Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Development of Chemometrics Method Based on Infrared Spectroscopy for the Determination of Cement Composition and Process Optimization [article](ACG Publications, 2022) Özdemir, Durmuş; Gümüş, Mehmet Gökhan; Tepeli, DilekIn combination with a multivariate calibration method, FTIR-ATR spectroscopy was presented as a rapid method for the determination of some major oxides (CaO, SiO2, Al2O3, Fe2O3) and minor oxides (MgO, SO4, Na2O, and K2O) in diverse materials (raw material, raw meal, additives, clinker, and types of cement) in cement manufacturing. The FTIR spectroscopy based multivariate models were generated by taking X-ray fluorescence (XRF) as a reference method. Among a number of spectral preprocessing methods, extended multiplicative scatter correction (EMSC) yielded the best PLS models. The standard error of prediction (SEP) for the optimal FTIR based PLS models ranged from 0.10 to 2.07 (w/w%), and the regression coefficient (R2) ranged from 0.95 to 0.99 for PLS predicted vs XRF reference plots. Statistical evaluation of the both methods was carried out by paired t-test at the 95% confidence level and the results showed that the FTIR-ATR combined with PLS model results are consistent with the XRF reference measurements for all the oxides studied. Compared to the XRF method, which can take anywhere from a few minutes to an hour for each measurement, the proposed method is faster, cheaper, and safer. The presented technology also allows rapid monitoring of a cement factory production line.Article Citation - WoS: 37Citation - Scopus: 41Determination of Olive Oil Adulteration With Vegetable Oils by Near Infrared Spectroscopy Coupled With Multivariate Calibration(SAGE Publications, 2010) Öztürk, Betül; Yalçın, Ayşegül; Özdemir, DurmuşThere has been growing public awareness about the health benefits of olive oil throughout the world in recent years, resulting in a significant increase in its consumption as part of the daily diet This demand has attracted fraudulent attempts to market olive oil which has been adulterated with cheaper oils. This study focuses on the near infrared (NIR) spectroscopic determination of adulteration of olive oil by vegetable oils using multivariate calibration. The binary, ternary and quaternary mixtures of olive, soybean, cotton, corn, canola and sunflower oils were prepared using a random design. The absorbance spectra of these synthetic samples were measured by a near infrared (NIR) spectrometer. A genetic algorithm-based variable selection algorithm, coupled with an inverse least squares multivariate calibration method (GILS) was used to build calibration models for possible adulterants and olive oil in the adulterated mixtures The correlation coefficients of actual versus predicted concentrations resulting from multivariate calibration models for the different oils were between 0 90 and 0.99 The results demonstrated that NIR spectroscopy in conjunction with the GILS method makes it possible to determine the adulteration of olive oils regardless of adulterant vegetable oils over a wide range of concentrations.Article Citation - WoS: 43Citation - Scopus: 48Determination of Honey Adulteration With Beet Sugar and Corn Syrup Using Infrared Spectroscopy and Genetic-Algorithm Multivariate Calibration(Wiley, 2018) Başar, Başak; Özdemir, DurmuşBACKGROUND Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm(-1) wavenumber range. RESULTS CONCLUSION Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values. The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. (c) 2018 Society of Chemical IndustryArticle Citation - WoS: 90Citation - Scopus: 101A Rapid Atr-Ftir Spectroscopic Method for Classification of Gelatin Gummy Candies in Relation To the Gelatin Source(Elsevier, 2019) Çebi, Nur; Doğan, Canan Ekinci; Ekin Meşe, Ayten; Özdemir, Durmuş; Arıcı, Muhammet; Sağdıç, OsmanGelatin is widely used in gummy candies because of its unique functional properties. Generally, porcine and bovine gelatins are used in the food industry. FTIR-ATR combined with chemometrics analysis such as hierarchical cluster analysis (HCA) (OPUS Version 7.2 software), principal component analysis (PCA) (OPUS Version 7.2 software) and partial least squares-discriminant analysis (PLS-DA) (Matlab R2017b) were used for classification and discrimination of gelatin gummy candies related to their gelatin source. The spectral region between 1734 and 1528 cm(-1) was