Genotypic variation of traits related to quality of cassava roots using affinity propagation algorithm
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , , |
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. |
id |
USP-18_ec7daca6ce2567c534162d01e9274c42 |
---|---|
oai_identifier_str |
oai:revistas.usp.br:article/100167 |
network_acronym_str |
USP-18 |
network_name_str |
Scientia Agrícola (Online) |
repository_id_str |
|
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 |
_version_ |
1800222792418852864 |