Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds

Detalhes bibliográficos
Autor(a) principal: Medeiros,André Dantas de
Data de Publicação: 2018
Outros Autores: Araújo,Joyce de Oliveira, León,Manuel Jesús Zavala, Silva,Laércio Junio da, Dias,Denise Cunha Fernandes dos Santos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência e Agrotecnologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000600643
Resumo: ABSTRACT Non-destructive and high performance analyses are highly desirable and important for assessing the quality of forest seeds. The aim of this study was to relate parameters obtained from semi-automated analysis of radiographs of Leucaena leucocephala seeds to their physiological potential by means of multivariate analysis. To do so, seeds from five lots collected from parent trees from the region of Viçosa, MG, Brazil, were used. The study was carried out through analysis of radiographic images of seeds, from which the percentage of damaged seeds (predation and fungi), and measurements of area, perimeter, circularity, relative density, and integrated density of the seeds were obtained. After the X-ray test, the seeds were tested for germination in order to assess variables related to seed physiological quality. Multivariate statistics were applied to the data generated, with use of principal component analysis (PCA). X-ray testing allowed visualization of details of the internal structure of seeds and differences regarding density of seed tissues. Semi-automated analysis of radiographic images of Leucaena leucocephala seeds provides information on seed physical characteristics and generates parameters related to seed physiological quality in a simple, fast, and inexpensive manner.
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spelling Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seedsForest speciesimage analysismultivariate analysisrelative densityseed radiographyABSTRACT Non-destructive and high performance analyses are highly desirable and important for assessing the quality of forest seeds. The aim of this study was to relate parameters obtained from semi-automated analysis of radiographs of Leucaena leucocephala seeds to their physiological potential by means of multivariate analysis. To do so, seeds from five lots collected from parent trees from the region of Viçosa, MG, Brazil, were used. The study was carried out through analysis of radiographic images of seeds, from which the percentage of damaged seeds (predation and fungi), and measurements of area, perimeter, circularity, relative density, and integrated density of the seeds were obtained. After the X-ray test, the seeds were tested for germination in order to assess variables related to seed physiological quality. Multivariate statistics were applied to the data generated, with use of principal component analysis (PCA). X-ray testing allowed visualization of details of the internal structure of seeds and differences regarding density of seed tissues. Semi-automated analysis of radiographic images of Leucaena leucocephala seeds provides information on seed physical characteristics and generates parameters related to seed physiological quality in a simple, fast, and inexpensive manner.Editora da UFLA2018-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000600643Ciência e Agrotecnologia v.42 n.6 2018reponame:Ciência e Agrotecnologia (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLA10.1590/1413-70542018426023318info:eu-repo/semantics/openAccessMedeiros,André Dantas deAraújo,Joyce de OliveiraLeón,Manuel Jesús ZavalaSilva,Laércio Junio daDias,Denise Cunha Fernandes dos Santoseng2019-01-28T00:00:00Zoai:scielo:S1413-70542018000600643Revistahttp://www.scielo.br/cagroPUBhttps://old.scielo.br/oai/scielo-oai.php||renpaiva@dbi.ufla.br|| editora@editora.ufla.br1981-18291413-7054opendoar:2022-11-22T16:31:36.889517Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
title Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
spellingShingle Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
Medeiros,André Dantas de
Forest species
image analysis
multivariate analysis
relative density
seed radiography
title_short Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
title_full Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
title_fullStr Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
title_full_unstemmed Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
title_sort Parameters based on X-ray images to assess the physical and physiological quality of Leucaena leucocephala seeds
author Medeiros,André Dantas de
author_facet Medeiros,André Dantas de
Araújo,Joyce de Oliveira
León,Manuel Jesús Zavala
Silva,Laércio Junio da
Dias,Denise Cunha Fernandes dos Santos
author_role author
author2 Araújo,Joyce de Oliveira
León,Manuel Jesús Zavala
Silva,Laércio Junio da
Dias,Denise Cunha Fernandes dos Santos
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Medeiros,André Dantas de
Araújo,Joyce de Oliveira
León,Manuel Jesús Zavala
Silva,Laércio Junio da
Dias,Denise Cunha Fernandes dos Santos
dc.subject.por.fl_str_mv Forest species
image analysis
multivariate analysis
relative density
seed radiography
topic Forest species
image analysis
multivariate analysis
relative density
seed radiography
description ABSTRACT Non-destructive and high performance analyses are highly desirable and important for assessing the quality of forest seeds. The aim of this study was to relate parameters obtained from semi-automated analysis of radiographs of Leucaena leucocephala seeds to their physiological potential by means of multivariate analysis. To do so, seeds from five lots collected from parent trees from the region of Viçosa, MG, Brazil, were used. The study was carried out through analysis of radiographic images of seeds, from which the percentage of damaged seeds (predation and fungi), and measurements of area, perimeter, circularity, relative density, and integrated density of the seeds were obtained. After the X-ray test, the seeds were tested for germination in order to assess variables related to seed physiological quality. Multivariate statistics were applied to the data generated, with use of principal component analysis (PCA). X-ray testing allowed visualization of details of the internal structure of seeds and differences regarding density of seed tissues. Semi-automated analysis of radiographic images of Leucaena leucocephala seeds provides information on seed physical characteristics and generates parameters related to seed physiological quality in a simple, fast, and inexpensive manner.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-01
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=S1413-70542018000600643
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000600643
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1413-70542018426023318
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 Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv Ciência e Agrotecnologia v.42 n.6 2018
reponame:Ciência e Agrotecnologia (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Ciência e Agrotecnologia (Online)
collection Ciência e Agrotecnologia (Online)
repository.name.fl_str_mv Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv ||renpaiva@dbi.ufla.br|| editora@editora.ufla.br
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