Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection

Autores
Rodríguez, Silvio David; Barletta, Diego A.; Wilderjans, Tom F.; Bernik, Delia Leticia
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The objective of this work is to report the improvements obtained in the discrimination of complex aroma samples with subtle differences in odor pattern, by the use of a fast procedure suitable for the cases of measurements in the field demanding decision-making in real time using a portable electronic nose. This device consists of a sensor array which records changes in conductivity as a function of time when aroma molecules reach the sensors. The core of the method consists of applying unfolded cluster analysis to selected time windows (UCATW) within the temporal evolution of the aroma profile recorded by the gas sensors, yielding an efficient, fast, and reliable data analysis tool that is easy to perform for electronic nose users. The performance of this data handling was tested in two case studies of food adulteration. The results demonstrated that this methodology enables to discriminate highly similar samples, herewith reducing the probability of achieving a wrong grouping due to the use of flawed data. The automation of this type of analysis is simple and improves the efficiency of the device significantly, herewith reducing the time of sensor’s signal recording that is necessary for a reliable assessment of the studied system. The results were validated by clustering the sample component scores that are obtained by applying parallel factor analysis (PARAFAC) to the original three-dimensional data array. An additional validation was obtained by means of a leave-one-out resampling procedure.
Fil: Rodríguez, Silvio David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Barletta, Diego A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Wilderjans, Tom F.. Katholieke Universiteit Leuve; Bélgica
Fil: Bernik, Delia Leticia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Materia
Aroma Discrimination
Electronic Nose
Food Quality Assessment
Time-Window Selection
Unfolded Cluster Analysis
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:11336/83675
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/83675
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window SelectionRodríguez, Silvio DavidBarletta, Diego A.Wilderjans, Tom F.Bernik, Delia LeticiaAroma DiscriminationElectronic NoseFood Quality AssessmentTime-Window SelectionUnfolded Cluster Analysishttps://purl.org/becyt/ford/1.7https://purl.org/becyt/ford/1The objective of this work is to report the improvements obtained in the discrimination of complex aroma samples with subtle differences in odor pattern, by the use of a fast procedure suitable for the cases of measurements in the field demanding decision-making in real time using a portable electronic nose. This device consists of a sensor array which records changes in conductivity as a function of time when aroma molecules reach the sensors. The core of the method consists of applying unfolded cluster analysis to selected time windows (UCATW) within the temporal evolution of the aroma profile recorded by the gas sensors, yielding an efficient, fast, and reliable data analysis tool that is easy to perform for electronic nose users. The performance of this data handling was tested in two case studies of food adulteration. The results demonstrated that this methodology enables to discriminate highly similar samples, herewith reducing the probability of achieving a wrong grouping due to the use of flawed data. The automation of this type of analysis is simple and improves the efficiency of the device significantly, herewith reducing the time of sensor’s signal recording that is necessary for a reliable assessment of the studied system. The results were validated by clustering the sample component scores that are obtained by applying parallel factor analysis (PARAFAC) to the original three-dimensional data array. An additional validation was obtained by means of a leave-one-out resampling procedure.Fil: Rodríguez, Silvio David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Barletta, Diego A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Wilderjans, Tom F.. Katholieke Universiteit Leuve; BélgicaFil: Bernik, Delia Leticia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaSpringer2014-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/83675Rodríguez, Silvio David; Barletta, Diego A.; Wilderjans, Tom F.; Bernik, Delia Leticia; Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection; Springer; Food Analytical Methods; 7; 10; 10-2014; 2042-20501936-9751CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s12161-014-9841-7info:eu-repo/semantics/altIdentifier/doi/10.1007/s12161-014-9841-7info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-12T09:36:29Zoai:ri.conicet.gov.ar:11336/83675instacron: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:34982025-11-12 09:36:29.516CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
title Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
spellingShingle Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
Rodríguez, Silvio David
Aroma Discrimination
Electronic Nose
Food Quality Assessment
Time-Window Selection
Unfolded Cluster Analysis
title_short Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
title_full Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
title_fullStr Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
title_full_unstemmed Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
title_sort Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
dc.creator.none.fl_str_mv Rodríguez, Silvio David
Barletta, Diego A.
