Fractional factorials in a case study nutrition experiment with banana trees
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/40640 |
Resumo: | In this paper we study combining designs concatenating levels from a full factorial for some factors with screening alternatives for the others. This was done to deal with a practical situation in plant nutrition experiments. The original problem was a study design for 14 potential factors in banana tree nutrition, and researchers imagined four full factorials were needed to test their hypothesis, being two from the 33 and two of the 34 series. As this would demand at least 216 experimental units and facing limited resources we seek for a different planning strategy. The idea was to combine in the same experiment four instances of DSD (Denitive Screening Designs) for 10 three-level factors, each in a different block, with a fraction of the full factorial of the 34 series. A central point treatment, with average level for all factors, was present in all blocks. Interchange algorithms were used to concatenate the factor levels. Resulting optimized design was compared to the designs sampled following the same principle. Design comparison criterion was the expected average variance of the estimates for factors (Ar optimality). Optimization reduced 4.02% of the average values of the criterion in a reference population of sampled designs. It was possible to show that the variance for linear and quadratic effects in the full factorial were higher than in the optimized plan. As an example, the analysis of an actual eld trial is presented. Authors recommend the use of fractional factorial strategy including DSD designs in agronomic trials, specially in the screening phase. |
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Fractional factorials in a case study nutrition experiment with banana treesFatoriais fracionários em um estudo de caso de experimento nutricional com bananeirasInterchange algorithmCombining designsScreening designsAlgoritmo de intercâmbioDelineamentos combinandosDelineamentos de triagemIn this paper we study combining designs concatenating levels from a full factorial for some factors with screening alternatives for the others. This was done to deal with a practical situation in plant nutrition experiments. The original problem was a study design for 14 potential factors in banana tree nutrition, and researchers imagined four full factorials were needed to test their hypothesis, being two from the 33 and two of the 34 series. As this would demand at least 216 experimental units and facing limited resources we seek for a different planning strategy. The idea was to combine in the same experiment four instances of DSD (Denitive Screening Designs) for 10 three-level factors, each in a different block, with a fraction of the full factorial of the 34 series. A central point treatment, with average level for all factors, was present in all blocks. Interchange algorithms were used to concatenate the factor levels. Resulting optimized design was compared to the designs sampled following the same principle. Design comparison criterion was the expected average variance of the estimates for factors (Ar optimality). Optimization reduced 4.02% of the average values of the criterion in a reference population of sampled designs. It was possible to show that the variance for linear and quadratic effects in the full factorial were higher than in the optimized plan. As an example, the analysis of an actual eld trial is presented. Authors recommend the use of fractional factorial strategy including DSD designs in agronomic trials, specially in the screening phase.Neste artigo, estudamos a combinação de planejamentos, concatenando níveis de um fatorial completo para alguns fatores com alternativas de triagem para os demais. Isso foi feito para lidar com uma situação prática em experimentos de nutrição de plantas. O problema original era o delineamento de um estudo para 14 fatores potenciais da nutrição da bananeira, e os pesquisadores imaginaram que quatro fatores fatoriais completos eram necessários para testar suas hipóteses, sendo dois da série 3 3 e dois da série 3 4 . Como isso demandaria pelo menos 216 unidades experimentais e, enfrentando recursos limitados, buscamos uma estratégia de planejamento diferente. A ideia foi combinar no mesmo experimento quatro instâncias de DSD (Definitive Screening Designs) para 10 fatores de três níveis, cada um em um bloco diferente, com uma fração do fatorial completo da série 3 4 . Um ponto central de tratamento, com nível médio para todos os fatores, esteve presente em todos os blocos. Algoritmos de troca foram usados para concatenar os níveis dos fatores. O projeto otimizado resultante foi comparado aos projetos amostrados seguindo o mesmo princípio. O critério de comparação de delineamento foi a variância média esperada das estimativas para fatores. A otimização reduziu 4, 02% dos valores médios do critério em uma população de referência de delineamentos amostrados. Foi possível mostrar que a variância para efeitos lineares e quadráticos no fatorial completo foi maior que no plano otimizado. Como exemplo, a análise de um teste de