Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition

Autores
Hidalgo, Melisa Jazmin; Gaiad, José Emilio; Goicoechea, Hector Casimiro; Mendoza, Alberto; Pérez Rodríguez, Michael; Pellerano, Roberto Gerardo
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.
Fil: Hidalgo, Melisa Jazmin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
Fil: Gaiad, José Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina
Fil: Mendoza, Alberto. Instituto Tecnologico de Monterrey.; México
Fil: Pérez Rodríguez, Michael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina. Instituto Tecnologico de Monterrey.; México
Fil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
Materia
ELEMENT PROFILES
MANDARIN JUICES
MP-AES, GEOGRAPHICAL ORIGIN AUTHENTICATION
PREDICTIVE MODELING
SUPPORT VECTOR MACHINE
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:11336/224882
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/224882
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental compositionHidalgo, Melisa JazminGaiad, José EmilioGoicoechea, Hector CasimiroMendoza, AlbertoPérez Rodríguez, MichaelPellerano, Roberto GerardoELEMENT PROFILESMANDARIN JUICESMP-AES, GEOGRAPHICAL ORIGIN AUTHENTICATIONPREDICTIVE MODELINGSUPPORT VECTOR MACHINEhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.Fil: Hidalgo, Melisa Jazmin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Gaiad, José Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; ArgentinaFil: Mendoza, Alberto. Instituto Tecnologico de Monterrey.; MéxicoFil: Pérez Rodríguez, Michael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina. Instituto Tecnologico de Monterrey.; MéxicoFil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaElsevier2023-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/224882Hidalgo, Melisa Jazmin; Gaiad, José Emilio; Goicoechea, Hector Casimiro; Mendoza, Alberto; Pérez Rodríguez, Michael; et al.; Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition; Elsevier; Food Chemistry: X; 20; 12-2023; 1-82590-1575CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2590157523004832info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fochx.2023.101040info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:25:03Zoai:ri.conicet.gov.ar:11336/224882instacron: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:34982025-10-15 14:25:04.148CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
title Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
spellingShingle Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
Hidalgo, Melisa Jazmin
ELEMENT PROFILES
MANDARIN JUICES
MP-AES, GEOGRAPHICAL ORIGIN AUTHENTICATION
PREDICTIVE MODELING
SUPPORT VECTOR MACHINE
title_short Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
title_full Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
title_fullStr Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
title_full_unstemmed Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
title_sort Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition
dc.creator.none.fl_str_mv Hidalgo, Melisa Jazmin
Gaiad, José Emilio
Goicoechea, Hector Casimiro
Mendoza, Alberto
Pérez Rodríguez, Michael
Pellerano, Roberto Gerardo
author Hidalgo, Melisa Jazmin
author_facet Hidalgo, Melisa Jazmin
Gaiad, José Emilio
Goicoechea, Hector Casimiro
Mendoza, Alberto
Pérez Rodríguez, Michael
Pellerano, Roberto Gerardo
author_role author
author2 Gaiad, José Emilio
Goicoechea, Hector Casimiro
Mendoza, Alberto
Pérez Rodríguez, Michael
Pellerano, Roberto Gerardo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv ELEMENT PROFILES
MANDARIN JUICES
MP-AES, GEOGRAPHICAL ORIGIN AUTHENTICATION
PREDICTIVE MODELING
SUPPORT VECTOR MACHINE
topic ELEMENT PROFILES
MANDARIN JUICES
MP-AES, GEOGRAPHICAL ORIGIN AUTHENTICATION
PREDICTIVE MODELING
SUPPORT VECTOR MACHINE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.
Fil: Hidalgo, Melisa Jazmin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
Fil: Gaiad, José Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina
Fil: Mendoza, Alberto. Instituto Tecnologico de Monterrey.; México
Fil: Pérez Rodríguez, Michael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina. Instituto Tecnologico de Monterrey.; México
Fil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina
description Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.
publishDate 2023
dc.date.none.fl_str_mv 2023-12
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/11336/224882
Hidalgo, Melisa Jazmin; Gaiad, José Emilio; Goicoechea, Hector Casimiro; Mendoza, Alberto; Pérez Rodríguez, Michael; et al.; Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition; Elsevier; Food Chemistry: X; 20; 12-2023; 1-8
2590-1575
CONICET Digital
CONICET
url http://hdl.handle.net/11336/224882
identifier_str_mv Hidalgo, Melisa Jazmin; Gaiad, José Emilio; Goicoechea, Hector Casimiro; Mendoza, Alberto; Pérez Rodríguez, Michael; et al.; Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition; Elsevier; Food Chemistry: X; 20; 12-2023; 1-8
2590-1575
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://linkinghub.elsevier.com/retrieve/pii/S2590157523004832
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fochx.2023.101040
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
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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 13.22299

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