Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]

Descripción del Articulo

The objective was to implement a non-invasive classification system for green coffee beans by using near-infrared spectroscopy (NIR) and multivariate data analysis. For this, 4 types of coffee were analyzed, according to variety and geographical location. The samples were repeated 5 times. The obser...

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Detalles Bibliográficos
Autores: Oblitas-Cruz, Jimy, Cieza-Rimarachin, Yuleyci, Castro-Silupu, Wilson
Formato: objeto de conferencia
Fecha de Publicación:2021
Institución:Universidad Privada del Norte
Repositorio:UPN-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.upn.edu.pe:11537/31098
Enlace del recurso:https://hdl.handle.net/11537/31098
http://dx.doi.org/10.18687/LACCEI2021.1.1.111
Nivel de acceso:acceso abierto
Materia:Café
Geografía
Espectroscopia
Green coffee beans
Geographical origin
https://purl.org/pe-repo/ocde/ford#2.11.04
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dc.title.es_PE.fl_str_mv Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
title Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
spellingShingle Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
Oblitas-Cruz, Jimy
Café
Geografía
Espectroscopia
Green coffee beans
Geographical origin
https://purl.org/pe-repo/ocde/ford#2.11.04
title_short Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
title_full Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
title_fullStr Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
title_full_unstemmed Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
title_sort Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]
author Oblitas-Cruz, Jimy
author_facet Oblitas-Cruz, Jimy
Cieza-Rimarachin, Yuleyci
Castro-Silupu, Wilson
author_role author
author2 Cieza-Rimarachin, Yuleyci
Castro-Silupu, Wilson
author2_role author
author
dc.contributor.author.fl_str_mv Oblitas-Cruz, Jimy
Cieza-Rimarachin, Yuleyci
Castro-Silupu, Wilson
dc.subject.es_PE.fl_str_mv Café
Geografía
Espectroscopia
Green coffee beans
Geographical origin
topic Café
Geografía
Espectroscopia
Green coffee beans
Geographical origin
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 The objective was to implement a non-invasive classification system for green coffee beans by using near-infrared spectroscopy (NIR) and multivariate data analysis. For this, 4 types of coffee were analyzed, according to variety and geographical location. The samples were repeated 5 times. The observed NIR spectrum was absorbance in the range of 1100 and 2500 nm. In order to reduce the data, the analysis of main components was used by testing 24 classification models, from which the one that reached the highest level of precision was the Linear Support Vector Machine (SVM) algorithm, reaching 98.8%, achieving fairly satisfactory discrimination with values of PC1 (97.9%), PC2 (1.9%) and PC3 (0.1%), reaching a total cumulative variation of the contribution of the first 3 PCs of 99.9%. These values demonstrated that NIR spectroscopy is a valid alternative for classification by geographical origin and variety of green coffee beans.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2022-08-05T15:13:38Z
dc.date.available.none.fl_str_mv 2022-08-05T15:13:38Z
dc.date.issued.fl_str_mv 2021-09-08
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.citation.es_PE.fl_str_mv Oblitas, J., Cieza, Y., & Castro, W. (2021). Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, (111). http://dx.doi.org/10.18687/LACCEI2021.1.1.111
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11537/31098
dc.identifier.journal.es_PE.fl_str_mv Proceedings of the LACCEI International Multi-conference for Engineering, Education and Technology
dc.identifier.doi.none.fl_str_mv http://dx.doi.org/10.18687/LACCEI2021.1.1.111
identifier_str_mv Oblitas, J., Cieza, Y., & Castro, W. (2021). Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, (111). http://dx.doi.org/10.18687/LACCEI2021.1.1.111
Proceedings of the LACCEI International Multi-conference for Engineering, Education and Technology
url https://hdl.handle.net/11537/31098
http://dx.doi.org/10.18687/LACCEI2021.1.1.111
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language spa
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
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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 LACCEI
dc.publisher.country.es_PE.fl_str_mv US
dc.source.es_PE.fl_str_mv Universidad Privada del Norte
