Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 34Citation - Scopus: 42Importance of Some Minor Compounds in Olive Oil Authenticity and Quality(Elsevier Ltd., 2020) Uncu, Oğuz; Özen, BanuBackground: Consumption and production of olive oils have been increasing steadily worldwide mainly due to proven health benefits and sensorial characteristics of olive oil. M the same time, rising demand makes it harder to protect olive oil genuineness; therefore, inauthentic products have been always a serious problem in olive oil industry. Scope and approach: Some minor compounds such as pigments (chlorophylls and carotenoids) including their derivatives pyropheophytins (PPPs), diacylglycerols (DAGs) and fatty acid ethyl esters (FAEEs) are all prominent compounds with their discriminatory and descriptive properties. Among several different approaches, use of these components to differentiate genuine and adulterated olive oils could be a promising choice since it is harder to mimic these compounds in fake mixtures. Recent studies focus on these compounds as authentication and quality tools for olive oil and potential of these compounds are aimed to be reviewed. Key findings and conclusions: Results from literature indicated that these parameters could be used in both authenticity and quality determination of olive oils with some limitations. Pigments were found to be more promising in geographical and/or varietal classification. All of the discussed components have successful applications in determination of olive oil quality with respect to storage history and oil grades. However, in detection of certain types of adulteration techniques such as soft deodorization, reviewed parameters did not work effectively alone. Regulations could be updated with these findings and use of combined parameters including discussed compounds could be further investigated for unsolved authentication problems.Article Citation - WoS: 82Citation - Scopus: 103A 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 BanuThe 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.Article Citation - WoS: 94Citation - Scopus: 106Distribution of Simple Phenols, Phenolic Acids and Flavonoids in Turkish Monovarietal Extra Virgin Olive Oils for Two Harvest Years(Elsevier Ltd., 2009) Ocakoğlu, Derya; Tokatlı, Figen; Özen, Fatma Banu; Korel, FigenMonovarietal extra virgin olive oils extracted from six dominant and economically important Turkish olive cultivars (memecik, erkence, domat, nizip-yaglik, gemlik, ayvalik) were examined for their simple phenolics, phenolic acids and flavonoid compounds over 2005 and 2006 harvest years. Total phenol contents, oxidative stabilities and chromatic ordinates as colour parameters were also measured. The most typical phenolic compounds that were identified in both years are hydroxytyrosol, tyrosol, vanillic acid, p-coumaric acid, cinnamic acid, luteolin, and apigenin. Multivariate data were analysed by principal component and partial least square-discriminant analyses. It was observed that phenolic profiles of olive oils depended highly on harvest season. In addition, oils of different olive cultivars have different distribution of phenols. No significant correlation was observed between oxidative stability and phenolic compounds. Increase in peroxide value over an accelerated oxidation period of 11 days showed weak correlations with total phenol content, vanillin, syringic acid and colour parameter a*, as 0.56, 0.55, -0.42, and 0.51, respectively, in terms of correlation coefficient r.Article Citation - WoS: 231Citation - Scopus: 264Detection of Adulteration of Extra-Virgin Olive Oil by Chemometric Analysis of Mid-Infrared Spectral Data(Elsevier Ltd., 2009) Gürdeniz, Gözde; Özen, Fatma BanuThis study focuses on the detection and quantification of extra-virgin olive oil adulteration with different edible oils using mid-infrared (IR) spectroscopy with chemometrics. Mid-IR spectra were manipulated with wavelet compression previous to principal component analysis (PCA). Detection limit of adulteration was determined as 5% for corn-sunflower binary mixture, cottonseed and rapeseed oils. For quantification of adulteration, mid-IR spectral data were manipulated with orthogonal signal correction (OSC) and wavelet compression before partial least square (PLS) analysis. The results revealed that models predict the adulterants, corn-sunflower binary mixture, cottonseed and rapeseed oils, in olive oil with error limits of 1.04, 1.4 and 1.32, respectively. Furthermore, the data were analysed with a general PCA model and PLS discriminant analysis (PLS-DA) to observe the efficiency of the model to detect adulteration regardless of the type of adulterant oil. In this case, detection limit for adulteration is determined as 10%.