Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds

Detalhes bibliográficos
Autor(a) principal: Soares, Júlia Martins
Data de Publicação: 2022
Outros Autores: Medeiros, André Dantas de, Pinheiro, Daniel Teixeira, Rosas, Jorge Tadeu Fim, Silva, Laércio Junio da, Machado, Daniel Lucas Magalhães, Dias, Denise Cunha Fernandes dos Santos
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/57060
Resumo: The use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.
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spelling Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds Glycine max L.seed physiological potentialImageJimage processingGlycine max L.potencial fisiológico de sementesImageJProcessamento de imagensThe use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.The use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.Universidade Estadual de Maringá2022-11-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5706010.4025/actasciagron.v45i1.57060Acta Scientiarum. Agronomy; Vol 45 (2023): Publicação contínua; e57060Acta Scientiarum. Agronomy; v. 45 (2023): Publicação contínua; e570601807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57060/751375155038Copyright (c) 2023 Acta Scientiarum. Agronomyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSoares, Júlia Martins Medeiros, André Dantas dePinheiro, Daniel TeixeiraRosas, Jorge Tadeu FimSilva, Laércio Junio daMachado, Daniel Lucas MagalhãesDias, Denise Cunha Fernandes dos Santos2023-01-31T19:21:07Zoai:periodicos.uem.br/ojs:article/57060Revistahttp://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:2023-01-31T19:21:07Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
title Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
spellingShingle Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
Soares, Júlia Martins
Glycine max L.
seed physiological potential
ImageJ
image processing
Glycine max L.
potencial fisiológico de sementes
ImageJ
Processamento de imagens
title_short Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
title_full Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
title_fullStr Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
title_full_unstemmed Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
title_sort Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
author Soares, Júlia Martins
author_facet Soares, Júlia Martins
Medeiros, André Dantas de
Pinheiro, Daniel Teixeira
Rosas, Jorge Tadeu Fim
Silva, Laércio Junio da
Machado, Daniel Lucas Magalhães
Dias, Denise Cunha Fernandes dos Santos
author_role author
author2 Medeiros, André Dantas de
Pinheiro, Daniel Teixeira
Rosas, Jorge Tadeu Fim
Silva, Laércio Junio da
Machado, Daniel Lucas Magalhães
Dias, Denise Cunha Fernandes dos Santos
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Soares, Júlia Martins
Medeiros, André Dantas de
Pinheiro, Daniel Teixeira
Rosas, Jorge Tadeu Fim
Silva, Laércio Junio da
Machado, Daniel Lucas Magalhães
Dias, Denise Cunha Fernandes dos Santos
dc.subject.por.fl_str_mv Glycine max L.
seed physiological potential
ImageJ
image processing
Glycine max L.
potencial fisiológico de sementes
ImageJ
Processamento de imagens
topic Glycine max L.
seed physiological potential
ImageJ
image processing
Glycine max L.
potencial fisiológico de sementes
ImageJ
Processamento de imagens
description The use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-22
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/57060
10.4025/actasciagron.v45i1.57060
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57060
identifier_str_mv 10.4025/actasciagron.v45i1.57060
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/57060/751375155038
dc.rights.driver.fl_str_mv Copyright (c) 2023 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 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 45 (2023): Publicação contínua; e57060
Acta Scientiarum. Agronomy; v. 45 (2023): Publicação contínua; e57060
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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