LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Caatinga |
Texto Completo: | https://periodicos.ufersa.edu.br/caatinga/article/view/11066 |
Resumo: | Based on its nutritional and economic value, the lima bean (Phaseolus lunatus L.) is the second most important species of the genus. It has high genetic diversity and potential for production and is considered an alternative food and income source. The objective of this study was to apply the restricted maximum likelihood/ best linear unbiased prediction (REML/ BLUP) methodology to estimate genetic parameters and predict genotypic values in F3 populations of lima beans. Twelve characteristics were evaluated in five populations with indeterminate growth habits (H39, H72, H53, H90, and H56). Model 83 from the Selegen program was used for analysis. Considering the genetic parameters, the highest values of genetic variance were for plant height and number of pods per plant. Pod thickness and seed width are favorable for breeding programs. Seed width selection gain was significant for populations H56 and H90 at 11.26 mm and 10.50 mm, respectively. As for the length and thickness of seeds, the gains were less significant, with population H53 showing the greatest gain. The REML/ BLUP methodology proved efficient in estimating genetic parameters and predicting gains in lima bean populations. The estimated selection gains indicated that the highest gains were obtained for plant height, the number of pods per plant, pod thickness, seed width, and the number of days to maturity. Populations H53 and H56 stood out for having large and white seeds, thus being potential populations for species improvement. |
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LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGYAVALIAÇÕES DE POPULAÇÕES DE FEIJÃO-FAVA VIA METODOLOGIA REML/BLUPPhaseolus lunatus. Parâmetros genéticos. Modelos mistos.Phaseolus lunatus. Genetic parameters. Mixed models.Based on its nutritional and economic value, the lima bean (Phaseolus lunatus L.) is the second most important species of the genus. It has high genetic diversity and potential for production and is considered an alternative food and income source. The objective of this study was to apply the restricted maximum likelihood/ best linear unbiased prediction (REML/ BLUP) methodology to estimate genetic parameters and predict genotypic values in F3 populations of lima beans. Twelve characteristics were evaluated in five populations with indeterminate growth habits (H39, H72, H53, H90, and H56). Model 83 from the Selegen program was used for analysis. Considering the genetic parameters, the highest values of genetic variance were for plant height and number of pods per plant. Pod thickness and seed width are favorable for breeding programs. Seed width selection gain was significant for populations H56 and H90 at 11.26 mm and 10.50 mm, respectively. As for the length and thickness of seeds, the gains were less significant, with population H53 showing the greatest gain. The REML/ BLUP methodology proved efficient in estimating genetic parameters and predicting gains in lima bean populations. The estimated selection gains indicated that the highest gains were obtained for plant height, the number of pods per plant, pod thickness, seed width, and the number of days to maturity. Populations H53 and H56 stood out for having large and white seeds, thus being potential populations for species improvement.O feijão-fava (Phaseolus lunatus L.) é a segunda espécie mais importante do gênero, apresenta diversidade genética e potencial para produção bem como valor nutricional e econômico, sendo considerada alternativa alimentar e de renda. O objetivo do trabalho é aplicar o método REML/BLUP para estimar os parâmetros genéticos e predizer os valores genotípicos em populações F3 de feijão-fava. Foram avaliados doze caracteres em cinco populações de hábito de crescimento indeterminado (H39, H72, H53, H90 e H56). Para as análises foi utilizado o modelo 83 do programa Selegen. Considerando os parâmetros genéticos, os maiores valores de variância genética foram para altura de planta e número de vagens por planta. Espessura de vagem, e largura de sementes, demostraram situação favorável ao programa de melhoramento. Os ganhos de seleção foram maiores e significativos em largura de sementes nas populações 56 e 90 com 11.26 mm e 10.50 mm, respectivamente. Quanto ao comprimento e espessura de sementes os ganhos foram menos significativos e a população 53 foi a que apresentou o maior ganho. A metodologia REML/BLUP mostrou-se eficiente na estimação dos parâmetros genéticos e predição de ganhos em populações de feijão-fava. Os ganhos de seleção estimados indicam que os maiores ganhos foram obtidos para os caracteres altura de plantas, número de vagens por planta, espessura de vagem, largura de semente e número de dias para a maturação. As populações H53 e H56 se destacaram por apresentar sementes grandes e brancas sendo assim populações promissoras no melhoramento da espécie.Universidade Federal Rural do Semi-Árido2022-09-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufersa.edu.br/caatinga/article/view/1106610.1590/1983-21252022v35n405rcREVISTA CAATINGA; Vol. 35 No. 4 (2022); 783-790Revista Caatinga; v. 35 n. 4 (2022); 783-7901983-21250100-316Xreponame:Revista Caatingainstname:Universidade Federal Rural do Semi-Árido (UFERSA)instacron:UFERSAenghttps://periodicos.ufersa.edu.br/caatinga/article/view/11066/11043Copyright (c) 2022 Revista Caatingainfo:eu-repo/semantics/openAccessCarvalho, Jhessica Lanna Rodrigues deVieira, Maria de Fátima BritoAlbuquerque, Tayná Mendes de Costa, Guilherme Alexandre Luz daGomes, Regina Lucia FerreiraLopes, Ângela Celis de Almeida2023-06-30T17:51:30Zoai:ojs.periodicos.ufersa.edu.br:article/11066Revistahttps://periodicos.ufersa.edu.br/index.php/caatinga/indexPUBhttps://periodicos.ufersa.edu.br/index.php/caatinga/oaipatricio@ufersa.edu.br|| caatinga@ufersa.edu.br1983-21250100-316Xopendoar:2024-04-29T09:47:01.403324Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)true |
