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Multivariate Analysis and Classification of 146 Odor Character Descriptors

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Multivariate Analysis and Classification of 146 Odor Character Descriptors

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dc.contributor.author Zarzo Castelló, Manuel es_ES
dc.date.accessioned 2022-05-09T18:04:38Z
dc.date.available 2022-05-09T18:04:38Z
dc.date.issued 2021-10 es_ES
dc.identifier.issn 1936-5802 es_ES
dc.identifier.uri http://hdl.handle.net/10251/182443
dc.description.abstract [EN] Introduction: Smells can be described by assigning the words that come to mind when sniffing an odorous material. A great number of terms can be applied, but not all of them are independent, and it is possible to establish groups of words often applied together when describing a smell. Such classification of olfactory descriptors is of scientific interest in order to better understand the dimensionality and structure of human olfactory perception space. For this purpose, compilations of olfactory profiles contain valuable information that may lead to certain consensus in odor classification. Methods: One of the most comprehensive odor databases is the Dravnieks¿ Atlas, which contains quantitative olfactory profiles for 160 samples. For each one, a large panel rated the applicability of 146 odor character descriptors on a numeric scale. Results: By applying principal component analysis to this Atlas, 105 descriptors were reorganized in 24 classes, and 33 attributes were considered as odors intermediate of two or three categories. The similarities between classes were studied by means of a further multivariate analysis based on latent variables, which provides valuable information about the most salient dimensions of odor space. Conclusions: Consistent with other reported statistical analyses of olfactory databases, the perceptual space of odor character is multidimensional with about 20¿30 dimensions, and it is better described as a continuum spectrum rather than as a segmented space. Implications: Attempts to classify all possible odor descriptors in a restricted number of classes appear to be inappropriate. Instead, 24 categories of related terms are proposed here, regarding the rest as intermediate smells, assuming that olfactory classes are not independent and follow certain hierarchy according to particular underlying dimensions. es_ES
dc.description.sponsorship Partial financial support was received from the Spanish Ministry or Education and Science under grant no. FU2004-1119. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Chemosensory Perception es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Odor classification es_ES
dc.subject Sensory analysis es_ES
dc.subject Olfactory psychophysics es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Multivariate Analysis and Classification of 146 Odor Character Descriptors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s12078-021-09288-1 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//IDI-20111190/ES/SISTEMA INTEGRADO PARA TRATAMIENTO DE ÁREAS CONTAMINADAS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//FU2004-1119/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Zarzo Castelló, M. (2021). Multivariate Analysis and Classification of 146 Odor Character Descriptors. Chemosensory Perception. 14(2):79-101. https://doi.org/10.1007/s12078-021-09288-1 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s12078-021-09288-1 es_ES
dc.description.upvformatpinicio 79 es_ES
dc.description.upvformatpfin 101 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\446882 es_ES
dc.contributor.funder Ministerio de Educación y Ciencia es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
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