Imputação de médias para análise de estabilidade e adaptabilidade em experimentos conjuntos incompletos: uma aplicação em café conilon

• Ano de defesa: 2012
• Autor(a) principal: Oliveira, Rafael Lédo Rocha de
• Orientador(a): Cruz, Cosme Damião
• Banca de defesa: Nascimento, Moysés , Ferrão, Romário Gava , Ribeiro Junior, José Ivo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Estatística Aplicada e Biometria
• Departamento: Estatística Aplicada e Biometria
• País: BR
• Palavras-chave em Português: Melhoramento genético; Clones de café conilon; Regressão linear simples
• Palavras-chave em Inglês: Genetic improvement; Clones conilon coffee; Simple linear regression
• Área do conhecimento CNPq: CNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVA
• Link de acesso: http://locus.ufv.br/handle/123456789/4046

This study aimed to develop, evaluate and verify the influence of medium values imputation through six methods on the genotype recommendation imputing missing in medium genotype from methodologies of stability and adaptability in experiments incomplete sets of conilon coffee, so that it can determine whether it is appropriate or not the implementation of missing means imputation. The first method imputes a missing value through a mathematical model that is a function of the experimental medium value added the effect of genotype; the second method adds to this model the environmental effect. The third, fourth and fifth methods created impute a missing value through a simple linear regression, whose independent variables are the environmental effects, which are estimated using all available data in the experiment set (method 3), or just the means of the genotypes that were evaluated in all environments (method 4). The independent variable of the fifth method are the mean responses of the genotype most correlated with the one you want to estimate a missing value. The dependent variable of these regressions are the mean responses of the genotype that you want to estimate the missing value. The sixth method keeps the sum of squares of the genotype x environment interaction. In order to evaluate and verify the influence of imputation methods proposed, it was obtained a data set provided by INCAPER (Capixaba Institute of Research, Technical Assistance and Rural Extension). It was from an experiment tin which 38 complete set genotypes (clones) of conilon coffee were evaluated in18 environments according to your productivity (bags/hectare). This experiment was submitted to Lin & Binns (1998) and Eberhart-Russell (1966) stability and adaptability analyses, generating, then, reference recommendations. After that, some means were removed randomly simulating experiments with 1%, 5% and 10% of missing means. Then, new mean values were generated through the imputation methods developed. The evaluation of these methodologies and verification of the influence of imputation on the recommendation of the genotypes was performed by calculating the mean squared error, the Spearman correlation between the Lin & Binns recommendation before and after imputation, and the percentage of changes on the recommendation of the genotypes in relation to the reference Eberhart-Russel recommendation. According to the results obtained in this study, the performance of the imputation of means by the developed methodologies with better performance (2, 3, 4 and 6) in incomplete experiment sets is advisable, since the changes in the recommendations of the genotypes was small compared with the number of missing means in the evaluated experiments.