Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação
Autor(a) principal: | |
---|---|
Data de Publicação: | 2011 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | http://locus.ufv.br/handle/123456789/4039 |
Resumo: | The aim of this study was to evaluate the efficiency of spatial analysis, which considers spatially dependent errors, for classification of common bean families in relation to traditional analysis in randomized blocks and lattice that assuming independent errors. Were considered different degrees of spatial dependence and experimental precision. Were taken as reference to simulate the results of seven experiments carried out in simple square lattice for genetic evaluation of yield (g/plot) of families and bean cultivars of winter crops and water used in 2007 and 2008. From the results presented in the simulation, it was possible to assess the quality of their experiments based on different analysis (Block, lattice and Spatial) and simulated average of 100 families in different scenarios for Spatial Dependence (DE) and Accuracy Selective (AS). In the process of simulation, the average yield (645 g/plot) and the residual variance (7744.00), was defined based on the analysis results of the tests in blocks of bean breeding program at UFV. To make up the four simulated scenarios were considered magnitude of spatial dependence (null, low, medium and high), corresponding to ranges of 0, 25, 50 and 100% of the maximum distance between plots. Were also simulated three classes of selective accuracy (0.95, 0.80 and 0.60), corresponding to the experimental precision very high, high and average, respectively. The actual classification of families was used to evaluate the efficiency of analysis methods tested by Spearman correlation applied to orders and genotypic classification of Selection Efficiency between classifications based on tested methodologies and the actual classification for the selection of 10, 20 and 30% of the best families. To compare the efficiency of adjustment of the models tested, was used the Akaike information criterion (AIC), based on likelihood. Spatial analysis has provided estimates of residual variance very close to the simulated residual variance and higher selective accuracy estimated in all scenarios, indicating greater experimental accuracy. With the reduction in the accuracy and selective increase in spatial dependence, there was greater influence of analysis on the classification of families, and the spatial analysis showed the best results, providing more efficient selection of bean families than traditional analysis of randomized blocks and lattice, mainly for the selection of fewer families. The results for selective accuracy estimated on the basis of F statistics were very close to those obtained with the Spearman correlation between estimated and simulated averages for families, indicating that the accuracy should be used selectively as a measure of experimental precision tests of genetic evaluation. |
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Campos, Josmar Furtado dehttp://lattes.cnpq.br/9936261923678557Peternelli, Luiz Alexandrehttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723301Z7Cecon, Paulo Robertohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788114T5Carneiro, Antônio Policarpo Souzahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4799449E8Santos, Gérson Rodrigues doshttp://lattes.cnpq.br/0674757734832405Finger, Fernando Luizhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4783681Y02015-03-26T13:32:11Z2012-03-192015-03-26T13:32:11Z2011-02-24CAMPOS, Josmar Furtado de. Efficiency of spatial statistical analysis in the classification of common bean families - the study via simulation. 2011. 63 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Viçosa, Viçosa, 2011.http://locus.ufv.br/handle/123456789/4039The aim of this study was to evaluate the efficiency of spatial analysis, which considers spatially dependent errors, for classification of common bean families in relation to traditional analysis in randomized blocks and lattice that assuming independent errors. Were considered different degrees of spatial dependence and experimental precision. Were taken as reference to simulate the results of seven experiments carried out in simple square lattice for genetic evaluation of yield (g/plot) of families and bean cultivars of winter crops and water used in 2007 and 2008. From the results presented in the simulation, it was possible to assess the quality of their experiments based on different analysis (Block, lattice and Spatial) and simulated average of 100 families in different scenarios for Spatial Dependence (DE) and Accuracy Selective (AS). In the process of simulation, the average yield (645 g/plot) and the residual variance (7744.00), was defined based on the analysis results of the tests in blocks of bean breeding program at UFV. To make up the four simulated scenarios were considered magnitude of spatial dependence (null, low, medium and high), corresponding to ranges of 0, 25, 50 and 100% of the maximum distance between plots. Were also simulated three classes of selective accuracy (0.95, 0.80 and 0.60), corresponding to the experimental precision very high, high and average, respectively. The actual classification of families was used to evaluate the efficiency of analysis methods tested by Spearman correlation applied to orders and genotypic classification of Selection Efficiency between classifications based on tested methodologies and the actual classification for the selection of 10, 20 and 30% of the best families. To compare the efficiency of adjustment of the models tested, was used the Akaike information criterion (AIC), based on likelihood. Spatial analysis has provided estimates of residual variance very close to the simulated residual variance and higher selective accuracy estimated in all scenarios, indicating greater experimental accuracy. With the reduction in the accuracy and selective increase in spatial dependence, there was greater