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    The Essential Oil Compositions of Origanum majorana L. Cultivated in Konya and Collected from Mersin-Turkey
    (ASSOC PHARMACEUTICAL TEACHERS INDIA, 2017) Bagci, Yavuz; Kan, Yuksel; Dogu, Suleyman; Celik, Sadiye Ayse
    Purpose: In this study, essential oil (EO) compositions of the dried and fresh aerial parts of Origanum majorana cultivated in the research field and collected from f from Mersin was investigated. Material and Methods: EO was distilled by using Clevenger type apparatus for 3 h and the chemical compositions were detected in GC-MS. While, the oil yields of the the collected marjoram was determined to be 2,5 ml both in dried and fresh aerial parts, the yields of the cultivated plants for fresh and dried parts were 3.6 ml and 5 ml, respectively. The cultivation of the plant had positive effects on the EO yield. Drying of the material also increased the oil yield in the cultivated marjoram. Results: While there were 42 and 35 of EO components were observed in the fresh and dried parts of the collected marjoram, respectively; in the cultivated plants there were 30 and 40 components detected. Besides EO yields, in this research the differences with respect to composition and components were determined between the cultivated and collected plants. On the other hand, in this study, it was determined that the EO compositions varied with respect to be fresh or dry of the plant parts. It was observed that carvacrol and linalool were the major EO contents. Conclusion: The aim of the study to compare of differences between the EO compounds and compositions varied according to be the plant fresh or dry and collected or cultivated.
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    The Essential Oil Compositions of Rosmarinus officinalis L. Cultivated in Konya and Collected from Mersin-Turkey
    (ASSOC PHARMACEUTICAL TEACHERS INDIA, 2017) Bagci, Yavuz; Kan, Yuksel; Dogu, Suleyman; Celik, Sadiye Ayse
    Purpose: In this research, essential oil (EO) compositions of the dried and fresh aerial parts of Rosmarinus officinalis cultivated in the reearch field in Selcuk University Medicinal and Aromatic Plants Department Area in Konya and collected from Mersin was investigated. Material and Methods: EO was distilled by using Clevenger type apparatus for 3 h and the chemical compositions were detected in GC-MS. Results: Although, the oil yields of the collected rosemary was determined to be 0.4 ml (in fresh) and 0.6 ml (in dried) aerial parts, the yields of the cultivated plants for fresh and dried parts were 0.32 ml (in fresh) and 0.9 ml (in dried), respectively. In this research the differences with respect to composition and components were determined between the cultivated and collected plants. On the other hand, in this study, it was also determined that the EO compositions varied with respect to be fresh or dry of the plant parts. While there were 67 and 55 of EO compositions were observed in the fresh and dried parts of the collected marjoram, respectively; in the cultivated plants there were 46 (in fresh) and 79 (in dried) components detected. Conclusion: In this study, it was observed that the major EO compositions were camphor, 1.8-cineole, borneol, a-pinene, linalool, verbenone, bornyl acetate, limonene and camphene. The objective of the study to detect the differences between the EO compositions varied according to be the plant fresh or dry and collected or cultivated.
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    Estimation of in vitro neuroprotective properties and quantification of rutin and fatty acids in buckwheat (Fagopyrum esculentum Moench) cultivated in Turkey
    (ELSEVIER, 2012) Gulpinar, Ali Rifat; Orhan, Ilkay Erdogan; Kan, Asuman; Senol, Fatma Sezer; Celik, Sadiye Ayse; Kartal, Murat
    Buckwheat (Fagopyrum esculentum Moench, Polygonaceae) is a popular food crop plant from Polygonaceae. In this study, we investigated the ethyl acetate and ethanol extracts of the seed, stem, and aerial parts of the plant for their neuroprotective effect through acetylcholinesterase, butyrylcholinesterase, and tyrosinase inhibitory and antioxidant activity. Antioxidant activity was measured using the scavenging activity tests against 2,2-diphenyl-1-picrylhydrazyl (DPPH), N,N-dimethyl-p-phenylendiamine (DMPD), superoxide, and hydrogen peroxide radicals and the metal-related methods; metal-chelating capacity and ferric-reducing antioxidant power (FRAP), and phosphomolibdenum-reducing antioxidant power (PRAP) assays. Total phenol and flavonoid contents were calculated spectrophotometrically. Chemical composition of the seed oil was identified by gas chromatography-mass spectrometry (GC-MS) and rutin was quantified by liquid chromatography-mass spectrometry (LC-MS). The extracts were more active against butyrylcholinesterase and highly able to scavenge DPPH. The ethyl acetate extract of the aerial parts and the ethanol extract of the stems displayed a remarkable effect in the FRAP assay. None of the extracts had capacity to chelate the iron. According to LC-MS analysis, the richest plant part in terms of rutin was found to be the aerial parts. GC-MS analysis revealed that the seed oil was dominated by oleic (33.15%), linoleic (31.93%), and palmitic (13.15%) acids. (c) 2011 Elsevier Ltd. All rights reserved.
