Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFG |
Texto Completo: | http://repositorio.bc.ufg.br/tede/handle/tede/9120 |
Resumo: | Improving rice yield has been a big challenge for rice breeding programs around the world. One alternative to identify inbred lines with high yield potential, and discover genes related to yield and its components is to explore the genic pool of the population originated from crosses between cultivars not regularly used, as those introduced from another country. The objective of this study was characterizing a recombinant inbred lines population from the cross between Maninjau and Epagri 108. There were evaluated 296 RILs in experiments conducted in Goianira (GO), Boa Vista (RR) and Pelotas (RS), in 2016. In the experiments in GO and RR, the alpha lattice design (17x18) with two replications were used, and in Pelotas was applied the BAF design. Data were collected for yield (PD) and plant height (AP) in the three places, days to flowering (DF), in RR and GO, 100-grain weight (PG), in RS and GO and leaf blast resistance (BS), in GO. The data were analyzed by a mixed model with the deviance analysis. Variance components were estimated by REML/BLUP and the genetic parameters and correlation coefficients were calculated. The statistics parameters as CV e , CV g , CV r and selective accuracy were also estimated. The G x E interaction analysis was processed by the MHPRVG method. Also, the genetic distances between the progenies that had highest breeding values in each place and their relatives (Maninjau and Epagri 108), was estimated, using a 24 SSR markers panel. For Boa Vista and Goianira, most of the highest yield RILs were like the parental Epagri 108. Most of the random effects of the statistic model used in this study were significant. The RILs population showed genetic variability inside (σ g2 significant). The experimental precision in RR and GO was from good to excellent with accuracy over 90% and in RS it was moderate (~50%), probably because of the environmental effect action. Yield showed moderate heritability (0,67) and the characters DF, AP and PG showed high heritability (>0,90). Positive significant correlation was observed between the characters PD and PG, and DF and AP, however the last one showed negative correlation with yield. Nine RILs had the best performance by the MHPRVG, and it was above 30% of the general mean. They are recommended for the breeding program use. The RIL 105 were ranked as the best for stability, adaptability and yield, simultaneously. These results suggest that there is a significant genetic variation between the RILs evaluated. Therefore, this population might be used either in selection of high yield performance genotypes or for QTL mapping foragronomic traits in many environments. |
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Brondani, Claudiohttp://lattes.cnpq.br/4775600104554147Souza, Thiago Livio Pessoa Oliveira deCastro, Adriano PereiraBrondani, Claudiohttp://lattes.cnpq.br/0852214262732752Garcia, Ana Letcycia Basso2018-12-05T09:52:37Z2017-05-30GARCIA, A. L. B. Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado. 2017. 137 f. Dissertação (Mestrado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2017.http://repositorio.bc.ufg.br/tede/handle/tede/9120ark:/38995/0013000007vnbImproving rice yield has been a big challenge for rice breeding programs around the world. One alternative to identify inbred lines with high yield potential, and discover genes related to yield and its components is to explore the genic pool of the population originated from crosses between cultivars not regularly used, as those introduced from another country. The objective of this study was characterizing a recombinant inbred lines population from the cross between Maninjau and Epagri 108. There were evaluated 296 RILs in experiments conducted in Goianira (GO), Boa Vista (RR) and Pelotas (RS), in 2016. In the experiments in GO and RR, the alpha lattice design (17x18) with two replications were used, and in Pelotas was applied the BAF design. Data were collected for yield (PD) and plant height (AP) in the three places, days to flowering (DF), in RR and GO, 100-grain weight (PG), in RS and GO and leaf blast resistance (BS), in GO. The data were analyzed by a mixed model with the deviance analysis. Variance components were estimated by REML/BLUP and the genetic parameters and correlation coefficients were calculated. The statistics parameters as CV e , CV g , CV r and selective accuracy were also estimated. The G x E interaction analysis was processed by the MHPRVG method. Also, the genetic distances between the progenies that had highest breeding values in each place and their relatives (Maninjau and Epagri 108), was estimated, using a 24 SSR markers panel. For Boa Vista and Goianira, most of the highest yield RILs were like the parental Epagri 108. Most of the random effects of the statistic model used in this study were significant. The RILs population showed genetic variability inside (σ g2 significant). The experimental precision in RR and GO was from good to excellent with accuracy over 90% and in RS it was moderate (~50%), probably because of the environmental effect action. Yield showed moderate heritability (0,67) and the characters DF, AP and PG