Data/hora: 08/06/2024 05:25:41

Biblioteca(s): 	Embrapa Algodão.	
Data corrente: 	12/02/2022	
Data da última atualização: 	24/02/2022	
Autoria: 	PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; ALVES, R. S.; FARIAS, F. J. C.; CARVALHO, L. P.; TEODORO, L. P. R.; TEODORO, P. E.; BHERING, L. L.	
Afiliação: 	MARCO ANTÔNIO PEIXITO, UNIVERSIDADE FEDERAL DE VIÇOSA; JENIFFER SANTANA PINTO COELHO EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA; RODRIGO SILVA ALVES, UNIVERSIDADE FEDERAL DE VIÇOSA; FRANCISCO JOSÉ CORREA FARIAS, CNPA; LUIZ PAULO DE CARVALHO, CNPA; LARISSA PEREIRA RIBEIRO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO; PAULO EDUARDO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO; LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA.	
Título: 	Models for optimizing selection based on adaptability and stability of cotton genotypes.	
Ano de publicação: 	2021	
Fonte/Imprenta: 	Ciência Rural, v. 51, n. 5, e20200530, p. 1-8, 2021.	
Páginas: 	8 p.	
ISSN: 	1678-4596	
DOI: 	10.1590/0103-8478cr20200530	
Idioma: 	Inglês	
Conteúdo: 	In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait.	
Palavras-Chave: 	Bayesian Information Criterion; BIC; Ensaios multi ambientes; Estabilidade; HMRPGV; Média Harmônica do Desempenho Relativo dos Valores Genéticos; Multi environment trials.	
Thesagro: 	Algodão; Fibra Vegetal; Gossypium Hirsutum; Produtividade.	
Thesaurus Nal: 	Cotton.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/231250/1/MODELS-FOR-OPTIMIZING-SELECTION-BASED-ON-ADAPTABILITY.pdf	
Registro original: 	Embrapa Algodão (CNPA)	
Exemplares: 	CNPA - (28872-1) - UPC - AP - DD -  -  -  - DIS