Statistical significance, selection accuracy, and experimental precision in plant breeding.

Detalhes bibliográficos
Autor(a) principal: RESENDE, M. D. V. de
Data de Publicação: 2022
Outros Autores: ALVES, R. S.
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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spelling 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
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