Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach

Detalhes bibliográficos
Autor(a) principal: Silva, Alessandra Querino da
Data de Publicação: 2022
Outros Autores: Oliveira, Luciano Antonio de, Silva, Carlos Pereira da, Mendes, Cristian Tiago Erazo, Ferreira, Ana Maria Oliveira, Sáfadi, Thelma, Carvalho, Maria Laene Moreira de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Agronomy (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/55960
Resumo: Brachiaria brizantha is the most economically important forage grass in Brazil and is propagated through sowing. Producing high-quality seeds has been a constant challenge due to their uneven maturation. The development and application of precise and non-destructive methods for identifying internal damages to seeds, such as the X-ray test, which quickly indicates the quality of the lots, is of fundamental importance for the seed industry. In this work, the quality of Brachiaria brizantha seeds was analyzed based on the morphological characteristics observed in X-ray images that were related to viability using a mixture model under a Bayesian approach, with the following objectives: i) verify the adequacy of the Bayesian modeling used in the data analysis; ii) associate the efficiency of using radiographs as a way to assess the viability of the seeds; and iii) relate the classifications carried out by evaluators with the probability of originating normal or abnormal seedlings. The methodology applied for the analysis proved to be adequate. Further, the Bayesian estimates for parameters related to internal morphology were established with associated levels of uncertainty, which represents an advantage over usual frequentist methods. Based on the model's estimates, seeds evaluated as potentially unviable by three evaluators had practically no probability of germination and did not germinate in the test applied later. Seeds classified as potentially viable had a high probability of developing into normal seedlings, while 73.27% showed this property in the germination test.
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spelling Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approachSeed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approachmixture model; Bayesian inference; X-ray test.mixture model; Bayesian inference; X-ray test.Brachiaria brizantha is the most economically important forage grass in Brazil and is propagated through sowing. Producing high-quality seeds has been a constant challenge due to their uneven maturation. The development and application of precise and non-destructive methods for identifying internal damages to seeds, such as the X-ray test, which quickly indicates the quality of the lots, is of fundamental importance for the seed industry. In this work, the quality of Brachiaria brizantha seeds was analyzed based on the morphological characteristics observed in X-ray images that were related to viability using a mixture model under a Bayesian approach, with the following objectives: i) verify the adequacy of the Bayesian modeling used in the data analysis; ii) associate the efficiency of using radiographs as a way to assess the viability of the seeds; and iii) relate the classifications carried out by evaluators with the probability of originating normal or abnormal seedlings. The methodology applied for the analysis proved to be adequate. Further, the Bayesian estimates for parameters related to internal morphology were established with associated levels of uncertainty, which represents an advantage over usual frequentist methods. Based on the model's estimates, seeds evaluated as potentially unviable by three evaluators had practically no probability of germination and did not germinate in the test applied later. Seeds classified as potentially viable had a high probability of developing into normal seedlings, while 73.27% showed this property in the germination test.Brachiaria brizantha is the most economically important forage grass in Brazil and is propagated through sowing. Producing high-quality seeds has been a constant challenge due to their uneven maturation. The development and application of precise and non-destructive methods for identifying internal damages to seeds, such as the X-ray test, which quickly indicates the quality of the lots, is of fundamental importance for the seed industry. In this work, the quality of Brachiaria brizantha seeds was analyzed based on the morphological characteristics observed in X-ray images that were related to viability using a mixture model under a Bayesian approach, with the following objectives: i) verify the adequacy of the Bayesian modeling used in the data analysis; ii) associate the efficiency of using radiographs as a way to assess the viability of the seeds; and iii) relate the classifications carried out by evaluators with the probability of originating normal or abnormal seedlings. The methodology applied for the analysis proved to be adequate. Further, the Bayesian estimates for parameters related to internal morphology were established with associated levels of uncertainty, which represents an advantage over usual frequentist methods. Based on the model's estimates, seeds evaluated as potentially unviable by three evaluators had practically no probability of germination and did not germinate in the test applied later. Seeds classified as potentially viable had a high probability of developing into normal seedlings, while 73.27% showed this property in the germination test.Universidade Estadual de Maringá2022-06-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5596010.4025/actasciagron.v44i1.55960Acta Scientiarum. Agronomy; Vol 44 (2022): Publicação contínua; e55960Acta Scientiarum. Agronomy; v. 44 (2022): Publicação contínua; e559601807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/55960/751375154484Copyright (c) 2022 Acta Scientiarum. Agronomyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccess Silva, Alessandra Querino daOliveira, Luciano Antonio de Silva, Carlos Pereira da Mendes, Cristian Tiago ErazoFerreira, Ana Maria Oliveira Sáfadi, ThelmaCarvalho, Maria Laene Moreira de 2022-07-28T14:25:31Zoai:periodicos.uem.br/ojs:article/55960Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgronPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/oaiactaagron@uem.br||actaagron@uem.br|| edamasio@uem.br1807-86211679-9275opendoar:2022-07-28T14:25:31Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
title Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
spellingShingle Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
Silva, Alessandra Querino da
mixture model; Bayesian inference; X-ray test.
