Food Engineering / Gıda Mühendisliği

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

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Author: search.filters.author.Özen, Fatma BanuInstitution Author: search.filters.institutionAuthor.Tokatlı, Figen

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  • Article
    Citation - WoS: 94
    Citation - Scopus: 106
    Distribution 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; Korel, Figen; Korel, Figen; Özen, Fatma Banu; Tokatlı, Figen; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Monovarietal 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: 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; Özen, Fatma Banu; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    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; Tokatlı, Figen; Özen, Fatma Banu; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    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.