Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2013 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
Texto Completo: | http://repositorio.uem.br:8080/jspui/handle/1/1340 |
Resumo: | New soybean varieties have always been released in the market of agricultural commodities. However, before being registered in the National Cultivar Register Council (RNC), they need to have different trait responses in comparison with the usual cultivars. Searching for more productive genotypes with stability, adaptability, resistance or tolerance to biotic and abiotic components in their respective growing environment has been the main objective of soybean breeding programs. The aim of this study was to evaluate the stability and adaptability of genetically modified insects-resistant and glyphosate-tolerant soybean genotypes as well as to test three multivariate methods of environmental stratification to identify homogeneous regions in the Paraná and Mato Grosso do Sul States. In the first chapter, 19 genotypes were clustered in two groups of relative maturity: high early (RM from 5.0 to 5.9) and early (RM from 6.0 to 6.7) RM during the two growing seasons of 2010/2011 and 2011/2012 when seven representative Counties usually cultivated with soybean were investigated. Both groups were evaluated using the alternative approach based on the supplementary genotype in the AMMI analysis (Additive Main Effects and Multiplicative Interaction Analysis). Thereafter, these results were compared with those from the methods of Eberhart and Russell (1966), Cruz et al. (1989) and Huenh (1990a). The insects-resistant and glyphosate-tolerant genotypes had satisfactory levels of crop yield and stability. The LS3, LS4 and LS7 cultivars were highlighted among the high early lines. Early lines as the LP3 and LP7 had also greater stability and can be recommended to all these evaluated environments. Evidence of similarity in the stability parameters estimated by the methods of Eberhart and Russell (1966) and Cruz et al. (1989) was found. In the second chapter, the grain yield from 14 sites in the soybean macro-region 2 (MRS 2) was analyzed, during the growing seasons 2010/2011, 2011/ 2012 and 2012/2013. Nine genotypes were tested, using the Murakami and Cruz method, SREG GGE biplot model, and Fox and Rosielle method. Based on the GGE SREG biplot model, the best environments for selecting genotypes were Goioerê and Campo Mourão Counties in the 201 region; the Naviraí County in the 202 region, and Sidrolândia and Maracaju Counties in the 204 region. SREG GGE biplot model gathered fewer clusters among the tested methods because the subdivisions and the new clusters of environments were different from those from the previous model. Based on these three methods, the Cascavel County was found to be a distinct environment in the regionalization proposed by Kaster and Farias (2012). |
id |
UEM-10_9eac947f5dabf5d28a99092945b5b6bc |
---|---|
oai_identifier_str |
oai:localhost:1/1340 |
network_acronym_str |
UEM-10 |
network_name_str |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
repository_id_str |
|
spelling |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do BrasilGenotype x Environment Interaction of Insect-Resistant and Glyphosate- Tolerant Soybean Lines cultivated in Central and South BrazilSoja GMSojaEstratificação ambientalAdaptabilidadeEstabilidadeBrasil.SoybeanGMOEnvironmental stratificationAdaptability and stabilityBrazil.Ciências AgráriasAgronomiaNew soybean varieties have always been released in the market of agricultural commodities. However, before being registered in the National Cultivar Register Council (RNC), they need to have different trait responses in comparison with the usual cultivars. Searching for more productive genotypes with stability, adaptability, resistance or tolerance to biotic and abiotic components in their respective growing environment has been the main objective of soybean breeding programs. The aim of this study was to evaluate the stability and adaptability of genetically modified insects-resistant and glyphosate-tolerant soybean genotypes as well as to test three multivariate methods of environmental stratification to identify homogeneous regions in the Paraná and Mato Grosso do Sul States. In the first chapter, 19 genotypes were clustered in two groups of relative maturity: high early (RM from 5.0 to 5.9) and early (RM from 6.0 to 6.7) RM during the two growing seasons of 2010/2011 and 2011/2012 when seven representative Counties usually cultivated with soybean were investigated. Both groups were evaluated using the alternative approach based on the supplementary genotype in the AMMI analysis (Additive Main Effects and Multiplicative Interaction Analysis). Thereafter, these results were compared with those from the methods of Eberhart and Russell (1966), Cruz et al. (1989) and Huenh (1990a). The insects-resistant and glyphosate-tolerant genotypes had satisfactory