Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools

Autores
Fernandes, David Douglas de Sousa; Romeo, Florencia; Krepper, Gabriela; Di Nezio, Maria Susana; Pistonesi, Marcelo Fabian; Centurión, María Eugenia; Ugulino de Araújo, Mário César; de Araújo, Mário César Ugulino; Goncalves Dias Diniz, Paulo Henrique
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, we developed an eco-friendly methodology for quantification and identification of adulteration in the fat content of chicken hamburgers by combining color histograms (in RGB, HSI, and Grayscale channels) obtained from digital images and chemometric tools. For this, 74 samples of chicken hamburgers with a fat content of 14.27–47.55% (w w−1) were studied, taking into account adulterations with a fat content higher than 20% (w w−1), as limited by Argentinean legislation. In both quantitative and qualitative approaches, chemometric models containing HSI histograms achieved the best results, because this is very suitable in situations where there is a need to separate the chromaticity from the intensity. In other words, the opacity of the sample surfaces increases with increasing fat content. PLS/HSI achieved the best quantification result with a R2 of 0.95, RMSEP of 2.01% w w−1, REP of 7.26% w w−1 and RPD of 4.47 in the prediction set, while SPA-LDA/Grayscale + HSI reached the most satisfactory in the test set with only one misclassified sample. Therefore, the proposed methodologies represent excellent alternatives to conventional Soxhlet extraction method, since they follow the primary principles of Green Analytical Chemistry, avoiding waste generation, besides not using either chemical reagents or solvents.
Fil: Fernandes, David Douglas de Sousa. Universidade Federal da Paraíba; Brasil
Fil: Romeo, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Krepper, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Di Nezio, Maria Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Pistonesi, Marcelo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Centurión, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Ugulino de Araújo, Mário César. Universidade Federal da Paraíba; Brasil
Fil: de Araújo, Mário César Ugulino. Universidade Federal da Paraíba; Brasil
Fil: Goncalves Dias Diniz, Paulo Henrique. Universidade Federal da Bahia; Brasil
Materia
ADULTERATION
CHEMOMETRICS
FAT CONTENT
FOOD QUALITY
MEAT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/109204
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric toolsFernandes, David Douglas de SousaRomeo, FlorenciaKrepper, GabrielaDi Nezio, Maria SusanaPistonesi, Marcelo FabianCenturión, María EugeniaUgulino de Araújo, Mário Césarde Araújo, Mário César UgulinoGoncalves Dias Diniz, Paulo HenriqueADULTERATIONCHEMOMETRICSFAT CONTENTFOOD QUALITYMEAThttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1In this work, we developed an eco-friendly methodology for quantification and identification of adulteration in the fat content of chicken hamburgers by combining color histograms (in RGB, HSI, and Grayscale channels) obtained from digital images and chemometric tools. For this, 74 samples of chicken hamburgers with a fat content of 14.27–47.55% (w w−1) were studied, taking into account adulterations with a fat content higher than 20% (w w−1), as limited by Argentinean legislation. In both quantitative and qualitative approaches, chemometric models containing HSI histograms achieved the best results, because this is very suitable in situations where there is a need to separate the chromaticity from the intensity. In other words, the opacity of the sample surfaces increases with increasing fat content. PLS/HSI achieved the best quantification result with a R2 of 0.95, RMSEP of 2.01% w w−1, REP of 7.26% w w−1 and RPD of 4.47 in the prediction set, while SPA-LDA/Grayscale + HSI reached the most satisfactory in the test set with only one misclassified sample. Therefore, the proposed methodologies represent excellent alternatives to conventional Soxhlet extraction method, since they follow the primary principles of Green Analytical Chemistry, avoiding waste generation, besides not using either chemical reagents or solvents.Fil: Fernandes, David Douglas de Sousa. Universidade Federal da Paraíba; BrasilFil: Romeo, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Krepper, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Di Nezio, Maria Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Pistonesi, Marcelo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Centurión, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Ugulino de Araújo, Mário César. Universidade Federal da Paraíba; BrasilFil: de Araújo, Mário César Ugulino. Universidade Federal da Paraíba; BrasilFil: Goncalves Dias Diniz, Paulo Henrique. Universidade Federal da Bahia; BrasilElsevier Science2019-02-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/109204Fernandes, David Douglas de Sousa; Romeo, Florencia; Krepper, Gabriela; Di Nezio, Maria Susana; Pistonesi, Marcelo Fabian; et al.; Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools; Elsevier Science; LWT - Food Science and Technology; 100; 19-2-2019; 20-270023-6438CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0023643818308806info:eu-repo/semantics/altIdentifier/doi/10.1016/j.lwt.2018.10.034info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:37:03Zoai:ri.conicet.gov.ar:11336/109204instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:37:03.74CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
title Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
spellingShingle Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
Fernandes, David Douglas de Sousa
ADULTERATION
