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	Provedor de dados Rev. Bras. Frutic. (2) Autor CAMPOS,BIANCA MACHADO (2) QUINTAL,SILVANA SILVA RED (2) VIANA,ALEXANDRE PIO (2) AMARAL JÚNIOR,ANTONIO TEIXEIRA DO (1) BARBOSA,CIBELLE DEGEL (1) DAHER,ROGÉRIO FIGUEIREDO (1) VIVAS,MARCELO (1) Mais... Palavra-chave Genetic variability (1) Guava (1) Heterotic group (1) Multivariate analysis (1) Psidium guajava (1) REML/BLUP (1) Variability (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2017 (1) 2016 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última SELECTION VIA MIXED MODELS IN SEGREGATING GUAVA FAMILIES BASED ON YIELD AND QUALITY TRAITS Rev. Bras. Frutic. QUINTAL,SILVANA SILVA RED; VIANA,ALEXANDRE PIO; CAMPOS,BIANCA MACHADO; VIVAS,MARCELO; AMARAL JÚNIOR,ANTONIO TEIXEIRA DO. ABSTRACT Aiming at the generation of new guava varieties with superior attributes, we conducted this study adopting the REML/BLUP procedure at individual level. Seventeen segregating guava families were evaluated in a randomized-block design with two replicates and 12 plants per plot. Families were obtained after controlled biparental pollination. The studied individuals showed high genotypic variance for fruit weight (FW), total yield (YLD), and ascorbic acid content (AAC). The heritability coefficients of the mean of progenies led to high progeny-selection accuracy for pulp yield (PY), soluble solids content (SSC), in addition to FW, YLD, and AAC; moderate accuracy for fruit acidity (FA) and SSC/FA ratio; and low accuracy for mesocarp thickness (MT) and... Tipo: Info:eu-repo/semantics/article Palavras-chave: Psidium guajava; Variability; REML/BLUP. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452017000200802 HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS Rev. Bras. Frutic. CAMPOS,BIANCA MACHADO; VIANA,ALEXANDRE PIO; QUINTAL,SILVANA SILVA RED; BARBOSA,CIBELLE DEGEL; DAHER,ROGÉRIO FIGUEIREDO. ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation. Tipo: Info:eu-repo/semantics/article Palavras-chave: Guava; Genetic variability; Multivariate analysis; Heterotic group. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151 Registros recuperados: 2 Primeira ... 1 ... Última

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