Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.

Characterization and evaluation of phytogenetic resources, preserved ex situ in germplasm banks, is needed to allow their use by breeders. Data recorded from the characterization of maize landraces conserved at the INTA Pergamino germplasm bank could be shown as three way matrices (landraces * trait...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: ZULIANI, P., DEFACIO, R., LAVALLE, A., BRAMARDI, S.
Formato: Artículo revista
Lenguaje:Español
Publicado: Universidad Nacional del Litoral 2018
Materias:
three-way data
multiple factor analysis
generalized Procrustes analysis
RV coefficient
Zea mays L
Análisis Factorial Múltiple
Análisis de Procrustes Generalizado
coeficiente RV
Acceso en línea:https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651
Aporte de:
Biblioteca Virtual - Publicaciones (UNL) de Universidad Nacional del Litoral
id I26-R133-article-7651
record_format ojs
spelling I26-R133-article-76512018-10-09T12:04:25Z Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction. COMPARACIÓN DE TÉCNICAS DE ANÁLISIS MULTIVARIADO MEDIANTE SIMULACIÓN PARA CARACTERIZACIÓN DE RECURSOS FITOGENÉTICOS EN FUNCIÓN DE CARACTERES SUSCEPTIBLES A INTERACCIÓN GENOTIPO-AMBIENTE ZULIANI, P. DEFACIO, R. LAVALLE, A. BRAMARDI, S. three-way data multiple factor analysis generalized Procrustes analysis RV coefficient Zea mays L Análisis Factorial Múltiple Análisis de Procrustes Generalizado coeficiente RV Zea mays L Characterization and evaluation of phytogenetic resources, preserved ex situ in germplasm banks, is needed to allow their use by breeders. Data recorded from the characterization of maize landraces conserved at the INTA Pergamino germplasm bank could be shown as three way matrices (landraces * trait * environment). Simulated data was generated through three way empirical data, which was used to compare Principal Components Analysis (PCA), Multiple Factorial Analysis (MFA) and the Generalized Procrustes Analysis (GPA) techniques. Escoufier’s RV coefficient quantified the correlation between data matrices. High concordance between configurations obtained with the three analysis strategies was shown. MFA and GPA demonstrated a highlighted potential for the multivariate genotype-environment interaction study. It was also found that Escoufier’s RV coefficient may be used as a simple tool to quantify this interaction. Los Recursos Fitogenéticos se conservan ex situ en bancos de germoplasma. Para que los mismos sean utilizados por los mejoradores deben ser caracterizados y evaluados. En el banco de Germoplasma del INTA Pergamino se realiza la caracterización y evaluación de poblaciones locales de maíz, donde los datos obtenidos pueden presentarse como matrices de tres vías (poblaciones * variable * ambiente). A partir de datos empíricos de tres vías se generaron datos simulados, los cuales se utilizaron para comparar las técnicas de Análisis de Componentes Principales (ACP), Análisis Factorial Múltiple (AFM) y Análisis de Procrustes Generalizado (APG). La correlación entre las matrices de datos se cuantifi có con el coefi ciente RV de Escoufi er. Los resultados muestran una alta concordancia entre las confi guraciones encontradas con las tres estrategias de análisis. Se destaca el potencial que tienen AFM y el APG en el estudio de la interacción genotipo-ambiente multivariada. También se pudo comprobar que el coefi ciente RV de Escoufi er, puede ser usado como una sencilla herramienta para cuantifi car dicha interacción. Universidad Nacional del Litoral 2018-09-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651 10.14409/fa.v17i1.7651 FAVE Sección Ciencias Agrarias; Vol. 17 Núm. 1 (2018): FAVE Sección Ciencias Agrarias; 75-86 FAVE Sección Ciencias Agrarias; Vol. 17 No. 1 (2018): FAVE Sección Ciencias Agrarias; 75-86 FAVE Sección Ciencias Agrarias; v. 17 n. 1 (2018): FAVE Sección Ciencias Agrarias; 75-86 2346-9129 1666-7719 10.14409/fa.v17i1 spa https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651/11077 https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651/11585 https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651/11586 Derechos de autor 2018 FAVE Sección Ciencias Agrarias
institution Universidad Nacional del Litoral
institution_str I-26
repository_str R-133
container_title_str Biblioteca Virtual - Publicaciones (UNL)
language Español
format Artículo revista
topic three-way data
multiple factor analysis
generalized Procrustes analysis
RV coefficient
Zea mays L
Análisis Factorial Múltiple
Análisis de Procrustes Generalizado
coeficiente RV
Zea mays L
spellingShingle three-way data
multiple factor analysis
generalized Procrustes analysis
RV coefficient
Zea mays L
Análisis Factorial Múltiple
Análisis de Procrustes Generalizado
coeficiente RV
Zea mays L
ZULIANI, P.