Repositorio Institucional - UPN
dc.source.none.fl_str_mv reponame:UPN-Institucional
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spelling Oblitas-Cruz, JimyCieza-Rimarachin, YuleyciCastro-Silupu, Wilson2022-08-05T15:13:38Z2022-08-05T15:13:38Z2021-09-08Oblitas, J., Cieza, Y., & Castro, W. (2021). Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, (111). http://dx.doi.org/10.18687/LACCEI2021.1.1.111https://hdl.handle.net/11537/31098Proceedings of the LACCEI International Multi-conference for Engineering, Education and Technologyhttp://dx.doi.org/10.18687/LACCEI2021.1.1.111The objective was to implement a non-invasive classification system for green coffee beans by using near-infrared spectroscopy (NIR) and multivariate data analysis. For this, 4 types of coffee were analyzed, according to variety and geographical location. The samples were repeated 5 times. The observed NIR spectrum was absorbance in the range of 1100 and 2500 nm. In order to reduce the data, the analysis of main components was used by testing 24 classification models, from which the one that reached the highest level of precision was the Linear Support Vector Machine (SVM) algorithm, reaching 98.8%, achieving fairly satisfactory discrimination with values of PC1 (97.9%), PC2 (1.9%) and PC3 (0.1%), reaching a total cumulative variation of the contribution of the first 3 PCs of 99.9%. These values demonstrated that NIR spectroscopy is a valid alternative for classification by geographical origin and variety of green coffee beans.El objetivo fue implementar un sistema de clasificación no invasivo de granos de café verde haciendo uso de la espectroscopia de infrarrojo cercano (NIR) y el análisis de datos multivariados. Para ello se analizó 4 clases de café, de acuerdo a variedad y ubicación geográfica. Las muestras fueron repetidas 5 veces. El espectro NIR observado fue la absorbancia en el rango de 1100 y 2500 nm. Para poder reducir los datos se usó el análisis de componentes principales probando 24 modelos de clasificación, del cual el que alcanzó el mayor nivel de precisión fue el algoritmo tipo Support vector machine (SVM) del tipo lineal, alcanzado un 98.8%, logrando una discriminación bastante satisfactoria con valores de PC1 (97,9%), PC2 (1,9%) y PC3 (0,1%), alcanzando una variación total acumulada de la contribución de los primeros 3 PC del 99,9%. Estos valores demostraron que la espectroscopia NIR es una alternativa válida para clasificación por origen geográfico y variedad de granos de café verdeRevisión por paresCajamarcaapplication/pdfspaLACCEIUSinfo: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:UPNCaféGeografíaEspectroscopiaGreen coffee beansGeographical originhttps://purl.org/pe-repo/ocde/ford#2.11.04Determination of the geographical origin of two coffee varieties by NIR spectroscopy [Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIR]info:eu-repo/semantics/conferenceObjectORIGINALDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdfDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdfapplication/pdf1183707https://repositorio.upn.edu.pe/bitstream/11537/31098/1/Determination%20of%20the%20geographical%20origin%20of%20two%20coffee%20varieties%20by%20NIR%20spectroscopy.pdfedc1ff6e72e11c9fee1c202043d0568cMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81037https://repositorio.upn.edu.pe/bitstream/11537/31098/2/license_rdf80294ba9ff4c5b4f07812ee200fbc42fMD52TEXTDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdf.txtDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdf.txtExtracted texttext/plain25896https://repositorio.upn.edu.pe/bitstream/11537/31098/4/Determination%20of%20the%20geographical%20origin%20of%20two%20coffee%20varieties%20by%20NIR%20spectroscopy.pdf.txteafcbd7084076c83e0b426d6ded892e5MD54THUMBNAILDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdf.jpgDetermination of the geographical origin of two coffee varieties by NIR spectroscopy.pdf.jpgGenerated Thumbnailimage/jpeg5660https://repositorio.upn.edu.pe/bitstream/11537/31098/5/Determination%20of%20the%20geographical%20origin%20of%20two%20coffee%20varieties%20by%20NIR%20spectroscopy.pdf.jpg8d9dcf1175fe9cafbb4dca5b86dfe08aMD55LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.upn.edu.pe/bitstream/11537/31098/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5311537/31098oai:repositorio.upn.edu.pe:11537/310982022-08-06 03:03:19.243Repositorio Institucional UPNjordan.rivero@upn.edu.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