Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication.
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126870 https://doi.org/10.1016/j.foodchem.2019.126060 |
Resumo: | This work proposes the development of a simple, fast, and inexpensive methodology based on color histograms (obtained from digital images), and supervised pattern recognition techniques to classify redwines produced in the São Francisco Valley (SFV) region to trace geographic origin, winemaker, and grape variety. PCA-LDA coupled with HSI histograms correctly differentiated all of the SFV samples from the other geographic regions in the testset; SPA-LDA selecting just 10 variables in the Gray scale+HSI histogram achieved 100% accuracy in the test set when classifying three different SFV winemakers. Regarding the three grape varieties, SPA-LDA selected 15 variables in the RGB histogram to obtain the best result, misclassifying only 2 samples in the tests et. Pairwise grape variety classification was also performed with only 1 misclassification. Besides following the principles of Green Chemistry, the proposed methodology is a suitable analytical tool; for tracing origins, grapetype, and even (SFV) winemakers |
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Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication.Cabernet SauvignonSyrahTouriga NacionalGeographical origin indicationColor histogramSuccessive projections algorithmRed winesDigital imagesThis work proposes the development of a simple, fast, and inexpensive methodology based on color histograms (obtained from digital images), and supervised pattern recognition techniques to classify redwines produced in the São Francisco Valley (SFV) region to trace geographic origin, winemaker, and grape variety. PCA-LDA coupled with HSI histograms correctly differentiated all of the SFV samples from the other geographic regions in the testset; SPA-LDA selecting just 10 variables in the Gray scale+HSI histogram achieved 100% accuracy in the test set when classifying three different SFV winemakers. Regarding the three grape varieties, SPA-LDA selected 15 variables in the RGB histogram to obtain the best result, misclassifying only 2 samples in the tests et. Pairwise grape variety classification was also performed with only 1 misclassification. Besides following the principles of Green Chemistry, the proposed methodology is a suitable analytical tool; for tracing origins, grapetype, and even (SFV) winemakersCARLOS MONTEIRO DE LIMA, Universidade Federal da Paraíba,DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Brazil; DAVID DOUGLAS SOUSA FERNANDES, Universidade Federal da Paraíba,DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Brazil; GIULIANO ELIAS PEREIRA, CNPUV; ADRIANO DE ARAÚJO GOMES, Universidade Federal do Rio Grande do Sul, InstitutodeQuímica,ZipCode90650-001,PortoAlegre,RS,Brazi; MÁRIO CÉSAR UGULINO DE ARAÚJO, Universidade Federal da Paraíba, DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Braz; PAULO HENRIQUE GONÇALVES DIAS DINIZ, Universidade Federal do Oeste da Bahia, ProgramadePós-GraduaçãoemQuímicaPuraeAplicada,ZipCode47810-059,Barreiras,BA,Brazi.LIMA, C. M. deFERNANDES, D. D. S.PEREIRA, G. E.GOMES, A. de A.ARAÚJO, M. C. U. deDINIZ, P. H. G. D.2020-11-21T09:14:03Z2020-11-21T09:14:03Z2020-11-202020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFood Chemistry, v. 312, p. 12606, 2020.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126870https://doi.org/10.1016/j.foodchem.2019.126060enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2020-11-21T09:14:10Zoai:www.alice.cnptia.embrapa.br:doc/1126870Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542020-11-21T09:14:10falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542020-11-21T09:14:10Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
title |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
spellingShingle |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. LIMA, C. M. de Cabernet Sauvignon Syrah Touriga Nacional Geographical origin indication Color histogram Successive projections algorithm Red wines Digital images |
title_short |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
title_full |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
title_fullStr |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
title_full_unstemmed |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
title_sort |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
author |
LIMA, C. M. de |
author_facet |
LIMA, C. M. de FERNANDES, D. D. S. PEREIRA, G. E. GOMES, A. de A. ARAÚJO, M. C. U. de DINIZ, P. H. G. D. |
author_role |
author |
author2 |
FERNANDES, D. D. S. PEREIRA, G. E. GOMES, A. de A. ARAÚJO, M. C. U. de DINIZ, P. H. G. D. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
CARLOS MONTEIRO DE LIMA, Universidade Federal da Paraíba,DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Brazil; DAVID DOUGLAS SOUSA FERNANDES, Universidade Federal da Paraíba,DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Brazil; GIULIANO ELIAS PEREIRA, CNPUV; ADRIANO DE ARAÚJO GOMES, Universidade Federal do Rio Grande do Sul, InstitutodeQuímica,ZipCode90650-001,PortoAlegre,RS,Brazi; MÁRIO CÉSAR UGULINO DE ARAÚJO, Universidade Federal da Paraíba, DepartamentodeQuímica,P.O.Box5093,ZipCode58051-970,JoãoPessoa,PB,Braz; PAULO HENRIQUE GONÇALVES DIAS DINIZ, Universidade Federal do Oeste da Bahia, ProgramadePós-GraduaçãoemQuímicaPuraeAplicada,ZipCode47810-059,Barreiras,BA,Brazi. |
dc.contributor.author.fl_str_mv |
LIMA, C. M. de FERNANDES, D. D. S. PEREIRA, G. E. GOMES, A. de A. ARAÚJO, M. C. U. de DINIZ, P. H. G. D. |
dc.subject.por.fl_str_mv |
Cabernet Sauvignon Syrah Touriga Nacional Geographical origin indication Color histogram Successive projections algorithm Red wines Digital images |
topic |
Cabernet Sauvignon Syrah Touriga Nacional Geographical origin indication Color histogram Successive projections algorithm Red wines Digital images |
description |
This work proposes the development of a simple, fast, and inexpensive methodology based on color histograms (obtained from digital images), and supervised pattern recognition techniques to classify redwines produced in the São Francisco Valley (SFV) region to trace geographic origin, winemaker, and grape variety. PCA-LDA coupled with HSI histograms correctly differentiated all of the SFV samples from the other geographic regions in the testset; SPA-LDA selecting just 10 variables in the Gray scale+HSI histogram achieved 100% accuracy in the test set when classifying three different SFV winemakers. Regarding the three grape varieties, SPA-LDA selected 15 variables in the RGB histogram to obtain the best result, misclassifying only 2 samples in the tests et. Pairwise grape variety classification was also performed with only 1 misclassification. Besides following the principles of Green Chemistry, the proposed methodology is a suitable analytical tool; for tracing origins, grapetype, and even (SFV) winemakers |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-11-21T09:14:03Z 2020-11-21T09:14:03Z 2020-11-20 2020 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Food Chemistry, v. 312, p. 12606, 2020. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126870 https://doi.org/10.1016/j.foodchem.2019.126060 |
identifier_str_mv |
Food Chemistry, v. 312, p. 12606, 2020. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126870 https://doi.org/10.1016/j.foodchem.2019.126060 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503498154377216 |