Genetic variability and genetic progress in seed traits in breeding the physic nut
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
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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Agro@mbiente on-line |
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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 |
_version_ |
1799770039554932737 |