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
Abstract
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.
Keywords
Near Infrared, Wood Analysis, Predictive Models, Wood Powder, Eucalyptus, Multivariate Analysis
Authors’ Info
Authors’ address
Taiana Guimaraes Arriel 0000-0002-3801-1878
Fernanda Maria Guedes Ramalho 0000-0001-5701-4479
Paulo Ricardo Gherardi Hein 0000-0002-9152-6803
Paulo Fernando Trugilho 0000-0002-6230-5462
Department of Forest Sciences, Federal University of Lavras, PO Box 3037, 37200-900 Lavras, MG (Brazil)
Corresponding author
Paper Info
Citation
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
Copyright Information
© SISEF - The Italian Society of Silviculture and Forest Ecology 2022
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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