showed high heritability (>0,90). Positive significant correlation was observed between the characters PD and PG, and DF and AP, however the last one showed negative correlation with yield. Nine RILs had the best performance by the MHPRVG, and it was above 30% of the general mean. They are recommended for the breeding program use. The RIL 105 were ranked as the best for stability, adaptability and yield, simultaneously. These results suggest that there is a significant genetic variation between the RILs evaluated. Therefore, this population might be used either in selection of high yield performance genotypes or for QTL mapping foragronomic traits in many environments.O aumento da produtividade em arroz é um desafio para os programas de melhoramento do mundo todo. Uma alternativa para identificar linhagens mais produtivas, ou mesmo descobrir genes correlacionados à produtividade e seus componentes, é conhecer e explorar o pool gênico de populações provenientes de cruzamentos entre cultivares ainda pouco utilizadas, como materiais introduzidos. O objetivo desse trabalho foi caracterizar uma população de linhas puras recombinantes (RILs), provenientes do cruzamento entre Maninjau x Epagri 108. Foram avaliadas 296 RILs em experimentos conduzidos em Goianira (GO), Boa Vista (RR) e Pelotas (RS), no ano de 2016. Em GO e RR os ensaios foram implantados em delineamento alfa-látice (17x18) e em Pelotas foi utilizado BAF. Foram coletados dados referentes à produtividade (PD) e altura de plantas (AP) nos três locais, além de dias até o florescimento (DF), em RR e GO, peso de 100 grãos (PG), em RS e GO. Os dados foram analisados via modelos mistos, através da análise de deviance. Os componentes de variância foram estimados via REML/BLUP e foram estimados os parâmetros genéticos e coeficientes de correlação entre caracteres, bem como os parâmetros estatísticos CV e , CV g , CV r e acurácia seletiva. A análise de interação G x E foi feita com base no método da MHPRVG. Foram estimadas as distâncias genéticas entre as linhagens de maior valor genotípico em cada local e os parentais do cruzamento, através de um painel de 24 marcadores SSR, e para Boa Vista e Goianira, a maioria das linhagens mais produtivas foram mais similares ao genitor Epagri 108. A maioria dos efeitos aleatórios do modelo estatístico adotado foi significativa. A população de RILs apresentou variabilidade genética (σ g2 significativo). A precisão dos experimentos de RR e GO foi de boa à ótima, com acurácia maior que 90%, enquanto do RS foi moderada (~50%), provavelmente devido à maior ação do efeito ambiental. A produtividade se revelou com h2 moderada (0,67) e os caracteres DF, AP e PG apresentaram alta herdabilidade (>0,90). Foi verificada correlação positiva significativa entre os caracteres PD e PG e DF e AP, porém esses dois últimos têm correlação negativa significativa com a produtividade. Nove RILs se destacaram pela MHPRVG, com desempenho superior a 30% em relação à média geral. Elas são, portanto, recomendadas para uso do programa de melhoramento. A RIL 105 foi classificada como a de melhor estabilidade, adaptabilidade e produtividade, simultaneamente. Os resultados indicam que a população tem alta variabilidade genética e, pode ser utilizada tanto na seleção de genótipos de bom desempenho produtivo, quanto na detecção de QTLs para caracteres de interesse agronômico em múltiplos locais.Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2018-12-04T12:12:31Z No. of bitstreams: 2 Dissertação - Ana Letycia Basso Garcia - 2017.pdf: 3161693 bytes, checksum: 8ea7726402d9acbdddc870e75a0b1cef (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-12-05T09:52:37Z (GMT) No. of bitstreams: 2 Dissertação - Ana Letycia Basso Garcia - 2017.pdf: 3161693 bytes, checksum: 8ea7726402d9acbdddc870e75a0b1cef (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Made available in DSpace on 2018-12-05T09:52:37Z (GMT). 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dc.title.eng.fl_str_mv |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
dc.title.alternative.eng.fl_str_mv |
Genetic characterization by mixed models of a irrigated rice recombinant inbred lines population |
title |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
spellingShingle |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado Garcia, Ana Letcycia Basso RILs Parâmetros genéticos Deviance MHPRVG Dissimilaridade Genetic parameters Deviance Dissimilarity FITOTECNIA::MELHORAMENTO VEGETAL |
title_short |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
title_full |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
title_fullStr |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
title_full_unstemmed |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
title_sort |
Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado |
author |
Garcia, Ana Letcycia Basso |
author_facet |
Garcia, Ana Letcycia Basso |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Brondani, Claudio |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/4775600104554147 |
dc.contributor.referee1.fl_str_mv |
Souza, Thiago Livio Pessoa Oliveira de |
dc.contributor.referee2.fl_str_mv |
Castro, Adriano Pereira |
dc.contributor.referee3.fl_str_mv |
Brondani, Claudio |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0852214262732752 |
