Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
Browse
2 results
Search Results
Master Thesis Chemometric Studies for Classification of Olive Oils and Detection of Adulteration(Izmir Institute of Technology, 2008) Gürdeniz, Gözde; Özen, BanuThe aim of this study is to classify extra-virgin olive oils according to variety, geographical origin and harvest year and also to detect and quantify olive oil adulteration. In order to classify extra virgin olive oils, principal component analysis was applied on both fatty acid composition and middle infrared spectra. Spectral data was manipulated with a wavelet function prior to principal component analysis. Results revealed more successful classification of oils according geographical origin and variety using fatty acid composition than spectral data. However, each method has quite good ability to differentiate olive oil samples with respect to harvest year.Middle infrared spectra of all olive oil samples were related with fatty acid profile and free fatty acidity using partial least square analysis. Orthogonal signal correction and wavelet compression were applied before partial least square analysis.Correlation coefficient and relative error of prediction for oleic acid (highest amount fatty acid) were determined as 0.93 and 1.38, respectively. Also, partial least square regression resulted in 0.85 as R2 value and 0.085 as standard error of prediction value for free fatty acidity quantification.In adulteration part, spectral data manipulated with principal component and partial least square analysis, to distinguish adulterated and pure olive oil samples, and to quantify level of adulteration, respectively. The detection limit of monovarietal adulteration varied between 5 and 10% and R2 value of partial least square was determined as higher than 0.95. Hazelnut, corn-sunflower binary mixture, cottonseed and rapeseed oils can be detected in olive oil at levels higher than 10%, 5%, 5% and 5%, respectively.Master Thesis Authentication and Prediction of Some Quality Parameters of Alcoholic Beverage Rakı With Infrared Spectroscopy(Izmir Institute of Technology, 2011) Yücesoy, Dila; Özen, BanuMid-infrared spectra of thirty- two Rakı samples of different brands, two types of Ouzo were collected and several chemical parameters were measured with analytical and instrumental methods. Moreover, Rakı samples were adulterated with methanol at 0.5-10% (vol/vol) and IR spectra were also obtained. Aims of this study are to classify Rakı samples according to raw material of Rakı and processing type, to predict some quality parameters of Rakı from IR spectra and also to detect adulteration of methanol in pure Rakı by using Fourier transform infrared spectroscopy in association with multivariate chemometric techniques and SIMCA. All samples were used to classify with respect to grape types (fresh or dried), raw material (only suma or suma and ethanol) and production process (double or triple distilled) by chemometric models. No clear classification could be found as parameters investigated because of predominant of alcoholic content in Rakı. In quantification analysis; pH, brix, electrical conductivity, total phenol and sugar content were determined with analytical reference methods for pure samples, then PLS were used to construct models to establish relationships between reference methods and FTIR spectra and to predict these quality parameters from spectral data. After PLS regression, highly good models were developed for brix and sugar. For adulteration analysis, six different Rakı samples were adulterated. First, PCA was used to detect Rakı samples adulterated with methanol. Then, PLS multivariate calibration model was constructed to determine the adulterant methanol content in Rakı . Consequently, successful results were obtained for detection of methanol in Raıı samples.