Food Engineering / Gıda Mühendisliği

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

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Publisher: search.filters.publisher.John Wiley and Sons Inc.Subject: search.filters.subject.Classification

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  • Article
    Citation - WoS: 14
    Citation - Scopus: 16
    Classification of Turkish Extra Virgin Olive Oils by a Saw Detector Electronic Nose
    (John Wiley and Sons Inc., 2011) Kadiroğlu, Pınar; Korel, Figen; Tokatlı, Figen
    An electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalik (A), Domat (D), Nizip (N), Gemlik-Edremit (GE), Ayvalik-Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose.
  • Article
    Citation - WoS: 37
    Citation - Scopus: 39
    Comparison 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, Figen
    The 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.