Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 24Citation - Scopus: 32Determination of Lignin and Extractive Content of Turkish Pine ( Pinus Brutia Ten.) Trees Using Near Infrared Spectroscopy and Multivariate Calibration(Springer Verlag, 2011) Üner, Birol; Karaman, İbrahim; Tanrıverdi, H.; Özdemir, DurmuşDetermination of quality parameters such as lignin and extractive content of wood samples by wet chemistry analyses takes a long time. Near-infrared (NIR) spectroscopy coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the NIR spectra, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. Pinus brutia Ten. is the most growing pine species in Turkey. Its rotation period is around 80 years; the forest products industry has widely accepted the use of Pinus brutia Ten. because of its ability to grow on a wide range of sites and its suitability to produce desirable products. Pinus brutia Ten. is widely used in construction, window door panel, floor covering, etc. Determination of lignin and extractive content of wood provides information to tree breeders on when to cut and how much chemicals are needed for the pulping and bleaching process. In this study, 58 samples of Pinus brutia Ten. trees were collected in Isparta region of Turkey, and their lignin and extractive content were determined with standard reference (TAPPI) methods. Then, the same samples were scanned with near-infrared spectrometer between 1,000 and 2,500 nm in diffuse reflectance mode, and multivariate calibration models were built with genetic inverse least squares method for both lignin and extractive content using the concentration information obtained from wet standard reference method. Overall, standard error of calibration (SEC) and standard error of prediction (SEP) ranged between 0.35% (w/w) and 2.40% (w/w).Article Citation - WoS: 3Citation - Scopus: 11Determination of Benazepril Hcl and Hydrochlorothiazide in Pharmaceutical Preparations Using Uv-Visible Spectrophotometry and Genetic Multivariate Calibration Method(Taiwan Food and Drug Administration, 2005) Özdemir, Durmuş; Dinç, ErdalSimultaneous determination of binary mixtures of benazepril and hydrochlorothiazide in pharmaceutical tablets using UV-visible spectrophotometry, classical least squares (CLS) and three genetic algorithms (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV- spectra of 28 synthetic mixtures of benazepril (12∼36 μg/mL) and hydrochlorothiazide (10∼22 μg/mL) and 16 tablets containing both compounds. The spectra cover the range from 210 to 360 nm in 0.1 mn intervals. Several calibration models were built with the four methods. The root mean square error of calibration (RMSEC) and validation (RMSEV) for the synthetic data were in the range of 0.19 and 0.34 μg/mL for all the genetic algorithm based methods. The root mean square error of Prediction (RMSEP) values for the tablets were in the range of 0.04∼0.20 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component was also included.Article Citation - WoS: 28Citation - Scopus: 27Determination of Thiamine Hcl and Pyridoxine Hcl in Pharmaceutical Preparations Using Uv-Visible Spectrophotometry and Genetic Algorithm Based Multivariate Calibration Methods(Pharmaceutical Society of Japan, 2004) Özdemir, Durmuş; Dinç, ErdalSimultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 μg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. 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 two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 μg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also includedArticle Citation - WoS: 16Citation - Scopus: 19Genetic Multivariate Calibration Methods for Near Infrared (nir) Spectroscopic Determination of Complex Mixtures(TUBITAK, 2004) Özdemir, Durmuş; Öztürk, BetülThe simultaneous determination of ternary mixtures of methylene chloride, ethyl acetate, and methanol using near infrared (NIR) spectroscopy and 4 different genetic algorithms based multivariate calibration methods was demonstrated. The 4 genetic multivariate calibration methods are genetic partial least squares (GPLS), genetic regression (GR), genetic classical least squares (GCLS) and genetic inverse least squares (GILS). The sample data set contains the NIR spectra of 63 ternary mixtures and covers the range from 900 to 2000 nm in 2 nm intervals. Of these 63 spectra, 42 were used as the calibration set, and 21 were reserved for the prediction purposes. Several calibration models were built with the 4 genetic algorithm based methods for each component that makes up the mixtures. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) were in the range of 0.22 to 2.5 (% by volume (v/v)) for all the 4 methods. A comparison of genetic algorithm selected wavelengths for each component and for each method was also included.