Firstly, I wish to express my grateful thanks to Assist. Prof. Ritchie Eanes for his guidance, mo... more Firstly, I wish to express my grateful thanks to Assist. Prof. Ritchie Eanes for his guidance, motivation, supports and encouragement throughout this project. I would like to express my gratitude to Assist. Prof. Durmuş Özdemir who contributed his time, effort, assistance and expertise in data processing part of the project. Also I would like to thank to Assoc. Prof. Ahmet E. Eroğlu for his valuable critiques and assistance. I wish to thank Ahmet Öğüt at Hıfzısıhha Institute for his helps in ICP-MS analysis and Steven Christopher at NIST for supplying the whale liver samples. I wish to express my special thanks to our research specialists Oya Altungöz for her patient and tolerant work in ICP-OES analysis and Sinan Yılmaz for his valuable helps in microwave digestion of the samples. I am grateful to all my friends in IYTE especially Arzu Erdem, Aslı Erdem, Betül Öztürk, Murat Erdoğan, Müşerref Yersel and Özge Tunusoğlu for their endless patience, support, encouragement, and motivatio...
In this study, oil samples of Ayvalik and Memecik, domestic olive cultivars of Aegean region prov... more In this study, oil samples of Ayvalik and Memecik, domestic olive cultivars of Aegean region providing aproximately 65 % of virgin olive oil production of Turkey, were analysed and classified by using common spectroscopic (FTNIR, FTIR-ATR, Excitation-Emission [EX-EM] Fluorescence Spectroscopy and Synchronous [SYN] Fluorescence Spectroscopy) methods. The analysed oil samples consisted of totally 9 samples – except 1 mixed organic oil sample – taken from North Aegean [Ayval›k olive cultivar] (n=4) and South Aegean [Memecik olive cultivar] (n=4) subzones. The samples were stored in PET glass at room temperature and they were divide into two groups including exposed to diffused day ligth and covered with aluminium folios [dark]. The classification of Ayval›k ve Memecik olive oil samples were carried out by the most used chemometric (Principal Component Analysis, PCA and Hierarchical Cluster Analysis, HCA) techniques. Ayval›k and Memecik oil samples were classified noticeable according t...
All of the imaging studies in nuclear medicine start with a suitable radiopharmaceutical preparat... more All of the imaging studies in nuclear medicine start with a suitable radiopharmaceutical preparation step. In radiopharmaceutical synthesis, an organic or biochemical molecule is combined with a radioactive element to form a complex. This process is known as radiolabeling (1). In a radiopharmaceutical labeling study, it is important to realize that whether or not the radiolabeled chemical complex is in the expected radiochemical form has a vital role for all the nuclear medicine imaging processes. The common method of radiopharmaceutical quality control is the chromatographic analysis such as PC, TLC, and HPLC. In nuclear medicine practice, application of these methods is called radiopharmaceutical quality control(2). The agrement of results obtained from such chromatographic analysis methods with the criterions given in United States Pharmacopea (USP) means the regulatory permission of the use of that radiopharmaceutical in proposed applications^). In this study separation of sever...
Bu calismada, Turkiye’nin zeytinyagi uretiminin % 65’ini Olusturan Ege bolgesinin hakim zeytin ce... more Bu calismada, Turkiye’nin zeytinyagi uretiminin % 65’ini Olusturan Ege bolgesinin hakim zeytin cesidi olan Ayvalik ve Memecik yag orneklerinin en yaygin spektroskopik yontemler ile (FTNIR, FTIR-ATR, Excitation-Emission [EX-EM] ve Senkronize [SYN] Floresans Spektroskopisi) analiz edilerek siniflandirilmasi gerceklestirilmistir. Analiz edilen yag ornekleri organik ve karisik cesitlerden uretilen bir ornek disinda Kuzey Ege (Ayvalik cesidi) (n=4) ve Guney Ege (Memecik cesidi) (n=4) alt bolgelerinden alinmis toplam 9 adetten Olusmaktadir. Oda sicakliginda PET siseler icinde muhafaza edilen yag ornekleri gun isigina maruz birakilan ve aluminyum folyo ile kaplanmis (karanlik) olarak iki gruba ayrilmistir. Ayvalik ve Memecik cesidi naturel zeytinyaglarinin siniflandirilmasi en yaygin kullanilan kemometrik yontemler ile (Temel Bilesen Analizi, PCA ve Asamali Kumeleme Analizi, HCA) gerceklestirilmistir. Ayvalik ve Memecik cesitleri spektroskopik yontemlerin sonuclari temelinde cesit, orijin ...
