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

Detalhes bibliográficos
Autor(a) principal: Rosado, Lucas Rodrigues
Data de Publicação: 2019
Outros Autores: Takarada, Luiz Mendes, Araújo, Ana Clara Caxito de, Souza, Kamila Rezende Dázio de, Hein, Paulo Ricardo Gherardi, Rosado, Sebastião Carlos da Silva, Gonçalves, Flávia Maria Avelar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/40121
Resumo: The 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.
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spelling Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in woodCarbohydrate storageHigh-throughtput phenotypingResilienceStarchSugarArmazenamento de carboidratosFenotipagem de alto rendimentoAmidoAçúcarEspectroscopia no infravermelho próximoThe 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.Universidade Federal de Lavras2020-04-16T17:11:11Z2020-04-16T17:11:11Z2019-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfROSADO, L. R. et al. Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood. Cerne, Lavras, v. 25, n. 1, p. 84-92, mar. 2019.http://repositorio.ufla.br/jspui/handle/1/40121Cernereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessRosado, Lucas RodriguesTakarada, Luiz MendesAraújo, Ana Clara Caxito deSouza, Kamila Rezende Dázio deHein, Paulo Ricardo GherardiRosado, Sebastião Carlos da SilvaGonçalves, Flávia Maria Avelareng2020-04-16T17:11:54Zoai:localhost:1/40121Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-04-16T17:11:54Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
title Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
spellingShingle Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
Rosado, Lucas Rodrigues
Carbohydrate storage
High-throughtput phenotyping
Resilience
Starch
Sugar
Armazenamento de carboidratos
Fenotipagem de alto rendimento
Amido
Açúcar
Espectroscopia no infravermelho próximo
title_short Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
title_full Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
title_fullStr Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
title_full_unstemmed Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
title_sort Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
author Rosado, Lucas Rodrigues
author_facet Rosado, Lucas Rodrigues
Takarada, Luiz Mendes
Araújo, Ana Clara Caxito de
Souza, Kamila Rezende Dázio de
Hein, Paulo Ricardo Gherardi
Rosado, Sebastião Carlos da Silva
Gonçalves, Flávia Maria Avelar
author_role author
author2 Takarada, Luiz Mendes
Araújo, Ana Clara Caxito de
Souza, Kamila Rezende Dázio de
Hein, Paulo Ricardo Gherardi
Rosado, Sebastião Carlos da Silva
Gonçalves, Flávia Maria Avelar
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Rosado, Lucas Rodrigues
Takarada, Luiz Mendes
Araújo, Ana Clara Caxito de
Souza, Kamila Rezende Dázio de
Hein, Paulo Ricardo Gherardi
Rosado, Sebastião Carlos da Silva
Gonçalves, Flávia Maria Avelar
dc.subject.por.fl_str_mv Carbohydrate storage
High-throughtput phenotyping
Resilience
Starch
Sugar
Armazenamento de carboidratos
Fenotipagem de alto rendimento
Amido
Açúcar
Espectroscopia no infravermelho próximo
topic Carbohydrate storage
High-throughtput phenotyping
Resilience
Starch
Sugar
Armazenamento de carboidratos
Fenotipagem de alto rendimento
Amido
Açúcar
Espectroscopia no infravermelho próximo
description The 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.
publishDate 2019
dc.date.none.fl_str_mv 2019-03
2020-04-16T17:11:11Z
2020-04-16T17:11:11Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv ROSADO, L. R. et al. Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood. Cerne, Lavras, v. 25, n. 1, p. 84-92, mar. 2019.
http://repositorio.ufla.br/jspui/handle/1/40121
identifier_str_mv ROSADO, L. R. et al. Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood. Cerne, Lavras, v. 25, n. 1, p. 84-92, mar. 2019.
url http://repositorio.ufla.br/jspui/handle/1/40121
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv Cerne
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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