campo real é apresentada. Os autores recomendam o uso de estratégias do tipo fatorial fracionária, incluindo desenhos de DSD em ensaios agronômicos, especialmente na fase de triagem.Universidade Federal de Lavras2020-05-06T17:56:07Z2020-05-06T17:56:07Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfRIBEIRO, P. C. M. et al. Fractional factorials in a case study nutrition experiment with banana trees. Revista Brasileira de Biometria, Lavras, v. 37, n. 3, p. 335-349, 2019.http://repositorio.ufla.br/jspui/handle/1/40640Revista Brasileira de Biometriareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessRibeiro, Paulo César MoraesCampos, Matheus PenaPio, Leila Aparecida SallesBueno Filho, Júlio Sílvio de Sousaeng2020-05-06T17:56:30Zoai:localhost:1/40640Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-05-06T17:56:30Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Fractional factorials in a case study nutrition experiment with banana trees Fatoriais fracionários em um estudo de caso de experimento nutricional com bananeiras |
title |
Fractional factorials in a case study nutrition experiment with banana trees |
spellingShingle |
Fractional factorials in a case study nutrition experiment with banana trees Ribeiro, Paulo César Moraes Interchange algorithm Combining designs Screening designs Algoritmo de intercâmbio Delineamentos combinandos Delineamentos de triagem |
title_short |
Fractional factorials in a case study nutrition experiment with banana trees |
title_full |
Fractional factorials in a case study nutrition experiment with banana trees |
title_fullStr |
Fractional factorials in a case study nutrition experiment with banana trees |
title_full_unstemmed |
Fractional factorials in a case study nutrition experiment with banana trees |
title_sort |
Fractional factorials in a case study nutrition experiment with banana trees |
author |
Ribeiro, Paulo César Moraes |
author_facet |
Ribeiro, Paulo César Moraes Campos, Matheus Pena Pio, Leila Aparecida Salles Bueno Filho, Júlio Sílvio de Sousa |
author_role |
author |
author2 |
Campos, Matheus Pena Pio, Leila Aparecida Salles Bueno Filho, Júlio Sílvio de Sousa |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Ribeiro, Paulo César Moraes Campos, Matheus Pena Pio, Leila Aparecida Salles Bueno Filho, Júlio Sílvio de Sousa |
dc.subject.por.fl_str_mv |
Interchange algorithm Combining designs Screening designs Algoritmo de intercâmbio Delineamentos combinandos Delineamentos de triagem |
topic |
Interchange algorithm Combining designs Screening designs Algoritmo de intercâmbio Delineamentos combinandos Delineamentos de triagem |
description |
In this paper we study combining designs concatenating levels from a full factorial for some factors with screening alternatives for the others. This was done to deal with a practical situation in plant nutrition experiments. The original problem was a study design for 14 potential factors in banana tree nutrition, and researchers imagined four full factorials were needed to test their hypothesis, being two from the 33 and two of the 34 series. As this would demand at least 216 experimental units and facing limited resources we seek for a different planning strategy. The idea was to combine in the same experiment four instances of DSD (Denitive Screening Designs) for 10 three-level factors, each in a different block, with a fraction of the full factorial of the 34 series. A central point treatment, with average level for all factors, was present in all blocks. Interchange algorithms were used to concatenate the factor levels. Resulting optimized design was compared to the designs sampled following the same principle. Design comparison criterion was the expected average variance of the estimates for factors (Ar optimality). Optimization reduced 4.02% of the average values of the criterion in a reference population of sampled designs. It was possible to show that the variance for linear and quadratic effects in the full factorial were higher than in the optimized plan. As an example, the analysis of an actual eld trial is presented. Authors recommend the use of fractional factorial strategy including DSD designs in agronomic trials, specially in the screening phase. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2020-05-06T17:56:07Z 2020-05-06T17:56:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
RIBEIRO, P. C. M. et al. Fractional factorials in a case study nutrition experiment with banana trees. Revista Brasileira de Biometria, Lavras, v. 37, n. 3, p. 335-349, 2019. http://repositorio.ufla.br/jspui/handle/1/40640 |
identifier_str_mv |
RIBEIRO, P. C. M. et al. Fractional factorials in a case study nutrition experiment with banana trees. Revista Brasileira de Biometria, Lavras, v. 37, n. 3, p. 335-349, 2019. |
url |
http://repositorio.ufla.br/jspui/handle/1/40640 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras |
publisher.none.fl_str_mv |
Universidade Federal de Lavras |
dc.source.none.fl_str_mv |
Revista Brasileira de Biometria reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
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UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1807835074698149888 |