Statistical significance, selection accuracy, and experimental precision in plant breeding.
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1150868 |
Resumo: | Genetic selection efficiency is measured by accuracy. Model selection relies on hypothesis testing with effectiveness given by statistical significance (p-value). Estimates of selection accuracy are based on variance parameters and precision. Model selection considers the amount of genetic variability and significance of effects. Questions arise as to which one to use: accuracy or p-value? We show there is a link between the two and both may be used. We derive equations for accuracy in multi-environment trials and determine numbers of repetitions and environments to reach accuracy. We propose a new methodology for accuracy classification based on p-values. This enables a better understanding of the level of accuracy being accepted when certain p-value is used. Accuracy of 90% is associated with p-value of 2%. Use of p-values up to 20% (accuracies above 50%) are acceptable to verify significance of genetic effects. Sample sizes for desired p-values are found via accuracy values. |
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Statistical significance, selection accuracy, and experimental precision in plant breeding.Plant breedingAgricultural statisticsGenetic varianceGenetic selection efficiency is measured by accuracy. Model selection relies on hypothesis testing with effectiveness given by statistical significance (p-value). Estimates of selection accuracy are based on variance parameters and precision. Model selection considers the amount of genetic variability and significance of effects. Questions arise as to which one to use: accuracy or p-value? We show there is a link between the two and both may be used. We derive equations for accuracy in multi-environment trials and determine numbers of repetitions and environments to reach accuracy. We propose a new methodology for accuracy classification based on p-values. This enables a better understanding of the level of accuracy being accepted when certain p-value is used. Accuracy of 90% is associated with p-value of 2%. Use of p-values up to 20% (accuracies above 50%) are acceptable to verify significance of genetic effects. Sample sizes for desired p-values are found via accuracy values.MARCOS DEON VILELA DE RESENDE, CNPCa; RODRIGO SILVA ALVES, UNIVERSIDADE FEDERAL DE VIÇOSA.RESENDE, M. D. V. deALVES, R. S.2023-01-11T14:01:25Z2023-01-11T14:01:25Z2023-01-112022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article19 p.Crop Breeding and Applied Biotechnology, v. 22, n. 3, 2022.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1150868enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-01-11T14:01:25Zoai:www.alice.cnptia.embrapa.br:doc/1150868Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542023-01-11T14:01:25falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-01-11T14:01:25Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
title |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
spellingShingle |
Statistical significance, selection accuracy, and experimental precision in plant breeding. RESENDE, M. D. V. de Plant breeding Agricultural statistics Genetic variance |
title_short |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
title_full |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
title_fullStr |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
title_full_unstemmed |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
title_sort |
Statistical significance, selection accuracy, and experimental precision in plant breeding. |
author |
RESENDE, M. D. V. de |
author_facet |
RESENDE, M. D. V. de ALVES, R. S. |
author_role |
author |
author2 |
ALVES, R. S. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
MARCOS DEON VILELA DE RESENDE, CNPCa; RODRIGO SILVA ALVES, UNIVERSIDADE FEDERAL DE VIÇOSA. |
dc.contributor.author.fl_str_mv |
RESENDE, M. D. V. de ALVES, R. S. |
dc.subject.por.fl_str_mv |
Plant breeding Agricultural statistics Genetic variance |
topic |
Plant breeding Agricultural statistics Genetic variance |
description |
Genetic selection efficiency is measured by accuracy. Model selection relies on hypothesis testing with effectiveness given by statistical significance (p-value). Estimates of selection accuracy are based on variance parameters and precision. Model selection considers the amount of genetic variability and significance of effects. Questions arise as to which one to use: accuracy or p-value? We show there is a link between the two and both may be used. We derive equations for accuracy in multi-environment trials and determine numbers of repetitions and environments to reach accuracy. We propose a new methodology for accuracy classification based on p-values. This enables a better understanding of the level of accuracy being accepted when certain p-value is used. Accuracy of 90% is associated with p-value of 2%. Use of p-values up to 20% (accuracies above 50%) are acceptable to verify significance of genetic effects. Sample sizes for desired p-values are found via accuracy values. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2023-01-11T14:01:25Z 2023-01-11T14:01:25Z 2023-01-11 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Crop Breeding and Applied Biotechnology, v. 22, n. 3, 2022. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1150868 |
identifier_str_mv |
Crop Breeding and Applied Biotechnology, v. 22, n. 3, 2022. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1150868 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
19 p. |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
_version_ |
1794503537500094464 |