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Registro Completo |
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Biblioteca(s): |
Embrapa Semiárido; Embrapa Uva e Vinho. |
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Data corrente: |
20/11/2020 |
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Data da última atualização: |
26/11/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
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. |
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Afiliação: |
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. |
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Título: |
Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Food Chemistry, v. 312, p. 12606, 2020. |
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DOI: |
https://doi.org/10.1016/j.foodchem.2019.126060 |
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Idioma: |
Inglês |
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Conteúdo: |
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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Palavras-Chave: |
Cabernet Sauvignon; Color histogram; Geographical origin indication; Histograma de cores; Imagens digitais Algoritmo; Indicação de origem geográfica; Successive projections algorithm; Syrah; Touriga Nacional; Vinho tinto. |
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Thesagro: |
Uva. |
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Thesaurus Nal: |
Digital images; Grapes; Red wines. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/218044/1/1-s2.0-S0308814619322083-main.pdf
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Marc: |
LEADER 02126naa a2200361 a 4500
001 2126870
005 2020-11-26
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.foodchem.2019.126060$2DOI
100 1 $aLIMA, C. M. de
245 $aDigital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication.$h[electronic resource]
260 $c2020
520 $aThis 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
650 $aDigital images
650 $aGrapes
650 $aRed wines
650 $aUva
653 $aCabernet Sauvignon
653 $aColor histogram
653 $aGeographical origin indication
653 $aHistograma de cores
653 $aImagens digitais Algoritmo
653 $aIndicação de origem geográfica
653 $aSuccessive projections algorithm
653 $aSyrah
653 $aTouriga Nacional
653 $aVinho tinto
700 1 $aFERNANDES, D. D. S.
700 1 $aPEREIRA, G. E.
700 1 $aGOMES, A. de A.
700 1 $aARAÚJO, M. C. U. de
700 1 $aDINIZ, P. H. G. D.
773 $tFood Chemistry$gv. 312, p. 12606, 2020.
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Registro original: |
Embrapa Uva e Vinho (CNPUV) |
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| 1. |  | 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. Digital image-based tracing of geographic origin, winemaker, and grape type forred wine authentication. Food Chemistry, v. 312, p. 12606, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Semiárido; Embrapa Uva e Vinho. |
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| Registros recuperados : 1 | |
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