iForest - Biogeosciences and Forestry


NIR-based models for estimating selected physical and chemical wood properties from fast-growing plantations

Breno Assis Loureiro, Taiana Guimaraes Arriel   , Fernanda Maria Guedes Ramalho, Paulo Ricardo Gherardi Hein, Paulo Fernando Trugilho

iForest - Biogeosciences and Forestry, Volume 15, Issue 5, Pages 372-380 (2022)
doi: https://doi.org/10.3832/ifor4030-015
Published: Oct 05, 2022 - Copyright © 2022 SISEF

Research Articles

As a faster, reliable, and low cost technique, applicable to large samplings, near infrared (NIR) spectroscopy technology has been widely applied for high-throughput phenotyping in forest breeding programmes. The aim of this study was to develop multivariate models for estimating the chemical and physical properties of juvenile wood based on NIR signatures of milled wood. Moreover, two approaches, namely, external validation by clone and by age, were tested to validate the model for estimating extractive content. NIR spectra of wood specimens taken from three clones of Eucalyptus urophylla (one to six years old) grown in southern Brazil were used to calibrate and validate models for predicting the wood basic density, total extractives, ash content, holocellulose content, syringyl to guaiacyl ratio (S/G) and elementary components of the wood. PLS-R models were validated by an independent set of wood specimens and presented promising statistics for the estimating wood density (R2p = 0.768), extractives (R2p = 0.912), ash (R2p = 0.936) and carbon (R2p = 0.697) contents from NIR signatures measured in the milled wood of young trees. Furthermore, NIR models for estimating the extractive content of wood were validated using the clones or ages left out of the training sets. Most models presented satisfactory statistics (R2 > 90%) and could be applied to routine laboratory analyses or to select potential trees in Eucalyptus breeding programmes.


Near Infrared, Wood Analysis, Predictive Models, Wood Powder, Eucalyptus, Multivariate Analysis

Corresponding author

Taiana Guimaraes Arriel


Assis Loureiro B, Arriel TG, Guedes Ramalho FM, Hein PRG, Trugilho PF (2022). NIR-based models for estimating selected physical and chemical wood properties from fast-growing plantations. iForest 15: 372-380. - doi: 10.3832/ifor4030-015

Academic Editor

Manuela Romagnoli

Paper history

Received: Dec 01, 2021
Accepted: Jul 21, 2022

First online: Oct 05, 2022
Publication Date: Oct 31, 2022
Publication Time: 2.53 months

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