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Campo DCValorIdioma
dc.creatorLoureiro, Breno Assis-
dc.creatorArriel, Taiana Guimaraes-
dc.creatorRamalho, Fernanda Maria Guedes-
dc.creatorHein, Paulo Ricardo Gherardi-
dc.creatorTrugilho, Paulo Fernando-
dc.date.accessioned2024-01-30T13:58:13Z-
dc.date.available2024-01-30T13:58:13Z-
dc.date.issued2022-10-05-
dc.identifier.citationLOUREIRO, B. A. et al. NIR-based models for estimating selected physical and chemical wood properties from fast-growing plantations. iForest: Biogeosciences and Forestry, [S.l.], v. 15, n. 5, p. 372-380, Oct. 2022. DOI: 10.3832/ifor4030-015.pt_BR
dc.identifier.urihttps://iforest.sisef.org/contents/?id=ifor4030-015pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/58861-
dc.description.abstractAs 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.pt_BR
dc.languageen_USpt_BR
dc.publisherItalian Society of Silviculture and Forest Ecology (SISEF)pt_BR
dc.rightsacesso abertopt_BR
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceiForest-Biogeosciences and Forestrypt_BR
dc.subjectNear infraredpt_BR
dc.subjectWood analysispt_BR
dc.subjectPredictive modelspt_BR
dc.subjectWood powderpt_BR
dc.subjectEucalyptuspt_BR
dc.subjectMultivariate analysispt_BR
dc.titleNIR-based models for estimating selected physical and chemical wood properties from fast-growing plantationspt_BR
dc.typeArtigopt_BR
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