Wilderjans, Tom F.
Bernik, Delia Leticia
author Rodríguez, Silvio David
author_facet Rodríguez, Silvio David
Barletta, Diego A.
Wilderjans, Tom F.
Bernik, Delia Leticia
author_role author
author2 Barletta, Diego A.
Wilderjans, Tom F.
Bernik, Delia Leticia
author2_role author
author
author
dc.subject.none.fl_str_mv Aroma Discrimination
Electronic Nose
Food Quality Assessment
Time-Window Selection
Unfolded Cluster Analysis
topic Aroma Discrimination
Electronic Nose
Food Quality Assessment
Time-Window Selection
Unfolded Cluster Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.7
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The objective of this work is to report the improvements obtained in the discrimination of complex aroma samples with subtle differences in odor pattern, by the use of a fast procedure suitable for the cases of measurements in the field demanding decision-making in real time using a portable electronic nose. This device consists of a sensor array which records changes in conductivity as a function of time when aroma molecules reach the sensors. The core of the method consists of applying unfolded cluster analysis to selected time windows (UCATW) within the temporal evolution of the aroma profile recorded by the gas sensors, yielding an efficient, fast, and reliable data analysis tool that is easy to perform for electronic nose users. The performance of this data handling was tested in two case studies of food adulteration. The results demonstrated that this methodology enables to discriminate highly similar samples, herewith reducing the probability of achieving a wrong grouping due to the use of flawed data. The automation of this type of analysis is simple and improves the efficiency of the device significantly, herewith reducing the time of sensor’s signal recording that is necessary for a reliable assessment of the studied system. The results were validated by clustering the sample component scores that are obtained by applying parallel factor analysis (PARAFAC) to the original three-dimensional data array. An additional validation was obtained by means of a leave-one-out resampling procedure.
Fil: Rodríguez, Silvio David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Barletta, Diego A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Wilderjans, Tom F.. Katholieke Universiteit Leuve; Bélgica
Fil: Bernik, Delia Leticia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
description The objective of this work is to report the improvements obtained in the discrimination of complex aroma samples with subtle differences in odor pattern, by the use of a fast procedure suitable for the cases of measurements in the field demanding decision-making in real time using a portable electronic nose. This device consists of a sensor array which records changes in conductivity as a function of time when aroma molecules reach the sensors. The core of the method consists of applying unfolded cluster analysis to selected time windows (UCATW) within the temporal evolution of the aroma profile recorded by the gas sensors, yielding an efficient, fast, and reliable data analysis tool that is easy to perform for electronic nose users. The performance of this data handling was tested in two case studies of food adulteration. The results demonstrated that this methodology enables to discriminate highly similar samples, herewith reducing the probability of achieving a wrong grouping due to the use of flawed data. The automation of this type of analysis is simple and improves the efficiency of the device significantly, herewith reducing the time of sensor’s signal recording that is necessary for a reliable assessment of the studied system. The results were validated by clustering the sample component scores that are obtained by applying parallel factor analysis (PARAFAC) to the original three-dimensional data array. An additional validation was obtained by means of a leave-one-out resampling procedure.
publishDate 2014
dc.date.none.fl_str_mv 2014-10
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/11336/83675
Rodríguez, Silvio David; Barletta, Diego A.; Wilderjans, Tom F.; Bernik, Delia Leticia; Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection; Springer; Food Analytical Methods; 7; 10; 10-2014; 2042-2050
1936-9751
CONICET Digital
CONICET
url http://hdl.handle.net/11336/83675
identifier_str_mv Rodríguez, Silvio David; Barletta, Diego A.; Wilderjans, Tom F.; Bernik, Delia Leticia; Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection; Springer; Food Analytical Methods; 7; 10; 10-2014; 2042-2050
1936-9751
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://link.springer.com/article/10.1007/s12161-014-9841-7
info:eu-repo/semantics/altIdentifier/doi/10.1007/s12161-014-9841-7
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 Springer
publisher.none.fl_str_mv Springer
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 13.24909

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