Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 13Citation - Scopus: 14Uv-Vis Spectroscopy for the Estimation of Variety and Chemical Parameters of Olive Oils(Springer, 2021) Jolayemi, Olusola Samuel; Tokatlı, Figen; Özen, BanuOlive oils produced in different years from different varieties were studied with UV-Vis spectroscopy for classification and prediction. Multivariate models were created with second derivative spectral data, and tested with external validation sets. For varietal classification, orthogonal partial least square discriminant analysis resolved oil samples into various classes with correct classification rate more than 89% for validation set (n = 20). A sample of fresh and stored oils were also classified with a correct classification rate more than 90% for validation set (n = 20). In the predictions of chemical parameters (70 for calibration, 30 for validation), the combination of UV-Vis spectroscopy with orthogonal partial least square regression models showed potential for simultaneous quantification of chlorophylls (0.6-5.6 mg/kg; R-val(2) , 0.79; RPD, 1.97); carotenoids (0.6-3.3 mg/kg; R-val(2), 0.80; RPD, 2.38); ratio of mono to polyunsaturated fatty acids (3.6-8.8; R-val(2) , 0.77; RPD, 1.90), oleuropein derivatives (1.2-62.3 mg/kg; R-val(2) , 0.66; RPD, 1.77), and total phenol content (62.2-505 mg/kg; R-val(2) , 0.67; RPD, 1.74), although showed poor to moderate results for the quantification of free fatty acid (0.3-5.4%; R-val(2), 0.67; RPD, 1.64); monounsaturated fatty acids (66-76.5%; R-val(2) , 0.71; RPD, 1.67); polyunsaturated fatty acids (8.6-18.2%; R-val(2) , 0.73; RPD, 1.65). The models were unable to estimate oxidative stability, saturated fatty acids, and individual phenolics such as hydroxytyrosol, pinoresinol, luteolin, total phenolic acids (R-val(2) , 0.26-0.64; RPD, 0.60-1.52). Results showed the capacities of UV-Vis spectroscopy for classification of olive oils, and prediction of total pigments and phenol content and ratio of mono to polyunsaturated fatty acids.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: 30Citation - Scopus: 30Discriminative Capacities of Infrared Spectroscopy and E-Nose on Turkish Olive Oils(Springer Verlag, 2017) Jolayemi, Olusola Samuel; Tokatlı, Figen; Buratti, Susanna; Alamprese, CristinaThe potentials of Fourier transform (FT) near- (NIR) and mid-infrared (IR) spectroscopy, and electronic nose (e-nose) on varietal classification of Turkish olive oils were demonstrated. A total of 63 samples were analyzed, comprising Ayvalik, Memecik, and Erkence oils. Spectra were pretreated with standard normal variate and second derivative. Classification models were built with orthogonal partial least square-discriminant analysis (OPLS-DA), considering the single data sets and also the combined FT-NIR-IR spectra. OPLS-DA models were validated both by cross validation and external prediction. All the models gave good results, being the average correct classification percentages in prediction higher than 90% for spectroscopic data and equal to 82% for e-nose data. The combined FT-NIR-IR data set gave the best results in terms of coefficients of determination (0.95 and 0.67). Different e-nose sensors discriminated Ayvalik, Memecik, and Erkence oils, explaining their distinct aromatic profiles.Article Citation - WoS: 40Citation - Scopus: 45Phenolic Characterization and Geographical Classification of Commercial Extra Virgin Olive Oils Produced in Turkey(John Wiley and Sons Inc., 2012) Alkan, Derya; Tokatlı, Figen; Özen, BanuThe aim of this research was to characterize the extra virgin olive oil samples from different locations in the Aegean coastal area of Turkey in terms of their phenolic compositions for two consecutive years to show the classification of oil samples with respect to harvest year and geography. Forty seven commercial olive oil samples were analyzed with HPLC-DAD, and 17 phenolic compounds were quantified. Hydroxytyrosol, tyrosol, vanillic acid, p-coumaric acid, ferulic acid, cinnamic acid, luteolin and apigenin were the characteristic phenols observed in all oil samples for two harvest years. Syringic acid, vanillin and m-coumaric acid were the phenolic compounds appeared in the olive oil depending on the harvest year. Partial least square-discriminant analysis (PLS-DA) of data revealed that oils from the north Aegean and south Aegean areas had different phenolic profiles. The phenolic compounds, which played significant roles in the discrimination of the olive