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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/52378
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dc.creatorNermy Ribeiro Valadarespt_BR
dc.creatorAna Clara Gonçalves Fernandespt_BR
dc.creatorClóvis Henrique Oliveira Rodriguespt_BR
dc.creatorOrlando Gonçalves Britopt_BR
dc.creatorLuan Souza de Paula Gomespt_BR
dc.creatorJailson Ramos Magalhãespt_BR
dc.creatorRayane Aguiar Alvespt_BR
dc.creatorAlcinei Místico Azevedopt_BR
dc.date.accessioned2023-04-24T12:05:38Z-
dc.date.available2023-04-24T12:05:38Z-
dc.date.issued2022-02-
dc.citation.volume294pt_BR
dc.citation.spage110759pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.scienta.2021.110759pt_BR
dc.identifier.issn0304-4238pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/52378-
dc.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.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Geraispt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIASpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofScientia Horticulturae-
dc.rightsAcesso Restritopt_BR
dc.subject.otherBatata-docept_BR
dc.subject.otherTeoria bayesiana de decisão estatísticapt_BR
dc.subject.otherPlantas - Melhoramento genéticopt_BR
dc.titleBayesian approach to estimate genetic parameters and selection of sweet potato half-sib progeniespt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S0304423821008669pt_BR
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