Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes

Detalhes bibliográficos
Autor(a) principal: Fonseca, Jales Mendes Oliveira
Data de Publicação: 2020
Outros Autores: Nunes, José Airton Rodrigues, Gonçalves, Flavia Maria Avelar, Souza Sobrinho, Fausto de, Benites, Flávio Rodrigo Gandolfi, Teixeira, Davi Henrique Lima
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/46870
Resumo: Forage plant breeders often use visual scores to assess agronomic traits because of the costs associated with in-depth phenotyping in the initial stages of breeding cycles. The aim of this study was to investigate the impact of the number of graders on the effectiveness of indirect selection of high-yielding genotypes and determine an optimal number of graders in the early-stage trials of Urochloa ruziziensis. For that purpose, five graders assessed 2.219 U. ruziziensis genotypes in an augmented block design. Biomass production and vigor scores were evaluated in two cuts and were analyzed using a linear mixed model approach. Vigor scores were analyzed considering each grader's score and the combinations of two, three, four, and five graders. Genetic variance was significant for both traits. Visual evaluation was effective in identifying productive genotypes based on the statistical criteria. The optimal number of graders for indirect selection of high-yielding U. ruziziensis genotypes is three.
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spelling Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypesBrachiaria ruziziensisVisual selectionAccuracyForage breedingSeleção indiretaSeleção visualPlantas forrageiras - MelhoramentoForage plant breeders often use visual scores to assess agronomic traits because of the costs associated with in-depth phenotyping in the initial stages of breeding cycles. The aim of this study was to investigate the impact of the number of graders on the effectiveness of indirect selection of high-yielding genotypes and determine an optimal number of graders in the early-stage trials of Urochloa ruziziensis. For that purpose, five graders assessed 2.219 U. ruziziensis genotypes in an augmented block design. Biomass production and vigor scores were evaluated in two cuts and were analyzed using a linear mixed model approach. Vigor scores were analyzed considering each grader's score and the combinations of two, three, four, and five graders. Genetic variance was significant for both traits. Visual evaluation was effective in identifying productive genotypes based on the statistical criteria. The optimal number of graders for indirect selection of high-yielding U. ruziziensis genotypes is three.Universidade Federal de Viçosa2021-08-18T19:01:16Z2021-08-18T19:01:16Z2020-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFONSECA, J. M. O. et al. Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 20, n. 3, e329220314, Jul./Sept. 2020. DOI: http://dx.doi.org/10.1590/1984-70332020v20n3a48.http://repositorio.ufla.br/jspui/handle/1/46870Crop Breeding and Applied Biotechnology - CBABreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFonseca, Jales Mendes OliveiraNunes, José Airton RodriguesGonçalves, Flavia Maria AvelarSouza Sobrinho, Fausto deBenites, Flávio Rodrigo GandolfiTeixeira, Davi Henrique Limaeng2021-08-18T19:07:16Zoai:localhost:1/46870Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-08-18T19:07:16Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
title Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
spellingShingle Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
Fonseca, Jales Mendes Oliveira
Brachiaria ruziziensis
Visual selection
Accuracy
Forage breeding
Seleção indireta
Seleção visual
Plantas forrageiras - Melhoramento
title_short Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
title_full Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
title_fullStr Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
title_full_unstemmed Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
title_sort Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes
author Fonseca, Jales Mendes Oliveira
author_facet Fonseca, Jales Mendes Oliveira
Nunes, José Airton Rodrigues
Gonçalves, Flavia Maria Avelar
Souza Sobrinho, Fausto de
Benites, Flávio Rodrigo Gandolfi
Teixeira, Davi Henrique Lima
author_role author
author2 Nunes, José Airton Rodrigues
Gonçalves, Flavia Maria Avelar
Souza Sobrinho, Fausto de
Benites, Flávio Rodrigo Gandolfi
Teixeira, Davi Henrique Lima
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Fonseca, Jales Mendes Oliveira
Nunes, José Airton Rodrigues
Gonçalves, Flavia Maria Avelar
Souza Sobrinho, Fausto de
Benites, Flávio Rodrigo Gandolfi
Teixeira, Davi Henrique Lima
dc.subject.por.fl_str_mv Brachiaria ruziziensis
Visual selection
Accuracy
Forage breeding
Seleção indireta
Seleção visual
Plantas forrageiras - Melhoramento
topic Brachiaria ruziziensis
Visual selection
Accuracy
Forage breeding
Seleção indireta
Seleção visual
Plantas forrageiras - Melhoramento
description Forage plant breeders often use visual scores to assess agronomic traits because of the costs associated with in-depth phenotyping in the initial stages of breeding cycles. The aim of this study was to investigate the impact of the number of graders on the effectiveness of indirect selection of high-yielding genotypes and determine an optimal number of graders in the early-stage trials of Urochloa ruziziensis. For that purpose, five graders assessed 2.219 U. ruziziensis genotypes in an augmented block design. Biomass production and vigor scores were evaluated in two cuts and were analyzed using a linear mixed model approach. Vigor scores were analyzed considering each grader's score and the combinations of two, three, four, and five graders. Genetic variance was significant for both traits. Visual evaluation was effective in identifying productive genotypes based on the statistical criteria. The optimal number of graders for indirect selection of high-yielding U. ruziziensis genotypes is three.
publishDate 2020
dc.date.none.fl_str_mv 2020-10
2021-08-18T19:01:16Z
2021-08-18T19:01:16Z
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 FONSECA, J. M. O. et al. Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 20, n. 3, e329220314, Jul./Sept. 2020. DOI: http://dx.doi.org/10.1590/1984-70332020v20n3a48.
http://repositorio.ufla.br/jspui/handle/1/46870
identifier_str_mv FONSECA, J. M. O. et al. Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 20, n. 3, e329220314, Jul./Sept. 2020. DOI: http://dx.doi.org/10.1590/1984-70332020v20n3a48.
url http://repositorio.ufla.br/jspui/handle/1/46870
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 Viçosa
publisher.none.fl_str_mv Universidade Federal de Viçosa
dc.source.none.fl_str_mv Crop Breeding and Applied Biotechnology - CBAB
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution 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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