Hedef, Onur

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https://hdl.handle.net/11147/16031
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01. Izmir Institute of Technology
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NO POVERTY1
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ZERO HUNGER2
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GOOD HEALTH AND WELL-BEING3
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QUALITY EDUCATION4
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GENDER EQUALITY5
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CLEAN WATER AND SANITATION6
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AFFORDABLE AND CLEAN ENERGY7
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DECENT WORK AND ECONOMIC GROWTH8
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
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REDUCED INEQUALITIES10
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SUSTAINABLE CITIES AND COMMUNITIES11
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
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LIFE ON LAND15
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
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PARTNERSHIPS FOR THE GOALS17
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  • Master Thesis
    Development of Molecular Fluorescence Spectroscopy Based Multivariate Calibration Models for Quantitative Determination of Fatty Acids and Triacylglycerol Compositions of Olive Oils
    (01. Izmir Institute of Technology, 2020) Hedef, Onur; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 01. Izmir Institute of Technology; 04. Faculty of Science
    This study illustrates the quantitative determination of fatty acid and triacylglycerol composition of olive oils by using multivariate calibration methods namely partial least squares (PLS) and genetic inverse least squares (GILS) coupled with molecular fluorescence spectroscopy. The reference analysis of the olive oils was carried out with gas chromatography (GC) and high-performance liquid chromatography (HPLC) for the compositions, respectively. A total of 125 olive oil samples were collected from Marmara and Aegean olive growing regions in western Turkey, right after the olives oils are produced in the 2010 -2011 season. Chromatographic and fluorescence analyses were performed simultaneously on the samples and then collected spectra were combined with reference analysis results for the multivariate calibration step. Among the several components analyzed by both GC and HPLC, 10 components from fatty acids and 10 components from triacylglycerols were chosen for modeling. Multivariate calibration models were constructed by randomly selecting 100 samples as calibration set and assigning the remaining 25 samples to the independent validation set using PLS and GILS with leave one out cross-validation based on the fluorescence spectra of the olive oils. The results have demonstrated that the compositions could be successfully determined by using molecular fluorescence spectroscopy. The standard error of cross-validation (SECV) and standard error of prediction (SEP) values were acceptable for most of the components. The regression coefficients (R2) of reference values vs. predicted values ranged from 0.70 to 0.98, indicating that molecular fluorescence spectroscopy combined with multivariate calibration could potentially be used for quantitative determination.