High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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=S0001-37652020000201029 |
Resumo: | Abstract New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality. |
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Anais da Academia Brasileira de Ciências (Online) |
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High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray imagesautomated image analysisBrachiaria ruziziensisImageJPhenoXrayrelative densityseed X-raysAbstract New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.Academia Brasileira de Ciências2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652020000201029Anais da Academia Brasileira de Ciências v.92 suppl.1 2020reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202020190209info:eu-repo/semantics/openAccessMEDEIROS,ANDRÉ D. DESILVA,LAÉRCIO J. DAPEREIRA,MÁRCIO D.OLIVEIRA,ARIADNE M.S.DIAS,DENISE C.F.S.eng2020-07-02T00:00:00Zoai:scielo:S0001-37652020000201029Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2020-07-02T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
title |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
spellingShingle |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images MEDEIROS,ANDRÉ D. DE automated image analysis Brachiaria ruziziensis ImageJ PhenoXray relative density seed X-rays |
title_short |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
title_full |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
title_fullStr |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
title_full_unstemmed |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
title_sort |
High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images |
author |
MEDEIROS,ANDRÉ D. DE |
author_facet |
MEDEIROS,ANDRÉ D. DE SILVA,LAÉRCIO J. DA PEREIRA,MÁRCIO D. OLIVEIRA,ARIADNE M.S. DIAS,DENISE C.F.S. |
author_role |
author |
author2 |
SILVA,LAÉRCIO J. DA PEREIRA,MÁRCIO D. OLIVEIRA,ARIADNE M.S. DIAS,DENISE C.F.S. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
MEDEIROS,ANDRÉ D. DE SILVA,LAÉRCIO J. DA PEREIRA,MÁRCIO D. OLIVEIRA,ARIADNE M.S. DIAS,DENISE C.F.S. |
dc.subject.por.fl_str_mv |
automated image analysis Brachiaria ruziziensis ImageJ PhenoXray relative density seed X-rays |
topic |
automated image analysis Brachiaria ruziziensis ImageJ PhenoXray relative density seed X-rays |
description |
Abstract New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
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=S0001-37652020000201029 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652020000201029 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765202020190209 |
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.92 suppl.1 2020 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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1754302868567883776 |