Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
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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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 |
_version_ |
1815439296411205632 |