dc.contributor.author.fl_str_mv |
Garcia, Ana Letcycia Basso |
contributor_str_mv |
Brondani, Claudio Souza, Thiago Livio Pessoa Oliveira de Castro, Adriano Pereira Brondani, Claudio |
dc.subject.por.fl_str_mv |
RILs Parâmetros genéticos Deviance MHPRVG Dissimilaridade |
topic |
RILs Parâmetros genéticos Deviance MHPRVG Dissimilaridade Genetic parameters Deviance Dissimilarity FITOTECNIA::MELHORAMENTO VEGETAL |
dc.subject.eng.fl_str_mv |
Genetic parameters Deviance Dissimilarity |
dc.subject.cnpq.fl_str_mv |
FITOTECNIA::MELHORAMENTO VEGETAL |
description |
Improving rice yield has been a big challenge for rice breeding programs around the world. One alternative to identify inbred lines with high yield potential, and discover genes related to yield and its components is to explore the genic pool of the population originated from crosses between cultivars not regularly used, as those introduced from another country. The objective of this study was characterizing a recombinant inbred lines population from the cross between Maninjau and Epagri 108. There were evaluated 296 RILs in experiments conducted in Goianira (GO), Boa Vista (RR) and Pelotas (RS), in 2016. In the experiments in GO and RR, the alpha lattice design (17x18) with two replications were used, and in Pelotas was applied the BAF design. Data were collected for yield (PD) and plant height (AP) in the three places, days to flowering (DF), in RR and GO, 100-grain weight (PG), in RS and GO and leaf blast resistance (BS), in GO. The data were analyzed by a mixed model with the deviance analysis. Variance components were estimated by REML/BLUP and the genetic parameters and correlation coefficients were calculated. The statistics parameters as CV e , CV g , CV r and selective accuracy were also estimated. The G x E interaction analysis was processed by the MHPRVG method. Also, the genetic distances between the progenies that had highest breeding values in each place and their relatives (Maninjau and Epagri 108), was estimated, using a 24 SSR markers panel. For Boa Vista and Goianira, most of the highest yield RILs were like the parental Epagri 108. Most of the random effects of the statistic model used in this study were significant. The RILs population showed genetic variability inside (σ g2 significant). The experimental precision in RR and GO was from good to excellent with accuracy over 90% and in RS it was moderate (~50%), probably because of the environmental effect action. Yield showed moderate heritability (0,67) and the characters DF, AP and PG showed high heritability (>0,90). Positive significant correlation was observed between the characters PD and PG, and DF and AP, however the last one showed negative correlation with yield. Nine RILs had the best performance by the MHPRVG, and it was above 30% of the general mean. They are recommended for the breeding program use. The RIL 105 were ranked as the best for stability, adaptability and yield, simultaneously. These results suggest that there is a significant genetic variation between the RILs evaluated. Therefore, this population might be used either in selection of high yield performance genotypes or for QTL mapping foragronomic traits in many environments. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017-05-30 |
dc.date.accessioned.fl_str_mv |
2018-12-05T09:52:37Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
GARCIA, A. L. B. Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado. 2017. 137 f. Dissertação (Mestrado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2017. |
dc.identifier.uri.fl_str_mv |
http://repositorio.bc.ufg.br/tede/handle/tede/9120 |
dc.identifier.dark.fl_str_mv |
ark:/38995/0013000007vnb |
identifier_str_mv |
GARCIA, A. L. B. Caracterização genética por modelos mistos de uma população de linhas puras recombinantes de arroz irrigado. 2017. 137 f. Dissertação (Mestrado em Genética e Melhoramento de Plantas) - Universidade Federal de Goiás, Goiânia, 2017. ark:/38995/0013000007vnb |
url |
http://repositorio.bc.ufg.br/tede/handle/tede/9120 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.program.fl_str_mv |
-6265679607231828330 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 |
dc.relation.department.fl_str_mv |
-6046953723502374070 |
dc.relation.cnpq.fl_str_mv |
2615607299470131967 |
dc.relation.sponsorship.fl_str_mv |
2075167498588264571 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.publisher.program.fl_str_mv |
Programa de Pós-graduação em Genética e Melhoramento de Plantas (EA) |
dc.publisher.initials.fl_str_mv |
UFG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Escola de Agronomia - EA (RG) |
publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFG instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
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UFG |
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UFG |
reponame_str |
Repositório Institucional da UFG |
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Repositório Institucional da UFG |
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bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFG - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
tasesdissertacoes.bc@ufg.br |
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1811721440539443200 |