Modelos biométricos aplicados na seleção de gerações avançadas de trigo
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/19632 |
Resumo: | Wheat is a cereal that has great economic importance in Brazil, the country produces 5,1 million tons, this situation makes the country one of the largest importers of this cereal. Thus, genetic improvement is of great importance in an attempt to increase yield, productivity and quality of the wheat produced. In addition, increasing the efficiency of breeding programs is essential to reducing the costs and time required to launch new cultivars. The objective of this study was to evaluate advanced wheat generations using multivariate and biometric models in order to obtain information for selecting superior genotypes. The research was conducted in the experimental area of the Laboratory of Genetic Improvement and Plant Production, Federal University of Santa Maria, Frederico Westphalen Campus / RS. For this purpose, 420 wheat genotypes were initially used in the F5 generation, conducted in the experimental design of families with interim controls in the 2017 agricultural year. The F6 generation was conducted with fifteen wheat genotypes, arranged in three replicates in 2018. The following characters were evaluated: a) days from emergence to flowering; b) plant height; c) spike length; d) number of fertile tillers; e) spike weight; f) kernel weight; g) number of spikelets; h) number of kernels per plant; (i) total plant kernel weight. Subsequently, the F7 generation was conducted in the field in a randomized complete block design. The following characters were evaluated: a) plant height; b) spikelets insertion height; c) number of fertile tillers; d) kernel width; e) hectolitic weight; f) number of spikelets and g) kernel weight per plant. From the information obtained, the genotypes were submitted to selection gain analysis and selection indices, variance components and genetic parameters, genetic diversity, phenotypic, genetic and environmental correlations, as well as predicted genotypic values. The selection of plants with higher tiller numbers increased in more productive genotypes. The formation of distinct groups indicated the presence of genetic variability among the evaluated populations. The cycle is the variable that presented the largest contribution to genetic divergence among the studied genotypes. The use of selection indices is advantageous in advanced wheat generations, since they provide selection gains, distributed among all evaluated characters, a situation that is better suited to breeding programs. The FAI-BLUP index revealed the possibility of reduction for plant height and increase in gains for tiller number and total grain mass per plant. The UFSM FW1 02 genotype provides to be superior to the control used in the assays, being able to be evaluated in cultivation and use value assays, since it gathers characteristics closer to the ideal, presenting high productive potential. |
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2020-02-20T12:56:16Z2020-02-20T12:56:16Z2019-11-20http://repositorio.ufsm.br/handle/1/19632Wheat is a cereal that has great economic importance in Brazil, the country produces 5,1 million tons, this situation makes the country one of the largest importers of this cereal. Thus, genetic improvement is of great importance in an attempt to increase yield, productivity and quality of the wheat produced. In addition, increasing the efficiency of breeding programs is essential to reducing the costs and time required to launch new cultivars. The objective of this study was to evaluate advanced wheat generations using multivariate and biometric models in order to obtain information for selecting superior genotypes. The research was conducted in the experimental area of the Laboratory of Genetic Improvement and Plant Production, Federal University of Santa Maria, Frederico Westphalen Campus / RS. For this purpose, 420 wheat genotypes were initially used in the F5 generation, conducted in the experimental design of families with interim controls in the 2017 agricultural year. The F6 generation was conducted with fifteen wheat genotypes, arranged in three replicates in 2018. The following characters were evaluated: a) days from emergence to flowering; b) plant height; c) spike length; d) number of fertile tillers; e) spike weight; f) kernel weight; g) number of spikelets; h) number of kernels per plant; (i) total plant kernel weight. Subsequently, the F7 generation was conducted in the field in a randomized complete block design. The following characters were evaluated: a) plant height; b) spikelets insertion height; c) number of fertile tillers; d) kernel width; e) hectolitic weight; f) number of spikelets and g) kernel weight per plant. From the information obtained, the genotypes were submitted to selection gain analysis and selection indices, variance components and genetic parameters, genetic diversity, phenotypic, genetic and environmental correlations, as well as predicted genotypic values. The selection of plants with higher tiller numbers increased in more productive genotypes. The formation of distinct groups indicated the presence of genetic variability among the evaluated populations. The cycle is the variable that presented the largest contribution to genetic divergence among the studied genotypes. The use of selection