In this study, the oil samples of Gemlik olive cultivar provided from different locations (n=10) ... more In this study, the oil samples of Gemlik olive cultivar provided from different locations (n=10) were analysed by using chromatographic ([GLC] Fatty Acid [FA] and [HPLC] Triacyl Glycerol [TAG] profiles) and spectroscopic (Excitation-Emission [EX-EM] Fluorescence Spectroscopy) methods. The classification of monocultivar (Gemlik cv) olive oil samples were carried out by the most used chemometric (Principal Component Analysis, PCA and Hierarchical Cluster Analysis, HCA) techniques. The oils made of 10 monocultivar (Gemlik olive) samples were succesfully classified according to locations (as Marmara, Aegean and Mediterannean zones) based on FA and TAG profiles. Also, similar classification exhibited the results of Excitation-Emission [EX-EM] fluoresence spectroscopy for Gemlik olive cultivar. In additon, the spectroscopic methods could be exhibited promising effects for the correct classification of virgin
In this study, stable isotope signatures (δ 13 C, δ 15 N, and δD) of both tea leaves and tea infu... more In this study, stable isotope signatures (δ 13 C, δ 15 N, 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. δ 13 C, δ 15 N, and δD in the samples were determined using isotope ratio mass spectrometry (IR-MS). δ 13 C in the samples ranged from −29.18 ± 0.01 to −25.7 ± 0.2, while δ 15 N 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.
Lung cancer is the major cause of cancer death in the World. Low dose CT screening for early diag... more Lung cancer is the major cause of cancer death in the World. Low dose CT screening for early diagnosis has still had some problems due to high rate of false-positive results. There is urgently need to new, in particular non-invasive biomarkers in the early diagnosis of lung cancer. The main objective of this study is to detect role of volatile organic compounds (VOCs) as potential biomarkers in early diagnosis of lung cancer. Newly diagnosed lung cancer patients and controls included into this prospective-case control study. Breath samples were collected via lab-made sample collector where the VOC content was enriched on a lab-made polythiphene solid phase microextraction (SPME) fibers. Then, the VOC content was analyzed by inserting into injection port of a gas chromatography coupled with mass detector (GC-MS) allowing thermal desorption. Commercial Carboxen/Polydimethylsiloxane SPME fibers were also utilized. A total of 67 lung cancer patients along with 69 controls9 breath samples were collected and analyzed. The results were interpreted with chemometric approach by using Principle Component Analysis (PCA). According to the first preliminary results of the study; via breathe sample analyses it is highly possible to distinguish lung cancer patients at early stages of their disease than the healthy controls with significantly different signal level of VOCs compounds in PCA.
Malassezia species which are lipophilic exobasidiomycetes fungi, have been accepted as members of... more Malassezia species which are lipophilic exobasidiomycetes fungi, have been accepted as members of normal cutaneous flora as well as causative agent of certain skin diseases. In routine microbiology laboratory, species identification based on phenotypic characters may not yield identical results with taxonomic studies. Lipophilic and lipid-dependent Malassezia yeasts require lipid-enriched complex media. For this reason, Fourier transform infrared (FT-IR) spectroscopy analysis focused on lipid window may be useful for identification of Malassezia species. In this study, 10 different standard Malassezia species (M.dermatis CBS 9145, M.furfur CBS 7019, M.japonica CBS 9432, M.globosa CBS 7966, M.nana CBS 9561, M.obtusa CBS 7876, M.pachydermatis CBS 1879, M.slooffiae CBS 7956, M.sympodialis CBS 7222 and M.yamatoensis CBS 9725) which are human pathogens, have been analyzed by FT-IR spectroscopy following standard cultivation onto modified Dixon agar medium. Results showed that two main gr...
