Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.

Detalhes bibliográficos
Autor(a) principal: ABREU, L. F.
Data de Publicação: 2023
Outros Autores: LANA, A. M. Q., CLIMACO, L. C., MATRANGOLO, W. J. R., BARBOSA, E. P., SILVA, K. T. da, ROWNTREE, J. E., SILVA, E. A. da, SIMEONE, M. L. F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108
https://doi.org/10.3390/ agronomy13102525
Resumo: Cratylia argentea is a leguminous shrub that has the potential for use as livestock feed in tropical areas. However, time-consuming and labor-intensive methods of chemical analysis limit the understanding of its nutritive value. Near-infrared spectroscopy (NIRS) is a low-cost technology widely used in forage crops to expedite chemical composition assessment. The objective of this study was to develop prediction models to assess the crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and dry matter (DM) of Cratylia based on NIRS and partial least squares analysis. A total of 155 samples were harvested at different maturity levels and used for model development, of which 107 were used for calibration and 48 for external validation. The cross-validation presented a root mean square error of prediction of 0.77, 2.56, 3.43, and 0.42; a ratio of performance to deviation of 4.8, 4.0, 3.8, and 3.4; and an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we concluded that NIRS accurately predicted the chemical parameters of Cratylia. Therefore, NIRS can serve as a useful tool for livestock producers and researchers to estimate Cratylia?s nutritive value.
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spelling Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.EspectroscopiaLeguminosaAnálise QuímicaForragemComposição QuímicaCratylia argentea is a leguminous shrub that has the potential for use as livestock feed in tropical areas. However, time-consuming and labor-intensive methods of chemical analysis limit the understanding of its nutritive value. Near-infrared spectroscopy (NIRS) is a low-cost technology widely used in forage crops to expedite chemical composition assessment. The objective of this study was to develop prediction models to assess the crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and dry matter (DM) of Cratylia based on NIRS and partial least squares analysis. A total of 155 samples were harvested at different maturity levels and used for model development, of which 107 were used for calibration and 48 for external validation. The cross-validation presented a root mean square error of prediction of 0.77, 2.56, 3.43, and 0.42; a ratio of performance to deviation of 4.8, 4.0, 3.8, and 3.4; and an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we concluded that NIRS accurately predicted the chemical parameters of Cratylia. Therefore, NIRS can serve as a useful tool for livestock producers and researchers to estimate Cratylia?s nutritive value.LUCAS FREIRES ABREU UNIVERSIDADE FEDERAL DE MINAS GERAIS, UNIVERSIDADE FEDERAL DE MINAS GERAIS; ÂNGELA MARIA QUINTÃO LANA, UNIVERSIDADE FEDERAL DE MINAS GERAIS; LEONARDO CAMPOS CLIMACO, EMATER; WALTER JOSE RODRIGUES MATRANGOLO, CNPMS; ELIZABETH PEREIRA BARBOSA, EPAMIG; KARINA TOLEDO DA SILVA, EPAMIG; JASON E. ROWNTREE, MICHIGAN STATE UNIVERSITY; EDILANE APARECIDA DA SILVA, EPAMIG; MARIA LUCIA FERREIRA SIMEONE, CNPMS.ABREU, L. F.LANA, A. M. Q.CLIMACO, L. C.MATRANGOLO, W. J. R.BARBOSA, E. P.SILVA, K. T. daROWNTREE, J. E.SILVA, E. A. daSIMEONE, M. L. F.2023-10-05T16:23:38Z2023-10-05T16:23:38Z2023-10-052023info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleAgronomy, v. 13, 2525, 2023.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108https://doi.org/10.3390/ agronomy13102525enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-10-05T16:23:38Zoai:www.alice.cnptia.embrapa.br:doc/1157108Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542023-10-05T16:23:38falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-10-05T16:23:38Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
title Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
spellingShingle Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
ABREU, L. F.
Espectroscopia
Leguminosa
Análise Química
Forragem
Composição Química
title_short Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
title_full Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
title_fullStr Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
title_full_unstemmed Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
title_sort Near-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
author ABREU, L. F.
author_facet ABREU, L. F.
LANA, A. M. Q.
CLIMACO, L. C.
MATRANGOLO, W. J. R.
BARBOSA, E. P.
SILVA, K. T. da
ROWNTREE, J. E.
SILVA, E. A. da
SIMEONE, M. L. F.
author_role author
author2 LANA, A. M. Q.
CLIMACO, L. C.
MATRANGOLO, W. J. R.
BARBOSA, E. P.
SILVA, K. T. da
ROWNTREE, J. E.
SILVA, E. A. da
SIMEONE, M. L. F.
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv LUCAS FREIRES ABREU UNIVERSIDADE FEDERAL DE MINAS GERAIS, UNIVERSIDADE FEDERAL DE MINAS GERAIS; ÂNGELA MARIA QUINTÃO LANA, UNIVERSIDADE FEDERAL DE MINAS GERAIS; LEONARDO CAMPOS CLIMACO, EMATER; WALTER JOSE RODRIGUES MATRANGOLO, CNPMS; ELIZABETH PEREIRA BARBOSA, EPAMIG; KARINA TOLEDO DA SILVA, EPAMIG; JASON E. ROWNTREE, MICHIGAN STATE UNIVERSITY; EDILANE APARECIDA DA SILVA, EPAMIG; MARIA LUCIA FERREIRA SIMEONE, CNPMS.
dc.contributor.author.fl_str_mv ABREU, L. F.
LANA, A. M. Q.
CLIMACO, L. C.
MATRANGOLO, W. J. R.
BARBOSA, E. P.
SILVA, K. T. da
ROWNTREE, J. E.
SILVA, E. A. da
SIMEONE, M. L. F.
dc.subject.por.fl_str_mv Espectroscopia
Leguminosa
Análise Química
Forragem
Composição Química
topic Espectroscopia
Leguminosa
Análise Química
Forragem
Composição Química
description Cratylia argentea is a leguminous shrub that has the potential for use as livestock feed in tropical areas. However, time-consuming and labor-intensive methods of chemical analysis limit the understanding of its nutritive value. Near-infrared spectroscopy (NIRS) is a low-cost technology widely used in forage crops to expedite chemical composition assessment. The objective of this study was to develop prediction models to assess the crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and dry matter (DM) of Cratylia based on NIRS and partial least squares analysis. A total of 155 samples were harvested at different maturity levels and used for model development, of which 107 were used for calibration and 48 for external validation. The cross-validation presented a root mean square error of prediction of 0.77, 2.56, 3.43, and 0.42; a ratio of performance to deviation of 4.8, 4.0, 3.8, and 3.4; and an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we concluded that NIRS accurately predicted the chemical parameters of Cratylia. Therefore, NIRS can serve as a useful tool for livestock producers and researchers to estimate Cratylia?s nutritive value.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-05T16:23:38Z
2023-10-05T16:23:38Z
2023-10-05
2023
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Agronomy, v. 13, 2525, 2023.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108
https://doi.org/10.3390/ agronomy13102525
identifier_str_mv Agronomy, v. 13, 2525, 2023.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108
https://doi.org/10.3390/ agronomy13102525
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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