Data/hora: 11/06/2024 05:21:27

Biblioteca(s): 	Embrapa Café.	
Tipo da produção científica: 	Artigo em Periódico Indexado	
Circulação/Nível: 	A - 1	
Data corrente: 	27/01/2021	
Data da última atualização: 	27/01/2021	
Autoria: 	ALVES, R. S.; RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e; ROCHA, J. R. A. S. C.; NUNES, A. C. P.; CARNEIRO, A. P. S.; SANTOS, G. A. dos.	
Afiliação: 	RODRIGO SILVA ALVES, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; CAMILA FERREIRA AZEVEDO, UFV; FABYANO FONSECA E SILVA, UFV; JOÃO ROMERO DO AMARAL SANTOS DE CARVALHO ROCHA, UFV; ANDREI CAÍQUE PIRES NUNES, UFV; ANTÔNIO POLICARPO SOUZA CARNEIRO, UFV; GLEISON AUGUSTO DOS SANTOS, UFV.	
Título: 	Optimization of Eucalyptus breeding through random regression models allowing for reaction norms in response to environmental gradients.	
Ano de publicação: 	2020	
Fonte/Imprenta: 	Tree Genetics & Genomes, v. 16, n. 2, p. 1-8, 2020.	
DOI: 	https://doi.org/10.1007/s11295-020-01431-5	
Idioma: 	Inglês	
Conteúdo: 	Reaction norms fitted through random regression models are a powerful tool to identify and quantify the genotype × environment (G × E) interaction and they represent a promising alternative in forest tree breeding for analysis of multi-environment trials. Thus, the objective of this study was to compare random regression models with the compound symmetry model in Eucalyptus breeding for analysis of multi-environment trials. To this end, a data set with 215 Eucalyptus clones of different species and hybrids evaluated in four environments for diameter at breast height and Pilodyn penetration was used. The random regression models provided a better fit for both traits. Results showed that there was genotypic variability among Eucalyptus clones and that the reaction norms over the environmental gradients identified the G × E interaction. The compound symmetry model and the random regression models are highly correlated in terms of genotype ranking for both traits. The main advantage of random regression models over the compound symmetry model is the ability to predict genotypic performance in environments where a genotype has not been evaluated. Thus, our results suggest that reaction norms fitted through random regression models can be successfully used in forest tree breeding for analysis of multi-environment trials.	
Thesagro: 	Árvore Florestal; Interação Genética; Seleção Genótipa.	
Thesaurus Nal: 	Forest trees; Genotype-environment interaction; Plant selection guides.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Café (CNPCa)	
Exemplares: 	CNPCa - (1482-1) - UPC - AP - DD -  -  -  - DIS