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

• Autor(a) principal: Arriel, Taiana Guimaraes
• Data de Publicação: 2019
• Outros Autores: Ramalho, Fernanda Maria Guedes, Lima, Rebeca Alves Barreto, Souza, Kelly Iapuque Rodrigues, Hein, Paulo Ricardo Gheradi, Trugilho, Paulo Fernando
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Cerne (Online)
• Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/2179
• topic: wood quality; multivariate statistic; NIRS; wood science; wood analysis

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).