levels of crop yield and stability. The LS3, LS4 and LS7 cultivars were highlighted among the high early lines. Early lines as the LP3 and LP7 had also greater stability and can be recommended to all these evaluated environments. Evidence of similarity in the stability parameters estimated by the methods of Eberhart and Russell (1966) and Cruz et al. (1989) was found. In the second chapter, the grain yield from 14 sites in the soybean macro-region 2 (MRS 2) was analyzed, during the growing seasons 2010/2011, 2011/ 2012 and 2012/2013. Nine genotypes were tested, using the Murakami and Cruz method, SREG GGE biplot model, and Fox and Rosielle method. Based on the GGE SREG biplot model, the best environments for selecting genotypes were Goioerê and Campo Mourão Counties in the 201 region; the Naviraí County in the 202 region, and Sidrolândia and Maracaju Counties in the 204 region. SREG GGE biplot model gathered fewer clusters among the tested methods because the subdivisions and the new clusters of environments were different from those from the previous model. Based on these three methods, the Cascavel County was found to be a distinct environment in the regionalization proposed by Kaster and Farias (2012).Novas cultivares de soja constantemente são apresentadas ao mercado. Para que sejam registradas, elas necessitam apresentar alguma característica que as diferenciem das demais. A busca por genótipos mais produtivos que apresentem estabilidade, adaptabilidade e resistência ou tolerância aos efeitos bióticos e abióticos, em seus respectivos locais de cultivo, são os objetivos principais dos programas de melhoramento. Objetivou-se, com este trabalho, avaliar a estabilidade e adaptabilidade de genótipos de soja geneticamente modificados tolerantes ao glifosato e resistentes a insetos, bem como testar três métodos multivariados para a estratificação ambiental, visando à identificação de ambientes homogêneos nos estados do Paraná e Mato Grosso do Sul. No primeiro capítulo, foram avaliados 19 genótipos de soja, divididos em dois grupos de maturação relativa (MR): superprecoces (MR 5.0 a 5.9) e precoces (MR 6.0 a 6.7), durante duas safras 2010/2011 e 2011/2012, cultivados em sete municípios de representação agrícola. Estas linhagens foram avaliadas, utilizando a abordagem alternativa, fundamentada no uso de genótipos suplementares na análise AMMI (Additive Main Effects and Multiplicative Interaction Analysis), e comparando-se os resultados provenientes dessa metodologia com a resposta das mesmas linhagens avaliadas pelos métodos de Eberhart e Russell (1966), Cruz et al. (1989) e Huenh (1990a). Os genótipos resistentes a insetos e tolerantes ao glifosato apresentaram níveis satisfatórios de rendimento de grãos e estabilidade. Entre as linhagens superprecoces, destacaram-se LS3, LS4 e LS7. Entre os genótipos precoces, LP3 e LP7 manifestaram maior estabilidade, sendo recomendável o seu cultivo em todos os ambientes avaliados. Ficou evidenciada a similaridade entre os parâmetros de estabilidade estimados por meio dos métodos de Eberhart e Russell (1966) e Cruz et al. (1989). No segundo capítulo, foram analisados os dados de produtividade de grãos de experimentos realizados em 14 municípios pertencentes à macrorregião sojícola (MRS) 2, durante os anos agrícolas 2010/2011, 2011/2012 e 2012/2013. Em cada local, foram testados 9 genótipos entre linhagens e cultivares comerciais. A análise foi realizada utilizando o método de Murakami e Cruz, o modelo SREG GGE biplot e o método de Fox e Rosielle. Por meio do modelo SREG GGE biplot, observou-se que os melhores ambientes para seleção de genótipos de soja na região 201 foram Campo Mourão e Goioerê; na região 202, foi Naviraí; e na região 204 os ambientes Sidrolândia e Maracaju. O modelo SREG GGE biplot formou um menor número de agrupamentos entre os métodos testados, os quais apresentaram subdivisões e reagrupamento de ambientes formados pelo modelo anterior. Por meio dos três métodos avaliados, Cascavel apresentou-se como um ambiente distinto da sua respectiva região, segundo a regionalização proposta por Kaster e Farias (2012).ix, 82 fUniversidade Estadual de MaringáBrasilUEMMaringá, PRPrograma de Pós-Graduação em Genética de MelhoramentoCarlos Alberto de Bastos AndradeLeandro Simões Azeredo Gonçalves - UELRonald José Barth Pinto - UEMCarlos Alberto Scapim - UEMLuis Fernando Alliprandini - FAPESPMotomiya, Wagner Rogério2018-04-05T16:28:11Z2018-04-05T16:28:11Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesishttp://repositorio.uem.br:8080/jspui/handle/1/1340porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM)instname:Universidade Estadual de Maringá (UEM)instacron:UEM2018-04-05T16:28:11Zoai:localhost:1/1340Repositório InstitucionalPUBhttp://repositorio.uem.br:8080/oai/requestopendoar:2024-04-23T14:54:16.265456Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil Genotype x Environment Interaction of Insect-Resistant and Glyphosate- Tolerant Soybean Lines cultivated in Central and South Brazil |
