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Application of Multivariate Regression Methods to Predict Sensory Quality of Red Wines

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Application of Multivariate Regression Methods to Predict Sensory Quality of Red Wines

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dc.contributor.author Aleixandre Tudo, José es_ES
dc.contributor.author Alvarez Cano, María Inmaculada es_ES
dc.contributor.author García Esparza, Mª José es_ES
dc.contributor.author Lizama Abad, Victoria es_ES
dc.contributor.author Aleixandre Benavent, José Luís es_ES
dc.date.accessioned 2016-07-12T07:38:58Z
dc.date.available 2016-07-12T07:38:58Z
dc.date.issued 2015
dc.identifier.issn 1212-1800
dc.identifier.uri http://hdl.handle.net/10251/67439
dc.description Copyright - Czech Academy of Agricultural Sciences The original publication is available on http://agriculturejournals.cz/web/cjfs.htm es_ES
dc.description.abstract Several multivariate methods including partial least squares (PLS) regression, principal component regression (PCR) or multiple linear regression (MLR) have been applied to predict wine quality, based on the definition of chemical and phenolic parameters of grapes and wines harvested at different ripening levels. Three different models including grape phenolic maturity parameters (grape), wine phenolic parameters (wine) and a combination of grape and wine phenolic parameters (grape + wine) were analysed for each of the wine sensory attributes. The grape parameter model has been presented as the best test to predict wine quality based on sensory scores. On the other hand, wine models showed lower accuracy. The combination of grape and wine parameters presented intermediate results showing sometimes good predictability. Moreover, PLS and PCR appeared as more accurate multivariate methods compared to MLR. Although MLR showed higher correlation coefficients, lower RPD values were observed, displaying thus its lower prediction accuracy. Multivariate calibration statistics appeared as a promising tool to predict wine sensory quality in an easy and inexpensive way. es_ES
dc.language Inglés es_ES
dc.publisher CZECH ACADEMY AGRICULTURAL SCIENCES es_ES
dc.relation.ispartof Czech Journal of Food Sciences es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject PLS regression es_ES
dc.subject Sensory attributes es_ES
dc.subject Phenolic parameters es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.title Application of Multivariate Regression Methods to Predict Sensory Quality of Red Wines es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.17221/370/2014-CJFS
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments es_ES
dc.description.bibliographicCitation Aleixandre Tudo, J.; Alvarez Cano, MI.; García Esparza, MJ.; Lizama Abad, V.; Aleixandre Benavent, JL. (2015). Application of Multivariate Regression Methods to Predict Sensory Quality of Red Wines. Czech Journal of Food Sciences. 33(3):217-227. doi:10.17221/370/2014-CJFS es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion https://dx.doi.org/10.17221/370/2014-CJFS es_ES
dc.description.upvformatpinicio 217 es_ES
dc.description.upvformatpfin 227 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 33 es_ES
dc.description.issue 3 es_ES
dc.relation.senia 290776 es_ES
dc.identifier.eissn 1805-9317


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