Chemistry / Kimya
Permanent URI for this collectionhttps://hdl.handle.net/11147/4072
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Article Citation - WoS: 10Citation - Scopus: 12Determination of the Quality and Purity Characteristics of Olive Oils Obtained From Different Regions of Turkey, Depending on Climatic Changes(Wiley, 2022) Sevim, Didar; Özdemir, Durmuş; Köseoğlu, Oya; Özdemir, Durmuş; Hakan, Mehmet; Büyükgök, Elif B.; Uslu, Hatice; Dursun, Özgür; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyVirgin olive oils (VOOs) obtained from olives grown in different regions of Turkey under changing climatic conditions sometimes show different sensory and chemical properties. This study was planned to determine whether these deviations are due to climatic changes or not. For this purpose, five different olive varieties (Ayvalik, Memecik, Gemlik, Nizip Yaglik, Kilis Yaglik) of commercial importance were harvested from the provinces/districts (four different region) where cultivation is intense during the 2017/2018-2020/2021 harvest years. Every year, olive samples were collected from 3 orchards from 13 provinces/districts. One hundred and fifty-six samples were subjected to the purity, quality and sensory analysis. Basic climatic values (average, minimum and maximum temperature, humidity and precipitation) were examined for four consecutive years. All of the examined olive oil samples were determined within the legal limits in terms of fatty acid composition and fatty acid ethyl ester values. However, delta-7-stigmastenol value from the sterol composition was found to be above 0.5% in some samples in all the years studied (total 21 samples). Delta-7-stigmastenol values of olive oil samples varied between 0.16% and 1.14%. Multiple linear regression analysis was applied using a genetic algorithm-based inverse least squares method to determine whether there is a relationship between climate data and delta-7-stigmastenol values. According to this result, it has been determined that the delta-7-stigmastenol value is high when the annual average relative humidity is low and the annual average temperature is high. There is an urgent need to make forward-looking plans due to climate change.Article Determination of Triacylglycerol Composition of Ayvalık and Memecik Olive Oils During Storage by Chemometric Methods(Sakarya Üniversitesi, 2017) Köseoğlu, Oya; Özdemir, Durmuş; Sevim, Didar; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyThe aim of present investigation is to discriminate two important Turkish olive cultivars (Ayvalık and Memecik) by studying their triacylglycerol (TAG) compositions during storage (15 months) taken from different orchard in Ayvalık and Aydın region which have a significant potential for olive oil production in Turkey, during 2009 and 2010 harvest years. Olives were harvested by hand at 2 different maturation indices and processed by an Abencor system. The olive oil samples were stored at room temperature and they were divided into two groups including exposed to diffused daylight and dark for a period of 15 months. Multivariate classification and clustering were done by the application of unsupervised chemometrics methods such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the TAG profiles of the olive oil samples. PCA and HCA analysis of olive oils showed significant differences according to harvest years and cultivars. PCA scores plot showed that the samples were classified into two main groups with respect to harvest years based on the first principal component (PC1). In terms of storage effect, there was no significant change in TAG compositions among the samples from beginning of storage to 15 months of storage regardless of storage conditions (either in dark or in daylight). In addition, PCA scores plot indicated that the samples were also successfully clustered into two sub-groups according to cultivars in both years based on the second principal component (PC2).Book Part Citation - WoS: 7Citation - Scopus: 14Olive Oil Adulteration With Sunflower and Corn Oil Using Molecular Fluorescence Spectroscopy(Elsevier Ltd., 2010) Öztürk, Betül; Arıkan, Aysun; Özdemir, Durmuş; Öztürk, Betül; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyAdulteration of olive oil with cheaper substitutes such as sunflower and corn oil is a major concern for the public. Rapid analysis methods are required for a quick and easy screening of possible adulteration attempts. Fluorescence spectroscopy coupled with a genetic algorithm-based multivariate calibration method allows the determination of olive oil adulteration with sunflower and corn oil. Because the standard error of prediction values are all below 1.30% (w/w) for the ternary set, fluorescence spectroscopy can be used as a fast screening method for possible olive oil adulteration with cheaper vegetable oils. In addition, the genetic algorithm used in the genetic inverse least squares (GILS) method is able to select and extract the most relevant information to build successful calibration models that have high predictive ability for the independent test samples.Article Citation - WoS: 23Citation - Scopus: 28Classification of Turkish Monocultivar (ayvalık and Memecik Cv.) Virgin Olive Oils From North and South Zones of Aegean Region Based on Their Triacyglycerol Profiles(John Wiley and Sons Inc., 2013) Gökçebag, Mümtaz; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyIn this study, a total of 22 domestic monocultivar (AyvalIk and Memecik cv.) virgin olive oil samples taken from various locations of the Aegean region, the main olive growing zone of Turkey, during two (2001-2002) crop years were classified and characterized by well-known chemometric methods (principal component analysis [PCA] and hierarchical cluster analysis [HCA]) on the basis of their triacylglycerol (TAG) components. The analyses of TAG components (LLL and major fractions LOO, OOO, POO, PLO, SOO, and ECN 42-ECN 50) in the oil samples were carried out according to the HPLC method described in a European Union Commission (EUC) regulation. In all analyzed samples the value of trilinolein (LLL), the least abundant TAG, did not exceed the maximum limit of 0.5 % given by the EUC regulation for different olive oil grades. The ranges of abundant TAG, namely LOO, OOO, POO, PLO, and SOO, were 13.30-16.08, 37.27-46.36, 21.39-23.24, 4.93-7.03, and 4.72-6.00 %. The TAG data of Aegean virgin olive oils were similar to those of products from important olive-oil-producing Mediterranean countries was determined. Also, the estimation of major fatty acids (FA) was carried out by using a formula based on TAG data. The PCA results showed that some TAG components have an important role in the characterization and geographical classification of 22 monocultivar virgin olive oil. The Aegean virgin olive oil samples were successfully classified and discriminated into two main groups as the North and South (growing) subzones or AyvalIk and Memecik olives (cultivars) according to the HCA results based on experimental TAG data and calculated major FA profile.Article Citation - WoS: 63Citation - Scopus: 73Near Infrared Spectroscopic Determination of Olive Oil Adulteration With Sunflower and Corn Oil(Taiwan Food and Drug Administration, 2007) Özdemir, Durmuş; Öztürk, Betül; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyDetermination of authenticity of extra virgin olive oils has become very important in recent years due to the increasing public concerns about possible adulterations with relatively cheap vegetable oils such as sunflower oil. This study was focused on the application of near infrared (NIR) spectroscopy in conjunction with multivariate calibration to identify the adulteration of olive oils. NIR transmittance measurements were made on pure olive oil and olive oil adulterated with varying concentrations (4-96%, v/v) of sunflower and corn oil in two sets of 26 binary and ternary mixtures. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the concentration of adulterants along with the concentration of olive oil in the samples. Over all, standard error of predictions ranged between 2.49 and 2.88% (v/v) for the binary mixtures of olive and sunflower oil and between 1.42 and 6.38% (v/v) for the ternary mixtures of olive, sunflower and corn oil.