Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorRosado, Lucas Rodrigues-
Autor(es): dc.creatorTakarada, Luiz Mendes-
Autor(es): dc.creatorAraújo, Ana Clara Caxito de-
Autor(es): dc.creatorSouza, Kamila Rezende Dázio de-
Autor(es): dc.creatorHein, Paulo Ricardo Gherardi-
Autor(es): dc.creatorRosado, Sebastião Carlos da Silva-
Autor(es): dc.creatorGonçalves, Flávia Maria Avelar-
Data de aceite: dc.date.accessioned2026-02-09T12:35:24Z-
Data de disponibilização: dc.date.available2026-02-09T12:35:24Z-
Data de envio: dc.date.issued2020-04-16-
Data de envio: dc.date.issued2020-04-16-
Data de envio: dc.date.issued2019-03-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/40121-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1164342-
Descrição: dc.descriptionThe non-structural carbon reserves in the various organs of trees are associated with their growth and the mechanism of resilience when exposed to environmental stresses, especially the water deficit. The goal of this study was to develop multivariate models to estimate the amount of non-structural carbohydrates (starch, sucrose, reducing sugars, total sugars and total non-structural carbohydrates) based on near infrared (NIR) spectra measured in solid wood and material reduced to powder. Partial least squares regression was used to associate the amount of non-structural carbohydrates (NSC) obtained by conventional laboratory analysis with NIR spectral signatures. The best predictive models were obtained from the wood reduced to powder. Validity for the NSC prediction in an external set of data presented the following statistics: reducing sugars with R²=0.90 and root mean square error (RMSE) of 2.54% dry matter, total sugars (R²=0.88, RMSE=2.76%), total NSC (R²=0.90, RMSE=2.58%), sucrose (R²=0.82, RMSE=0.06%) and starch (R²=0.80, RMSE=1.03%). The ability of models to estimate the NSC concentration in the growth rings and under divergent environmental conditions demonstrates the potential of the NIR tool to study the physiological responses of plants to different environmental stresses.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherUniversidade Federal de Lavras-
Direitos: dc.rightsacesso aberto-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
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Palavras-chave: dc.subjectCarbohydrate storage-
Palavras-chave: dc.subjectHigh-throughtput phenotyping-
Palavras-chave: dc.subjectResilience-
Palavras-chave: dc.subjectStarch-
Palavras-chave: dc.subjectSugar-
Palavras-chave: dc.subjectArmazenamento de carboidratos-
Palavras-chave: dc.subjectFenotipagem de alto rendimento-
Palavras-chave: dc.subjectAmido-
Palavras-chave: dc.subjectAçúcar-
Palavras-chave: dc.subjectEspectroscopia no infravermelho próximo-
Título: dc.titleNear infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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