dc.title.none.fl_str_mv |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY AVALIAÇÕES DE POPULAÇÕES DE FEIJÃO-FAVA VIA METODOLOGIA REML/BLUP |
title |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
spellingShingle |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY Carvalho, Jhessica Lanna Rodrigues de Phaseolus lunatus. Parâmetros genéticos. Modelos mistos. Phaseolus lunatus. Genetic parameters. Mixed models. |
title_short |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
title_full |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
title_fullStr |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
title_full_unstemmed |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
title_sort |
LIMA BEAN POPULATIONS ASSESSMENTS VIA REML/BLUP METHODOLOGY |
author |
Carvalho, Jhessica Lanna Rodrigues de |
author_facet |
Carvalho, Jhessica Lanna Rodrigues de Vieira, Maria de Fátima Brito Albuquerque, Tayná Mendes de Costa, Guilherme Alexandre Luz da Gomes, Regina Lucia Ferreira Lopes, Ângela Celis de Almeida |
author_role |
author |
author2 |
Vieira, Maria de Fátima Brito Albuquerque, Tayná Mendes de Costa, Guilherme Alexandre Luz da Gomes, Regina Lucia Ferreira Lopes, Ângela Celis de Almeida |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Carvalho, Jhessica Lanna Rodrigues de Vieira, Maria de Fátima Brito Albuquerque, Tayná Mendes de Costa, Guilherme Alexandre Luz da Gomes, Regina Lucia Ferreira Lopes, Ângela Celis de Almeida |
dc.subject.por.fl_str_mv |
Phaseolus lunatus. Parâmetros genéticos. Modelos mistos. Phaseolus lunatus. Genetic parameters. Mixed models. |
topic |
Phaseolus lunatus. Parâmetros genéticos. Modelos mistos. Phaseolus lunatus. Genetic parameters. Mixed models. |
description |
Based on its nutritional and economic value, the lima bean (Phaseolus lunatus L.) is the second most important species of the genus. It has high genetic diversity and potential for production and is considered an alternative food and income source. The objective of this study was to apply the restricted maximum likelihood/ best linear unbiased prediction (REML/ BLUP) methodology to estimate genetic parameters and predict genotypic values in F3 populations of lima beans. Twelve characteristics were evaluated in five populations with indeterminate growth habits (H39, H72, H53, H90, and H56). Model 83 from the Selegen program was used for analysis. Considering the genetic parameters, the highest values of genetic variance were for plant height and number of pods per plant. Pod thickness and seed width are favorable for breeding programs. Seed width selection gain was significant for populations H56 and H90 at 11.26 mm and 10.50 mm, respectively. As for the length and thickness of seeds, the gains were less significant, with population H53 showing the greatest gain. The REML/ BLUP methodology proved efficient in estimating genetic parameters and predicting gains in lima bean populations. The estimated selection gains indicated that the highest gains were obtained for plant height, the number of pods per plant, pod thickness, seed width, and the number of days to maturity. Populations H53 and H56 stood out for having large and white seeds, thus being potential populations for species improvement. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-20 |
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://periodicos.ufersa.edu.br/caatinga/article/view/11066 10.1590/1983-21252022v35n405rc |
url |
https://periodicos.ufersa.edu.br/caatinga/article/view/11066 |
identifier_str_mv |
10.1590/1983-21252022v35n405rc |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufersa.edu.br/caatinga/article/view/11066/11043 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Revista Caatinga info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Revista Caatinga |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural do Semi-Árido |
publisher.none.fl_str_mv |
Universidade Federal Rural do Semi-Árido |
dc.source.none.fl_str_mv |
REVISTA CAATINGA; Vol. 35 No. 4 (2022); 783-790 Revista Caatinga; v. 35 n. 4 (2022); 783-790 1983-2125 0100-316X reponame:Revista Caatinga instname:Universidade Federal Rural do Semi-Árido (UFERSA) instacron:UFERSA |
instname_str |
Universidade Federal Rural do Semi-Árido (UFERSA) |
instacron_str |
UFERSA |
institution |
UFERSA |
reponame_str |
Revista Caatinga |
collection |
Revista Caatinga |
repository.name.fl_str_mv |
Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA) |
repository.mail.fl_str_mv |
patricio@ufersa.edu.br|| caatinga@ufersa.edu.br |
_version_ |
1797674029962756096 |