Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRPE |
Texto Completo: | http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9517 |
Resumo: | The objective of this work was to apply artificial intelligence, through the use of the ESOM clustering algorithm, to the study of the genetic diversity of genotypes of table grapes from the Embrapa Semiárido Vine Germplasm Active Bank. The following quantitative agronomic variables of 93 table grape genotypes were evaluated: yield (kg/plant), number of clusters per plant, cluster weight (g), cluster length and width (cm), berry weight (g), length and diameter of berries (mm), soluble solids content (ºBrix), titratable acidity (g/100ml) and soluble solids/titratable acidity ratio. The experiment was carried out in the Experimental Field of Mandacaru, Juazeiro-BA, and data referring to four harvesting seasons (2018.1, 2018.2, 2019.1 and 2019.2) were analyzed. The grouping performed by the ESOM network was able to discover genetic patterns and differences between the studied table grape genotypes, allowing the formation of 10 heterotic groups. Group 0 had the highest maximum values for the variables yield (8.44 kg), cluster weight (520.19 g), cluster length (22.30 cm), cluster width (15.10 cm), weight of berry (8.00 g), berry length (26.84 mm), berry diameter (22.17 mm) and soluble solids (23.90 °Brix) and also presented the highest mean values for cluster weight (331.20 g), cluster length (16.6 cm), cluster width (10.5 cm), berry weight (5.78 g), berry length (23.5 mm) and berry diameter (19.7 mm). The presence of genetic variability for the analyzed variables was evidenced by the formation of genetic variability maps, demonstrating a broad genetic base for the 93 genotypes analyzed. The variables with less variability were cluster length and berry length. The ESOM matrix of genetic similarity indicated the most promising crosses among the 10 heterotic table grape groups based on genetic divergence. The crossing of genotypes from group 0, mostly composed of genotypes with seeds and large berries, with genotypes from group 1, 2, 4, 5 and 7, which are seedless and have smaller berries being the most indicated. Crosses between genotypes from groups 0 and 9 are not indicated. Despite being the most genetically distant groups, all individuals in group 9 have a small berry size and have seeds, characteristics considered undesirable in a table grape breeding program. ESOM proved to be promising in the analysis of genetic diversity and consequent formation of heterotic groups, in addition to indicating which crosses are more promising. Future studies on the validation of ESOM as an efficient grouping method for plant genetic improvement are indicated. |
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MUSSER, Rosimar dos SantosLEÃO, Patricia Coelho de SouzaNASCIMENTO, André Câmara Alves doPRUDÊNCIO, Ricardo Bastos CavalcanteMONTARROYOS, Angélica Virgínia Valoishttp://lattes.cnpq.br/6475049011154793CALDAS, Raphael Miller de Souza2024-02-20T17:26:48Z2021-08-18CALDAS, Raphael Miller de Souza. Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido. 2021. 70 f. Dissertação (Programa de Pós-Graduação em Melhoramento Genético de Plantas) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9517The objective of this work was to apply artificial intelligence, through the use of the ESOM clustering algorithm, to the study of the genetic diversity of genotypes of table grapes from the Embrapa Semiárido Vine Germplasm Active Bank. The following quantitative agronomic variables of 93 table grape genotypes were evaluated: yield (kg/plant), number of clusters per plant, cluster weight (g), cluster length and width (cm), berry weight (g), length and diameter of berries (mm), soluble solids content (ºBrix), titratable acidity (g/100ml) and soluble solids/titratable acidity ratio. The experiment was carried out in the Experimental Field of Mandacaru, Juazeiro-BA, and data referring to four harvesting seasons (2018.1, 2018.2, 2019.1 and 2019.2) were analyzed. The grouping performed by the ESOM network was able to discover genetic patterns and differences between the studied table grape genotypes, allowing the formation of 10 heterotic groups. Group 0 had the highest maximum values for the variables yield (8.44 kg), cluster weight (520.19 g), cluster length (22.30 cm), cluster width (15.10 cm), weight of berry (8.00 g), berry length (26.84 mm), berry diameter (22.17 mm) and soluble solids (23.90 °Brix) and also presented the highest mean values for cluster weight (331.20 g), cluster length (16.6 cm), cluster width (10.5 cm), berry weight (5.78 g), berry length (23.5 mm) and berry diameter (19.7 mm). The presence of genetic variability for the analyzed variables was evidenced by the formation of genetic variability maps, demonstrating a broad genetic base for the 93 genotypes analyzed. The variables with less variability were cluster length and berry length. The ESOM matrix of genetic similarity indicated the most promising crosses among the 10 heterotic table grape groups based on genetic divergence. The crossing of genotypes from group 0, mostly composed of genotypes with seeds and large berries, with genotypes from group 1, 2, 4, 5 and 7, which are seedless and have smaller berries