Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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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: 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%.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.