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    Phytochemical contents and enzyme inhibitory and antioxidant properties of Anethum graveolens L. (dill) samples cultivated under organic and conventional agricultural conditions
    (PERGAMON-ELSEVIER SCIENCE LTD, 2013) Orhan, Ilkay Erdogan; Senol, F. Sezer; Ozturk, Nilgun; Celik, Sadiye Ayse; Pulur, Aysen; Kan, Yuksel
    Inhibitory effect of the n-hexane, dichloromethane, ethyl acetate, and ethanol extracts from Anethum graveolens L. (dill) cultivated under organic (AG-O) and conventional (AG-C) conditions was tested against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and tyrosinase at 200 mu g mL(-1). Their antioxidant activity was determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH), N,N-dimethyl-p-phenylendiamine (DMPD), and nitric oxide (NO) radical scavenging assays as well as ferric ion-chelation capacity, ferric-(FRAP), and phosphomolybdenum-reducing antioxidant power (PRAP). The phytochemical analyses have been performed on both of the plant samples. GC-MS analysis pointed out that alpha-phellandrene was the main component in both of the essential oils in varying amounts (47.75% for AG-O and 27.94% for AG-C), while oleic acid was the dominant in the fruit oils of two samples (36.39% for AG-O and 53.87% for AG-C). HPLC analysis showed that both of the extracts contained rosmarinic acid as the major phenolic acid. The extracts inhibited BChE at moderate level, while the ethanol extracts exerted remarkable NO scavenging effect. The results emphasize that cultivation conditions may have effect on bioactivity and phytochemical content on plant samples. (c) 2013 Elsevier Ltd. All rights reserved.
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    Prediction of Kinematic Viscosities of Biodiesels Derived from Edible and Non-edible Vegetable Oils by Using Artificial Neural Networks
    (SPRINGER HEIDELBERG, 2015) Eryilmaz, Tanzer; Yesilyurt, Murat Kadir; Taner, Alper; Celik, Sadiye Ayse
    In the present study, the seeds named as wild mustard (Sinapis arvensis L.) and safflower (Carthamus tinctorius L.) were used as feedstocks for production of biodiesels. In order to obtain wild mustard seed oil (WMO) and safflower seed oil (SO), screw press apparatus was used. wild mustard seed oil biodiesel (WMOB) and safflower seed oil biodiesel (SOB) were produced using methanol and NaOH by transesterification process. Various properties of these biodiesels such as density (883.62-886.35 ), specific gravity (0.88442-0.88709), kinematic viscosity (5.75-4.11 ), calorific value (40.63-38.97 ), flash point (171-), water content (328.19-412.15 ), color (2.0-1.8), cloud point [5.8-, pour point [(-3.1)-(-13.1), cold filter plugging point [(-2.0)-], copper strip corrosion (1a-1a) and pH (7.831-7.037) were determined. Furthermore, kinematic viscosities of biodiesels and euro-diesel (ED) were measured at 298.15-373.15 K intervals with 1 K increments. Four different equations were used to predict the viscosities of fuels. Regression analyses were done in MATLAB program, and , correlation constants and root-mean-square error were determined. 1-7-7-3 artificial neural network (ANN) model with a back propagation learning algorithm was developed to predict the viscosities of fuels. The performance of neural network-based model was compared with the performance of viscosity prediction models using same observed data. It was found that ANN model consistently gave better predictions (0.9999 values for all fuels) compared to these models. ANN model was showed 0.34 % maximum errors. Based on the results of this study, ANNs appear to be a promising technique for predicting viscosities of biodiesels.