Análise estatística espacial na avaliação de produtividade no melhoramento genético do feijoeiro

• Ano de defesa: 2009
• Autor(a) principal: Feres, Andréia Luiza Gonzaga
• Orientador(a): Carneiro, Antônio Policarpo Souza
• Banca de defesa: Cecon, Paulo Roberto , Martins Filho, Sebastião
• 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: Dependência espacial; Médias móveis; Papadakis; Seleção
• Palavras-chave em Inglês: Spatial dependence; Moving means; Papadakis method; Selection
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS
• Link de acesso: http://locus.ufv.br/handle/123456789/4021

Spatial dependence is a tendency that a variable´s value, observed in certain position, leads to approximate to its neighbors value than the value of the rest of the elements observed in the sample. The aim of this work was to evaluate the efficiency of some methods of geostatistic analyses to improve the experimental accuracy of tests that selects families for genetic improvement program of beans plantation. Date set were used to evaluate the productivity of eight experiments set in lattice design, located in Coimbra s Experimental Station controlled by the Plant Science Department at Federal University of Viçosa UFV. For each study was analyzed the neighborhood methods: Moving Means Method, Papadakis Method, Moving Means Replication, Papadakis Method Replication and the method that contains errors dependent in the comparison between traditional analyses in lattice which do not consider the spatial dependence among plots according to its fitting model, and the family classification in study. The existence of experiment s spatial dependence was observed through the Durbin-Watson s test, empirical and theoretical semivariogram with a geostatistic fitting model for residues checking the coherence of data and noticing the occurrence of spatial dependence in 6 out of 8 experiments in study (Chapter1). Five out of the six experiments showed spatial dependence for analyses in blocks and one for analyses in lattice and blocks, reaching 2.6 to 33.3m. In chapter 2, it was used the Durbin-Watson s test to observe the spatial dependence among residues for different methodologies, besides the Akaike Information Criteria (AIC) and the Maximum Likelihood Method to compare the fitting model. The variation coefficient and the relative efficiency were used to compare the efficiency of tested methodologies related to the analyses in lattice. The Spearman s Correlation Coefficient and the efficiency of selection were also used to compare the classification of beans plantation families acquired through the analyses in lattice and through the spatial analyses method. It was noticed that the spatial analyses method had a better fitting to the data than the methods that assume independent errors. The experiments accuracy, the analyses in lattice efficiency was higher compared to the analyses in blocks when there is higher spatial dependence. The spatial analyses method, Moving Means Method, Papadakis Method and the method with independent errors showed reasonable efficiency, while the proposed methodologies, Moving Means Replication and Papadakis were highly efficient than the analyses in lattice. Papadakis replication Method showed to be more efficient once its neighborhood is constituted by a superior and inferior plot compared to the reference plot. The tested methods showed reasonable concordance level compared to the selected families for analyses in lattice. The Moving Means Replication and Papadakis Replication methodologies showed highly efficient to improve the experiments accuracy, besides to guarantee the independence among residues, being an excellent alternative for analyses compared to the analyses in lattice.