Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis

Autores
Caceres, Jorge; Moncayo, Samuel; Rosales, Juan D.; de Villena, Francisco Javier Manuel; Alvira, Fernando Carlos; Bilmes, Gabriel M.
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The adulteration and traceability of olive oils are serious problems in the olive oil industry. In this work, a method based on laser-induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification, quality control, traceability, and adulteration detection of extra virgin olive oils. Instant identification of the samples is achieved using a spectral library, which was obtained by analysis of representative samples using a single laser pulse and treatment by NNs. The samples used in this study belong to four countries. The study also included different regions of each country. The results obtained allow the identification of the oils tested with a certainty of more than 95%. Single-shot measurements were enough for clear identification of the samples. The method can be developed for automatic real-time, fast, reliable, and robust measurements, and the system can be packed into portable form for non-specialist users.
Fil: Caceres, Jorge. Universidad Complutense de Madrid; España
Fil: Moncayo, Samuel. Universidad Complutense de Madrid; España
Fil: Rosales, Juan D.. Universidad Complutense de Madrid; España
Fil: de Villena, Francisco Javier Manuel. Universidad Complutense de Madrid; España
Fil: Alvira, Fernando Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Fil: Bilmes, Gabriel M.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
Materia
Laser-Induced Breakdown Spectroscopy
Libs
Neural Networks
Olive Oils
Edible Oils
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/12031
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysisCaceres, JorgeMoncayo, SamuelRosales, Juan D.de Villena, Francisco Javier ManuelAlvira, Fernando CarlosBilmes, Gabriel M.Laser-Induced Breakdown SpectroscopyLibsNeural NetworksOlive OilsEdible Oilshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The adulteration and traceability of olive oils are serious problems in the olive oil industry. In this work, a method based on laser-induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification, quality control, traceability, and adulteration detection of extra virgin olive oils. Instant identification of the samples is achieved using a spectral library, which was obtained by analysis of representative samples using a single laser pulse and treatment by NNs. The samples used in this study belong to four countries. The study also included different regions of each country. The results obtained allow the identification of the oils tested with a certainty of more than 95%. Single-shot measurements were enough for clear identification of the samples. The method can be developed for automatic real-time, fast, reliable, and robust measurements, and the system can be packed into portable form for non-specialist users.Fil: Caceres, Jorge. Universidad Complutense de Madrid; EspañaFil: Moncayo, Samuel. Universidad Complutense de Madrid; EspañaFil: Rosales, Juan D.. Universidad Complutense de Madrid; EspañaFil: de Villena, Francisco Javier Manuel. Universidad Complutense de Madrid; EspañaFil: Alvira, Fernando Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Bilmes, Gabriel M.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; ArgentinaSoc Applied Spectroscopy2013-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/12031Caceres, Jorge; Moncayo, Samuel; Rosales, Juan D.; de Villena, Francisco Javier Manuel; Alvira, Fernando Carlos; et al.; Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis; Soc Applied Spectroscopy; Applied Spectroscopy; 67; 9; 9-2013; 1064-10720003-7028enginfo:eu-repo/semantics/altIdentifier/doi/10.1366/12-06916info:eu-repo/semantics/altIdentifier/url/http://journals.sagepub.com/doi/abs/10.1366/12-06916info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-17T11:57:17Zoai:ri.conicet.gov.ar:11336/12031instacron: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:34982025-09-17 11:57:18.209CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
title Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
spellingShingle Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
Caceres, Jorge
Laser-Induced Breakdown Spectroscopy
Libs
Neural Networks
Olive Oils
Edible Oils
title_short Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
title_full Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
title_fullStr Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
title_full_unstemmed Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
title_sort Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis
dc.creator.none.fl_str_mv Caceres, Jorge
Moncayo, Samuel
Rosales, Juan D.
de Villena, Francisco Javier Manuel
Alvira, Fernando Carlos
Bilmes, Gabriel M.
author Caceres, Jorge
author_facet Caceres, Jorge
Moncayo, Samuel
Rosales, Juan D.
de Villena, Francisco Javier Manuel
Alvira, Fernando Carlos
Bilmes, Gabriel M.
author_role author
author2 Moncayo, Samuel
Rosales, Juan D.
de Villena, Francisco Javier Manuel
Alvira, Fernando Carlos
Bilmes, Gabriel M.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Laser-Induced Breakdown Spectroscopy
Libs
Neural Networks
Olive Oils
Edible Oils
topic Laser-Induced Breakdown Spectroscopy
Libs
Neural Networks
Olive Oils
Edible Oils
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The adulteration and traceability of olive oils are serious problems in the olive oil industry. In this work, a method based on laser-induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification, quality control, traceability, and adulteration detection of extra virgin olive oils. Instant identification of the samples is achieved using a spectral library, which was obtained by analysis of representative samples using a single laser pulse and treatment by NNs. The samples used in this study belong to four countries. The study also included different regions of each country. The results obtained allow the identification of the oils tested with a certainty of more than 95%. Single-shot measurements were enough for clear identification of the samples. The method can be developed for automatic real-time, fast, reliable, and robust measurements, and the system can be packed into portable form for non-specialist users.
Fil: Caceres, Jorge. Universidad Complutense de Madrid; España
Fil: Moncayo, Samuel. Universidad Complutense de Madrid; España
Fil: Rosales, Juan D.. Universidad Complutense de Madrid; España
Fil: de Villena, Francisco Javier Manuel. Universidad Complutense de Madrid; España
Fil: Alvira, Fernando Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Fil: Bilmes, Gabriel M.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina
description The adulteration and traceability of olive oils are serious problems in the olive oil industry. In this work, a method based on laser-induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification, quality control, traceability, and adulteration detection of extra virgin olive oils. Instant identification of the samples is achieved using a spectral library, which was obtained by analysis of representative samples using a single laser pulse and treatment by NNs. The samples used in this study belong to four countries. The study also included different regions of each country. The results obtained allow the identification of the oils tested with a certainty of more than 95%. Single-shot measurements were enough for clear identification of the samples. The method can be developed for automatic real-time, fast, reliable, and robust measurements, and the system can be packed into portable form for non-specialist users.
publishDate 2013
dc.date.none.fl_str_mv 2013-09
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/11336/12031
Caceres, Jorge; Moncayo, Samuel; Rosales, Juan D.; de Villena, Francisco Javier Manuel; Alvira, Fernando Carlos; et al.; Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis; Soc Applied Spectroscopy; Applied Spectroscopy; 67; 9; 9-2013; 1064-1072
0003-7028
url http://hdl.handle.net/11336/12031
identifier_str_mv Caceres, Jorge; Moncayo, Samuel; Rosales, Juan D.; de Villena, Francisco Javier Manuel; Alvira, Fernando Carlos; et al.; Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to olive oils analysis; Soc Applied Spectroscopy; Applied Spectroscopy; 67; 9; 9-2013; 1064-1072
0003-7028
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1366/12-06916
info:eu-repo/semantics/altIdentifier/url/http://journals.sagepub.com/doi/abs/10.1366/12-06916
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Soc Applied Spectroscopy
publisher.none.fl_str_mv Soc Applied Spectroscopy
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
_version_ 1843606916466475008
score 13.001348

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