Mixed models and multivariate analysis for selection of superior maize genotypes

Selections via the mixed model and the multivariate analysis approach can be powerful tools for selecting cultivars in plant breeding programs. Therefore, this study aimed to compare the use of mixed models, multivariate analysis and traditional phenotypic selection to identify superior maize (Zea m...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Oliveira,Gustavo H.F, Amaral,Camila B, Silva,Flavia A.M, Dutra,Sophia M.F, Marconato,Marcela B, Moro,Gustavo V
Lenguaje:	English
Publicado:	Instituto de Investigaciones Agropecuarias, INIA 2016
Materias:	Blup K-means Zea mays
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392016000400005
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:scielo:S0718-58392016000400005
record_format	dspace
spelling	oai:scielo:S0718-583920160004000052018-10-01Mixed models and multivariate analysis for selection of superior maize genotypesOliveira,Gustavo H.FAmaral,Camila BSilva,Flavia A.MDutra,Sophia M.FMarconato,Marcela BMoro,Gustavo V Blup K-means Zea mays Selections via the mixed model and the multivariate analysis approach can be powerful tools for selecting cultivars in plant breeding programs. Therefore, this study aimed to compare the use of mixed models, multivariate analysis and traditional phenotypic selection to identify superior maize (Zea mays L.) genotypes. Seventy-one (71) maize Topcrosses and three commercial cultivars were evaluated using these three methods. Plant height, ear height, ear placement, stalk lodging and breakage, and grain yield were evaluated. There was a difference between selection methods, as the selection with mixed models and the selection based on the average phenotypic afforded the inclusion of genotypes with high productivity, which did not occur for the multivariate analysis. The selection by multivariate analysis allowed the inclusion of genotypes with better agronomic and other desirable traits, not only those with highest productivity, in a maize breeding program.info:eu-repo/semantics/openAccessInstituto de Investigaciones Agropecuarias, INIAChilean journal of agricultural research v.76 n.4 20162016-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392016000400005en10.4067/S0718-58392016000400005
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Blup K-means Zea mays
spellingShingle	Blup K-means Zea mays Oliveira,Gustavo H.F Amaral,Camila B Silva,Flavia A.M Dutra,Sophia M.F Marconato,Marcela B Moro,Gustavo V Mixed models and multivariate analysis for selection of superior maize genotypes
description	Selections via the mixed model and the multivariate analysis approach can be powerful tools for selecting cultivars in plant breeding programs. Therefore, this study aimed to compare the use of mixed models, multivariate analysis and traditional phenotypic selection to identify superior maize (Zea mays L.) genotypes. Seventy-one (71) maize Topcrosses and three commercial cultivars were evaluated using these three methods. Plant height, ear height, ear placement, stalk lodging and breakage, and grain yield were evaluated. There was a difference between selection methods, as the selection with mixed models and the selection based on the average phenotypic afforded the inclusion of genotypes with high productivity, which did not occur for the multivariate analysis. The selection by multivariate analysis allowed the inclusion of genotypes with better agronomic and other desirable traits, not only those with highest productivity, in a maize breeding program.
author	Oliveira,Gustavo H.F Amaral,Camila B Silva,Flavia A.M Dutra,Sophia M.F Marconato,Marcela B Moro,Gustavo V
author_facet	Oliveira,Gustavo H.F Amaral,Camila B Silva,Flavia A.M Dutra,Sophia M.F Marconato,Marcela B Moro,Gustavo V
author_sort	Oliveira,Gustavo H.F
title	Mixed models and multivariate analysis for selection of superior maize genotypes
title_short	Mixed models and multivariate analysis for selection of superior maize genotypes
title_full	Mixed models and multivariate analysis for selection of superior maize genotypes
title_fullStr	Mixed models and multivariate analysis for selection of superior maize genotypes
title_full_unstemmed	Mixed models and multivariate analysis for selection of superior maize genotypes
title_sort	mixed models and multivariate analysis for selection of superior maize genotypes
publisher	Instituto de Investigaciones Agropecuarias, INIA
publishDate	2016
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392016000400005
work_keys_str_mv	AT oliveiragustavohf mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes AT amaralcamilab mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes AT silvaflaviaam mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes AT dutrasophiamf mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes AT marconatomarcelab mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes AT morogustavov mixedmodelsandmultivariateanalysisforselectionofsuperiormaizegenotypes
_version_	1714205364026605568

Mixed models and multivariate analysis for selection of superior maize genotypes

Ejemplares similares