The surface characteristics of rolled aluminum products such as sheets and foils are strongly aff... more The 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 infrared spectroscopy with grazing angle spectra collection accessories can be used for nondestructive analysis of these contaminants.
Determination of quality parameters such as lignin and extractive content of wood samples by wet ... more Determination 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 spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. Pinus nigra Arnold. Var. pallasiana is the second most growing pine species in Turkey. Even though its rotation period is very high, around 120 years, the forest products industry has widely accepted the use of Pinus nigra because of its ability to grow on a wide range of sites and its suitability to produce desirable products. In this study, 51 samples of Pinus nigra trees were collected and their lignin and extractive content were determined with standard reference (TAPPI) methods. Then, the same samples were scanned with near infrared spectrometer between 1000 and 2500 nm in diffuse reflectance mode. 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) were ranged between 0.35% (w/w) and 2.4% (w/w).
There has been growing public awareness about the health benefits of olive oil throughout the wor... more There 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 predic...
Biodiesel is gaining more importance as an attractive fuel due to the enormous consumption of ene... more Biodiesel is gaining more importance as an attractive fuel due to the enormous consumption of energy in the world. It can easily be isolated from transesterification reactions of vegetable oils or fats with alcohols in the presence of catalyst [1]. The quality of final product is an important issue and therefore a lot of techniques have been developed. Near infrared (NIR) spectroscopy has recently become an alternative method to the conventional analytical methods such as chromatography. In this study, laboratory scaled biodiesel was produced from two different vegetable oils (sunflower and corn oil). In addition, the mixture of vegetable oils and a mono alcohol with their corresponding biodiesel were prepared to represent the reaction media for sunflower and corn oil respectively. Development of multivariate calibration methods are carried following the near infrared spectroscopic measurements. Since NIR measurements include several spectral overlaps due to the multicomponent media...
The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy an... more The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy and three different genetic algorithm-based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are genetic regression (GR), genetic classical least squares (GCLS), and genetic inverse least squares (GILS). The sample data set was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) with the permission of
International Journal of Food Science and Technology, 2006
Determination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemi... more Determination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemistry analyses takes long time. Near infrared spectroscopy (NIR) coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. In this study, two different wheat data sets are investigated with the aim of establishing successful calibration models using NIR spectra of wheat samples. The first data set (material 1) was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) and contained 100 NIR spectra of wheat of which wet chemical analysis of protein and moisture content were done with reference methods. The second data set (material 2) contained 176 spectra and was downloaded from http://www.spectroscopynow.com/Spy/basehtml/SpyH/1,1181,2-1-2-0-0-newsdetail-0-74,00.html. This wheat data set was given with the quality parameters, such as protein content, moisture content, other residues, dry mass, protein content in dry mass and hardness that were determined previously. Multivariate calibration models generated with genetic inverse least squares method demonstrated very good prediction results for the parameter mentioned here. Overall, the average per cent recoveries (APR) ranged between 99.23% and 100.34% with a standard deviation (SD) ranging from 0.34 to 3.15 for all the parameters investigated, except hardness. The APR value of hardness was 103.32 with the SD of 14.97.
Genetic algorithm based multivariate calibration models were generated for infrared spectroscopic... more Genetic algorithm based multivariate calibration models were generated for infrared spectroscopic determination of aluminum rolling oil additives and contaminants such as gear and hydraulic oils. Two different additives and six different suspected contaminants were investigated in the base oil lubricant. Routine analysis samples from 9 different aluminum rolling systems were collected in a period of 2 months in an aluminum rolling plant and gas chromatography (GC) is used as the reference method. Infrared absorbance spectra of the samples were then collected and the reference values obtained with GC were used together with these spectra for model building. Inverse least squares method was optimized with a genetic algorithm by selecting the most contributing regions of the infrared spectra for each component. The R 2 values between GC and multivariate spectroscopic determinations were around 0.99 indicating a good correlation between the two methods. Performance of genetic algorithm based multivariate calibration models were also compared with partial least squares (PLS) method. The study showed that infrared spectroscopy coupled with multivariate calibration can be used for continuous monitoring of additives and contaminants in aluminum rolling oil. By this way, analysis time is significantly reduced and simultaneous determination of all the components can be accomplished.
