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Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine

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Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine

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dc.contributor.author Aleixandre Tudo, José es_ES
dc.contributor.author Helené Nieuwoudt es_ES
dc.contributor.author Aleixandre Benavent, José Luís es_ES
dc.contributor.author Du Toit, Wessel J. es_ES
dc.date.accessioned 2016-06-17T13:24:10Z
dc.date.issued 2015-02-04
dc.identifier.issn 0021-8561
dc.identifier.uri http://hdl.handle.net/10251/66103
dc.description.abstract [EN] The validation of ultraviolet-visible (UV-vis) spectroscopy combined with partial least-squares (PLS) regression to quantify red wine tannins is reported. The methylcellulose precipitable (MCP) tannin assay and the bovine serum albumin (BSA) tannin assay were used as reference methods. To take the high variability of wine tannins into account when the calibration models were built, a diverse data set was collected from samples of South African red wines that consisted of 18 different cultivars, from regions spanning the wine grape-growing areas of South Africa with their various sites, climates, and soils, ranging in vintage from 2000 to 2012. A total of 240 wine samples were analyzed, and these were divided into a calibration set (n = 120) and a validation set (n = 120) to evaluate the predictive ability of the models. To test the robustness of the PLS calibration models, the predictive ability of the classifying variables cultivar, vintage year, and experimental versus commercial wines was also tested. In general, the statistics obtained when BSA was used as a reference method were slightly better than those obtained with MCP. Despite this, the MCP tannin assay should also be considered as a valid reference method for developing PLS calibrations. The best calibration statistics for the prediction of new samples were coefficient of correlation (R(2)val) = 0.89, root mean standard error of prediction (RMSEP) = 0.16, and residual predictive deviation (RPD) = 3.49 for MCP and R(2)val = 0.93, RMSEP = 0.08, and RPD = 4.07 for BSA, when only the UV region (260-310 nm) was selected, which also led to a faster analysis time. In addition, a difference in the results obtained when the predictive ability of the classifying variables vintage, cultivar, or commercial versus experimental wines was studied suggests that tannin composition is highly affected by many factors. This study also discusses the correlations in tannin values between the methylcellulose and protein precipitation methods es_ES
dc.description.sponsorship We are grateful to the National Research Foundation (NRF, Thrip program) and Winetech for financial support. en_EN
dc.language Inglés es_ES
dc.publisher American Chemical Society es_ES
dc.relation.ispartof Journal of Agricultural and Food Chemistry es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Tannins es_ES
dc.subject Bovine serum albumin es_ES
dc.subject Methyl cellulose es_ES
dc.subject PLS regression es_ES
dc.subject Chemometrics es_ES
dc.subject Robustness es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.title Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine es_ES
dc.type Artículo es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1021/jf503412t
dc.rights.accessRights Cerrado 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.; Helené Nieuwoudt; Aleixandre Benavent, JL.; Du Toit, WJ. (2015). Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine. Journal of Agricultural and Food Chemistry. 63(4):1088-1098. https://doi.org/10.1021/jf503412t es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://dx.doi.org/10.1021/jf503412t es_ES
dc.description.upvformatpinicio 1088 es_ES
dc.description.upvformatpfin 1098 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 63 es_ES
dc.description.issue 4 es_ES
dc.relation.senia 304715 es_ES
dc.identifier.eissn 1520-5118


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