Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species

Detalhes bibliográficos
Autor(a) principal: Nascimento,Cristiano Souza do
Data de Publicação: 2022
Outros Autores: Araújo,Roberto Daniel de, Silva,Claudia Eugênio da, Nascimento,Claudete Catanhede do, Menezes,Valdiek da Silva, Santos,Joaquim dos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência e Agrotecnologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542022000100210
Resumo: ABSTRACT Near infrared spectroscopy (NIR) is a tool capable of providing efficient results for organic molecules of different materials. We developed a predictive model using Fourier Transform NIR Spectroscopy to distinguish the types of tannins in different forest species in the Amazon. Samples were obtained from different regions of the State of Amazonas/Brazil, and tests for tannins were performed, including obtaining NIRS spectra. The assembly of spectral data matrices versus analytes of interest was crossed with the results of traditional analyses. In addition, a calibration and validation set was constructed for condensed tannins, hydrolyzable tannins, and samples with no tannins. Finally, the performance of classification models was evaluated for sensitivity, identification index, and errors. The condensed tannin classes were detected in 63% of the species studied, followed by 34% of the species not containing tannin. The discriminant analysis produced groupings of classes, with a hit sensitivity index >90%. The developed model can be applied in studies of ecology, forestry and chemotaxonomy, with a focus on phenolic compounds such as tannins. The proposed methodology has advantages over the reference methods, reflected as a lower need for sample preparation, shorter analysis time, no use of reagents, and, consequently, no generation of waste.
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spelling Near infrared spectroscopy as a tool to discriminate tannins from Amazonian speciesCondensed tanninsAmazon woodsNIRSdiscriminant analysisnon-destructive methodology.ABSTRACT Near infrared spectroscopy (NIR) is a tool capable of providing efficient results for organic molecules of different materials. We developed a predictive model using Fourier Transform NIR Spectroscopy to distinguish the types of tannins in different forest species in the Amazon. Samples were obtained from different regions of the State of Amazonas/Brazil, and tests for tannins were performed, including obtaining NIRS spectra. The assembly of spectral data matrices versus analytes of interest was crossed with the results of traditional analyses. In addition, a calibration and validation set was constructed for condensed tannins, hydrolyzable tannins, and samples with no tannins. Finally, the performance of classification models was evaluated for sensitivity, identification index, and errors. The condensed tannin classes were detected in 63% of the species studied, followed by 34% of the species not containing tannin. The discriminant analysis produced groupings of classes, with a hit sensitivity index >90%. The developed model can be applied in studies of ecology, forestry and chemotaxonomy, with a focus on phenolic compounds such as tannins. The proposed methodology has advantages over the reference methods, reflected as a lower need for sample preparation, shorter analysis time, no use of reagents, and, consequently, no generation of waste.Editora da UFLA2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542022000100210Ciência e Agrotecnologia v.46 2022reponame:Ciência e Agrotecnologia (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLA10.1590/1413-7054202246001422info:eu-repo/semantics/openAccessNascimento,Cristiano Souza doAraújo,Roberto Daniel deSilva,Claudia Eugênio daNascimento,Claudete Catanhede doMenezes,Valdiek da SilvaSantos,Joaquim doseng2022-07-04T00:00:00Zoai:scielo:S1413-70542022000100210Revistahttp://www.scielo.br/cagroPUBhttps://old.scielo.br/oai/scielo-oai.php||renpaiva@dbi.ufla.br|| editora@editora.ufla.br1981-18291413-7054opendoar:2022-11-22T16:31:48.072439Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
title Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
spellingShingle Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
Nascimento,Cristiano Souza do
Condensed tannins
Amazon woods
NIRS
discriminant analysis
non-destructive methodology.
title_short Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
title_full Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
title_fullStr Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
title_full_unstemmed Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
title_sort Near infrared spectroscopy as a tool to discriminate tannins from Amazonian species
author Nascimento,Cristiano Souza do
author_facet Nascimento,Cristiano Souza do
Araújo,Roberto Daniel de
Silva,Claudia Eugênio da
Nascimento,Claudete Catanhede do
Menezes,Valdiek da Silva
Santos,Joaquim dos
author_role author
author2 Araújo,Roberto Daniel de
Silva,Claudia Eugênio da
Nascimento,Claudete Catanhede do
Menezes,Valdiek da Silva
Santos,Joaquim dos
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Nascimento,Cristiano Souza do
Araújo,Roberto Daniel de
Silva,Claudia Eugênio da
Nascimento,Claudete Catanhede do
Menezes,Valdiek da Silva
Santos,Joaquim dos
dc.subject.por.fl_str_mv Condensed tannins
Amazon woods
NIRS
discriminant analysis
non-destructive methodology.
topic Condensed tannins
Amazon woods
NIRS
discriminant analysis
non-destructive methodology.
description ABSTRACT Near infrared spectroscopy (NIR) is a tool capable of providing efficient results for organic molecules of different materials. We developed a predictive model using Fourier Transform NIR Spectroscopy to distinguish the types of tannins in different forest species in the Amazon. Samples were obtained from different regions of the State of Amazonas/Brazil, and tests for tannins were performed, including obtaining NIRS spectra. The assembly of spectral data matrices versus analytes of interest was crossed with the results of traditional analyses. In addition, a calibration and validation set was constructed for condensed tannins, hydrolyzable tannins, and samples with no tannins. Finally, the performance of classification models was evaluated for sensitivity, identification index, and errors. The condensed tannin classes were detected in 63% of the species studied, followed by 34% of the species not containing tannin. The discriminant analysis produced groupings of classes, with a hit sensitivity index >90%. The developed model can be applied in studies of ecology, forestry and chemotaxonomy, with a focus on phenolic compounds such as tannins. The proposed methodology has advantages over the reference methods, reflected as a lower need for sample preparation, shorter analysis time, no use of reagents, and, consequently, no generation of waste.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542022000100210
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1413-7054202246001422
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv Ciência e Agrotecnologia v.46 2022
reponame:Ciência e Agrotecnologia (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
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reponame_str Ciência e Agrotecnologia (Online)
collection Ciência e Agrotecnologia (Online)
repository.name.fl_str_mv Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)
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