Genetic variability and genetic progress in seed traits in breeding the physic nut

Detalhes bibliográficos
Autor(a) principal: Gomes Leitão, Liliana Rocivalda
Data de Publicação: 2021
Outros Autores: Ribeiro Araújo, Linda Brenna, Mesquita, Rosilene Oliveira, Campos de Magalhães Bertini, Cândida Hermínia
Tipo de documento: Artigo
Idioma: por
Título da fonte: Agro@mbiente on-line
Texto Completo: https://revista.ufrr.br/agroambiente/article/view/6921
Resumo: Determining the chemical composition of seeds of the physic nut (Jatropha curcas L.) is of great importance for the species due to the oil content of the seeds (the principal trait of interest). Identifying promising genotypes with selectable seed traits is one of the strategies adopted in breeding the physic nut in order to increase the yield and quality of the oil. Therefore, the aim of this study was to determine the chemical composition of seed traits in ten half-sibling progeny of the physic nut, and to identify which progeny have good genetic performance for transmission to the offspring. The experimental design was completely randomised, with ten treatments and four replications. The treatments were represented by seeds from half-sibling progeny in which the carbohydrate, protein and lipid content, and the composition of the fatty acids were evaluated. The genetic parameters and the gains from their selection were predicted for the principal seed traits using mixed-model analysis, including REML (restricted maximum likelihood) and BLUP (best linear unbiased prediction). The physic-nut seeds showed an average dry matter (DM) concentration of 60 mg g-1 carbohydrates, 42 mg g-1 protein and 142 mg g-1 total lipids. Unsaturated fatty acids represented more than 85% of the total fatty acid composition, with the oil classified as oleic-linoleic. Considering the predictions of the genetic parameters, the lipid traits can be selected for the purpose of breeding, resulting in genetic progress in the yield and quality of physic-nut oil.
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spelling Genetic variability and genetic progress in seed traits in breeding the physic nutFatty acids. Genetic components. Selection gain. Jatropha curcas L. Mixed models.Determining the chemical composition of seeds of the physic nut (Jatropha curcas L.) is of great importance for the species due to the oil content of the seeds (the principal trait of interest). Identifying promising genotypes with selectable seed traits is one of the strategies adopted in breeding the physic nut in order to increase the yield and quality of the oil. Therefore, the aim of this study was to determine the chemical composition of seed traits in ten half-sibling progeny of the physic nut, and to identify which progeny have good genetic performance for transmission to the offspring. The experimental design was completely randomised, with ten treatments and four replications. The treatments were represented by seeds from half-sibling progeny in which the carbohydrate, protein and lipid content, and the composition of the fatty acids were evaluated. The genetic parameters and the gains from their selection were predicted for the principal seed traits using mixed-model analysis, including REML (restricted maximum likelihood) and BLUP (best linear unbiased prediction). The physic-nut seeds showed an average dry matter (DM) concentration of 60 mg g-1 carbohydrates, 42 mg g-1 protein and 142 mg g-1 total lipids. Unsaturated fatty acids represented more than 85% of the total fatty acid composition, with the oil classified as oleic-linoleic. Considering the predictions of the genetic parameters, the lipid traits can be selected for the purpose of breeding, resulting in genetic progress in the yield and quality of physic-nut oil.UFRR2021-05-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revista.ufrr.br/agroambiente/article/view/692110.18227/1982-8470ragro.v15i0.6921AGRO@MBIENTE ON-LINE JOURNALRAGR; Vol. 15 (2021)REVISTA AGRO@MBIENTE ON-LINE; Vol. 15 (2021)REVISTA AGRO@MBIENTE ON-LINE; v. 15 (2021)1982-8470reponame:Agro@mbiente on-lineinstname:Universidade Federal de Roraima (UFRR)instacron:UFRRporhttps://revista.ufrr.br/agroambiente/article/view/6921/3333Copyright (c) 2021 REVISTA AGRO@MBIENTE ON-LINEinfo:eu-repo/semantics/openAccessGomes Leitão, Liliana RocivaldaRibeiro Araújo, Linda BrennaMesquita, Rosilene OliveiraCampos de Magalhães Bertini, Cândida Hermínia2021-12-29T14:46:47Zoai:oai.revista.ufrr.br:article/6921Revistahttps://revista.ufrr.br/index.php/agroambientePUBhttps://revista.ufrr.br/index.php/agroambiente/oai||scpuchoa@dsi.ufrr.br|| arcanjoalves@oi.com.br1982-84701982-8470opendoar:2021-12-29T14:46:47Agro@mbiente on-line - Universidade Federal de Roraima (UFRR)false
dc.title.none.fl_str_mv Genetic variability and genetic progress in seed traits in breeding the physic nut
title Genetic variability and genetic progress in seed traits in breeding the physic nut
spellingShingle Genetic variability and genetic progress in seed traits in breeding the physic nut
Gomes Leitão, Liliana Rocivalda
Fatty acids. Genetic components. Selection gain. Jatropha curcas L. Mixed models.