Firstly, I wish to express my grateful thanks to Assist. Prof. Ritchie Eanes for his guidance, mo... more Firstly, I wish to express my grateful thanks to Assist. Prof. Ritchie Eanes for his guidance, motivation, supports and encouragement throughout this project. I would like to express my gratitude to Assist. Prof. Durmuş Özdemir who contributed his time, effort, assistance and expertise in data processing part of the project. Also I would like to thank to Assoc. Prof. Ahmet E. Eroğlu for his valuable critiques and assistance. I wish to thank Ahmet Öğüt at Hıfzısıhha Institute for his helps in ICP-MS analysis and Steven Christopher at NIST for supplying the whale liver samples. I wish to express my special thanks to our research specialists Oya Altungöz for her patient and tolerant work in ICP-OES analysis and Sinan Yılmaz for his valuable helps in microwave digestion of the samples. I am grateful to all my friends in IYTE especially Arzu Erdem, Aslı Erdem, Betül Öztürk, Murat Erdoğan, Müşerref Yersel and Özge Tunusoğlu for their endless patience, support, encouragement, and motivatio...
In this study, oil samples of Ayvalik and Memecik, domestic olive cultivars of Aegean region prov... more In this study, oil samples of Ayvalik and Memecik, domestic olive cultivars of Aegean region providing aproximately 65 % of virgin olive oil production of Turkey, were analysed and classified by using common spectroscopic (FTNIR, FTIR-ATR, Excitation-Emission [EX-EM] Fluorescence Spectroscopy and Synchronous [SYN] Fluorescence Spectroscopy) methods. The analysed oil samples consisted of totally 9 samples – except 1 mixed organic oil sample – taken from North Aegean [Ayval›k olive cultivar] (n=4) and South Aegean [Memecik olive cultivar] (n=4) subzones. The samples were stored in PET glass at room temperature and they were divide into two groups including exposed to diffused day ligth and covered with aluminium folios [dark]. The classification of Ayval›k ve Memecik olive oil samples were carried out by the most used chemometric (Principal Component Analysis, PCA and Hierarchical Cluster Analysis, HCA) techniques. Ayval›k and Memecik oil samples were classified noticeable according t...
All of the imaging studies in nuclear medicine start with a suitable radiopharmaceutical preparat... more All of the imaging studies in nuclear medicine start with a suitable radiopharmaceutical preparation step. In radiopharmaceutical synthesis, an organic or biochemical molecule is combined with a radioactive element to form a complex. This process is known as radiolabeling (1). In a radiopharmaceutical labeling study, it is important to realize that whether or not the radiolabeled chemical complex is in the expected radiochemical form has a vital role for all the nuclear medicine imaging processes. The common method of radiopharmaceutical quality control is the chromatographic analysis such as PC, TLC, and HPLC. In nuclear medicine practice, application of these methods is called radiopharmaceutical quality control(2). The agrement of results obtained from such chromatographic analysis methods with the criterions given in United States Pharmacopea (USP) means the regulatory permission of the use of that radiopharmaceutical in proposed applications^). In this study separation of sever...
Bu calismada, Turkiye’nin zeytinyagi uretiminin % 65’ini Olusturan Ege bolgesinin hakim zeytin ce... more Bu calismada, Turkiye’nin zeytinyagi uretiminin % 65’ini Olusturan Ege bolgesinin hakim zeytin cesidi olan Ayvalik ve Memecik yag orneklerinin en yaygin spektroskopik yontemler ile (FTNIR, FTIR-ATR, Excitation-Emission [EX-EM] ve Senkronize [SYN] Floresans Spektroskopisi) analiz edilerek siniflandirilmasi gerceklestirilmistir. Analiz edilen yag ornekleri organik ve karisik cesitlerden uretilen bir ornek disinda Kuzey Ege (Ayvalik cesidi) (n=4) ve Guney Ege (Memecik cesidi) (n=4) alt bolgelerinden alinmis toplam 9 adetten Olusmaktadir. Oda sicakliginda PET siseler icinde muhafaza edilen yag ornekleri gun isigina maruz birakilan ve aluminyum folyo ile kaplanmis (karanlik) olarak iki gruba ayrilmistir. Ayvalik ve Memecik cesidi naturel zeytinyaglarinin siniflandirilmasi en yaygin kullanilan kemometrik yontemler ile (Temel Bilesen Analizi, PCA ve Asamali Kumeleme Analizi, HCA) gerceklestirilmistir. Ayvalik ve Memecik cesitleri spektroskopik yontemlerin sonuclari temelinde cesit, orijin ...
