Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles

Bibliographic Details
Main Author: Alves, Ana
Publication Date: 2020
Other Authors: Hevia, Andrea, Simões, Rita, Majada, Juan, Alia, Ricardo, Rodrigues, José
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.5/20344
Summary: Wood density is one of the most important physical properties of the wood, used in improvement programs for wood quality of major timber species. Traditional core sampling of standing trees has been widely used to assess wood density profiles at high spatial resolution by X-ray microdensitometry methods, but alternative methods to predict wood properties quality are also needed. Near-infrared (NIR) spectroscopy, a non-destructive technique, is being increasingly used for wood property assessment and has already been demonstrated to be able to predict wood density. However, the estimation of wood density profiles by NIR has not yet been extensively studied, and improved models using spectra information (NIR) and X-ray data need to be developed. To this end, partial least square regression (PLS-R) models for predicting wood density were developed at a 1.4 mm spatial resolution on Pinus pinaster wood cores, with an improved spatial synchronization along the tangential and radial directions of the strip, between X-ray data and NIR spectra. The validation of the best model showed a high coefficient of determination (0.95), low error (0.026) and no outlier. Compression wood samples were not detected as outliers and were correctly predicted by the model. However, pith spectra were detected as outliers and its predicted values were overestimated by 33% due to unusual spectra suggesting a diverse chemical composition. The results suggest that NIR-PLS models obtained can be used for screening maritime pine wood density profiles along the radii at 1.4 mm spatial resolution
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spelling Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profileswood densityx-raynear-infrared spectraWood density is one of the most important physical properties of the wood, used in improvement programs for wood quality of major timber species. Traditional core sampling of standing trees has been widely used to assess wood density profiles at high spatial resolution by X-ray microdensitometry methods, but alternative methods to predict wood properties quality are also needed. Near-infrared (NIR) spectroscopy, a non-destructive technique, is being increasingly used for wood property assessment and has already been demonstrated to be able to predict wood density. However, the estimation of wood density profiles by NIR has not yet been extensively studied, and improved models using spectra information (NIR) and X-ray data need to be developed. To this end, partial least square regression (PLS-R) models for predicting wood density were developed at a 1.4 mm spatial resolution on Pinus pinaster wood cores, with an improved spatial synchronization along the tangential and radial directions of the strip, between X-ray data and NIR spectra. The validation of the best model showed a high coefficient of determination (0.95), low error (0.026) and no outlier. Compression wood samples were not detected as outliers and were correctly predicted by the model. However, pith spectra were detected as outliers and its predicted values were overestimated by 33% due to unusual spectra suggesting a diverse chemical composition. The results suggest that NIR-PLS models obtained can be used for screening maritime pine wood density profiles along the radii at 1.4 mm spatial resolutionSpringerRepositório da Universidade de LisboaAlves, AnaHevia, AndreaSimões, RitaMajada, JuanAlia, RicardoRodrigues, José2020-09-17T14:25:53Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/20344engWood Science and Technology (2020) 54:1151–1164https://doi.org/10.1007/s00226-020-01207-zinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T15:58:39Zoai:repositorio.ulisboa.pt:10400.5/20344Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:59:11.501260Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
title Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
spellingShingle Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
Alves, Ana
wood density
x-ray
near-infrared spectra
title_short Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
title_full Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
title_fullStr Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
title_full_unstemmed Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
title_sort Improving spatial synchronization between X-ray and near-infrared spectra information to predict wood density profiles
author Alves, Ana
author_facet Alves, Ana
Hevia, Andrea
Simões, Rita
Majada, Juan
Alia, Ricardo
Rodrigues, José
author_role author
author2 Hevia, Andrea
Simões, Rita
Majada, Juan
Alia, Ricardo
Rodrigues, José
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Alves, Ana
Hevia, Andrea
Simões, Rita
Majada, Juan
Alia, Ricardo
Rodrigues, José
dc.subject.por.fl_str_mv wood density
x-ray
near-infrared spectra
topic wood density
x-ray
near-infrared spectra
description Wood density is one of the most important physical properties of the wood, used in improvement programs for wood quality of major timber species. Traditional core sampling of standing trees has been widely used to assess wood density profiles at high spatial resolution by X-ray microdensitometry methods, but alternative methods to predict wood properties quality are also needed. Near-infrared (NIR) spectroscopy, a non-destructive technique, is being increasingly used for wood property assessment and has already been demonstrated to be able to predict wood density. However, the estimation of wood density profiles by NIR has not yet been extensively studied, and improved models using spectra information (NIR) and X-ray data need to be developed. To this end, partial least square regression (PLS-R) models for predicting wood density were developed at a 1.4 mm spatial resolution on Pinus pinaster wood cores, with an improved spatial synchronization along the tangential and radial directions of the strip, between X-ray data and NIR spectra. The validation of the best model showed a high coefficient of determination (0.95), low error (0.026) and no outlier. Compression wood samples were not detected as outliers and were correctly predicted by the model. However, pith spectra were detected as outliers and its predicted values were overestimated by 33% due to unusual spectra suggesting a diverse chemical composition. The results suggest that NIR-PLS models obtained can be used for screening maritime pine wood density profiles along the radii at 1.4 mm spatial resolution
publishDate 2020
dc.date.none.fl_str_mv 2020-09-17T14:25:53Z
2020
2020-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/20344
url http://hdl.handle.net/10400.5/20344
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Wood Science and Technology (2020) 54:1151–1164
https://doi.org/10.1007/s00226-020-01207-z
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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