. ISSN 2317-6342. Available at: <http://cerne.ufla.br/site/index.php/CERNE/article/view/2179>. Date accessed: 10 dec. 2019.
Section
Article