influence of analysis on the classification of families, and the spatial analysis showed the best results, providing more efficient selection of bean families than traditional analysis of randomized blocks and lattice, mainly for the selection of fewer families. The results for selective accuracy estimated on the basis of F statistics were very close to those obtained with the Spearman correlation between estimated and simulated averages for families, indicating that the accuracy should be used selectively as a measure of experimental precision tests of genetic evaluation.O objetivo deste trabalho foi avaliar a eficiência da análise Espacial, que considera erros dependentes espacialmente, para classificação de famílias de feijoeiro em relação às análises tradicionais em blocos casualizados e em látice que assumem erros independentes. Considerou-se diferentes graus de dependência espacial e de precisão experimental. Foram tomados como referência para simulação os resultados de sete ensaios instalados em látice quadrado simples para avaliação genética da produtividade de grãos (g/parcela) de famílias e cultivares de feijoeiro das safras de inverno e das águas de 2007 e 2008. A partir dos resultados apresentados na simulação, foi possível avaliar a qualidade dos respectivos experimentos com base nas diferentes análises (Bloco, Látice e Espacial) e médias simuladas das 100 famílias nos diferentes cenários para Dependência Espacial (DE) e Acurácia Seletiva (AS). No processo de simulação, a média de produção (645 g/parcela), bem como a variância residual (7744,00), foi definida com base nos resultados de análises em blocos de ensaios do programa de melhoramento do feijoeiro da UFV. Para a composição dos cenários simulados foram consideradas quatro magnitudes de dependência espacial (nula, baixa, média e alta), correspondendo aos alcances 0, 25, 50 e 100% da distância máxima entre parcelas. Também foram simuladas três classes de acurácia seletiva (0,95, 0,80 e 0,60), correspondente a precisão experimental muito alta, alta e média, respectivamente. A classificação real das famílias foi utilizada para avaliar a eficiência das metodologias de análise testadas através da correlação de Spearman aplicada às ordens de classificação genotípica e da Eficiência de Seleção entre classificações com base nas metodologias testadas e na classificação real, para a seleção de 10, 20 e 30% das melhores famílias. Para comparar a eficiência de ajuste dos modelos testados, foi utilizado o critério de Informação de Akaike (AIC), baseado em verossimilhança. A análise Espacial apresentou estimativas de variância residual muito próxima da variância residual simulada e maior acurácia seletiva estimada em todos os cenários, indicando maior precisão experimental. Com a redução na acurácia seletiva e aumento na dependência espacial, observou-se maior influência do tipo de análise sobre a classificação das famílias, sendo que a análise espacial apresentou os melhores resultados, proporcionando seleção mais eficiente das famílias do feijoeiro do que as análises tradicionais em Látice e em Blocos casualizados, principalmente, para seleção de menor número de famílias. Os resultados para acurácia seletiva estimada em função da estatística F foram muito próximos aos obtidos para a correlação de Spearman entre médias estimadas e simuladas para as famílias, indicando que a acurácia seletiva deve ser utilizada como medida de precisão experimental nos ensaios de avaliação genética.application/pdfporUniversidade Federal de ViçosaMestrado em Estatística Aplicada e BiometriaUFVBREstatística Aplicada e BiometriaModelo não-linearDependência espacialSemivariogramaAcurácia seletivaEficiência de seleçãoModelo exponencialGeoestatísticaNonlinear modelSpatial dependenceSemivariogramAccuracy selectiveEfficiency of selectionExponential modelGeostatisticsCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MELHORAMENTO VEGETALEficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulaçãoEfficiency of spatial statistical analysis in the classification of common bean families - the study via simulationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALtexto completo.pdfapplication/pdf446864https://locus.ufv.br//bitstream/123456789/4039/1/texto%20completo.pdf1ba8efc18a08b922adc7e2c5eb3dc55cMD51TEXTtexto completo.pdf.txttexto completo.pdf.txtExtracted texttext/plain104302https://locus.ufv.br//bitstream/123456789/4039/2/texto%20completo.pdf.txt4fd458ec190d9a29f95c83d0a9dd9a23MD52THUMBNAILtexto completo.pdf.jpgtexto completo.pdf.jpgIM Thumbnailimage/jpeg3585https://locus.ufv.br//bitstream/123456789/4039/3/texto%20completo.pdf.jpgc014d3f69e19d4b7a6595264dc5b0043MD53123456789/40392016-04-09 23:16:24.636oai:locus.ufv.br:123456789/4039Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452016-04-10T02:16:24LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.por.fl_str_mv |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
dc.title.alternative.eng.fl_str_mv |
Efficiency of spatial statistical analysis in the classification of common bean families - the study via simulation |
title |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
spellingShingle |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação Campos, Josmar Furtado de Modelo não-linear Dependência espacial Semivariograma Acurácia seletiva Eficiência de seleção Modelo exponencial Geoestatística Nonlinear model Spatial dependence Semivariogram Accuracy selective Efficiency of selection Exponential model Geostatistics CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MELHORAMENTO VEGETAL |
title_short |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
title_full |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
title_fullStr |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
title_full_unstemmed |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
title_sort |
Eficiência da análise estatística espacial na classificação de famílias do feijoeiro - estudo via simulação |
author |
Campos, Josmar Furtado de |
author_facet |
