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Doctoral Thesis
DOI
https://doi.org/10.11606/T.11.2010.tde-19042010-142813
Document
Author
Full name
Édila Cristina de Souza
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Piracicaba, 2010
Supervisor
Committee
Dias, Carlos Tadeu dos Santos (President)
Macedo, Osmar Jesus
Pião, Antonio Carlos Simões
Sanches, Adhemar
Sarries, Gabriel Adrian
Title in Portuguese
Os métodos biplot e escalonamento multidimensional nos delineamentos experimentais
Keywords in Portuguese
Análise multivariada
Correlação genética e ambiental
Escalonamento multidimensional
Estabilidade
Fenótipos
Genética
Melão.
Abstract in Portuguese
O objetivo deste trabalho foi avaliar os métodos estatísticos de análise da interação de genótipos com ambientes (G × A), enfatizando a adaptabilidade e a estabilidade fenotípica. As variáveis estudadas foram produção e teor de sólidos solúveis totais (SST) do melão do tipo Gália, testando 9 genótipos em 12 ambientes. O experimento foi conduzido no delineamento aleatorizado em blocos com 3 repetições, realizado no Pólo Agroindustrial Mossoró-Assu no Rio Grande do Norte. O desempenho dos cultivares foi analisado por meio da utilização de análises de variância, metodologias de adaptabilidade e estabilidade. Realizou-se as análises para a produção e o teor de sólidos solúveis, utilizando as metodologias AMMI (Additive Main Effects and Multiplicative Interaction) e SREG (Sites Regression), representando graficamente de forma simultânea os genótipos e ambientes através dos gráficos Biplot AMMI, GGEbiplot e Trilinear plot. A análise AMMI possui a vantagem de estudar detalhadamente a estrutura do efeito de interação, além de representar simultaneamente os escores dos efeitos da interação para cada fator. Na análise SREG, incorpora o efeito de genótipo e na maioria dos casos está altamente correlacionado com os escores do primeiro componente principal, possui a vantagem de permitir a avaliação gráfica direta do efeito de genótipo. Propõe-se, também a metodologia MDS (Multidimensional Scalling) para verificar as similaridades e dissimilaridades entre os ambientes, através de uma matriz de distancias, representando geometricamente os dados no espaço bidimensional (Biplot) para cada variável estudada, em que pode-se observar as disparidades entre os ambientes, mostrando que esses apresentam características diferentes
Title in English
The Biplot Methods and Multidimensional Scaling in experimental designs
Keywords in English
Adaptability
Biplot
Interaction G × E
Multivariate analysis
Stability
Abstract in English
The objective of this study was to evaluate statistical methods of analysis of the interaction of genotypes with environments (G × A), emphasizing the adaptability and stability phenotype. The variables studied were production and soluble solids contents (SST) Melon Galia type, testing 9 genotypes in 12 environments. The experiment was conducted in a randomized block with 3 replications, it was done at Pole Agroindustrial Mossor´o-Assu in Rio Grande do Norte. The performance of cultivars was analyzed by using analysis of variance, methods of adaptability and stability. It carried out the analysis for the production and soluble solids, using the methodologies AMMI (Additive Main Effects and Multiplicative Interaction) and SREG (Sites Regression), graphing simultaneously the genotypes and environments through the AMMI Biplot graphs, GGE Biplot and trilinear plot. The AMMI analysis has the advantage of studying in detail the structure of the interaction effect, and represents both the scores of the interaction effects for each factor. The analysis SREG, incorporates the effect of genotype and in most cases is highly correlated with the scores of the first principal component, it has the advantage of allowing direct graphical assessment of the effect of genotype. It was also proposed the methodology MDS (Multidimensional Scalling) to check the similarities and dissimilarities between the environments, through a distance matrix, representing geometrically the data in two-dimensional space (Biplot) each variable studied, in wich one can be observed disparities environmental show different characteristics.
 
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Edila_Souza.pdf (1.71 Mbytes)
Publishing Date
2010-04-26
 
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