Relationships of rice yield and quality based on genotype by trait (GT) biplot

Detalhes bibliográficos
Autor(a) principal: SHARIFI,PEYMAN
Data de Publicação: 2018
Outros Autores: EBADI,ALI AKBAR
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100343
Resumo: ABSTRACT An experiment was conducted to examine the influencing characters on rice by using 64 rice genotypes, including four local landraces, four released cultivars and 56 mutant lines (M5) derived from these genotypes, with application of the genotype by trait (GT) biplot methodology. The first two principal components (PC1 and PC2) accounted for 46.6% of total variation in 64 genotypes. The polygon view of GT biplot suggested seven sections for 64 genotypes. The vertex G38 had good amounts of grain yield, panicle length, hundred grain weight, internodes length, plant height and fertility percentage. Generally based on vector view it was demonstrated that the selection of high grain yield would be performed via thousand grain weight, panicle weight and number of filled grain per panicle. These traits should be considered simultaneously as effective selection criteria evolving high yielding rice genotypes because of their large contribution to grain yield. The genotypes G2, G4 and G7 could be considered for the developing of desirable progenies in the selection strategy of rice improvement programs. This study revealed GT biplot can graphically display the interrelationships among traits. In conclusion, it is recommended the use of GGE biplot to identify superior genotypes for simultaneous improvement of several traits.
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spelling Relationships of rice yield and quality based on genotype by trait (GT) biplotGrain yieldpolygon viewtrait associationsricevector viewABSTRACT An experiment was conducted to examine the influencing characters on rice by using 64 rice genotypes, including four local landraces, four released cultivars and 56 mutant lines (M5) derived from these genotypes, with application of the genotype by trait (GT) biplot methodology. The first two principal components (PC1 and PC2) accounted for 46.6% of total variation in 64 genotypes. The polygon view of GT biplot suggested seven sections for 64 genotypes. The vertex G38 had good amounts of grain yield, panicle length, hundred grain weight, internodes length, plant height and fertility percentage. Generally based on vector view it was demonstrated that the selection of high grain yield would be performed via thousand grain weight, panicle weight and number of filled grain per panicle. These traits should be considered simultaneously as effective selection criteria evolving high yielding rice genotypes because of their large contribution to grain yield. The genotypes G2, G4 and G7 could be considered for the developing of desirable progenies in the selection strategy of rice improvement programs. This study revealed GT biplot can graphically display the interrelationships among traits. In conclusion, it is recommended the use of GGE biplot to identify superior genotypes for simultaneous improvement of several traits.Academia Brasileira de Ciências2018-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100343Anais da Academia Brasileira de Ciências v.90 n.1 2018reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201820150852info:eu-repo/semantics/openAccessSHARIFI,PEYMANEBADI,ALI AKBAReng2018-04-25T00:00:00Zoai:scielo:S0001-37652018000100343Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2018-04-25T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Relationships of rice yield and quality based on genotype by trait (GT) biplot
title Relationships of rice yield and quality based on genotype by trait (GT) biplot
spellingShingle Relationships of rice yield and quality based on genotype by trait (GT) biplot
SHARIFI,PEYMAN
Grain yield
polygon view
trait associations
rice
vector view
title_short Relationships of rice yield and quality based on genotype by trait (GT) biplot
title_full Relationships of rice yield and quality based on genotype by trait (GT) biplot
title_fullStr Relationships of rice yield and quality based on genotype by trait (GT) biplot
title_full_unstemmed Relationships of rice yield and quality based on genotype by trait (GT) biplot
title_sort Relationships of rice yield and quality based on genotype by trait (GT) biplot
author SHARIFI,PEYMAN
author_facet SHARIFI,PEYMAN
EBADI,ALI AKBAR
author_role author
author2 EBADI,ALI AKBAR
author2_role author
dc.contributor.author.fl_str_mv SHARIFI,PEYMAN
EBADI,ALI AKBAR
dc.subject.por.fl_str_mv Grain yield
polygon view
trait associations
rice
vector view
topic Grain yield
polygon view
trait associations
rice
vector view
description ABSTRACT An experiment was conducted to examine the influencing characters on rice by using 64 rice genotypes, including four local landraces, four released cultivars and 56 mutant lines (M5) derived from these genotypes, with application of the genotype by trait (GT) biplot methodology. The first two principal components (PC1 and PC2) accounted for 46.6% of total variation in 64 genotypes. The polygon view of GT biplot suggested seven sections for 64 genotypes. The vertex G38 had good amounts of grain yield, panicle length, hundred grain weight, internodes length, plant height and fertility percentage. Generally based on vector view it was demonstrated that the selection of high grain yield would be performed via thousand grain weight, panicle weight and number of filled grain per panicle. These traits should be considered simultaneously as effective selection criteria evolving high yielding rice genotypes because of their large contribution to grain yield. The genotypes G2, G4 and G7 could be considered for the developing of desirable progenies in the selection strategy of rice improvement programs. This study revealed GT biplot can graphically display the interrelationships among traits. In conclusion, it is recommended the use of GGE biplot to identify superior genotypes for simultaneous improvement of several traits.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100343
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100343
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765201820150852
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.90 n.1 2018
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
instacron_str ABC
institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
repository.name.fl_str_mv Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)
repository.mail.fl_str_mv ||aabc@abc.org.br
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