Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
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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Acta Scientiarum. Agronomy (Online) |
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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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1799305901169967104 |