Biometric traits as a tool for the identification and breeding of coffea canephora genotypes

Detalhes bibliográficos
Autor(a) principal: Dubberstein, Danielly
Data de Publicação: 2020
Outros Autores: Partelli, Fábio L., Guilhen, J. H. S., Rodrigues, Weverton Pereira, Ramalho, José C., Ribeiro-Barros, Ana Isabel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/120673
Resumo: grants n. 84320893 grants n. 420789/2016-2 n. 304687/2017-0 E-26/202.323/2017 UID/04129/2020 UIDP/04035/2020
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spelling Biometric traits as a tool for the identification and breeding of coffea canephora genotypesBiometricsBreedingClusteringConilon coffeeMultivariate analysisMolecular BiologyGeneticsgrants n. 84320893 grants n. 420789/2016-2 n. 304687/2017-0 E-26/202.323/2017 UID/04129/2020 UIDP/04035/2020Cross-pollination and gametophytic self-incompatibility reduce the stability of Coffea canephora genotypes. This is an important crop for Brazil, the largest producer of this type of coffee and also a major exporter. The study of biometric characteristics is essential to assist in the selection of promising plant materials. We examined the diversity of morpho-agronomic traits of genotypes of C. canephora cv. Conilon through the evaluation of branch and leaf parameters. Assessments included plagiotropic branch length, number of nodes in plagiotropic branches, distance between nodes in plagiotropic branches, orthotropic branch length, number of nodes in orthotropic branch, distance between nodes in orthotropic branch, plant height, canopy diameter, leaf length, leaf width, and leaf area in two periods. The data from the 43 coffee genotypes were tested by multivariate and cluster analyses. Six groups were formed by the Tocher optimization method, and five groups by the unweighted pair group method with arithmetic mean (UPGMA) hierarchical method, suggesting an important genetic variability among plant materials. Both Tocher optimization and UPGMA hierarchical methods were consistent for clustering the genotypes, ordering them in six and five dissimilar groups, respectively, with genotypes 25 and 37 standing out with the greatest dissimilarity, constituting isolated groups by both methods. Pearson’s correlation ranged from very weak to very strong, positive and negative, among the characteristics, as also shown by principal component analyses. These analyses indicated the morpho-agronomic traits with a greater degree of correlation, assisting in the choice of promising plant materials. The genetic parameters estimates demonstrate genetic variability and thus breeding potential within the Conilon coffee genotypes studied. These results emphasize the usefulness of biometric evaluations as a tool for the identification and breeding of genotypes to compose new Conilon coffee cultivars.GeoBioTec - Geobiociências, Geoengenharias e GeotecnologiasRUNDubberstein, DaniellyPartelli, Fábio L.Guilhen, J. H. S.Rodrigues, Weverton PereiraRamalho, José C.Ribeiro-Barros, Ana Isabel2021-07-07T22:19:12Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/120673eng1676-5680PURE: 32400282https://doi.org/10.4238/gmr18541info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:03:09Zoai:run.unl.pt:10362/120673Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:44:25.005121Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
title Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
spellingShingle Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
Dubberstein, Danielly
Biometrics
Breeding
Clustering
Conilon coffee
Multivariate analysis
Molecular Biology
Genetics
title_short Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
title_full Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
title_fullStr Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
title_full_unstemmed Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
title_sort Biometric traits as a tool for the identification and breeding of coffea canephora genotypes
author Dubberstein, Danielly
author_facet Dubberstein, Danielly
Partelli, Fábio L.
Guilhen, J. H. S.
Rodrigues, Weverton Pereira
Ramalho, José C.
Ribeiro-Barros, Ana Isabel
author_role author
author2 Partelli, Fábio L.
Guilhen, J. H. S.
Rodrigues, Weverton Pereira
Ramalho, José C.
Ribeiro-Barros, Ana Isabel
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv GeoBioTec - Geobiociências, Geoengenharias e Geotecnologias
RUN
dc.contributor.author.fl_str_mv Dubberstein, Danielly
Partelli, Fábio L.
Guilhen, J. H. S.
Rodrigues, Weverton Pereira
Ramalho, José C.
Ribeiro-Barros, Ana Isabel
dc.subject.por.fl_str_mv Biometrics
Breeding
Clustering
Conilon coffee
Multivariate analysis
Molecular Biology
Genetics
topic Biometrics
Breeding
Clustering
Conilon coffee
Multivariate analysis
Molecular Biology
Genetics
description grants n. 84320893 grants n. 420789/2016-2 n. 304687/2017-0 E-26/202.323/2017 UID/04129/2020 UIDP/04035/2020
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2021-07-07T22:19:12Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/120673
url http://hdl.handle.net/10362/120673
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1676-5680
PURE: 32400282
https://doi.org/10.4238/gmr18541
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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