Physicochemical properties of seeds of Capparis species growing wild in Turkey

While Capparis spinosa var. herbaceace (2009) seeds collected from the Mardin-midyat region contains the highest protein (22.25 %), C. spinosa var. spinosa seeds (2009) collected from the Mu?la-Milas region contained the lowest protein (18.25 %). In addition, oil contents of C. spinosa and Capparis ovata seeds changed between 27.74 to 31.09 and 28.66 to 31.40 %, respectively. Crude cellulose contents of C. spinosa and C. ovata seeds were found as 28.24 and 29.67 %, respectively. It was found that ash content of C. spinosa and C. ovata seeds were found between 2.13 and 2.23 %, respectively. Phenolic matter content of C. spinosa and C. ovata were found between 1.98 mg (GAE) and 1.76 mg (GAE), respectively. Radical activity values of C. spinosa and C. ovata were determined as 83.432 and 83.718 %, respectively.     

Predicting field capacity,wilting point,and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches

In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R ²), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P?<?0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP?=?0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.     

Determination of lead, cadmium and copper in roadside soil and plants in Elazig, Turkey

The concentrations of lead, cadmium and copper in roadside soil and plants in Elazig, Turkey were investigated. Soil samples were collected at distances of 0, 25 and 50 m from the roadside. The concentrations of lead, cadmium and copper were measured by Flame Atomic Absorption Spectrophotometry (FAAS). A slotted tube atom trap (STAT) was used to increase the sensitivity of lead and cadmium in FAAS. Lead concentrations in soil samples varied from 1.3 to 45 mg kg⁻¹ while mean lead levels in plants ranged from120 ng g⁻¹ for grape in point-4 to 866 ng g⁻¹ for apple leaves in point-2. Lead analyses showed that there was a considerable contamination in both soil and plants affected from traffic intensity. Overall level of Cd in soil samples lies between 78 and 527 ng/g while cadmium concentration in different vegetations varied in the range of 0.8–98.0 ng g⁻¹. Concentrations of copper in soil and plant samples were found in the range of 11.1–27.9 mg kg⁻¹ for soil and 0.8–5.6 mg kg⁻¹ for plants. Standard reference material (SRM) was used to find the accuracy of the results of soil analyses.     

Comparative evaluation of some macro- and micro-element and heavy metal contents in commercial fruit juices

Micro- and macro-element contents of several commercial fruit juices purchased from marked were determined by inductively coupled plasma atomic emission spectroscopy. Among the minor elements determined, Zn, Cu, Mn, Mo, Co, Cd and Ni were found to be lover. Major mineral contents of fruit juices were established as Ca, K, Mg and P. The potassium contents of fruit juices were determined at the higher levels. K contents of fruit juices ranged between 475 mg/kg (B apricot) and 1478 mg/kg (B peach). In addition while Ca contents of fruit juices change between 19.3 mg/kg (E cherry) and 81.8 mg/kg (C orange), Mg contents ranged at the levels between 23.7 mg/kg (A apricot) and 65.4 mg/kg (D orange). Generally Ca and contents of peach, orange and apricot juices that belong to A and D companies were determined at the high levels.     

Determination of heavy metals in bee honey with connected and not connected metal wires using inductively coupled plasma atomic emission spectrometry (ICP–AES)

Two honey samples are taken from two parts of the same honeycomb: one that contacts to the surface of the wire and the other taken from the surface that does not contact the wires. Heavy metal contents of these two samples were determined by inductively coupled plasma atomic emission spectrometry). The Mo, Cd, Cr, Fe, Mn, Ni and Zn contents of the honey in contact with wire is higher when compared to the other. Especially, Fe and Zn contents of honey in contact with wire is much higher than the non-contact one. These values are, respectively, 190.21 and 112.76 ppm. Besides, Ni content of honey in contact with wire is approximately 50% higher.     

Detection of fungal development in closed spaces through the determination of specific chemical targets

In addition to the biodegradation problems encountered in buildings, exposure of their occupants to moulds is responsible for numerous diseases: infections (invasive nosocomial aspergillosis), immediate or delayed allergies, food-borne infections and different types of irritation. In this context, the aim of our work has been to determine specific chemical tracers for fungal development on construction materials. More generally, by detecting a specific chemical fingerprint of fungal development, our objective was to propose a microbiological alert system which could control systems and/or procedures for the microbiological treatment of indoor areas.

We therefore characterized the chemical emissions from six types of construction material contaminated artificially by moulds. Chemical fingerprints were established for 19 compounds arising specifically from fungal metabolism: 2-ethylhexanoic acid methyl ester, 1-octen-3-ol, 3-heptanol, 3-methyl-1-butanol, 2-methyl-1-butanol, 1,3-octadiene, 2-(5H)-furanone, 2-heptene, -pinene, 2-methylisoborneol, 4-heptanone, 2-methylfuran, 3-methylfuran, dimethyldisulfide, methoxybenzene, a terpenoid and three sesquiterpenes.

Determining the origin of these compounds and their specific links with a growth substrate or fungal species made it possible to judge the pertinence of choosing these compounds as tracers.