In this study, the oil samples of Gemlik olive cultivar provided from different locations (n=10) ... more In this study, the oil samples of Gemlik olive cultivar provided from different locations (n=10) were analysed by using chromatographic ([GLC] Fatty Acid [FA] and [HPLC] Triacyl Glycerol [TAG] profiles) and spectroscopic (Excitation-Emission [EX-EM] Fluorescence Spectroscopy) methods. The classification of monocultivar (Gemlik cv) olive oil samples were carried out by the most used chemometric (Principal Component Analysis, PCA and Hierarchical Cluster Analysis, HCA) techniques. The oils made of 10 monocultivar (Gemlik olive) samples were succesfully classified according to locations (as Marmara, Aegean and Mediterannean zones) based on FA and TAG profiles. Also, similar classification exhibited the results of Excitation-Emission [EX-EM] fluoresence spectroscopy for Gemlik olive cultivar. In additon, the spectroscopic methods could be exhibited promising effects for the correct classification of virgin
In this study, stable isotope signatures (δ 13 C, δ 15 N, and δD) of both tea leaves and tea infu... more In this study, stable isotope signatures (δ 13 C, δ 15 N, 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. δ 13 C, δ 15 N, and δD in the samples were determined using isotope ratio mass spectrometry (IR-MS). δ 13 C in the samples ranged from −29.18 ± 0.01 to −25.7 ± 0.2, while δ 15 N 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.
Lung cancer is the major cause of cancer death in the World. Low dose CT screening for early diag... more Lung cancer is the major cause of cancer death in the World. Low dose CT screening for early diagnosis has still had some problems due to high rate of false-positive results. There is urgently need to new, in particular non-invasive biomarkers in the early diagnosis of lung cancer. The main objective of this study is to detect role of volatile organic compounds (VOCs) as potential biomarkers in early diagnosis of lung cancer. Newly diagnosed lung cancer patients and controls included into this prospective-case control study. Breath samples were collected via lab-made sample collector where the VOC content was enriched on a lab-made polythiphene solid phase microextraction (SPME) fibers. Then, the VOC content was analyzed by inserting into injection port of a gas chromatography coupled with mass detector (GC-MS) allowing thermal desorption. Commercial Carboxen/Polydimethylsiloxane SPME fibers were also utilized. A total of 67 lung cancer patients along with 69 controls9 breath samples were collected and analyzed. The results were interpreted with chemometric approach by using Principle Component Analysis (PCA). According to the first preliminary results of the study; via breathe sample analyses it is highly possible to distinguish lung cancer patients at early stages of their disease than the healthy controls with significantly different signal level of VOCs compounds in PCA.
Malassezia species which are lipophilic exobasidiomycetes fungi, have been accepted as members of... more Malassezia species which are lipophilic exobasidiomycetes fungi, have been accepted as members of normal cutaneous flora as well as causative agent of certain skin diseases. In routine microbiology laboratory, species identification based on phenotypic characters may not yield identical results with taxonomic studies. Lipophilic and lipid-dependent Malassezia yeasts require lipid-enriched complex media. For this reason, Fourier transform infrared (FT-IR) spectroscopy analysis focused on lipid window may be useful for identification of Malassezia species. In this study, 10 different standard Malassezia species (M.dermatis CBS 9145, M.furfur CBS 7019, M.japonica CBS 9432, M.globosa CBS 7966, M.nana CBS 9561, M.obtusa CBS 7876, M.pachydermatis CBS 1879, M.slooffiae CBS 7956, M.sympodialis CBS 7222 and M.yamatoensis CBS 9725) which are human pathogens, have been analyzed by FT-IR spectroscopy following standard cultivation onto modified Dixon agar medium. Results showed that two main gr...
The surface characteristics of rolled aluminum products such as sheets and foils are strongly aff... more The 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 infrared spectroscopy with grazing angle spectra collection accessories can be used for nondestructive analysis of these contaminants.
