Estimation of genetic parameters and selection gains for sweet potato using Bayesian inference with a priori information

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dc.creatorNermy Ribeiro Valadares
dc.creatorAna Clara Gonçalves Fernandes
dc.creatorClovis Henrique Oliveira Rodrigues
dc.creatorLis Lorena Melúcio Guedes
dc.creatorJailson Ramos Magalhães
dc.creatorRayane Aguiar Alves
dc.creatorValter Carvalho de Andrade Júnior
dc.creatorAlcinei Mistico Azevedo
dc.date.accessioned2024-09-16T11:33:03Z
dc.date.accessioned2025-09-09T01:10:24Z
dc.date.available2024-09-16T11:33:03Z
dc.date.issued2023
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.doihttps://doi.org/10.4025/actasciagron.v45i1.56160
dc.identifier.issn1807-8621
dc.identifier.urihttps://hdl.handle.net/1843/76471
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofActa Scientiarum
dc.rightsAcesso Aberto
dc.subjectBatata-doce
dc.subjectMelhoramento genético
dc.subjectTeoria bayesiana de decisão estatistica
dc.subjectBiometria
dc.subjectAgricultura -- Experimentação
dc.subject.otherBatata-doce
dc.subject.otherMelhoramento genético
dc.subject.otherTeoria bayesiana de decisão estatistica
dc.subject.otherBiometria
dc.subject.otherAgricultura -- Experimentação
dc.titleEstimation of genetic parameters and selection gains for sweet potato using Bayesian inference with a priori information
dc.typeArtigo de periódico
local.citation.epage10
local.citation.spage1
local.citation.volume45
local.description.resumoThe selection of superior sweet potato genotypes using Bayesian inference is an important strategy for genetic improvement. Sweet potatoes are of social and economic importance, being the material for ethanol production. The estimation of variance components and genetic parameters using Bayesian inference is more accurate than that using the frequently used statistical methodologies. This is because the former allows for using a priori knowledge from previous research. Therefore, the present study estimated genetic parameters and selection gains, predicted genetic values, and selected sweet potato genotypes using a Bayesian approach with a priori information. Root shape, soil insect resistance, and root and shoot productivity of 24 sweet potato genotypes were measured. Heritability, genotypic variation coefficient, residual variation coefficient, relative variation index, and selection gains direct, indirect and simultaneous were estimated, and the data were analyzed using Bayesian inference. Data from 11 experiments were used to obtain a priori information. Bayesian inference was a useful tool for decision-making, and significant genetic gains could be achieved with the selection of the evaluated genotypes. Root shape, soil insect resistance, commercial root productivity, and total root productivity showed higher heritability values. Clones UFVJM06, UFVJM40, UFVJM54, UFVJM09, and CAMBRAIA can be used as parents in future breeding programs.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttp://www.periodicos.uem.br/ojs/

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