Path analysis for selection of feijoa with greater pulp weight
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ciência Rural |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000600203 |
Resumo: | ABSTRACT: The objective of this paper was to identify the direct and indirect effects of feijoa fruits (Acca sellowiana) traitson pulp weight, in order to use these traits in indirect genotypes selection. Fruits of five feijoa plants were collected in Rio Grande do Sul, in the years of 2009, 2010 and 2011. Six traits were evaluated: diameter, length, total weight, pulp weight, peel thickness and number of seeds per fruit. In the path analysis, with or without ridge regression, pulp weight was considered as the basic variable, and the other traits were considered as explanatory variables. Total weight and fruit diameter had high direct effect, and are the main traits associated with pulp weight. These traits may serve as criteria for indirect selection to increase feijoa pulp weight, since they are easy to be measured. |
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Ciência rural (Online) |
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Path analysis for selection of feijoa with greater pulp weightAcca sellowianamulticollinearityridge path analysisindirect selectionABSTRACT: The objective of this paper was to identify the direct and indirect effects of feijoa fruits (Acca sellowiana) traitson pulp weight, in order to use these traits in indirect genotypes selection. Fruits of five feijoa plants were collected in Rio Grande do Sul, in the years of 2009, 2010 and 2011. Six traits were evaluated: diameter, length, total weight, pulp weight, peel thickness and number of seeds per fruit. In the path analysis, with or without ridge regression, pulp weight was considered as the basic variable, and the other traits were considered as explanatory variables. Total weight and fruit diameter had high direct effect, and are the main traits associated with pulp weight. These traits may serve as criteria for indirect selection to increase feijoa pulp weight, since they are easy to be measured.Universidade Federal de Santa Maria2017-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000600203Ciência Rural v.47 n.6 2017reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20161062info:eu-repo/semantics/openAccessDonazzolo,JoelSalla,Vanessa PadilhaSasso,Simone Aparecida ZoletDanner,Moeses AndrigoCitadin,IdemirNodari,Rubens Onofreeng2017-05-02T00:00:00ZRevista |
dc.title.none.fl_str_mv |
Path analysis for selection of feijoa with greater pulp weight |
title |
Path analysis for selection of feijoa with greater pulp weight |
spellingShingle |
Path analysis for selection of feijoa with greater pulp weight Donazzolo,Joel Acca sellowiana multicollinearity ridge path analysis indirect selection |
title_short |
Path analysis for selection of feijoa with greater pulp weight |
title_full |
Path analysis for selection of feijoa with greater pulp weight |
title_fullStr |
Path analysis for selection of feijoa with greater pulp weight |
title_full_unstemmed |
Path analysis for selection of feijoa with greater pulp weight |
title_sort |
Path analysis for selection of feijoa with greater pulp weight |
author |
Donazzolo,Joel |
author_facet |
Donazzolo,Joel Salla,Vanessa Padilha Sasso,Simone Aparecida Zolet Danner,Moeses Andrigo Citadin,Idemir Nodari,Rubens Onofre |
author_role |
author |
author2 |
Salla,Vanessa Padilha Sasso,Simone Aparecida Zolet Danner,Moeses Andrigo Citadin,Idemir Nodari,Rubens Onofre |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Donazzolo,Joel Salla,Vanessa Padilha Sasso,Simone Aparecida Zolet Danner,Moeses Andrigo Citadin,Idemir Nodari,Rubens Onofre |
dc.subject.por.fl_str_mv |
Acca sellowiana multicollinearity ridge path analysis indirect selection |
topic |
Acca sellowiana multicollinearity ridge path analysis indirect selection |
description |
ABSTRACT: The objective of this paper was to identify the direct and indirect effects of feijoa fruits (Acca sellowiana) traitson pulp weight, in order to use these traits in indirect genotypes selection. Fruits of five feijoa plants were collected in Rio Grande do Sul, in the years of 2009, 2010 and 2011. Six traits were evaluated: diameter, length, total weight, pulp weight, peel thickness and number of seeds per fruit. In the path analysis, with or without ridge regression, pulp weight was considered as the basic variable, and the other traits were considered as explanatory variables. Total weight and fruit diameter had high direct effect, and are the main traits associated with pulp weight. These traits may serve as criteria for indirect selection to increase feijoa pulp weight, since they are easy to be measured. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 |
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=S0103-84782017000600203 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000600203 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-8478cr20161062 |
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 |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência Rural v.47 n.6 2017 reponame:Ciência Rural instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Ciência Rural |
collection |
Ciência Rural |
repository.name.fl_str_mv |
|
repository.mail.fl_str_mv |
|
_version_ |
1749140551333052416 |