oils, were tyrosol, oleuropein aglycon, cinnamic acid, apigenin and hydroxytyrosol to tyrosol ratio. The Aegean coastal region is the largest olive oil producer and exporter of Turkey. This study shows that the olive oils from different parts of the region have their own defining characteristics that can be used in the authentication studies and geographical labeling of Turkish olive oils. © AOCS 2011.Article Citation - WoS: 37Citation - Scopus: 39Comparison of Fatty Acid Profiles and Mid-Infrared Spectral Data for Classification of Olive Oils(John Wiley and Sons Inc., 2010) Gürdeniz, Gözde; Özen, Banu; Tokatlı, FigenThe composition of olive oils may vary depending on environmental and technological factors. Fatty acid profiles and Fourier-transform infrared (FT-IR) spectroscopy data in combination with chemometric methods were used to classify extra-virgin olive oils according to geographical origin and harvest year. Oils were obtained from 30 different areas of northern and southern parts of the Aegean Region of Turkey for two consecutive harvest years. Fatty acid composition data analyzed with principal component analysis was more successful in distinguishing northern olive oil samples from southern samples compared to spectral data. Both methods have the ability to differentiate olive oil samples with respect to harvest year. Partial least squares (PLS) analysis was also applied to detect a correlation between fatty acid profile and spectral data. Correlation coefficients (R2) of a calibration set for stearic, oleic, linoleic, arachidic and linolenic acids were determined as 0.83, 0.97, 0.97, 0.83 and 0.69, respectively. Fatty acid profiles were very effective in classification of oils with respect to geographic origin and harvest year. On the other hand, FT-IR spectra in combination with PLS could be a useful and rapid tool for the determination of some of the fatty acids of olive oils.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: 75Citation - Scopus: 78Classification of Turkish Olive Oils With Respect To Cultivar, Geographic Origin and Harvest Year, Using Fatty Acid Profile and Mid-Ir Spectroscopy(Springer Verlag, 2008) Gürdeniz, Gözde; Özen, Fatma Banu; Tokatlı, FigenFatty acid composition and mid-infrared spectra of olive oils in combination with chemometric techniques were used in the classification of Turkish olive oils with respect to their varieties, growing location and harvest year. In particular, olive oil samples belonging to five different cultivars were obtained from the same orchard in the middle part of Aegean region and two of these varieties were also received from another orchard in northern part of the same region of Turkey in two consecutive harvest years. Evaluation of nine different fatty acid compositions with principal component analysis revealed clear differentiation with respect to variety, geographical origin and harvest year. On the other hand, mid-infrared spectra also achieved varietal and seasonal discrimination to some extent, but differentiation is not as clear as that obtained using fatty acid compositions. © 2008 Springer-Verlag.Article Citation - WoS: 68Citation - Scopus: 76Differentiation of Mixtures of Monovarietal Olive Oils by Mid-Infrared Spectroscopy and Chemometrics(John Wiley and Sons Inc., 2007) Gürdeniz, Gözde; Tokatlı, Figen; Özen, Fatma BanuFourier transform infrared (FT-IR) spectroscopy in combination with chemometric techniques has become a useful tool for authenticity determination of extra-virgin olive oils. Spectroscopic analysis of monovarietal extra-virgin olive oils obtained from three different olive cultivars (Erkence, Ayvalik and Nizip) and mixtures (Erkence-Nizip and Ayvalik-Nizip) of monovarietal olive oils was performed with an FT-IR spectrometer equipped with a ZnSe attenuated total reflection sample accessory and a deuterated tri-glycine sulfate detector. Using spectral data, principal component analysis successfully classified each cultivar and differentiated the mixtures from pure mono-varietal oils. Quantification of two different monovarietal oil mixtures (2-20%) is achieved using partial least square (PLS) regression models. Correlation coefficients (R2) of the proposed PLS regression models are 0.94 and 0.96 for the Erkence-Nizip and Ayvalik-Nizip mixtures, respectively. Cross-validation was applied to check the goodness of fit for the PLS regression models, and R 2 of the cross-validation was determined as 0.84 and 0.91, respectively, for the two mixtures.