Campos, Josmar Furtado de |
author_role |
author |
dc.contributor.authorLattes.por.fl_str_mv |
http://lattes.cnpq.br/9936261923678557 |
dc.contributor.author.fl_str_mv |
Campos, Josmar Furtado de |
dc.contributor.advisor-co1.fl_str_mv |
Peternelli, Luiz Alexandre |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723301Z7 |
dc.contributor.advisor-co2.fl_str_mv |
Cecon, Paulo Roberto |
dc.contributor.advisor-co2Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788114T5 |
dc.contributor.advisor1.fl_str_mv |
Carneiro, Antônio Policarpo Souza |
dc.contributor.advisor1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4799449E8 |
dc.contributor.referee1.fl_str_mv |
Santos, Gérson Rodrigues dos |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/0674757734832405 |
dc.contributor.referee2.fl_str_mv |
Finger, Fernando Luiz |
dc.contributor.referee2Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4783681Y0 |
contributor_str_mv |
Peternelli, Luiz Alexandre Cecon, Paulo Roberto Carneiro, Antônio Policarpo Souza Santos, Gérson Rodrigues dos Finger, Fernando Luiz |
dc.subject.por.fl_str_mv |
Modelo não-linear Dependência espacial Semivariograma Acurácia seletiva Eficiência de seleção Modelo exponencial Geoestatística |
topic |
Modelo não-linear Dependência espacial Semivariograma Acurácia seletiva Eficiência de seleção Modelo exponencial Geoestatística Nonlinear model Spatial dependence Semivariogram Accuracy selective Efficiency of selection Exponential model Geostatistics CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MELHORAMENTO VEGETAL |
dc.subject.eng.fl_str_mv |
Nonlinear model Spatial dependence Semivariogram Accuracy selective Efficiency of selection Exponential model Geostatistics |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MELHORAMENTO VEGETAL |
description |
The aim of this study was to evaluate the efficiency of spatial analysis, which considers spatially dependent errors, for classification of common bean families in relation to traditional analysis in randomized blocks and lattice that assuming independent errors. Were considered different degrees of spatial dependence and experimental precision. Were taken as reference to simulate the results of seven experiments carried out in simple square lattice for genetic evaluation of yield (g/plot) of families and bean cultivars of winter crops and water used in 2007 and 2008. From the results presented in the simulation, it was possible to assess the quality of their experiments based on different analysis (Block, lattice and Spatial) and simulated average of 100 families in different scenarios for Spatial Dependence (DE) and Accuracy Selective (AS). In the process of simulation, the average yield (645 g/plot) and the residual variance (7744.00), was defined based on the analysis results of the tests in blocks of bean breeding program at UFV. To make up the four simulated scenarios were considered magnitude of spatial dependence (null, low, medium and high), corresponding to ranges of 0, 25, 50 and 100% of the maximum distance between plots. Were also simulated three classes of selective accuracy (0.95, 0.80 and 0.60), corresponding to the experimental precision very high, high and average, respectively. The actual classification of families was used to evaluate the efficiency of analysis methods tested by Spearman correlation applied to orders and genotypic classification of Selection Efficiency between classifications based on tested methodologies and the actual classification for the selection of 10, 20 and 30% of the best families. To compare the efficiency of adjustment of the models tested, was used the Akaike information criterion (AIC), based on likelihood. Spatial analysis has provided estimates of residual variance very close to the simulated residual variance and higher selective accuracy estimated in all scenarios, indicating greater experimental accuracy. With the reduction in the accuracy and selective increase in spatial dependence, there was greater influence of analysis on the classification of families, and the spatial analysis showed the best results, providing more efficient selection of bean families than traditional analysis of randomized blocks and lattice, mainly for the selection of fewer families. The results for selective accuracy estimated on the basis of F statistics were very close to those obtained with the Spearman correlation between estimated and simulated averages for families, indicating that the accuracy should be used selectively as a measure of experimental precision tests of genetic evaluation. |
publishDate |
2011 |
dc.date.issued.fl_str_mv |
2011-02-24 |
dc.date.available.fl_str_mv |
2012-03-19 2015-03-26T13:32:11Z |
dc.date.accessioned.fl_str_mv |
2015-03-26T13:32:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
CAMPOS, Josmar Furtado de. Efficiency of spatial statistical analysis in the classification of common bean families - the study via simulation. 2011. 63 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Viçosa, Viçosa, 2011. |
dc.identifier.uri.fl_str_mv |
http://locus.ufv.br/handle/123456789/4039 |
identifier_str_mv |
CAMPOS, Josmar Furtado de. Efficiency of spatial statistical analysis in the classification of common bean families - the study via simulation. 2011. 63 f. Dissertação (Mestrado em Estatística Aplicada e Biometria) - Universidade Federal de Viçosa, Viçosa, 2011. |
url |
http://locus.ufv.br/handle/123456789/4039 |
dc.language.iso.fl_str_mv |
por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Universidade Federal de Viçosa |
dc.publisher.program.fl_str_mv |
Mestrado em Estatística Aplicada e Biometria |
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UFV |
dc.publisher.country.fl_str_mv |
BR |
dc.publisher.department.fl_str_mv |
Estatística Aplicada e Biometria |
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Universidade Federal de Viçosa |
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LOCUS Repositório Institucional da UFV |
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