Designing the best breeding strategy for Coffea canephora: Genetic evaluation of pure and hybrid individuals aiming to select for productivity and disease resistance traits.
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/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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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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1794503516832661504 |