selected for chemometric analysis. The potential of FTIR spectroscopy for determination of bovine and porcine source in gummy candies was examined and validated by a real-time polymerase chain reaction (PCR) method. Twenty commercial samples were tested by developed ATR-FTIR methodology and RT-PCR technique, mutually confirming and supporting results were obtained. Gummy candies were classified and discriminated in relation to the bovine or porcine source of gelatin with 100% success without any sample preparation using FTIR-ATR technique.Conference Object Citation - WoS: 2Citation - Scopus: 1Determination of Aluminum Oxide Thickness on the Annealed Surface of 8000 Series Aluminum Foil by Fourier Transform Infrared Spectroscopy(Springer, 2017) İnanç Uçar, Özlem; Ekin Meşe, Ayten; Birbaşar, Onur; Dündar, Murat; Özdemir, DurmuşAluminum foil produced with prescribed thermomechanical processing route develop oxide film. Alloy chemistry and annealing practices, particularly its duration and exposed temperature, determine the characteristics of the oxide film. The magnitude and characteristics of the oxide film may impair surface features leading to serious problems in some applications, such as coating, printing and in some severe cases failure in formability. Therefore, it is important for the rolling industry to be able to monitor the oxide formation on the foil products and quantify its thickness. Well known methods to measure an oxide thickness that is in the order of nanometer, require meticulous sample preparation techniques, long duration for measurements and sophisticated equipment. However, in this study, a simple and rapid grazing angle attenuated total reflectance infrared (GA-ATR-FTIR) spectroscopic method combined with chemometrics multivariate calibration has been developed for the oxide thickness determination which is validated with x-ray photoelectron spectroscopy (XPS). 3000 and 8000 series aluminum foil materials which were produced by twin roll casting technique were used in this study. Foil samples were annealed at various different temperatures and annealing times in a laboratory scale furnace. Immediately after collecting GA-ATR-FTIR spectra, the 3000 series alloy samples were sent to a laboratory where XPS reference oxide thickness measurements had been performed. Partial Least Squares (PLS) method was used to develop a multivariate calibration model based on FTIR spectra and XPS reference oxide thickness values in order to predict the aluminum oxide thickness. The correlation coefficient of XPS reference oxide thickness values versus grazing angle ATR-FTIR based PLS predicted values was found as 0.9903 the standard error of cross validation (SECV) was found to be 0.29 nm in range of 4.9–14.0 nm for Al2O3. In addition, the standard error of prediction (SEP) for the validation set was 0.24 nm with the model generated with three principal components (PCs). © The Minerals, Metals & Materials Society 2017.Conference Object Determination of Aluminum Rolling Oil and Machinery Oil Residues on Finished Aluminum Sheet and Foil Using Elemental Analysis and Fourier Transform Infrared Spectroscopy Coupled With Multivariate Calibration(John Wiley and Sons Inc., 2014) İnanç Uçar, Özlem; Mollaoğlu Altuner, Hatice; Günyüz, Mert; Dündar, Mustafa Murat; Özdemir, DurmuşThe surface characteristics of rolled aluminum products such as sheets and foils are strongly affected by the particular rolling process and the type of aluminum rolling oil compositions. After the rolling process, coiled aluminum sheets and foils undergoes annealing to form desired crystal structure and remove the rolling oil residues. Depending on the time and the temperature that rolled aluminum exposed for annealing, rolling oil residues are mostly removed from the coiled aluminum products but if there is any contamination in rolling oil due to hydraulic and gearing parts of the rolling systems these heavier oils are not easily evaporates from the aluminum surfaces especially inner parts of the coiled aluminum sheets and foils. These rolling oil contaminants create serious problems for the some specific applications of these aluminum products in certain industries such as automotive and coating as remaining thin oil layer prevents proper painting and coating. Therefore, it is very crucial for the rolling industry to be able to monitor the heavy oil contamination on the rolled products and determine the source of these contaminants .In this