Determination of quality parameters such as lignin and extractive content of wood samples by wet ... more Determination 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 spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. Pinus nigra Arnold. Var. pallasiana is the second most growing pine species in Turkey. Even though its rotation period is very high, around 120 years, the forest products industry has widely accepted the use of Pinus nigra because of its ability to grow on a wide range of sites and its suitability to produce desirable products. In this study, 51 samples of Pinus nigra trees were collected and their lignin and extractive content were determined with standard reference (TAPPI) methods. Then, the same samples were scanned with near infrared spectrometer between 1000 and 2500 nm in diffuse reflectance mode. 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) were ranged between 0.35% (w/w) and 2.4% (w/w).
There has been growing public awareness about the health benefits of olive oil throughout the wor... more There 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 predic...
Biodiesel is gaining more importance as an attractive fuel due to the enormous consumption of ene... more Biodiesel is gaining more importance as an attractive fuel due to the enormous consumption of energy in the world. It can easily be isolated from transesterification reactions of vegetable oils or fats with alcohols in the presence of catalyst [1]. The quality of final product is an important issue and therefore a lot of techniques have been developed. Near infrared (NIR) spectroscopy has recently become an alternative method to the conventional analytical methods such as chromatography. In this study, laboratory scaled biodiesel was produced from two different vegetable oils (sunflower and corn oil). In addition, the mixture of vegetable oils and a mono alcohol with their corresponding biodiesel were prepared to represent the reaction media for sunflower and corn oil respectively. Development of multivariate calibration methods are carried following the near infrared spectroscopic measurements. Since NIR measurements include several spectral overlaps due to the multicomponent media...
The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy an... more The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy and three different genetic algorithm-based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are genetic regression (GR), genetic classical least squares (GCLS), and genetic inverse least squares (GILS). The sample data set was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) with the permission of
International Journal of Food Science and Technology, 2006
Determination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemi... more Determination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemistry analyses takes long time. Near infrared spectroscopy (NIR) coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. In this study, two different wheat data sets are investigated with the aim of establishing successful calibration models using NIR spectra of wheat samples. The first data set (material 1) was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) and contained 100 NIR spectra of wheat of which wet chemical analysis of protein and moisture content were done with reference methods. The second data set (material 2) contained 176 spectra and was downloaded from http://www.spectroscopynow.com/Spy/basehtml/SpyH/1,1181,2-1-2-0-0-newsdetail-0-74,00.html. This wheat data set was given with the quality parameters, such as protein content, moisture content, other residues, dry mass, protein content in dry mass and hardness that were determined previously. Multivariate calibration models generated with genetic inverse least squares method demonstrated very good prediction results for the parameter mentioned here. Overall, the average per cent recoveries (APR) ranged between 99.23% and 100.34% with a standard deviation (SD) ranging from 0.34 to 3.15 for all the parameters investigated, except hardness. The APR value of hardness was 103.32 with the SD of 14.97.
Genetic algorithm based multivariate calibration models were generated for infrared spectroscopic... more Genetic algorithm based multivariate calibration models were generated for infrared spectroscopic determination of aluminum rolling oil additives and contaminants such as gear and hydraulic oils. Two different additives and six different suspected contaminants were investigated in the base oil lubricant. Routine analysis samples from 9 different aluminum rolling systems were collected in a period of 2 months in an aluminum rolling plant and gas chromatography (GC) is used as the reference method. Infrared absorbance spectra of the samples were then collected and the reference values obtained with GC were used together with these spectra for model building. Inverse least squares method was optimized with a genetic algorithm by selecting the most contributing regions of the infrared spectra for each component. The R 2 values between GC and multivariate spectroscopic determinations were around 0.99 indicating a good correlation between the two methods. Performance of genetic algorithm based multivariate calibration models were also compared with partial least squares (PLS) method. The study showed that infrared spectroscopy coupled with multivariate calibration can be used for continuous monitoring of additives and contaminants in aluminum rolling oil. By this way, analysis time is significantly reduced and simultaneous determination of all the components can be accomplished.
Uploads
Papers by Durmuş Özdemir