indices is advantageous in advanced wheat generations, since they provide selection gains, distributed among all evaluated characters, a situation that is better suited to breeding programs. The FAI-BLUP index revealed the possibility of reduction for plant height and increase in gains for tiller number and total grain mass per plant. The UFSM FW1 02 genotype provides to be superior to the control used in the assays, being able to be evaluated in cultivation and use value assays, since it gathers characteristics closer to the ideal, presenting high productive potential.O trigo é um cereal que apresenta grande importância econômica no Brasil, o país produz 5,1 milhões de toneladas, essa situação faz com que o país seja um dos maiores importadores do cereal. Assim, o melhoramento genético tem grande importância na busca por aumento da produtividade e a qualidade do trigo produzido. Além disso, aumentar a eficiência dos programas de melhoramento é essencial para reduzir os custos e o tempo necessários para o lançamento de novas cultivares. O objetivo do estudo/pesquisa foi avaliar gerações avançadas de trigo por meio de modelos multivariados e biométricos, a fim de obter informações para seleção de genótipos superiores. A pesquisa foi conduzida na área experimental do Laboratório de Melhoramento Genético e Produção de Plantas, da Universidade Federal de Santa Maria, Campus de Frederico Westphalen/RS. Para tanto foram utilizadas inicialmente 420 progênies de trigo na geração F5, conduzidos no delineamento experimental de famílias com testemunhas intercalares, no ano agrícola de 2017. A geração F6 foi conduzida com quinze genótipos de trigo, dispostas em três repetições em 2018. Foram avaliados os seguintes caracteres: a) dias da emergência ao florescimento; b) altura de planta; c) comprimento da espiga; d) número de afilhos férteis; e) massa da espiga; f) massa de grãos da espiga; g) número de espiguetas; h) número de grãos por planta; i) massa total de grãos da planta. Posteriormente a geração F7 foi conduzida a campo no delineamento experimental de blocos casualizados, sendo onze genótipos de trigo, dispostas em três repetições. Foram avaliados os seguintes caracteres: a) altura de planta; b) altura de inserção de espiga; c) número de afilhos férteis; d) largura de grão; e) massa hectolitrica; f) número de espiguetas e g) massa de grãos por planta. A partir das informações obtidas, os genótipos foram submetidos a análise de ganhos por seleção e índices de seleção, componentes de variância e parâmetros genéticos, diversidade genética, correlações fenotípicas, genéticas e ambientais, além de valores genotípicos preditos. A seleção de plantas com maior número de afilhos, resultou em genótipos mais produtivos. A formação de grupos distintos indicou a presença de variabilidade genética entre as populações avaliadas. O ciclo é variável e apresentou a maior contribuição para divergência genética entre os genótipos estudados. O uso dos índices de seleção é vantajoso em gerações avançadas de trigo, uma vez que estes proporcionam ganhos com a seleção, distribuídos entre todos os caracteres avaliados, situação mais adequada aos programas de melhoramento. O índice FAI-BLUP revelou a possibilidade de redução para altura de planta e aumento nos ganhos para número de afilhos e massa total de grãos por planta. O genótipo UFSM FW1 02 se mostrou superior a testemunha utilizada nos ensaios, estando apta a ser avaliada em ensaios de valor de cultivo e uso, pois reúne características mais próximas do ideal, apresentando elevado potencial produtivo.Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqporUniversidade Federal de Santa MariaUFSM Frederico WestphalenPrograma de Pós-Graduação em Agronomia - Agricultura e AmbienteUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessModelos biométricosDivergência genéticaParâmetros genéticosTriticum aestivum LBiometric modelsGenetic divergenceGenetic parametersTriticum aestivum LCNPQ::CIENCIAS AGRARIAS::AGRONOMIAModelos biométricos aplicados na seleção de gerações avançadas de trigoBiometric models applied in selecting advanced wheat generationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisMarchioro, Volmir Sergiohttp://lattes.cnpq.br/3744130894870798Follmann, Diego Nicolauhttp://lattes.cnpq.br/0243535910191720Nardino, Maiconhttp://lattes.cnpq.br/7811009170361239http://lattes.cnpq.br/0438730068843897Meier, Carine5001000000096009455af8c-9ffa-465d-a5a2-0a472c7c42300357cdde-a210-45dc-8c77-8d7a243e8a03a0820514-037f-447e-a8cf-3a95dcfc87738a0cc736-4350-4cf3-a9a1-810be4832105reponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGAAA_2019_MEIER_CARINE.pdfDIS_PPGAAA_2019_MEIER_CARINE.pdfDissertação de Mestradoapplication/pdf2474840http://repositorio.ufsm.br/bitstream/1/19632/1/DIS_PPGAAA_2019_MEIER_CARINE.pdf1288fd5239cc4462d000367017df417aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
dc.title.alternative.eng.fl_str_mv |
Biometric models applied in selecting advanced wheat generations |
title |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
spellingShingle |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo Meier, Carine Modelos biométricos Divergência genética Parâmetros genéticos Triticum aestivum L Biometric models Genetic divergence Genetic parameters Triticum aestivum L CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