study, it was aimed to develop a nondestructive infrared spectroscopic method combined with chemometric multivariate calibration techniques for the quantitative determination of rolling oil residues and contaminants on the rolled aluminum products. To be able to generate multivariate calibration methods, an industrial elemental analysis system was adopted for the quantitative determination of heavy oil contaminants on the rolled aluminum products and these were used as reference values for infrared analysis of the same samples. In addition, apart from conventional use of elemental analysis systems for the total organic analysis, the raw data (raw chromatogram) obtained from elemental analysis was used to directly generate multivariate calibration models for each contaminant by using synthetically contaminated surfaces as the calibration samples. The results promised that elemental analysis can be used not just for the total organic content but also specifically to determine amount of each contaminant on the aluminum surfaces, it is also, expected that infrared spectroscopy with grazing angle spectra collection accessories can be used for nondestructive analysis of these contaminants.s.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, DurmuşAdulteration 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: 19Citation - Scopus: 24Geographical Origin of Imported and Domestic Teas (camellia Sinensis) From Turkey as Determined by Stable Isotope Signatures(Taylor and Francis Ltd., 2017) Cengiz, Mehmet Fatih; Turan, Önder; Özdemir, Durmuş; Albayrak, Yalçın; Perinçek, Fatih; Kocabaş, HalilIn this study, stable isotope signatures (δ13C, δ15N, and δD) of both tea leaves and tea infusions were investigated to identify the geographical origin of Turkish domestic and imported tea samples. Sixteen domestic tea samples collected from different locations in the Black Sea Region, which produces almost 100% of tea in Turkey, and 11 imported tea samples (Kenya, India, Sri Lanka, Indonesia, and China) purchased from importers were studied. δ13C, δ15N, and δD in the samples were determined using isotope ratio mass spectrometry (IR-MS). δ13C in the samples ranged from −29.18 ± 0.01 to −25.7 ± 0.2, while δ15N ranged between 1.1 ± 0.2 and 5.2 ± 0.8. However, δD in the samples were found to be in the range from 56.5 ± 0.3 to 72 ± 1. The classifications of the tea samples into domestic and imported tea samples were achieved with 100% accuracy using multivariate statistical analyses (principal component analysis, PCA, and hierarchical cluster analysis, HCA). In conclusion, the domestic tea samples had a distinctive isotopic fingerprint and the isotopic ratios used in the study can be significant predictors in determination of the geographical source of Turkish tea.Article Citation - WoS: 5Citation - Scopus: 4Uv-Visible Spectrophotometric Quantitative Analysis of Ternary Mixture Using Multivariate Calibration Methods Optimized by a Genetic Algorithm(Syscom 18 SRL, 2010) Özdemir, Durmuş; Dinç, Erdal; Baleanu, DimutruSimultaneous determination of ternary mixtures of caffeine, paracetamol and metamizol in commercial tablet formulations using UV-visible spectrophotometry combined with classical least squares (CLS) and genetic algorithm (GA) based multivariate calibration methods were demonstrated. The three genetic multivariate calibration methods are named as Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The GR method is based on a genetic algorithm based wavelength selection followed by a simple linear regression step whereas the GCLS and GILS are multivariate calibration methods modified by a wavelength selection principle using a genetic algorithm. The sample data set contains the UV-visible spectra of 47 synthetic mixtueres (4 to 48 μg/mL) and 16 tablets containing these components from two different producers. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the three components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of 0.04 and 2.34 μg/mL for all the four methods. Predictive ability of the calibration models generated with synthetic samples was tested with actual tablet samples and results obtained from four methods were compared. The SEP values for the tablets were in the range of 0.31 and 15.44 mg/tablets.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; Dıraman, Harun; Özdemir, DurmuşIn 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.
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