Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Development of Fast and Simple Analytical Methods for the Determination of Honey Adulteration and Forgery Based on Chemometric Multivariate Data Analysis by Using Molecular Spectroscopy(Izmir Institute of Technology, 2016) Başar, Başak; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyHoney is one of the most valuable and expensive nutrition due to its health effects on human body. In recent years, honey adulteration has become an important problem and is a subject of many publications. There exists various analytical methods for determination of honey adulteration with 13C/12C isotope ratio mass spectrometry (IR-MS) being the most common. However, one of the recent studies indicates that different honey types depending on geographical and botanical origin may have significantly different 13C/12C isotope ratios rendering this method questionable. Thus, development of an analytical method for qualitative and quantitative determination of forgery and adulteration of honey without tedious and complicated sample preparation while being relatively simple and fast new analytical methods became a must. In this study, Fourier Transform Infrared spectroscopy coupled with Attenuated Total Reflectance and Fourier Transform Near Infrared spectroscopy based chemometrics multivariate calibration models were developed for the quantitative determination of honey adulteration. To simulate adulteration scenarios, artificially adulterated honey samples were prepared by adding beet sugar, corn syrup, glucose and sucrose with various concentrations to pure honey samples. Two different multivariate calibration methods namely Genetic Inverse Least Squares and Partial Least Squares were used and the applicability of these methods have been evaluated with an independent validations and test set composed of FTIR spectra of more than 100 pure honey samples along with the adulterated samples. Standard error of cross validation and standard error of prediction values for honey content of the samples were found 2.52% and 2.19% (w/w %), respectively.Master Thesis Development of Rapid and Simple Spectroscopic Techniques Based on Chemometrics Data Analysis for the Determination of Goat Milk Adulteration With Cow Milk(Izmir Institute of Technology, 2015) Samancıoğlu, Hülya; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyMilk and milk products are one of the most consumed foods. However, there has been an increase in milk adulteration, especially goat milk. Current methods for detection of milk adulteration are expensive, impractical and are not sufficient to answer quantitatively. Therefore, to meet this demand, a rapid, easy to use and inexpensive method was developed in this study. The proposed methodology is based on Fourier Transform Infrared Spectroscopy (FTIR) with the combination of multivariate calibration techniques for determination of adulteration of goat milk with cow milk. During the study, 150 raw goat milk samples were collected from different goats in 3 different seasons (June-2014, December 2014, March2015). Then, adulterated samples were prepared with goat milk, cow milk and water. Both adulterated and raw goat milk samples were analyzed with FTIR. Afterwards, 7 different multivariate calibration models (for each season (3), binary combination of seasons(3) and a ternary combination of all the seasons) were generated with synthetically prepared samples by using Genetic Inverse Least Squares (GILS) and Partial Least Squares (PLS) methods. These models were used to predict both adulterated and raw goat milk samples in order to evaluate the success of the models. Standard Error of Prediction (SEP) values for goat milk, cow milk and water are 7.9, 6.3 and 4.9 (w/w %), respectively, indicate satisfactory predictions by GILS. On the other hand, PLS models gave SEP values ranging between 6.4 and 12.9 (w/w %).Master Thesis Development of Genetic Algorithms Based Multivariate Calibration Models for the Determination of Lubricating Oil Compositions Using Fourier Transform Infrared Spectroscopy(Izmir Institute of Technology, 2013) Anıl, İrem; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of TechnologyEngine oils consist of base oils and additives. There have been a number of changes in the composition of engine oils depending on the time and using conditions like the decrease in the aditive amounts and increase in the amount of oxidation products. Although there are many physical and chemical standard test methods for the determination of oil quality, none of these methods alone can be used to determine the whole composition of engine oils. The main objective of this work, is to develop a single anlytical method that is simple, rapid and accurate for the quantitative determination of lubricating oil compositions using Fourier transform infrared (FTIR) spectroscopy combined with chemometric multivariate data analysis. For this study, a number of most intensively produced engine oils are chosen in an industrial lubrication oil plant and then synthetic mixtures of oil components were prepared in order to develop multivariate calibration models. The FTIR spectra of these samples were recorded using a three reflection attenuated total reflectance (ATR) accessory. The collected spectral data and the reference concentration values of the samples are then used in multivariate calibration modelling step using a genetic algorithm based inverse leaast squares (GILS) calibration method. It was observed that the correlation coefficients between the reference concentration values and the GILS predicted concentrations were around 0.99. As a result, FTIR spectroscopy combined with multivariate calibration can be a rapid method for the quaantitative determination of engine oil compositions.