Application of image analysis to the prediction of EBC barley kernel weight distribution

Detalhes bibliográficos
Autor(a) principal: Amaral, A. L.
Data de Publicação: 2009
Outros Autores: Rocha, Orlando, Gonçalves, Cristina, Ferreira, António Augusto, Ferreira, Eugénio C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/9613
Resumo: It is known that the barley kernel size is an important factor regarding the uniformity of the malting and brewery processes, barley valuation, approval andmarket value. In order to facilitate the barley purchasing process, a fast field technique for kernel size evaluation, such as the image analysis technique proposed in this work, would be greatly appreciated as a fast and simple procedure for barley selection. In this study a close correlation between the image analysis and the standard EBC was obtained with a correlation factor of 0.999 and a regression coefficient of 0.991 between the two methodologies. The proposed IA methodologywas found to accurately predict the Scarlett and Prestige barley varietiesweight distribution especially when considering the crucial ‘business transactions selection’ classes.
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spelling Application of image analysis to the prediction of EBC barley kernel weight distributionBarley analysisKernel sizeImage analysisPartial least squaresScience & TechnologyIt is known that the barley kernel size is an important factor regarding the uniformity of the malting and brewery processes, barley valuation, approval andmarket value. In order to facilitate the barley purchasing process, a fast field technique for kernel size evaluation, such as the image analysis technique proposed in this work, would be greatly appreciated as a fast and simple procedure for barley selection. In this study a close correlation between the image analysis and the standard EBC was obtained with a correlation factor of 0.999 and a regression coefficient of 0.991 between the two methodologies. The proposed IA methodologywas found to accurately predict the Scarlett and Prestige barley varietiesweight distribution especially when considering the crucial ‘business transactions selection’ classes.Unicer, S.A.Elsevier B.V.Universidade do MinhoAmaral, A. L.Rocha, OrlandoGonçalves, CristinaFerreira, António AugustoFerreira, Eugénio C.2009-112009-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/9613engAmaral, A. L., Rocha, O., Gonçalves, C., Ferreira, A. A., & Ferreira, E. C. (2009, November). Application of image analysis to the prediction of EBC barley kernel weight distribution. Industrial Crops and Products. Elsevier BV. http://doi.org/10.1016/j.indcrop.2009.07.0030926-669010.1016/j.indcrop.2009.07.003https://www.sciencedirect.com/science/article/pii/S0926669009000971info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:23:45Zoai:repositorium.sdum.uminho.pt:1822/9613Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:17:34.009759Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Application of image analysis to the prediction of EBC barley kernel weight distribution
title Application of image analysis to the prediction of EBC barley kernel weight distribution
spellingShingle Application of image analysis to the prediction of EBC barley kernel weight distribution
Amaral, A. L.
Barley analysis
Kernel size
Image analysis
Partial least squares
Science & Technology
title_short Application of image analysis to the prediction of EBC barley kernel weight distribution
title_full Application of image analysis to the prediction of EBC barley kernel weight distribution
title_fullStr Application of image analysis to the prediction of EBC barley kernel weight distribution
title_full_unstemmed Application of image analysis to the prediction of EBC barley kernel weight distribution
title_sort Application of image analysis to the prediction of EBC barley kernel weight distribution
author Amaral, A. L.
author_facet Amaral, A. L.
Rocha, Orlando
Gonçalves, Cristina
Ferreira, António Augusto
Ferreira, Eugénio C.
author_role author
author2 Rocha, Orlando
Gonçalves, Cristina
Ferreira, António Augusto
Ferreira, Eugénio C.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Amaral, A. L.
Rocha, Orlando
Gonçalves, Cristina
Ferreira, António Augusto
Ferreira, Eugénio C.
dc.subject.por.fl_str_mv Barley analysis
Kernel size
Image analysis
Partial least squares
Science & Technology
topic Barley analysis
Kernel size
Image analysis
Partial least squares
Science & Technology
description It is known that the barley kernel size is an important factor regarding the uniformity of the malting and brewery processes, barley valuation, approval andmarket value. In order to facilitate the barley purchasing process, a fast field technique for kernel size evaluation, such as the image analysis technique proposed in this work, would be greatly appreciated as a fast and simple procedure for barley selection. In this study a close correlation between the image analysis and the standard EBC was obtained with a correlation factor of 0.999 and a regression coefficient of 0.991 between the two methodologies. The proposed IA methodologywas found to accurately predict the Scarlett and Prestige barley varietiesweight distribution especially when considering the crucial ‘business transactions selection’ classes.
publishDate 2009
dc.date.none.fl_str_mv 2009-11
2009-11-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/9613
url https://hdl.handle.net/1822/9613
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Amaral, A. L., Rocha, O., Gonçalves, C., Ferreira, A. A., & Ferreira, E. C. (2009, November). Application of image analysis to the prediction of EBC barley kernel weight distribution. Industrial Crops and Products. Elsevier BV. http://doi.org/10.1016/j.indcrop.2009.07.003
0926-6690
10.1016/j.indcrop.2009.07.003
https://www.sciencedirect.com/science/article/pii/S0926669009000971
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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