title_full |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
title_fullStr |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
title_full_unstemmed |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
title_sort |
Modelos biométricos aplicados na seleção de gerações avançadas de trigo |
author |
Meier, Carine |
author_facet |
Meier, Carine |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Marchioro, Volmir Sergio |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/3744130894870798 |
dc.contributor.referee1.fl_str_mv |
Follmann, Diego Nicolau |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/0243535910191720 |
dc.contributor.referee2.fl_str_mv |
Nardino, Maicon |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/7811009170361239 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0438730068843897 |
dc.contributor.author.fl_str_mv |
Meier, Carine |
contributor_str_mv |
Marchioro, Volmir Sergio Follmann, Diego Nicolau Nardino, Maicon |
dc.subject.por.fl_str_mv |
Modelos biométricos Divergência genética Parâmetros genéticos Triticum aestivum L |
topic |
Modelos biométricos Divergência genética Parâmetros genéticos Triticum aestivum L Biometric models Genetic divergence Genetic parameters Triticum aestivum L CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Biometric models Genetic divergence Genetic parameters Triticum aestivum L |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
Wheat is a cereal that has great economic importance in Brazil, the country produces 5,1 million tons, this situation makes the country one of the largest importers of this cereal. Thus, genetic improvement is of great importance in an attempt to increase yield, productivity and quality of the wheat produced. In addition, increasing the efficiency of breeding programs is essential to reducing the costs and time required to launch new cultivars. The objective of this study was to evaluate advanced wheat generations using multivariate and biometric models in order to obtain information for selecting superior genotypes. The research was conducted in the experimental area of the Laboratory of Genetic Improvement and Plant Production, Federal University of Santa Maria, Frederico Westphalen Campus / RS. For this purpose, 420 wheat genotypes were initially used in the F5 generation, conducted in the experimental design of families with interim controls in the 2017 agricultural year. The F6 generation was conducted with fifteen wheat genotypes, arranged in three replicates in 2018. The following characters were evaluated: a) days from emergence to flowering; b) plant height; c) spike length; d) number of fertile tillers; e) spike weight; f) kernel weight; g) number of spikelets; h) number of kernels per plant; (i) total plant kernel weight. Subsequently, the F7 generation was conducted in the field in a randomized complete block design. The following characters were evaluated: a) plant height; b) spikelets insertion height; c) number of fertile tillers; d) kernel width; e) hectolitic weight; f) number of spikelets and g) kernel weight per plant. From the information obtained, the genotypes were submitted to selection gain analysis and selection indices, variance components and genetic parameters, genetic diversity, phenotypic, genetic and environmental correlations, as well as predicted genotypic values. The selection of plants with higher tiller numbers increased in more productive genotypes. The formation of distinct groups indicated the presence of genetic variability among the evaluated populations. The cycle is the variable that presented the largest contribution to genetic divergence among the studied genotypes. The use of selection indices is advantageous in advanced wheat generations, since they provide selection gains, distributed among all evaluated characters, a situation that is better suited to breeding programs. The FAI-BLUP index revealed the possibility of reduction for plant height and increase in gains for tiller number and total grain mass per plant. The UFSM FW1 02 genotype provides to be superior to the control used in the assays, being able to be evaluated in cultivation and use value assays, since it gathers characteristics closer to the ideal, presenting high productive potential. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-11-20 |
dc.date.accessioned.fl_str_mv |
2020-02-20T12:56:16Z |
dc.date.available.fl_str_mv |
2020-02-20T12:56:16Z |
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.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/19632 |
url |
http://repositorio.ufsm.br/handle/1/19632 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
500100000009 |
dc.relation.confidence.fl_str_mv |
600 |
dc.relation.authority.fl_str_mv |
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dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria UFSM Frederico Westphalen |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Agronomia - Agricultura e Ambiente |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria UFSM Frederico Westphalen |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
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Universidade Federal de Santa Maria (UFSM) |
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UFSM |
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Manancial - Repositório Digital da UFSM |
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