Food Engineering / Gıda Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/12

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Author: search.filters.author.Tokatlı, FigenSubject: search.filters.subject.FTIR

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  • Article
    Citation - WoS: 75
    Citation - Scopus: 78
    Classification 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, Figen
    Fatty 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: 68
    Citation - Scopus: 76
    Differentiation of Mixtures of Monovarietal Olive Oils by Mid-Infrared Spectroscopy and Chemometrics
    (John Wiley and Sons Inc., 2007) Gürdeniz, Gözde; Tokatlı, Figen; Özen, Fatma Banu
    Fourier 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.