title_short Genetic variability and genetic progress in seed traits in breeding the physic nut
title_full Genetic variability and genetic progress in seed traits in breeding the physic nut
title_fullStr Genetic variability and genetic progress in seed traits in breeding the physic nut
title_full_unstemmed Genetic variability and genetic progress in seed traits in breeding the physic nut
title_sort Genetic variability and genetic progress in seed traits in breeding the physic nut
author Gomes Leitão, Liliana Rocivalda
author_facet Gomes Leitão, Liliana Rocivalda
Ribeiro Araújo, Linda Brenna
Mesquita, Rosilene Oliveira
Campos de Magalhães Bertini, Cândida Hermínia
author_role author
author2 Ribeiro Araújo, Linda Brenna
Mesquita, Rosilene Oliveira
Campos de Magalhães Bertini, Cândida Hermínia
author2_role author
author
author
dc.contributor.author.fl_str_mv Gomes Leitão, Liliana Rocivalda
Ribeiro Araújo, Linda Brenna
Mesquita, Rosilene Oliveira
Campos de Magalhães Bertini, Cândida Hermínia
dc.subject.por.fl_str_mv Fatty acids. Genetic components. Selection gain. Jatropha curcas L. Mixed models.
topic Fatty acids. Genetic components. Selection gain. Jatropha curcas L. Mixed models.
description Determining the chemical composition of seeds of the physic nut (Jatropha curcas L.) is of great importance for the species due to the oil content of the seeds (the principal trait of interest). Identifying promising genotypes with selectable seed traits is one of the strategies adopted in breeding the physic nut in order to increase the yield and quality of the oil. Therefore, the aim of this study was to determine the chemical composition of seed traits in ten half-sibling progeny of the physic nut, and to identify which progeny have good genetic performance for transmission to the offspring. The experimental design was completely randomised, with ten treatments and four replications. The treatments were represented by seeds from half-sibling progeny in which the carbohydrate, protein and lipid content, and the composition of the fatty acids were evaluated. The genetic parameters and the gains from their selection were predicted for the principal seed traits using mixed-model analysis, including REML (restricted maximum likelihood) and BLUP (best linear unbiased prediction). The physic-nut seeds showed an average dry matter (DM) concentration of 60 mg g-1 carbohydrates, 42 mg g-1 protein and 142 mg g-1 total lipids. Unsaturated fatty acids represented more than 85% of the total fatty acid composition, with the oil classified as oleic-linoleic. Considering the predictions of the genetic parameters, the lipid traits can be selected for the purpose of breeding, resulting in genetic progress in the yield and quality of physic-nut oil.
publishDate 2021
dc.date.none.fl_str_mv 2021-05-07
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revista.ufrr.br/agroambiente/article/view/6921
10.18227/1982-8470ragro.v15i0.6921
url https://revista.ufrr.br/agroambiente/article/view/6921
identifier_str_mv 10.18227/1982-8470ragro.v15i0.6921
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revista.ufrr.br/agroambiente/article/view/6921/3333
dc.rights.driver.fl_str_mv Copyright (c) 2021 REVISTA AGRO@MBIENTE ON-LINE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 REVISTA AGRO@MBIENTE ON-LINE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UFRR
publisher.none.fl_str_mv UFRR
dc.source.none.fl_str_mv AGRO@MBIENTE ON-LINE JOURNALRAGR; Vol. 15 (2021)
REVISTA AGRO@MBIENTE ON-LINE; Vol. 15 (2021)
REVISTA AGRO@MBIENTE ON-LINE; v. 15 (2021)
1982-8470
reponame:Agro@mbiente on-line
instname:Universidade Federal de Roraima (UFRR)
instacron:UFRR
instname_str Universidade Federal de Roraima (UFRR)
instacron_str UFRR
institution UFRR
reponame_str Agro@mbiente on-line
collection Agro@mbiente on-line
repository.name.fl_str_mv Agro@mbiente on-line - Universidade Federal de Roraima (UFRR)
repository.mail.fl_str_mv ||scpuchoa@dsi.ufrr.br|| arcanjoalves@oi.com.br
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