SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of Seed Science |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-15372022000100148 |
Resumo: | Abstract: Recently is growing the need for non-invasive, fast, and accurate technologies that can predict seed quality. Between these technologies, X-ray image analysis stand out for evaluation of the internal morphology of the seeds. Thus, the aim of the present study was to evaluate the efficiency of a specialized software for analyzing digital radiographs of Urochloa decumbens seeds called SARS (Sistema de Análise de Radiografias de Sementes - Seed Radiograph Analysis System). Five comercial seed lots of U. decumbens cv. Basilisk were used. The seed lots were produced in the 2018/2019 crop season. Radiographic images of the seeds were analyzed in SARS, through which physical characteristics were obtained. The seeds were then subjected to germination test, in which variables related to the physiological quality were evaluated. It was possible to observe that the seeds with greater germination and vigor showed strong and significant correlations with some of the physical variables obtained using SARS. Thus, high correlation of seedling length and relative seed density is important for validating the seed radiographic image analysis method. SARS proved to be an efficient tool for analyzing digital radiographs of U. decumbens seeds. It can generate descriptors which support morphometric and internal analysis of the seeds. Physical parameters obtained by using the technique have close relationship with the germination and vigor of the seeds. |
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SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seedsforage speciesimage analysisradiographic images of seedsAbstract: Recently is growing the need for non-invasive, fast, and accurate technologies that can predict seed quality. Between these technologies, X-ray image analysis stand out for evaluation of the internal morphology of the seeds. Thus, the aim of the present study was to evaluate the efficiency of a specialized software for analyzing digital radiographs of Urochloa decumbens seeds called SARS (Sistema de Análise de Radiografias de Sementes - Seed Radiograph Analysis System). Five comercial seed lots of U. decumbens cv. Basilisk were used. The seed lots were produced in the 2018/2019 crop season. Radiographic images of the seeds were analyzed in SARS, through which physical characteristics were obtained. The seeds were then subjected to germination test, in which variables related to the physiological quality were evaluated. It was possible to observe that the seeds with greater germination and vigor showed strong and significant correlations with some of the physical variables obtained using SARS. Thus, high correlation of seedling length and relative seed density is important for validating the seed radiographic image analysis method. SARS proved to be an efficient tool for analyzing digital radiographs of U. decumbens seeds. It can generate descriptors which support morphometric and internal analysis of the seeds. Physical parameters obtained by using the technique have close relationship with the germination and vigor of the seeds.ABRATES - Associação Brasileira de Tecnologia de Sementes2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-15372022000100148Journal of Seed Science v.44 2022reponame:Journal of Seed Scienceinstname:Associação Brasileira de Tecnologia de Sementes (ABRATES)instacron:ABRATES10.1590/2317-1545v44264545info:eu-repo/semantics/openAccessRamos,Amanda Karoliny FernandesMedeiros,André Dantas dePereira,Márcio DiasAraújo,Yuri FelipeSilva,Laércio Junio daAlves,Charline Zaratineng2022-11-24T00:00:00Zoai:scielo:S2317-15372022000100148Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=2317-1537&lng=en&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||abrates@abrates.org.br2317-15452317-1537opendoar:2022-11-24T00:00Journal of Seed Science - Associação Brasileira de Tecnologia de Sementes (ABRATES)false |
dc.title.none.fl_str_mv |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
title |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
spellingShingle |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds Ramos,Amanda Karoliny Fernandes forage species image analysis radiographic images of seeds |
title_short |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
title_full |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
title_fullStr |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
title_full_unstemmed |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
title_sort |
SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds |
author |
Ramos,Amanda Karoliny Fernandes |
author_facet |
Ramos,Amanda Karoliny Fernandes Medeiros,André Dantas de Pereira,Márcio Dias Araújo,Yuri Felipe Silva,Laércio Junio da Alves,Charline Zaratin |
author_role |
author |
author2 |
Medeiros,André Dantas de Pereira,Márcio Dias Araújo,Yuri Felipe Silva,Laércio Junio da Alves,Charline Zaratin |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Ramos,Amanda Karoliny Fernandes Medeiros,André Dantas de Pereira,Márcio Dias Araújo,Yuri Felipe Silva,Laércio Junio da Alves,Charline Zaratin |
dc.subject.por.fl_str_mv |
forage species image analysis radiographic images of seeds |
topic |
forage species image analysis radiographic images of seeds |
description |
Abstract: Recently is growing the need for non-invasive, fast, and accurate technologies that can predict seed quality. Between these technologies, X-ray image analysis stand out for evaluation of the internal morphology of the seeds. Thus, the aim of the present study was to evaluate the efficiency of a specialized software for analyzing digital radiographs of Urochloa decumbens seeds called SARS (Sistema de Análise de Radiografias de Sementes - Seed Radiograph Analysis System). Five comercial seed lots of U. decumbens cv. Basilisk were used. The seed lots were produced in the 2018/2019 crop season. Radiographic images of the seeds were analyzed in SARS, through which physical characteristics were obtained. The seeds were then subjected to germination test, in which variables related to the physiological quality were evaluated. It was possible to observe that the seeds with greater germination and vigor showed strong and significant correlations with some of the physical variables obtained using SARS. Thus, high correlation of seedling length and relative seed density is important for validating the seed radiographic image analysis method. SARS proved to be an efficient tool for analyzing digital radiographs of U. decumbens seeds. It can generate descriptors which support morphometric and internal analysis of the seeds. Physical parameters obtained by using the technique have close relationship with the germination and vigor of the seeds. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S2317-15372022000100148 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-15372022000100148 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2317-1545v44264545 |
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 |
ABRATES - Associação Brasileira de Tecnologia de Sementes |
publisher.none.fl_str_mv |
ABRATES - Associação Brasileira de Tecnologia de Sementes |
dc.source.none.fl_str_mv |
Journal of Seed Science v.44 2022 reponame:Journal of Seed Science instname:Associação Brasileira de Tecnologia de Sementes (ABRATES) instacron:ABRATES |
instname_str |
Associação Brasileira de Tecnologia de Sementes (ABRATES) |
instacron_str |
ABRATES |
institution |
ABRATES |
reponame_str |
Journal of Seed Science |
collection |
Journal of Seed Science |
repository.name.fl_str_mv |
Journal of Seed Science - Associação Brasileira de Tecnologia de Sementes (ABRATES) |
repository.mail.fl_str_mv |
||abrates@abrates.org.br |
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1754212983387455488 |