Bayesian approach to estimate genetic parameters and selection of sweet potato half-sib progenies

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dc.creatorNermy Ribeiro Valadares
dc.creatorAna Clara Gonçalves Fernandes
dc.creatorClóvis Henrique Oliveira Rodrigues
dc.creatorOrlando Gonçalves Brito
dc.creatorLuan Souza de Paula Gomes
dc.creatorJailson Ramos Magalhães
dc.creatorRayane Aguiar Alves
dc.creatorAlcinei Místico Azevedo
dc.date.accessioned2023-04-24T12:05:38Z
dc.date.accessioned2025-09-08T23:06:06Z
dc.date.available2023-04-24T12:05:38Z
dc.date.issued2022-02
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/10.1016/j.scienta.2021.110759
dc.identifier.issn0304-4238
dc.identifier.urihttps://hdl.handle.net/1843/52378
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofScientia Horticulturae
dc.rightsAcesso Restrito
dc.subjectBatata-doce
dc.subjectTeoria bayesiana de decisão estatística
dc.subjectPlantas - Melhoramento genético
dc.titleBayesian approach to estimate genetic parameters and selection of sweet potato half-sib progenies
dc.typeArtigo de periódico
local.citation.spage110759
local.citation.volume294
local.description.resumoThe selection of progenies in breeding programs can generate great advances when associated with Bayesian inference because it allows the incorporation of a priori knowledge. Selection at self plant level is advantageous when evaluating half-sib progenies. However, it becomes very difficult for sweet potato cultivation are expected to support the improvement of sweet potato populations. In this context, BLUPIS (best linear unbiased prediction individual simulated) becomes an good alternative technique. Therefore, this study aimed to use the a priori knowledge obtained in previous sweet potato experiments through Bayesian inference to estimate genetic parameters and gains from selection and afterwards to choose the better half-sib progenies considering the BLUPIS. Sixteen progenies were evaluated for root and branch yield, root shape, and resistance to soil insects. The data were analyzed using Bayesian theory, considering data from 12 previous experiments to obtain the informative a priori. All variables tested, as total root yield, commercial root yield, branch green mass yield, average weight of commercial roots, root shape e resistance to soil insects showed high values for coefficient of heritability. Expressive gains are expected to support the improvement of sweet potato populations. This applied methodology, will be allowed breeders to re-design and select the most promising progenies during all breeding process for improve well determined and specific traits in sweet potato.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S0304423821008669

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