Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Chuquizuta Trigoso, Tony, Oblitas Cruz, Jimy, Arteaga Miñano, Hubert, Castro Silupu, Wilson
Formato: objeto de conferencia
Fecha de Publicación:2020
Institución:Universidad Privada del Norte
Repositorio:UPN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.upn.edu.pe:11537/26913
Enlace del recurso:https://hdl.handle.net/11537/26913
https://doi.org/10.1109/EIRCON51178.2020.9253756
Nivel de acceso:acceso abierto
Materia:Jugos de fruta
Ingeniería de la producción
Industria alimentaria
https://purl.org/pe-repo/ocde/ford#2.11.04
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dc.title.es_PE.fl_str_mv Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
title Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
spellingShingle Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
Chuquizuta Trigoso, Tony
Jugos de fruta
Ingeniería de la producción
Industria alimentaria
https://purl.org/pe-repo/ocde/ford#2.11.04
title_short Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
title_full Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
title_fullStr Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
title_full_unstemmed Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
title_sort Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
author Chuquizuta Trigoso, Tony
author_facet Chuquizuta Trigoso, Tony
Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Castro Silupu, Wilson
author_role author
author2 Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Castro Silupu, Wilson
author2_role author
author
author
dc.contributor.author.fl_str_mv Chuquizuta Trigoso, Tony
Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Castro Silupu, Wilson
dc.subject.es_PE.fl_str_mv Jugos de fruta
Ingeniería de la producción
Industria alimentaria
topic Jugos de fruta
Ingeniería de la producción
Industria alimentaria
https://purl.org/pe-repo/ocde/ford#2.11.04
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.11.04
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2021-06-21T17:18:57Z
dc.date.available.none.fl_str_mv 2021-06-21T17:18:57Z
dc.date.issued.fl_str_mv 2020-11-17
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.citation.es_PE.fl_str_mv Chuquizuta, T. ...[et al]. (2020). Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy. IEEE Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9253756
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11537/26913
dc.identifier.journal.es_PE.fl_str_mv IEEE Engineering International Research Conference (EIRCON)
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/EIRCON51178.2020.9253756
identifier_str_mv Chuquizuta, T. ...[et al]. (2020). Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy. IEEE Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9253756
IEEE Engineering International Research Conference (EIRCON)
url https://hdl.handle.net/11537/26913
https://doi.org/10.1109/EIRCON51178.2020.9253756
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.*.fl_str_mv Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América
dc.rights.uri.*.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/3.0/us/
eu_rights_str_mv openAccess
rights_invalid_str_mv Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América
https://creativecommons.org/licenses/by-nc-sa/3.0/us/
dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv IEEE
dc.publisher.country.es_PE.fl_str_mv PE
dc.source.es_PE.fl_str_mv Universidad Privada del Norte
Repositorio Institucional - UPN
dc.source.none.fl_str_mv reponame:UPN-Institucional
instname:Universidad Privada del Norte
instacron:UPN
instname_str Universidad Privada del Norte
instacron_str UPN
institution UPN
reponame_str UPN-Institucional
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spelling Chuquizuta Trigoso, TonyOblitas Cruz, JimyArteaga Miñano, HubertCastro Silupu, Wilson2021-06-21T17:18:57Z2021-06-21T17:18:57Z2020-11-17Chuquizuta, T. ...[et al]. (2020). Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy. IEEE Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9253756https://hdl.handle.net/11537/26913IEEE Engineering International Research Conference (EIRCON)https://doi.org/10.1109/EIRCON51178.2020.9253756El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.ABSTRACT Nowadays, process control in the juice industry requires fast, safe and easily applicable methods. In this regard, the use of dielectric spectroscopy is being coupled to statistical methods such as machine learning in order to develop new methods to identify adulteration. However, there is a small number of scientific reports above the application of the aforementioned methods when citric fruit juices is being identified. Therefore, the objective of this research was to evaluate dielectric spectroscopy and four different classification techniques (Support Vector Machine - SVM, K-nearest neighbor-KNN, Linear Discriminat -LD and Quadratic Discriminat-QD) to discriminate between three citrus juices. For this purpose, samples of Citrus limetta, Citrus limettioides and Citrus reticulata were evaluated; obtaining its dielectric spectral profiles in the range of 5 to 9 GHz. Then from the spectral profiles the loss factor (e”) was calculated using the reflection coefficient. Next e” value was pretreated, reducing noise through a savitzky golay filter, and new variables created through Principal Component Analysis (PCA). Finally, the models for classification were constructed with the previously mentioned techniques and the principal components. The results shown that using four components the variance can be explained in 97%; likewise, the discrimination values vary between 88.9 and 100.0%, with SVM, LD and QD the best discrimination techniques all successfully at 100.0 %. Therefore; It is concluded that the technique of dielectric spectroscopy and machine learning presents potential for the discrimination of citrus fruit juices.Cajamarcaapplication/pdfengIEEEPEinfo:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de Américahttps://creativecommons.org/licenses/by-nc-sa/3.0/us/Universidad Privada del NorteRepositorio Institucional - UPNreponame:UPN-Institucionalinstname:Universidad Privada del Norteinstacron:UPNJugos de frutaIngeniería de la producciónIndustria alimentariahttps://purl.org/pe-repo/ocde/ford#2.11.04Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopyinfo:eu-repo/semantics/conferenceObjectCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81037https://repositorio.upn.edu.pe/bitstream/11537/26913/1/license_rdf80294ba9ff4c5b4f07812ee200fbc42fMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.upn.edu.pe/bitstream/11537/26913/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5211537/26913oai:repositorio.upn.edu.pe:11537/269132021-06-21 12:19:02.439Repositorio Institucional UPNjordan.rivero@upn.edu.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Application of machine Learning in the discrimination of citrus fruit juices: uses of dielectric spectroscopy
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