Use este identificador para citar o ir al link de este elemento: http://hdl.handle.net/1843/52378
Tipo: Artigo de Periódico
Título: Bayesian approach to estimate genetic parameters and selection of sweet potato half-sib progenies
Autor(es): Nermy Ribeiro Valadares
Ana Clara Gonçalves Fernandes
Clóvis Henrique Oliveira Rodrigues
Orlando Gonçalves Brito
Luan Souza de Paula Gomes
Jailson Ramos Magalhães
Rayane Aguiar Alves
Alcinei Místico Azevedo
Resumen: The 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.
Asunto: Batata-doce
Teoria bayesiana de decisão estatística
Plantas - Melhoramento genético
Idioma: eng
País: Brasil
Editor: Universidade Federal de Minas Gerais
Sigla da Institución: UFMG
Departamento: ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
Tipo de acceso: Acesso Restrito
Identificador DOI: https://doi.org/10.1016/j.scienta.2021.110759
URI: http://hdl.handle.net/1843/52378
Fecha del documento: feb-2022
metadata.dc.url.externa: https://www.sciencedirect.com/science/article/pii/S0304423821008669
metadata.dc.relation.ispartof: Scientia Horticulturae
Aparece en las colecciones:Artigo de Periódico

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