Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1179313
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dc.contributor.authorPEREIRA, G. Z.
dc.contributor.authorPEREIRA, G. de M.
dc.contributor.authorGOMES, R. da C.
dc.contributor.authorFEIJO, G. L. D.
dc.contributor.authorSURITA, L. M. A.
dc.contributor.authorPEREIRA, M. W. F.
dc.contributor.authorMENEZES, G. R. de O.
dc.contributor.authorCARA, J. R. F.
dc.contributor.authorÍTAVO, L. C. V.
dc.contributor.authorSILVA, C. da L. e
dc.contributor.authorAMIN, M.
dc.contributor.authorGOMES, M. de N. B.
dc.date.accessioned2025-10-02T13:48:27Z-
dc.date.available2025-10-02T13:48:27Z-
dc.date.created2025-10-02
dc.date.issued2025
dc.identifier.citationPLoS ONE, v. 20, n. 1, e0317434, 2025.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1179313-
dc.descriptionABSTRACT - This work aimed to evaluate the use of Visible and Near-infrared Spectroscopy (Vis-NIRS) as a tool in the classification of bovine carcasses. A total of 133 animals (77 females, 29 males surgically castrated and 27 males immunologically castrated) were used. Vis-NIRS spectra were collected in a chilling room 24 h postmortem directly on the hanging carcasses over the longissimus thoracis between the surface of the 5th and 6th ribs. The data were evaluated by principal component analysis (PCA) and the partial least squares regression (PLSR) method. For the prediction of sex, the best model was the Standard Normal Variate (SNV) because it presented a relatively high coefficient of determination for prediction, presenting a percentage of correctness of 75.51% and an error of 24.49%. Regarding age, none of the models were able to differentiate the samples through Vis-NIRS. The findings confirm that Vis-NIRS prediction models are a valuable tool for differentiating carcasses based on sex. To further enhance the precision of these predictions, we recommend using Vis-NIRS equipment with the full infrared wavelength range to collect and predict sex and age in intact beef samples.
dc.language.isoeng
dc.rightsopenAccess
dc.titleVis-NIRS as an auxiliary tool in the classification of bovine carcasses.
dc.typeArtigo de periódico
dc.subject.thesagroCarcaça
dc.subject.thesagroCastração
dc.subject.thesagroRaio Infravermelho
dc.subject.nalthesaurusAnalytical methods
dc.subject.nalthesaurusBeef carcasses
dc.subject.nalthesaurusChemical composition
dc.subject.nalthesaurusNear-infrared spectroscopy
riaa.ainfo.id1179313
riaa.ainfo.lastupdate2025-10-02
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0317434
dc.contributor.institutionGABRIELA ZARDO PEREIRA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; GABRIEL DE MORAIS PEREIRA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; RODRIGO DA COSTA GOMES, CNPGC; GELSON LUIS DIAS FEIJO, CNPGC; LUCY MERY ANTONIA SURITA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; MARÍLIA WILLIANI FILGUEIRA PEREIRA, UNIVERSIDADE FEDERAL RURAL DO SEMI-ÁRIDO; GILBERTO ROMEIRO DE OLIVEIRA MENEZES, CNPGC; JAQUELINE RODRIGUES FERREIRA CARA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; LUIS CARLOS VINHAS ÍTAVO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; SAULO DA LUZ E SILVA, UNIVERSIDADE DE SÃO PAULO; MELISSA AMIN, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; MARINA DE NADAI BONIN GOMES, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL.
Appears in Collections:Artigo em periódico indexado (CNPGC)

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