CHEMOMETRICS
FAT CONTENT
FOOD QUALITY
MEAT
title_short Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
title_full Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
title_fullStr Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
title_full_unstemmed Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
title_sort Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools
dc.creator.none.fl_str_mv Fernandes, David Douglas de Sousa
Romeo, Florencia
Krepper, Gabriela
Di Nezio, Maria Susana
Pistonesi, Marcelo Fabian
Centurión, María Eugenia
Ugulino de Araújo, Mário César
de Araújo, Mário César Ugulino
Goncalves Dias Diniz, Paulo Henrique
author Fernandes, David Douglas de Sousa
author_facet Fernandes, David Douglas de Sousa
Romeo, Florencia
Krepper, Gabriela
Di Nezio, Maria Susana
Pistonesi, Marcelo Fabian
Centurión, María Eugenia
Ugulino de Araújo, Mário César
de Araújo, Mário César Ugulino
Goncalves Dias Diniz, Paulo Henrique
author_role author
author2 Romeo, Florencia
Krepper, Gabriela
Di Nezio, Maria Susana
Pistonesi, Marcelo Fabian
Centurión, María Eugenia
Ugulino de Araújo, Mário César
de Araújo, Mário César Ugulino
Goncalves Dias Diniz, Paulo Henrique
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ADULTERATION
CHEMOMETRICS
FAT CONTENT
FOOD QUALITY
MEAT
topic ADULTERATION
CHEMOMETRICS
FAT CONTENT
FOOD QUALITY
MEAT
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this work, we developed an eco-friendly methodology for quantification and identification of adulteration in the fat content of chicken hamburgers by combining color histograms (in RGB, HSI, and Grayscale channels) obtained from digital images and chemometric tools. For this, 74 samples of chicken hamburgers with a fat content of 14.27–47.55% (w w−1) were studied, taking into account adulterations with a fat content higher than 20% (w w−1), as limited by Argentinean legislation. In both quantitative and qualitative approaches, chemometric models containing HSI histograms achieved the best results, because this is very suitable in situations where there is a need to separate the chromaticity from the intensity. In other words, the opacity of the sample surfaces increases with increasing fat content. PLS/HSI achieved the best quantification result with a R2 of 0.95, RMSEP of 2.01% w w−1, REP of 7.26% w w−1 and RPD of 4.47 in the prediction set, while SPA-LDA/Grayscale + HSI reached the most satisfactory in the test set with only one misclassified sample. Therefore, the proposed methodologies represent excellent alternatives to conventional Soxhlet extraction method, since they follow the primary principles of Green Analytical Chemistry, avoiding waste generation, besides not using either chemical reagents or solvents.
Fil: Fernandes, David Douglas de Sousa. Universidade Federal da Paraíba; Brasil
Fil: Romeo, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Krepper, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Di Nezio, Maria Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Pistonesi, Marcelo Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Centurión, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
Fil: Ugulino de Araújo, Mário César. Universidade Federal da Paraíba; Brasil
Fil: de Araújo, Mário César Ugulino. Universidade Federal da Paraíba; Brasil
Fil: Goncalves Dias Diniz, Paulo Henrique. Universidade Federal da Bahia; Brasil
description In this work, we developed an eco-friendly methodology for quantification and identification of adulteration in the fat content of chicken hamburgers by combining color histograms (in RGB, HSI, and Grayscale channels) obtained from digital images and chemometric tools. For this, 74 samples of chicken hamburgers with a fat content of 14.27–47.55% (w w−1) were studied, taking into account adulterations with a fat content higher than 20% (w w−1), as limited by Argentinean legislation. In both quantitative and qualitative approaches, chemometric models containing HSI histograms achieved the best results, because this is very suitable in situations where there is a need to separate the chromaticity from the intensity. In other words, the opacity of the sample surfaces increases with increasing fat content. PLS/HSI achieved the best quantification result with a R2 of 0.95, RMSEP of 2.01% w w−1, REP of 7.26% w w−1 and RPD of 4.47 in the prediction set, while SPA-LDA/Grayscale + HSI reached the most satisfactory in the test set with only one misclassified sample. Therefore, the proposed methodologies represent excellent alternatives to conventional Soxhlet extraction method, since they follow the primary principles of Green Analytical Chemistry, avoiding waste generation, besides not using either chemical reagents or solvents.
publishDate 2019
dc.date.none.fl_str_mv 2019-02-19
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/109204
Fernandes, David Douglas de Sousa; Romeo, Florencia; Krepper, Gabriela; Di Nezio, Maria Susana; Pistonesi, Marcelo Fabian; et al.; Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools; Elsevier Science; LWT - Food Science and Technology; 100; 19-2-2019; 20-27
0023-6438
CONICET Digital
CONICET
url http://hdl.handle.net/11336/109204
identifier_str_mv Fernandes, David Douglas de Sousa; Romeo, Florencia; Krepper, Gabriela; Di Nezio, Maria Susana; Pistonesi, Marcelo Fabian; et al.; Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools; Elsevier Science; LWT - Food Science and Technology; 100; 19-2-2019; 20-27
0023-6438
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0023643818308806
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.lwt.2018.10.034
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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