Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139213
Title: Environmental stratification and genotype recommendation toward the soybean ideotype: a Bayesian approach.
Authors: EVANGELISTA, J. S. P. C.
PEIXOTO, M. A.
COELHO, I. F.
ALVES, R. S.
SILVA, F. F. e
RESENDE, M. D. V. de
SILVA, F. L. da
BHERING, L. L.
Affiliation: JENIFFER SANTANA PINTO COELHO EVANGELISTA, UFV; MARCO ANTÔNIO PEIXOTO, UFV; IGOR FERREIRA COELHO, UFV; RODRIGO SILVA ALVES, UFV; FABYANO FONSECA E SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; FELIPE LOPES DA SILVA, UFV; LEONARDO LOPES BHERING, UFV.
Date Issued: 2021
Citation: Crop Breeding and Applied Biotechnology, v. 21, n. 1, e359721111, 2021.
Description: The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding.
Thesagro: Genótipo
Soja
Glycine Soja
NAL Thesaurus: Seed stratification
Genotype
Soybeans
Bayesian theory
DOI: https://doi.org/10.1590/1984-70332021v21n1a11
Type of Material: Artigo de periódico
Access: openAccess
Appears in Collections:Artigo em periódico indexado (SAPC)

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