Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.

Detalhes bibliográficos
Autor(a) principal: ALKIMIM, E. R.
Data de Publicação: 2021
Outros Autores: CAIXETA, E. T., SOUSA, T. V., GOIS, I. B., SILVA, F. L. da, SAKIYAMA, N. S., ZAMBOLIM, L., ALVES, R. S., RESENDE, M. D. V. de
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/1139243
https://doi.org/10.1371/journal.pone.0260997
Resumo: Breeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.
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spelling Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.Melhoramento Genético VegetalCafé RobustaPlant breedingCoffeaBreeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.EMILLY RUAS ALKIMIM, UFTM; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; TIAGO VIEIRA SOUSA, IFTM; ITAMARA BOMFIM GOIS, UFV; FELIPE LOPES DA SILVA, UFV; NEY SUSSUMU SAKIYAMA, UFV; LAÉRCIO ZAMBOLIM, UFV; RODRIGO SILVA ALVES, INCT CAFÉ; MARCOS DEON VILELA DE RESENDE, CNPCa.ALKIMIM, E. R.CAIXETA, E. T.SOUSA, T. V.GOIS, I. B.SILVA, F. L. daSAKIYAMA, N. S.ZAMBOLIM, L.ALVES, R. S.RESENDE, M. D. V. de2022-01-21T18:12:54Z2022-01-21T18:12:54Z2022-01-212021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlePlos One, v. 16, n. 12, e0260997, 2021.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139243https://doi.org/10.1371/journal.pone.0260997enginfo: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:EMBRAPA2022-01-21T18:13:04Zoai:www.alice.cnptia.embrapa.br:doc/1139243Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542022-01-21T18:13:04falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542022-01-21T18:13:04Repositório 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 Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
title Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
spellingShingle Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
ALKIMIM, E. R.
Melhoramento Genético Vegetal
Café Robusta
Plant breeding
Coffea
title_short Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
title_full Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
title_fullStr Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
title_full_unstemmed Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
title_sort Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
author ALKIMIM, E. R.
author_facet ALKIMIM, E. R.
CAIXETA, E. T.
SOUSA, T. V.
GOIS, I. B.
SILVA, F. L. da
SAKIYAMA, N. S.
ZAMBOLIM, L.
ALVES, R. S.
RESENDE, M. D. V. de
author_role author
author2 CAIXETA, E. T.
SOUSA, T. V.
GOIS, I. B.
SILVA, F. L. da
SAKIYAMA, N. S.
ZAMBOLIM, L.
ALVES, R. S.
RESENDE, M. D. V. de
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv EMILLY RUAS ALKIMIM, UFTM; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa; TIAGO VIEIRA SOUSA, IFTM; ITAMARA BOMFIM GOIS, UFV; FELIPE LOPES DA SILVA, UFV; NEY SUSSUMU SAKIYAMA, UFV; LAÉRCIO ZAMBOLIM, UFV; RODRIGO SILVA ALVES, INCT CAFÉ; MARCOS DEON VILELA DE RESENDE, CNPCa.
dc.contributor.author.fl_str_mv ALKIMIM, E. R.
CAIXETA, E. T.
SOUSA, T. V.
GOIS, I. B.
SILVA, F. L. da
SAKIYAMA, N. S.
ZAMBOLIM, L.
ALVES, R. S.
RESENDE, M. D. V. de
dc.subject.por.fl_str_mv Melhoramento Genético Vegetal
Café Robusta
Plant breeding
Coffea
topic Melhoramento Genético Vegetal
Café Robusta
Plant breeding
Coffea
description Breeding programs of the species Coffea canephora rely heavily on the significant genetic variability between and within its two varietal groups (conilon and robusta). The use of hybrid families and individuals has been less common. The objectives of this study were to evaluate parents and families from the populations of conilon, robusta, and its hybrids and to define the best breeding and selection strategies for productivity and disease resistance traits. As such, 71 conilon clones, 56 robusta clones, and 20 hybrid families were evaluated over several years for the following traits: vegetative vigor, incidence of rust and cercosporiosis, fruit ripening time, fruit size, plant height, canopy diameter, and yield per plant. Components of variance and genetic parameters were estimated via residual maximum likelihood (REML) and genotypic values were predicted via best linear unbiased prediction (BLUP). Genetic variability among parents (clones) and hybrid families was detected for most of the evaluated traits. The Mulamba-Rank index suggests potential gains up to 17% for the genotypic aggregate of traits in the hybrid population. An intrapopulation recurrent selection within the hybrid population would be the best breeding strategy because the genetic variability, narrow and broad senses heritabilities and selective accuracies for important traits were maximized in the crossed population. Besides, such strategy is simple, low cost and quicker than the concurrent reciprocal recurrent selection in the two parental populations, and this maximizes the genetic gain for unit of time.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022-01-21T18:12:54Z
2022-01-21T18:12:54Z
2022-01-21
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 Plos One, v. 16, n. 12, e0260997, 2021.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139243
https://doi.org/10.1371/journal.pone.0260997
identifier_str_mv Plos One, v. 16, n. 12, e0260997, 2021.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139243
https://doi.org/10.1371/journal.pone.0260997
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.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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