Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados Bragantia (1) PAB (1) Autor Benin,Giovani (1) Bornhofen,Elesandro (1) Carrera,Constanza Soledad (1) Dardanelli,Julio (1) Duarte,Thiago (1) Funes,Gustavo Javier (1) Marchioro,Sergio Volmir (1) Martínez,María José (1) Resnik,Silvia Liliana (1) Reynoso,Cora Marcela (1) Stoco,Matheus Giovane (1) Storck,Lindolfo (1) Woyann,Leomar Guilherme (1) Mais... Palavra-chave Multi-environment trials (2) Environmental variation (1) Glycine max (1) Grain yield (1) Multiple linear regression (1) Protein composition (1) Rank correlation (1) Triticum aestivum L. (1) Univariate and multivariate methods (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2017 (1) 2011 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Amino acid composition of soybean seeds as affected by climatic variables PAB Carrera,Constanza Soledad; Reynoso,Cora Marcela; Funes,Gustavo Javier; Martínez,María José; Dardanelli,Julio; Resnik,Silvia Liliana. The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average... Tipo: Info:eu-repo/semantics/article Palavras-chave: Glycine max; Environmental variation; Multiple linear regression; Multi-environment trials; Protein composition. Ano: 2011 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2011001200001 Statistical methods to study adaptability and stability of wheat genotypes Bragantia Bornhofen,Elesandro; Benin,Giovani; Storck,Lindolfo; Woyann,Leomar Guilherme; Duarte,Thiago; Stoco,Matheus Giovane; Marchioro,Sergio Volmir. ABSTRACT The sensitivity of wheat crop to environmental variations frequently results in significant genotype (G) x environment (E) interaction (GEI). We compared statistical methods to analyze adaptability and stability of wheat genotypes in value for cultivation and use (VCU) trials. We used yield performance data of 22 wheat genotypes evaluated in three locations (Guarapuava, Cascavel, and Abelardo Luz) in 2012 and 2013. Each trial consisted of a complete randomized block design with three replications. The GEI was evaluated using methodologies based on mixed models, analysis of variance, linear regression, multivariate, and nonparametric analysis. The Spearman’s rank correlation coefficient was used to verify similarities in the genotype selection... Tipo: Info:eu-repo/semantics/article Palavras-chave: Triticum aestivum L.; Univariate and multivariate methods; Rank correlation; Grain yield; Multi-environment trials. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052017000100001 Registros recuperados: 2 Primeira ... 1 ... Última

Empresa Brasileira de Pesquisa Agropecuária - Embrapa Todos os direitos reservados, conforme Lei n° 9.610 Política de Privacidade Área restrita		Embrapa Parque Estação Biológica - PqEB s/n° Brasília, DF - Brasil - CEP 70770-901 Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco