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

Página do item simplificado
dc.creatorLucas Freires Abreu
dc.creatorÂngela Maria Quintão Lana
dc.creatorLeonardo Campos Climaco
dc.creatorWalter José Rodrigues Matrangolo
dc.creatorElizabeth Pereira Barbosa
dc.creatorKarina Toledo da Silva
dc.creatorJason Rowntree
dc.creatorEdilane Aparecida da Silva
dc.creatorMaria Lucia Ferreira Simeone
dc.date.accessioned2025-01-23T23:48:32Z
dc.date.accessioned2025-09-09T00:49:58Z
dc.date.available2025-01-23T23:48:32Z
dc.date.issued2023-09-29
dc.format.mimetypepdf
dc.identifier.doihttps://doi.org/10.3390/agronomy13102525
dc.identifier.issn2073-4395
dc.identifier.urihttps://hdl.handle.net/1843/79456
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofAgronomy
dc.rightsAcesso Aberto
dc.subjectZootecnia
dc.subjectLeguminosas
dc.subjectNutrição animal
dc.subject.otherNIRS
dc.subject.otherWet chemistry
dc.subject.otherForage analysis
dc.subject.otherShrub legume
dc.titleNear-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea
dc.typeArtigo de periódico
local.citation.epage12
local.citation.issue10
local.citation.spage1
local.citation.volume13
local.description.resumoCratylia 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.
local.identifier.orcidhttps://orcid.org/0000-0001-6988-5183
local.identifier.orcidhttps://orcid.org/0000-0003-0066-6198
local.identifier.orcidhttps://orcid.org/0009-0006-1603-0062
local.identifier.orcidhttps://orcid.org/0000-0001-6171-5470
local.identifier.orcidhttps://orcid.org/0000-0001-7212-6794
local.identifier.orcidhttps://orcid.org/0000-0002-9350-3824
local.identifier.orcidhttps://orcid.org/0000-0002-2003-0341
local.publisher.countryBrasil
local.publisher.departmentVET - DEPARTAMENTO DE ZOOTECNIA
local.publisher.initialsUFMG
local.url.externahttps://www.mdpi.com/2073-4395/13/10/2525

Arquivos

Pacote original

Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea.pdf
Tamanho:
1.38 MB
Formato:
Adobe Portable Document Format
Baixar

Licença do pacote

Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
License.txt
Tamanho:
1.99 KB
Formato:
Plain Text
Descrição:
Baixar

Coleções

Artigo de Periódico

Logo UFMG