Mostrar el registro sencillo del ítem
dc.contributor.author
Rodríguez, Silvio David
dc.contributor.author
Barletta, Diego A.
dc.contributor.author
Wilderjans, Tom F.
dc.contributor.author
Bernik, Delia Leticia
dc.date.available
2019-09-16T20:59:58Z
dc.date.issued
2014-10
dc.identifier.citation
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
dc.identifier.issn
1936-9751
dc.identifier.uri
http://hdl.handle.net/11336/83675
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Aroma Discrimination
dc.subject
Electronic Nose
dc.subject
Food Quality Assessment
dc.subject
Time-Window Selection
dc.subject
Unfolded Cluster Analysis
dc.subject.classification
Otras Ciencias Naturales y Exactas
dc.subject.classification
Otras Ciencias Naturales y Exactas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-06-11T19:43:31Z
dc.journal.volume
7
dc.journal.number
10
dc.journal.pagination
2042-2050
dc.journal.pais
Alemania
dc.journal.ciudad
Berlin
dc.description.fil
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
dc.description.fil
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
dc.description.fil
Fil: Wilderjans, Tom F.. Katholieke Universiteit Leuve; Bélgica
dc.description.fil
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
dc.journal.title
Food Analytical Methods
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s12161-014-9841-7
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1007/s12161-014-9841-7
Archivos asociados