Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 35Citation - Scopus: 43Potential of Fourier-Transform Infrared Spectroscopy in Adulteration Detection and Quality Assessment in Buffalo and Goat Milks(Elsevier, 2021) Şen, Sevval; Dündar, Zahide; Uncu, Oğuz; Özen, BanuAdulteration of higher priced milks with cheaper ones to obtain extra profit can be the cause of adverse health effects as well as economic loss. In this study, it was aimed to differentiate goat-cow and buffalo-cow milk mixtures and also to estimate the critical quality parameters of these milks by the evaluation of Fourier-transform infrared (FTIR) spectroscopic data with chemometric methods. Raw goat and buffalo milks were mixed with cow milk at 1-50% (v/v) concentrations and FTIR spectra of the pure and mixed samples were obtained at 4000-650 cm-1. Orthogonal partial least square discriminant analysis (OPLS-DA) resulted in differentiation of goat-cow and buffalo-cow milk mixtures with 93% and 91% correct classification rates, respectively. Detection level for mixing is determined as higher than 5% for both milks. Total fat, protein, lactose and non-fat solid contents were predicted from FTIR spectral data of the combination of three types of milks by partial least square models with R2 values of 0.99. As a result, FTIR spectroscopy provides rapid and simultaneous detection of adulteration and prediction of quality parameters regardless of the milk type.Article Citation - WoS: 25Citation - Scopus: 30Prediction of Chemical Parameters and Authentication of Various Cold Pressed Oils With Fluorescence and Mid-Infrared Spectroscopic Methods(Elsevier Ltd., 2021) Doğruer, Ilgın; Uyar, H. Hilal; Uncu, Oğuz; Özen, BanuIt was aimed to compare the performances of two spectroscopic methods, fluorescence and mid-infrared spectroscopy, in terms of their adulteration detection and estimation of several chemical properties for various cold pressed seed oils. Spectroscopic profiles, fatty acid, free fatty acid and total phenol contents of pumpkin seed, grape seed, black cumin oil, and sesame seed oils were determined and these oils were mixed with sunflower oil at 1–50% (v/v). Both spectroscopic techniques provided comparable results for determination of adulteration of each oil type and the most successful prediction was obtained for pumpkin seed oil at levels >%1. Combined data set of oils resulted in successful quantification of their free fatty acid value, total phenol and major fatty acids contents with both spectroscopic methods regardless of oil type. Both techniques could be used as reliable, fast and environmentally friendly alternatives in the analyses of different types of seed oils. © 2020 Elsevier LtdArticle Citation - WoS: 14Citation - Scopus: 18Evaluation of Three Spectroscopic Techniques in Determination of Adulteration of Cold Pressed Pomegranate Seed Oils(Elsevier Ltd., 2020) Uncu, Oğuz; Napiórkowska, Alicja; Szajna, Tomasz K.; Özen, BanuIt was aimed to compare three spectroscopic methods in determination of adulteration of cold pressed pomegranate seed oils (PSOs) with sunflower oil in this research. UV–visible, mid-infrared and fluorescence spectra of pure and adulterated pomegranate oils (1–50%, v/v) were collected and data were analyzed with multivariate statistical analysis techniques. According to orthogonal partial least square discriminant analysis, best differentiation between pure and mixed samples was obtained with mid-infrared spectroscopy having 100% success rate. Fluorescence and UV–visible spectroscopy also provided good discrimination between samples with 96 and 88% successful classification rates, respectively. As a result of partial least square regression analysis, detection limits for mid-infrared, UV–visible and fluorescence spectroscopies are determined as >1, 5 and 10% in order. Since all spectroscopic methods provided detection of mixtures of cold pressed PSOs with sunflower oil at low concentrations they could serve as easy to use and rapid techniques in control laboratories. © 2020 Elsevier B.V.