Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108
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dc.contributor.authorABREU, L. F.
dc.contributor.authorLANA, A. M. Q.
dc.contributor.authorCLIMACO, L. C.
dc.contributor.authorMATRANGOLO, W. J. R.
dc.contributor.authorBARBOSA, E. P.
dc.contributor.authorSILVA, K. T. da
dc.contributor.authorROWNTREE, J. E.
dc.contributor.authorSILVA, E. A. da
dc.contributor.authorSIMEONE, M. L. F.
dc.date.accessioned2023-10-05T16:23:38Z-
dc.date.available2023-10-05T16:23:38Z-
dc.date.created2023-10-05
dc.date.issued2023
dc.identifier.citationAgronomy, v. 13, 2525, 2023.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1157108-
dc.descriptionCratylia 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.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectEspectroscopia
dc.titleNear-infrared spectroscopy and chemometrics methods to predict the chemical composition of Cratylia argentea.
dc.typeArtigo de periódico
dc.subject.thesagroLeguminosa
dc.subject.thesagroAnálise Química
dc.subject.thesagroForragem
dc.subject.thesagroComposição Química
riaa.ainfo.id1157108
riaa.ainfo.lastupdate2023-10-05
dc.identifier.doihttps://doi.org/10.3390/ agronomy13102525
dc.contributor.institutionLUCAS 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.
Aparece nas coleções:Artigo em periódico indexado (CNPMS)

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