Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm

Detalhes bibliográficos
Autor(a) principal: Oliveira, Eder Jorge de
Data de Publicação: 2015
Outros Autores: Santana, Fernanda Alves, Oliveira, Luciana Alves de, Santos, Vanderlei da Silva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/100167
Resumo: The conservation, sustainable evaluation and use of cassava (Manihot esculenta Crantz) genetic resources are essential to the development of new commercial varieties. This study aimed to evaluate the quality of cassava roots and to estimate genetic variation and clustering in cassava germplasm using the Affinity Propagation algorithm (AP), which is based on the concept of "message passing" between data points. AP finds "exemplars" of each group and members of the input set representative of clusters. The genotypic data of 474 cassava accessions were evaluated over a period of two years for starch yield (StYi), root dry matter (DMC), amylose content (AML), and the level of cyanogenic compounds (CyC). The AP algorithm enabled the formation of nine diversity groups, whose number reflects the high genetic diversity of this germplasm. A high homogeneity of genetic distances was observed within all the groups, except for two groups in which there was a partial overlap caused mainly by a high variation of the CyC trait. In addition, no relationship between the genetic structure and CyC (sweet and bitter cassava) was observed. Analysis of variance of the nine clusters confirmed the presence of differences between the groups. Thus, the results of this study can be used in future breeding programs (hybridization or selection) to introduce new genetic variability into commercial cultivars to avoid problems related to low genetic variation and to improve the quality of cassava roots.
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spelling Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm The conservation, sustainable evaluation and use of cassava (Manihot esculenta Crantz) genetic resources are essential to the development of new commercial varieties. This study aimed to evaluate the quality of cassava roots and to estimate genetic variation and clustering in cassava germplasm using the Affinity Propagation algorithm (AP), which is based on the concept of "message passing" between data points. AP finds "exemplars" of each group and members of the input set representative of clusters. The genotypic data of 474 cassava accessions were evaluated over a period of two years for starch yield (StYi), root dry matter (DMC), amylose content (AML), and the level of cyanogenic compounds (CyC). The AP algorithm enabled the formation of nine diversity groups, whose number reflects the high genetic diversity of this germplasm. A high homogeneity of genetic distances was observed within all the groups, except for two groups in which there was a partial overlap caused mainly by a high variation of the CyC trait. In addition, no relationship between the genetic structure and CyC (sweet and bitter cassava) was observed. Analysis of variance of the nine clusters confirmed the presence of differences between the groups. Thus, the results of this study can be used in future breeding programs (hybridization or selection) to introduce new genetic variability into commercial cultivars to avoid problems related to low genetic variation and to improve the quality of cassava roots. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2015-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/10016710.1590/0103-9016-2014-0043Scientia Agricola; v. 72 n. 1 (2015); 53-61Scientia Agricola; Vol. 72 Núm. 1 (2015); 53-61Scientia Agricola; Vol. 72 No. 1 (2015); 53-611678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/100167/98834Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessOliveira, Eder Jorge de Santana, Fernanda Alves Oliveira, Luciana Alves de Santos, Vanderlei da Silva 2015-08-31T11:54:04Zoai:revistas.usp.br:article/100167Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2015-08-31T11:54:04Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
title Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
spellingShingle Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
Oliveira, Eder Jorge de
title_short Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
title_full Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
title_fullStr Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
title_full_unstemmed Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
title_sort Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
author Oliveira, Eder Jorge de
author_facet Oliveira, Eder Jorge de
Santana, Fernanda Alves
Oliveira, Luciana Alves de
Santos, Vanderlei da Silva
author_role author
author2 Santana, Fernanda Alves
Oliveira, Luciana Alves de
Santos, Vanderlei da Silva
author2_role author
author
author
dc.contributor.author.fl_str_mv Oliveira, Eder Jorge de
Santana, Fernanda Alves
Oliveira, Luciana Alves de
Santos, Vanderlei da Silva
description The conservation, sustainable evaluation and use of cassava (Manihot esculenta Crantz) genetic resources are essential to the development of new commercial varieties. This study aimed to evaluate the quality of cassava roots and to estimate genetic variation and clustering in cassava germplasm using the Affinity Propagation algorithm (AP), which is based on the concept of "message passing" between data points. AP finds "exemplars" of each group and members of the input set representative of clusters. The genotypic data of 474 cassava accessions were evaluated over a period of two years for starch yield (StYi), root dry matter (DMC), amylose content (AML), and the level of cyanogenic compounds (CyC). The AP algorithm enabled the formation of nine diversity groups, whose number reflects the high genetic diversity of this germplasm. A high homogeneity of genetic distances was observed within all the groups, except for two groups in which there was a partial overlap caused mainly by a high variation of the CyC trait. In addition, no relationship between the genetic structure and CyC (sweet and bitter cassava) was observed. Analysis of variance of the nine clusters confirmed the presence of differences between the groups. Thus, the results of this study can be used in future breeding programs (hybridization or selection) to introduce new genetic variability into commercial cultivars to avoid problems related to low genetic variation and to improve the quality of cassava roots.
publishDate 2015
dc.date.none.fl_str_mv 2015-02-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/100167
10.1590/0103-9016-2014-0043
url https://www.revistas.usp.br/sa/article/view/100167
identifier_str_mv 10.1590/0103-9016-2014-0043
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/100167/98834
dc.rights.driver.fl_str_mv Copyright (c) 2015 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 72 n. 1 (2015); 53-61
Scientia Agricola; Vol. 72 Núm. 1 (2015); 53-61
Scientia Agricola; Vol. 72 No. 1 (2015); 53-61
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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