Food Engineering / Gıda Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/12

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Author: search.filters.author.Tokatlı, FigenSubject: search.filters.subject.Anthocyanins

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  • Article
    Citation - WoS: 27
    Citation - Scopus: 29
    Differentiation of Wines With the Use of Combined Data of Uv-Visible Spectra and Color Characteristics
    (Academic Press Inc., 2016) Şen, İlknur; Tokatlı, Figen
    UV-visible spectra and color parameters of monovarietal wines with orthogonal partial least square-discriminant analysis (OPLS-DA) were shown to be practical and rapid methods for classification purposes. Red and white wines from the 2006-2009 vintages were characterized in terms of color, anthocyanin content and UV-visible spectra. Syrah and Cabernet Sauvignon wines had high color density and intensity. Kalecik Karasi wines had the highest CIELab parameters and the lowest color density. Boğazkere and Öküzgözü wines showed similarities with respect to their high red color parameters and were distinct from other wines. Merlot, Syrah and Öküzgözü wines had the highest total anthocyanin content (61.9-55. mg/L as median values). White wines made from Chardonnay, Muscat and Emir grapes were found to have different color characteristics. The vintage-based discrimination of red wines was mostly apparent in total anthocyanin contents. Different UV wavelength regions were found to be effective in classification with respect to variety and vintage. Correct classification rates in the validation set were 100% and 75%, for varietal and vintage classifications, respectively. This study demonstrated the potential of combination of UV-visible spectra and color characteristics to be used in the authentication of wines.
  • Article
    Citation - WoS: 27
    Citation - Scopus: 30
    Combination of Visible and Mid-Infrared Spectra for the Prediction of Chemical Parameters of Wines
    (Elsevier Ltd., 2016) Şen, İlknur; Öztürk, Burcu; Tokatlı, Figen; Özen, Banu
    Rapid and environmentally friendly methods for the prediction of chemical compositions have been an interest in the wine industry. The objective of the study was to show the potentials of combined use of visible and mid-infrared (MIR) spectroscopies to improve the prediction of various chemical compounds of wine as opposed to using mid-infrared range only. Wine samples of twelve grape varieties from two harvest years were analyzed. The chemical composition of wine samples was related to MIR and visible spectra using orthogonal partial least square (OPLS) regression technique. The prediction abilities were tested with crossvalidation and independent validation sets. The coefficient of determination of validation (R2 val) for anthocyanin compounds of red wines were between 0.76 and 0.90, and that for total phenol content was 0.90. Range of R2 val for glycerol, glycerol/ethanol ratio, malic acid, o-coumaric acid and °Brix were between 0.77 and 0.96. The spectral ranges that played significant roles in the predictions were also determined. The validations with independent data sets showed that the combination of visible and MIR ranges with multivariate methods improved the prediction of anthocyanin compounds and total phenols; produced comparable results for the rest of the parameters as MIR. This is the first study in the literature that shows the practical use of visible spectra along MIR. The combined use of these spectral ranges with multivariate models can be applied for the rapid, on-line determination of quality parameters and chemical profiles of wines.