Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 61Citation - Scopus: 70Use of Ftir and Uv-Visible Spectroscopy in Determination of Chemical Characteristics of Olive Oils(Elsevier, 2019) Uncu, Oğuz; Özen, Banu; Tokatlı, FigenIt was aimed to predict fatty acid ethyl ester (FAEE), wax, diacylglycerol (DAG) and color pigment contents of olive oils by using rapid and non-destructive spectroscopic techniques (FTIR and UV-vis) individually and in combination. Prediction models were constructed by using partial least squares (PLS) regression with cross and external validation. FAEEs were estimated best with FTIR + UV-Vis spectroscopy (R-cv.(2) = 0.84, R-pred(2) = 0.90, and RPD = 3.0). PLS model with R-cv.(2) = 0.79, R-pred(2) = 0.71, and RPD = 1.9 was obtained for the estimation of 1,2 DAG using FTIR spectral data. Major pigments, lutein, pheophytin a and their derivatives and total xanthophylls were quantified successfully by FTIR + UV-Vis with a range of R-cv.(2) of 0.71-0.85, R-pred(2) of 0.70-0.84, and RPD = 1.5-2.5 values but the prediction of the rest of the pigments were poor (R-cv(2) = 0.60-0.76, R-pred(2) = 0.42-0.62, and RPD = 1.2-1.5). Combination of two spectral data resulted in average prediction of wax content of oils (R-cal(2) = 0.95, R-pred(2) = 0.75, and RPD = 1.9). FTIR and UV-vis spectroscopic techniques in combination with PLS regression provided promising results for the prediction of several chemical parameters of olive oils; therefore, they could be alternatives to traditional analysis methods.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: 20Citation - Scopus: 21Geographical Differentiation of a Monovarietal Olive Oil Using Various Chemical Parameters and Mid-Infrared Spectroscopy(Royal Society of Chemistry, 2016) Uncu, Oğuz; Özen, BanuIncreased demand for monovarietal olive oils from local olive varieties with unique characteristics as well as regulations such as 'Protected Designation of Origin' makes it necessary to identify methods for geographical classification of this product. Geographical differentiation of olive oils from a local olive variety from nine distinct locations of a peninsula in the west part of Turkey is investigated by using mid-infrared spectroscopic data and several chemical parameters (total phenol content, fatty acid and phenol profile, total carotene and chlorophyll content and oxidative stability). The best differentiation with respect to geographical origin was obtained with partial least square-discriminant analysis (PLS-DA) of a combination of various chemical parameters. The fatty acid profile also provided good separation of geographic locations and was slightly better than mid-infrared analysis. The best separation was achieved with respect to palmitic, oleic and linoleic acid contents of olive oils. However, mid-infrared spectroscopy with the advantages of being environmentally friendly, cost effective and a fast method could also be used to differentiate monovarietal olive oils with respect to their growing locations by factors such as micro-climates, proximity of regions and position to the sea.Article Citation - WoS: 55Citation - Scopus: 59Prediction of Various Chemical Parameters of Olive Oils With Fourier Transform Infrared Spectroscopy(Academic Press Inc., 2015) Uncu, Oğuz; Özen, BanuVibrational spectroscopic techniques offer advantages such as rapid and accurate measurements with minimum sample preparation and waste generation. In this study, it was aimed at determining some important quality parameters (oxidative stability, colour pigments, fatty acid profile and phenolic composition) of olive oils by Fourier transform infrared spectroscopy as one of the vibrational spectroscopic methods. Partial least square calibration models were constructed in order to reveal any correlation between quality parameters and spectral data. Regression coefficients for developed models showed that oxidative stability (0.99), chlorophyll content (0.98), some major fatty acids (palmitic (0.87), oleic (0.94), and linoleic acids (0.97), saturated (0.91), monounsaturated (0.94) and polyunsaturated fatty acids (0.97)), hydroxytyrosol as a phenolic compound (0.97) and total phenolic content (0.99) were predicted successfully. Variable influence on the projection values indicated that palmitic, vanillic and cinnamic acids and hydroxytyrosol are the most significant contributors to oxidative stability of olive oils. © 2015 Elsevier Ltd.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%.