being the most indicated. Crosses between genotypes from groups 0 and 9 are not indicated. Despite being the most genetically distant groups, all individuals in group 9 have a small berry size and have seeds, characteristics considered undesirable in a table grape breeding program. ESOM proved to be promising in the analysis of genetic diversity and consequent formation of heterotic groups, in addition to indicating which crosses are more promising. Future studies on the validation of ESOM as an efficient grouping method for plant genetic improvement are indicated.O objetivo deste trabalho foi aplicar a inteligência artificial, através do uso do algoritmo de agrupamento Emergent self-organizing maps (ESOM), ao estudo da diversidade genética de acessos de uvas de mesa do Banco Ativo de Germoplasma de videira da Embrapa Semiárido. Foram avaliadas as seguintes variáveis agronômicas quantitativas de 93 acessos de uva de mesa: produção (kg/planta), número de cachos por planta, peso do cacho (g), comprimento e largura dos cachos (cm), peso da baga (g), comprimento e diâmetro das bagas (mm), teor de sólidos solúveis (ºBrix), acidez titulável (g/100ml) e relação de sólidos solúveis/acidez titulável. O experimento foi realizado no Campo Experimental de Mandacaru, Juazeiro-BA, sendo analisados os dados referentes a quatro safras (2018.1, 2018.2, 2019.1 e 2019.2). O agrupamento realizado pelo algoritmo ESOM foi capaz de descobrir padrões genéticos e diferenças entre os acessos de uva de mesa estudados, permitindo a formação de 10 grupos heteróticos. O grupo 0 apresentou os maiores valores máximos para as variáveis produção (8,44 kg), peso do cacho (520,19 g), comprimento do cacho (22,30 cm), largura do cacho (15,10 cm), peso da baga (8,00 g), comprimento da baga (26,84 mm), diâmetro da baga (22,17 mm) e sólidos solúveis (23,90 °Brix). Também apresentou os maiores valores médios para o peso do cacho (331,20 g), comprimento do cacho (16,6 cm), largura do cacho (10,5 cm), peso da baga (5,78 g), comprimento da baga (23,5 mm) e diâmetro da baga (19,7 mm). A presença de variabilidade genética para as variáveis analisadas foi evidenciada pela formação dos mapas de variabilidade genética, demonstrando ampla base genética para os 93 acessos analisados. A matriz ESOM de similaridade genética indicou os cruzamentos mais promissores entre os 10 grupos heteróticos de uva de mesa com base na divergência genética. O cruzamento de genótipos do grupo 0, composto por genótipos, em sua maioria, pirênicos e com bagas de tamanho grande, com genótipos dos grupo 1, 2, 4, 5 e 7, que sejam apirênicos e de bagas de tamanho menor são os mais indicados. Cruzamentos entre genótipos dos grupos 0 e 9 não são indicados. Apesar de serem os grupos mais distantes geneticamente, todos os indivíduos do grupo 9 possuem um tamanho pequeno de baga e sementes, características consideradas indesejáveis em um programa de melhoramento genético de uvas de mesa. Os ESOM se mostraram promissores na análise da diversidade genética e consequente formação de grupos heteróticos, além de indicar quais cruzamentos mais promissores. Estudos futuros sobre a validação dos ESOM como um método de agrupamento eficiente no melhoramento genético de plantas são indicados.Submitted by (ana.araujo@ufrpe.br) on 2024-02-20T17:26:47Z No. of bitstreams: 1 Raphael Miller de Souza Caldas.pdf: 1362716 bytes, checksum: 4aba7dd0b22061507c469837fb5cdda4 (MD5)Made available in DSpace on 2024-02-20T17:26:48Z (GMT). No. of bitstreams: 1 Raphael Miller de Souza Caldas.pdf: 1362716 bytes, checksum: 4aba7dd0b22061507c469837fb5cdda4 (MD5) Previous issue date: 2021-08-18application/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Melhoramento Genético de PlantasUFRPEBrasilDepartamento de AgronomiaVideiraVariabilidade genéticaInteligência artificialAgrupamento de dadosRecurso genéticoFITOTECNIA::MELHORAMENTO VEGETALInteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiáridoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-6234655866848882505600600600-68005538799722292052615607299470131967info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEORIGINALRaphael Miller de Souza Caldas.pdfRaphael Miller de Souza Caldas.pdfapplication/pdf1362716http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9517/2/Raphael+Miller+de+Souza+Caldas.pdf4aba7dd0b22061507c469837fb5cdda4MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9517/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede2/95172024-02-20 14:26:48.719oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:38:22.779693Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.por.fl_str_mv |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
title |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
spellingShingle |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido CALDAS, Raphael Miller de Souza Videira Variabilidade genética Inteligência artificial Agrupamento de dados Recurso genético FITOTECNIA::MELHORAMENTO VEGETAL |
title_short |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
title_full |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
title_fullStr |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
title_full_unstemmed |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
title_sort |
Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido |
author |
CALDAS, Raphael Miller de Souza |
author_facet |
CALDAS, Raphael Miller de Souza |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
MUSSER, Rosimar dos Santos |
dc.contributor.advisor-co1.fl_str_mv |
LEÃO, Patricia Coelho de Souza |
dc.contributor.advisor-co2.fl_str_mv |
NASCIMENTO, André Câmara Alves do |
dc.contributor.referee1.fl_str_mv |
PRUDÊNCIO, Ricardo Bastos Cavalcante |
dc.contributor.referee2.fl_str_mv |
MONTARROYOS, Angélica Virgínia Valois |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6475049011154793 |
dc.contributor.author.fl_str_mv |
CALDAS, Raphael Miller de Souza |
contributor_str_mv |
MUSSER, Rosimar dos Santos LEÃO, Patricia Coelho de Souza NASCIMENTO, André Câmara Alves do PRUDÊNCIO, Ricardo Bastos Cavalcante MONTARROYOS, Angélica Virgínia Valois |
dc.subject.por.fl_str_mv |
Videira Variabilidade genética Inteligência artificial Agrupamento de dados Recurso genético |
topic |
Videira Variabilidade genética Inteligência artificial Agrupamento de dados Recurso genético FITOTECNIA::MELHORAMENTO VEGETAL |
dc.subject.cnpq.fl_str_mv |
FITOTECNIA::MELHORAMENTO VEGETAL |
description |
The objective of this work was to apply artificial intelligence, through the use of the ESOM clustering algorithm, to the study of the genetic diversity of genotypes of table grapes from the Embrapa Semiárido Vine Germplasm Active Bank. The following quantitative agronomic variables of 93 table grape genotypes were evaluated: yield (kg/plant), number of clusters per plant, cluster weight (g), cluster length and width (cm), berry weight (g), length and diameter of berries (mm), soluble solids content (ºBrix), titratable acidity (g/100ml) and soluble solids/titratable acidity ratio. The experiment was carried out in the Experimental Field of Mandacaru, Juazeiro-BA, and data referring to four harvesting seasons (2018.1, 2018.2, 2019.1 and 2019.2) were analyzed. The grouping performed by the ESOM network was able to discover genetic patterns and differences between the studied table grape genotypes, allowing the formation of 10 heterotic groups. Group 0 had the highest maximum values for the variables yield (8.44 kg), cluster weight (520.19 g), cluster length (22.30 cm), cluster width (15.10 cm), weight of berry (8.00 g), berry length (26.84 mm), berry diameter (22.17 mm) and soluble solids (23.90 °Brix) and also presented the highest mean values for cluster weight (331.20 g), cluster length (16.6 cm), cluster width (10.5 cm), berry weight (5.78 g), berry length (23.5 mm) and berry diameter (19.7 mm). The presence of genetic variability for the analyzed variables was evidenced by the formation of genetic variability maps, demonstrating a broad genetic base for the 93 genotypes analyzed. The variables with less variability were cluster length and berry length. The ESOM matrix of genetic similarity indicated the most promising crosses among the 10 heterotic table grape groups based on genetic divergence. The crossing of genotypes from group 0, mostly composed of genotypes with seeds and large berries, with genotypes from group 1, 2, 4, 5 and 7, which are seedless and have smaller berries being the most indicated. Crosses between genotypes from groups 0 and 9 are not indicated. Despite being the most genetically distant groups, all individuals in group 9 have a small berry size and have seeds, characteristics considered undesirable in a table grape breeding program. ESOM proved to be promising in the analysis of genetic diversity and consequent formation of heterotic groups, in addition to indicating which crosses are more promising. Future studies on the validation of ESOM as an efficient grouping method for plant genetic improvement are indicated. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021-08-18 |
dc.date.accessioned.fl_str_mv |
2024-02-20T17:26:48Z |
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 |
CALDAS, Raphael Miller de Souza. Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido. 2021. 70 f. Dissertação (Programa de Pós-Graduação em Melhoramento Genético de Plantas) - Universidade Federal Rural de Pernambuco, Recife. |
dc.identifier.uri.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9517 |
identifier_str_mv |
CALDAS, Raphael Miller de Souza. Inteligência artificial aplicada ao estudo da diversidade genética do Banco de Germoplasma de videira da EMBRAPA Semiárido. 2021. 70 f. Dissertação (Programa de Pós-Graduação em Melhoramento Genético de Plantas) - Universidade Federal Rural de Pernambuco, Recife. |
url |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9517 |
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por |
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por |
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openAccess |
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Universidade Federal Rural de Pernambuco |
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Programa de Pós-Graduação em Melhoramento Genético de Plantas |
dc.publisher.initials.fl_str_mv |
UFRPE |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Departamento de Agronomia |
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Universidade Federal Rural de Pernambuco |
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