Using Machine Learning to classify low-growing forage plants of Megathyrsus maximus (Syn. Panicum maximum).

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dc.contributorNÉSTOR EDUARDO VILLAMIZAR FRONTADO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL
dc.contributorGELSON DOS SANTOS DIFANTE, UNIVERSIDADE DE MATO GROSSO DO SUL
dc.contributorALEXANDRE ROMEIRO DE ARAUJO, CNPGC
dc.contributorDENISE BAPTAGLIN MONTAGNER, CNPGC
dc.contributorHITALO RODRIGUES DA SILVA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL
dc.contributorLARISSA PEREIRA RIBEIRO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL.
dc.creatorFRONTADO, N. E. V.
dc.creatorDIFANTE, G. dos S.
dc.creatorARAUJO, A. R. de
dc.creatorMONTAGNER, D. B.
dc.creatorSILVA, H. R. da
dc.creatorTEODORO, L. P. R.
dc.date2025-10-09T19:57:17Z
dc.date2025-10-09T19:57:17Z
dc.date2025-10-09
dc.date2024
dc.date.accessioned2026-07-07T03:43:11Z
dc.descriptionForage plants of the species Megathyrsus maximus (Syn. Panicum maximum) are an important alternative for the more than 160 million hectares devoted to meat production on pasture. Train and validate machine learning algorithms to identify the most accurate model in classifying cultivars and genotypes of this species. The objective was to evaluate the performance of two classification models low-growing M. maximus forages using dry mass production data and pasture structural and morphogenic variables as inputs.
dc.identifierIn: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 58., 2024, Cuiabá. Zootecnia para segurança alimentar e sustentabilidade climática: anais. Brasília, DF: SBZ; Cuiabá: Universidade Federal de Mato Grosso, 2024.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1179561
dc.identifier.urihttp://hdl.handle.net/123456789/441575
dc.languageeng
dc.rightsopenAccess
dc.subjectGenótipo
dc.subjectPanicum Maximum
dc.subjectForage
dc.subjectGenotype
dc.subjectMegathyrsus maximus
dc.subjectMorphogenesis
dc.subjectPastures
dc.titleUsing Machine Learning to classify low-growing forage plants of Megathyrsus maximus (Syn. Panicum maximum).
dc.typeResumo em anais e proceedings

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