DEFACIO, R.
LAVALLE, A.
BRAMARDI, S.
Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
topic_facet three-way data
multiple factor analysis
generalized Procrustes analysis
RV coefficient
Zea mays L
Análisis Factorial Múltiple
Análisis de Procrustes Generalizado
coeficiente RV
Zea mays L
author ZULIANI, P.
DEFACIO, R.
LAVALLE, A.
BRAMARDI, S.
author_facet ZULIANI, P.
DEFACIO, R.
LAVALLE, A.
BRAMARDI, S.
author_sort ZULIANI, P.
title Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
title_short Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
title_full Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
title_fullStr Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
title_full_unstemmed Comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
title_sort comparison of multivariate analysis techniques by simulation to charac- terize plant genetic resources in terms of characters wich are susceptible to genotype-environment interaction.
description Characterization and evaluation of phytogenetic resources, preserved ex situ in germplasm banks, is needed to allow their use by breeders. Data recorded from the characterization of maize landraces conserved at the INTA Pergamino germplasm bank could be shown as three way matrices (landraces * trait * environment). Simulated data was generated through three way empirical data, which was used to compare Principal Components Analysis (PCA), Multiple Factorial Analysis (MFA) and the Generalized Procrustes Analysis (GPA) techniques. Escoufier’s RV coefficient quantified the correlation between data matrices. High concordance between configurations obtained with the three analysis strategies was shown. MFA and GPA demonstrated a highlighted potential for the multivariate genotype-environment interaction study. It was also found that Escoufier’s RV coefficient may be used as a simple tool to quantify this interaction.
publisher Universidad Nacional del Litoral
publishDate 2018
url https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/FAVEAgrarias/article/view/7651
work_keys_str_mv AT zulianip comparisonofmultivariateanalysistechniquesbysimulationtocharacterizeplantgeneticresourcesintermsofcharacterswicharesusceptibletogenotypeenvironmentinteraction
AT defacior comparisonofmultivariateanalysistechniquesbysimulationtocharacterizeplantgeneticresourcesintermsofcharacterswicharesusceptibletogenotypeenvironmentinteraction
AT lavallea comparisonofmultivariateanalysistechniquesbysimulationtocharacterizeplantgeneticresourcesintermsofcharacterswicharesusceptibletogenotypeenvironmentinteraction
AT bramardis comparisonofmultivariateanalysistechniquesbysimulationtocharacterizeplantgeneticresourcesintermsofcharacterswicharesusceptibletogenotypeenvironmentinteraction
AT zulianip comparaciondetecnicasdeanalisismultivariadomediantesimulacionparacaracterizacionderecursosfitogeneticosenfunciondecaracteressusceptiblesainteracciongenotipoambiente
AT defacior comparaciondetecnicasdeanalisismultivariadomediantesimulacionparacaracterizacionderecursosfitogeneticosenfunciondecaracteressusceptiblesainteracciongenotipoambiente
AT lavallea comparaciondetecnicasdeanalisismultivariadomediantesimulacionparacaracterizacionderecursosfitogeneticosenfunciondecaracteressusceptiblesainteracciongenotipoambiente
AT bramardis comparaciondetecnicasdeanalisismultivariadomediantesimulacionparacaracterizacionderecursosfitogeneticosenfunciondecaracteressusceptiblesainteracciongenotipoambiente
first_indexed 2023-07-05T22:52:39Z
last_indexed 2023-07-05T22:52:39Z
_version_ 1770622874256670720

Ejemplares similares