SARS software for analysis of radiographic images of Urochloa decumbens (Stapf) RD Webster seeds

Detalhes bibliográficos
Autor(a) principal: Ramos,Amanda Karoliny Fernandes
Data de Publicação: 2022
Outros Autores: Medeiros,André Dantas de, Pereira,Márcio Dias, Araújo,Yuri Felipe, Silva,Laércio Junio da, Alves,Charline Zaratin
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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spelling 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
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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)
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reponame_str Journal of Seed Science
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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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