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dc.contributor.authorOblitas, J.es_PE
dc.contributor.authorCieza-Rimarachin, Y.es_PE
dc.contributor.authorCastro, W.es_PE
dc.date.accessioned2026-02-08T00:07:49Z
dc.date.available2026-02-08T00:07:49Z
dc.date.issued2021-07-23
dc.identifier.urihttp://hdl.handle.net/20.500.14074/9539
dc.description.abstractThe 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.es_PE
dc.description.sponsorshipEste trabajo fue financiado por el Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYTes_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherLatin American and Caribbean Consortium of Engineering Institutionses_PE
dc.relation.ispartofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85122041424&doi=10.18687%2FLACCEI2021.1.1.111&partnerID=40&md5=fcb854325cf3de18cd97298fe1e3f96bes_PE
dc.relation.ispartofurn:isbn:978-958-52071-8-9es_PE
dc.relation.ispartofProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology,es_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/es_PE
dc.subjectGreen coffee beanses_PE
dc.subjectNIR spectroscopyes_PE
dc.subjectGeographical origines_PE
dc.titleDetermination of the geographical origin of two coffee varieties by NIR spectroscopy; Determinación del origen geográfico de dos variedades de café mediante espectroscopia NIRes_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
dc.publisher.countryPEes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#4.01.06es_PE
dc.identifier.doihttp://dx.doi.org/10.18687/LACCEI2021.1.1.111es_PE


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