Food Engineering / Gıda Mühendisliği

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

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Author: search.filters.author.Uncu, OğuzSubject: search.filters.subject.Chemometrics

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  • Article
    Citation - WoS: 12
    Citation - Scopus: 12
    Mid-Infrared Spectroscopic Detection of Sunflower Oil Adulteration With Safflower Oil
    (CSIC Consejo Superior de Investigaciones Cientificas, 2019) Uncu, Oğuz; Özen, Banu; Tokatlı, Figen
    The oil industry is in need of rapid analysis techniques to differentiate mixtures of safflower-sunflower oils from pure oils. The current adulteration detection methods are generally cumbersome and detection limits are questionable. The aim of this study was to test the capability of a mid-infrared spectroscopic method to detect the adulteration of sunflower oil with safflower oil compared to fatty acid analysis. Mid-infrared spectra of pure oils and their mixtures at the 10-60% range were obtained at 4000-650 cm(-1) wavenumber and fatty acid profiles were determined. Data were analyzed by multivariate statistical analysis techniques. The lowest level of detection was obtained with mid-infrared spectroscopy at 30% while the fatty acid profile could determine adulteration at around 60%. Adulteration levels were predicted successfully using PLS regression analysis of infrared data with R-2 (calibration) = 0.96 and R-2 (validation) = 0.93. As a rapid and minimum waste generating technique, mid-infrared spectroscopy could be a useful tool for the screening of raw material to detect safflower-sunflower oil mixtures.
  • Article
    Citation - WoS: 82
    Citation - Scopus: 103
    A Comparative Study of Mid-Infrared, Uv-Visible and Fluorescence Spectroscopy in Combination With Chemometrics for the Detection of Adulteration of Fresh Olive Oils With Old Olive Oils
    (Elsevier Ltd., 2019) Uncu, Oğuz; Uncu, Oğuz; Özen, Banu; Özen, Fatma Banu
    The work aimed to detect and quantify adulteration of fresh olive oils with old olive oils from the previous harvest year by using different spectroscopic approaches in combination with chemometrics. Adulterated samples prepared in varying concentrations (10.50%(v/v)) were analyzed with fluorescence, Fourier transform-infrared (FT-IR), and ultraviolet-visible (UV-vis) spectroscopic methods. Orthogonal partial least square-discriminant analysis (OPLS-DA) and partial least squares (PLS) regression techniques were used for the differentiation of adulterated oils from the pure oils and prediction of adulteration levels, respectively. After the application of various pre-treatment methods, all of the OPLS-DA classification models generated for every spectroscopic technique successfully differentiated adulterated and non-adulterated oils with over 90% correct classification rate. FT-IR + UV-vis and fluorescence spectral data were also successfully used to predict adulteration levels with high coefficient of determinations for both calibration (0.94 and 0.98) and prediction (0.91 and 0.97) models and low error values for calibration (4.22% and 2.68%), and prediction (5.20% and 2.82%), compared to individual FT-IR and UV-vis spectroscopy were obtained. Therefore, FT-IR + UV-vis and fluorescence spectroscopy as being fast and environmentally friendly tools have great potential for both classification and quantification of adulteration practices involving old olive oil.