Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Classification of Virgin Olive Oils From Different Olive Varieties and Geographical Regions by Electronic Nose and Detection of Adulteration(Izmir Institute of Technology, 2008) Kadiroğlu, Pınar; Korel, Figen; Korel, Figen; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyExtra virgin olive oils produced from fresh and healthy olive fruits have a delicate and unique flavor that makes them highly appreciated by consumers. Their taste and aroma are closely related to volatile and non-volatile compounds and determined by chromatographic and sensory analyses. However, these methods are expensive and time consuming to be used routinely in food industry. Electronic nose that can mimic the human sense of smell and provide low-cost and rapid sensory information is a new approach allowing the discrimination of aroma fingerprints of oils. In this study, the aroma fingerprints of Turkish extra virgin olive oils produced from various olive varieties (Ayvalık, Gemlik, Memecik, Erkence, Domat and Nizip) and Ayvalık and Gemlik olive varieties growing in two different regions of West Turkey (İzmir and Edremit) and the commercial extra virgin olive oils obtained from Tariş Olive and Olive Oil Agricultural Sales Cooperatives Union during two consecutive harvest years were determined by an electronic nose. In addition, the electronic nose was proposed for the detection of adulteration of these oils with monovarietal olive oils and with other edible oils such as sunflower, corn, soybean and hazelnut oils. The data were analyzed using chemometric methods by soft independent modeling of class analogy (SIMCA) software. As a conclusion, it was found that the electronic nose could provide good separation on some of the varieties and geographical regions. The electronic nose has been able to differentiate adulterated and non-adulterated extra virgin olive oils at higher than 10 % adulteration level successfully.Master Thesis Chemometric Studies for Classification of Olive Oils and Detection of Adulteration(Izmir Institute of Technology, 2008) Gürdeniz, Gözde; Özen, Fatma Banu; Özen, Banu; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThe 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 Development of Chromatographic and Moleculer Spetroscopic Multivariate Chemometric Models for the Geographical Classification of Olive Oils(İzmir Institute of Technology, 2013) Çelik, Deniz; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyOlive oil is a fat obtained from the olive (the fruit of Olea europaea; family Oleaceae), a traditional tree crop of the Mediterranean Basin. The oil is produced by grinding whole olives and extracting the oil by mechanical or chemical means. It is commonly used in cooking, cosmetics, pharmaceuticals, and soaps and as a fuel for traditional oil lamps. The classification of olive based on geographical origin is of great interest since the quality of olive oil depends on its chemical composition and geographical origin. In this study, it is aimed to develop classification models using elemental and molecular composition of olive oil samples via chromatographic method and molecular spectrometry. For this purpose, olive oil samples from diffirent regions of Turkey (Manisa and Bursa) were collected from producers and they were scanned with Fourier Transform Infrared spectrometer equiped with attenuated total reflectance (FTIR-ATR) accesory, and Gas Chromatography (GC), High Performance Liquid Chromatography (HPLC). Afterwards, any clustering of samples based on their regions was investigated using principal component analysis (PCA) and hierarchical cluster analysis (HCA). In conclusion, although molecular spectrometry is more advantageous for the classification of olive oil samples in the case of saving time, saving chemicals and ease of usage, chromatography gave better classification results based on geograpical origin compared to results obtained with molecular spectrometry.Master Thesis Classification of Turkish Virgin Olive Oils Based on Their Phenolic Profiles(Izmir Institute of Technology, 2008) Ocakoğlu, Derya; Tokatlı, Figen; Tokatlı, Figen; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyVirgin olive oil is different from other plant oils with its high phenolic content. The resistance to oxidation and the protection against some diseases has been linked to these components of olive oil. The sensorial characteristic of extra virgin olive oil is also related to its phenolic compounds.In this work, it is aimed to determine the phenolic profiles of Turkish olive oils, which have high economic value for Turkey. Phenolic profiles of monovarietal extra virgin olive oil samples extracted from six dominant and economically important Turkish olive cultivars (memecik, erkence, domat, nizip-yaglik, gemlik, ayvalik) and commercial extra virgin olive oil samples from two different areas (south and north) of the Aegean coast were determined for 2005 and 2006 harvest years. Total phenol contents, oxidative stabilities and chromatic ordinates as colour parameters were also measured. The effect of cultivar, geographical area and harvest year on phenolic profiles of olive oils was investigated. Multivariate data were subjected to principal component and partial least square-discriminant analyses.Typical phenolic substances of extra virgin olive oils from different variety and regions are; p-coumaric acid, cinnamic acid & apigenin for memecik, erkence oils and also for oils of south Aegean; vanillin & syringic acid for ayvalik, gemlik and also for oils of north Aegean. Domat oils were characterized by their relatively high content of oleuropein aglycon. Nizip oils were separated by their 4-hydroxyphenyl acetic acid content, which was determined in very low amounts or none in other olive oils. It was observed that harvest year strongly affected the phenolic profiles of olive oils. In addition, phenolic composition was found to be useful in discriminating the olive oils from different variety and geographical area.