Thus the detecting specific volatile organic compounds emitted as from the second day of fungal growth demonstrated that this approach had the advantage of detecting fungal development both reliably and rapidly before any visible signs of contamination could be detected.     

Medical waste management in Turkey: A case study of Istanbul

The objective of this study was to analyze the present status of medical waste management in the light of the Medical Waste Control Regulation (MWCR) in Istanbul, the largest city in Turkey. About 17% of the hospitals, 20% of bed capacity, and 54% of private hospitals in Turkey are located in Istanbul. The first regulation about medical waste management in Turkey was published in 1993, and as a candidate state, it was changed in 2005 in accordance with EU Environmental Directives. In this work, a survey of 14 questions about the amount, collection, and temporary storage of medical wastes was applied to 192 hospitals in Istanbul through face-to-face interviews. It was found that the estimated quantity of medical waste from the hospitals is about 22tons/day and the average generation rate is 0.63kg/bed-day. Recyclable materials are collected separately at a rate of 83%. Separate collection of different types of wastes is consistently practiced, but 25% of the hospitals still use inappropriate containers for medical waste collection. Almost 77% of the hospitals use appropriate equipment for the medical waste collection personnel. The percentage of the hospitals that have temporary storage depots is 63%. Medical waste management in Istanbul is carried out by applying the MWCR.     

Toxaphen in der Umwelt

Toxaphene is a mixture of more than 200 polychlorinated C₁₀-terpenes. Due to its persistence and long-range transport, it is distributed all over the world. Many of the components are very stable under environmental conditions, while others are easily degraded by UV-light or microorganisms. The main conversion pathway is reductive dechlorination and dehydrochlorination; oxidative degradation possibly occurs only after previous dechlorination. Accumulation especially in the aquatic environment has led in many cases to high residue levels in fish, marine mammals, and sea birds of the northern hemispere. Toxaphene is mutagenic in the Ames test and of high toxicity for fish, but few data are available on the toxicity of single components or their mode of action.     

Physicochemical properties and mineral contents of seven different date fruit (Phoenix dactylifera L.) varieties growing from Saudi Arabia

The date (Phoenix dactylifera L.) fruits (Soukari, Soulag, Barhi, Khulas, Rozaiz, Soughi and Monaif) were evaluated with respect to some physical and chemical properties. While crude protein contents of fruits change between 1.51 % (Soulag) to 2.41 % (Soughi), crude fibre contents ranged between 1.91 % (Soukari) to 3.90 % (Barhi). Vitamin C contents of date samples changed between 971.82 mg/kg (Soughi) to 1,453.15 mg/kg (Barhi). Antioxidant activity of date fruits ranged from 80.07 IC₅₀ (Soukari) to 81.21 IC₅₀ (Soulag). The highest phenolic content was found in Khulas with a mean value of 198 mg GAE/100 g. Energy values of date fruits ranged from 3,725 kcal/kg (Soulag) to 3,870 kcal/kg (Soukari). Sucrose contents of date fruits changed between 1.02 % (Soulag) to 55.71 % (Soukari). Mineral contents of several date fruits were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES). Date samples contain potassium at a range between 7,468 mg/kg (Khulas) to 9,619 mg/kg (Soulag). Phosphorus contents of fruits were found between 1,848 mg/kg (Soulag) to 3,066 mg/kg (Rozaiz) and followed by magnesium and calcium. The highest Zn (9.33 mg/kg), Cu (4.27 mg/kg) and Mn (3.26 mg/kg) were found in Rozaiz, Soukari and Barhi samples, respectively.     

Detection and object-based classification of offshore oil slicks using ENVISAT-ASAR images

The aim of this study is to propose and test a multi-level methodology for detection of oil slicks in ENVISAT Advanced Synthetic Aperture Radar (ASAR) imagery, which can be used to support the identification of hydrocarbon seeps. We selected Andrusov Ridge in the Central Black Sea as the test study area where extensive hydrocarbon seepages were known to occur continuously. Hydrocarbon seepage from tectonic or stratigraphic origin at the sea floor causes oily gas plumes to rise up to the sea surface and form thin oil films called oil slicks. Microwave sensors like synthetic aperture radar (SAR) are very suitable for ocean remote sensing as they measure the backscattered radiation from the surface and show the roughness of the terrain. Oil slicks dampen the sea waves creating dark patches in the SAR image. The proposed and applied methodology includes three levels: visual interpretation, image filtering and object-based oil spill detection. Level I, after data preparation with visual interpretation, includes dark spots identification and subsets/scenes creation. After this process, the procedure continues with categorization of subsets/scenes into three cases based on contrast difference of dark spots to the surroundings. In level II, by image and morphological filtering, it includes preparation of subsets/scenes for segmentation. Level III includes segmentation and feature extraction which is followed by object-based classification. The object-based classification is applied with the fuzzy membership functions defined by extracted features of ASAR subsets/scenes, where the parameters of the detection algorithms are tuned specifically for each case group. As a result, oil slicks are discriminated from look-alikes with an overall classification accuracy of 83% for oil slicks and 77% for look-alikes obtained by averaging three different cases.