mixture model; Bayesian inference; X-ray test.
title_short Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
title_full Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
title_fullStr Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
title_full_unstemmed Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
title_sort Seed quality of Brachiaria brizantha by X-ray image analysis using a Bayesian approach
author Silva, Alessandra Querino da
author_facet Silva, Alessandra Querino da
Oliveira, Luciano Antonio de
Silva, Carlos Pereira da
Mendes, Cristian Tiago Erazo
Ferreira, Ana Maria Oliveira
Sáfadi, Thelma
Carvalho, Maria Laene Moreira de
author_role author
author2 Oliveira, Luciano Antonio de
Silva, Carlos Pereira da
Mendes, Cristian Tiago Erazo
Ferreira, Ana Maria Oliveira
Sáfadi, Thelma
Carvalho, Maria Laene Moreira de
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Silva, Alessandra Querino da
Oliveira, Luciano Antonio de
Silva, Carlos Pereira da
Mendes, Cristian Tiago Erazo
Ferreira, Ana Maria Oliveira
Sáfadi, Thelma
Carvalho, Maria Laene Moreira de
dc.subject.por.fl_str_mv mixture model; Bayesian inference; X-ray test.
mixture model; Bayesian inference; X-ray test.
topic mixture model; Bayesian inference; X-ray test.
mixture model; Bayesian inference; X-ray test.
description Brachiaria brizantha is the most economically important forage grass in Brazil and is propagated through sowing. Producing high-quality seeds has been a constant challenge due to their uneven maturation. The development and application of precise and non-destructive methods for identifying internal damages to seeds, such as the X-ray test, which quickly indicates the quality of the lots, is of fundamental importance for the seed industry. In this work, the quality of Brachiaria brizantha seeds was analyzed based on the morphological characteristics observed in X-ray images that were related to viability using a mixture model under a Bayesian approach, with the following objectives: i) verify the adequacy of the Bayesian modeling used in the data analysis; ii) associate the efficiency of using radiographs as a way to assess the viability of the seeds; and iii) relate the classifications carried out by evaluators with the probability of originating normal or abnormal seedlings. The methodology applied for the analysis proved to be adequate. Further, the Bayesian estimates for parameters related to internal morphology were established with associated levels of uncertainty, which represents an advantage over usual frequentist methods. Based on the model's estimates, seeds evaluated as potentially unviable by three evaluators had practically no probability of germination and did not germinate in the test applied later. Seeds classified as potentially viable had a high probability of developing into normal seedlings, while 73.27% showed this property in the germination test.
publishDate 2022
dc.date.none.fl_str_mv 2022-06-29
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/55960
10.4025/actasciagron.v44i1.55960
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/55960
identifier_str_mv 10.4025/actasciagron.v44i1.55960
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/55960/751375154484
dc.rights.driver.fl_str_mv Copyright (c) 2022 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual de Maringá
publisher.none.fl_str_mv Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Agronomy; Vol 44 (2022): Publicação contínua; e55960
Acta Scientiarum. Agronomy; v. 44 (2022): Publicação contínua; e55960
1807-8621
1679-9275
reponame:Acta Scientiarum. Agronomy (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Agronomy (Online)
collection Acta Scientiarum. Agronomy (Online)
repository.name.fl_str_mv Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaagron@uem.br||actaagron@uem.br|| edamasio@uem.br
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