title |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
spellingShingle |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil Motomiya, Wagner Rogério Soja GM Soja Estratificação ambiental Adaptabilidade Estabilidade Brasil. Soybean GMO Environmental stratification Adaptability and stability Brazil. Ciências Agrárias Agronomia |
title_short |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
title_full |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
title_fullStr |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
title_full_unstemmed |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
title_sort |
Interação genótipos por ambientes em linhagens de soja resistentes a insetos e tolerantes ao glifosato na região centro-sul do Brasil |
author |
Motomiya, Wagner Rogério |
author_facet |
Motomiya, Wagner Rogério |
author_role |
author |
dc.contributor.none.fl_str_mv |
Carlos Alberto de Bastos Andrade Leandro Simões Azeredo Gonçalves - UEL Ronald José Barth Pinto - UEM Carlos Alberto Scapim - UEM Luis Fernando Alliprandini - FAPESP |
dc.contributor.author.fl_str_mv |
Motomiya, Wagner Rogério |
dc.subject.por.fl_str_mv |
Soja GM Soja Estratificação ambiental Adaptabilidade Estabilidade Brasil. Soybean GMO Environmental stratification Adaptability and stability Brazil. Ciências Agrárias Agronomia |
topic |
Soja GM Soja Estratificação ambiental Adaptabilidade Estabilidade Brasil. Soybean GMO Environmental stratification Adaptability and stability Brazil. Ciências Agrárias Agronomia |
description |
New soybean varieties have always been released in the market of agricultural commodities. However, before being registered in the National Cultivar Register Council (RNC), they need to have different trait responses in comparison with the usual cultivars. Searching for more productive genotypes with stability, adaptability, resistance or tolerance to biotic and abiotic components in their respective growing environment has been the main objective of soybean breeding programs. The aim of this study was to evaluate the stability and adaptability of genetically modified insects-resistant and glyphosate-tolerant soybean genotypes as well as to test three multivariate methods of environmental stratification to identify homogeneous regions in the Paraná and Mato Grosso do Sul States. In the first chapter, 19 genotypes were clustered in two groups of relative maturity: high early (RM from 5.0 to 5.9) and early (RM from 6.0 to 6.7) RM during the two growing seasons of 2010/2011 and 2011/2012 when seven representative Counties usually cultivated with soybean were investigated. Both groups were evaluated using the alternative approach based on the supplementary genotype in the AMMI analysis (Additive Main Effects and Multiplicative Interaction Analysis). Thereafter, these results were compared with those from the methods of Eberhart and Russell (1966), Cruz et al. (1989) and Huenh (1990a). The insects-resistant and glyphosate-tolerant genotypes had satisfactory levels of crop yield and stability. The LS3, LS4 and LS7 cultivars were highlighted among the high early lines. Early lines as the LP3 and LP7 had also greater stability and can be recommended to all these evaluated environments. Evidence of similarity in the stability parameters estimated by the methods of Eberhart and Russell (1966) and Cruz et al. (1989) was found. In the second chapter, the grain yield from 14 sites in the soybean macro-region 2 (MRS 2) was analyzed, during the growing seasons 2010/2011, 2011/ 2012 and 2012/2013. Nine genotypes were tested, using the Murakami and Cruz method, SREG GGE biplot model, and Fox and Rosielle method. Based on the GGE SREG biplot model, the best environments for selecting genotypes were Goioerê and Campo Mourão Counties in the 201 region; the Naviraí County in the 202 region, and Sidrolândia and Maracaju Counties in the 204 region. SREG GGE biplot model gathered fewer clusters among the tested methods because the subdivisions and the new clusters of environments were different from those from the previous model. Based on these three methods, the Cascavel County was found to be a distinct environment in the regionalization proposed by Kaster and Farias (2012). |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2018-04-05T16:28:11Z 2018-04-05T16:28:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.uem.br:8080/jspui/handle/1/1340 |
url |
http://repositorio.uem.br:8080/jspui/handle/1/1340 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil UEM Maringá, PR Programa de Pós-Graduação em Genética de Melhoramento |
publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil UEM Maringá, PR Programa de Pós-Graduação em Genética de Melhoramento |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
collection |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
|
_version_ |
1813258639100608512 |