The evaluation of potentially toxic elements using artificial neural networks and fuzzy linear regression analysis methods in cappadocian volcanic ash soils of Turkey.

The aim of this study is to determine the relationships between some potentially toxic elements (PTE) (Cu, Mn, Ni, Zn) in human stomach and intestinal tissues and toxic element contents in soil, vegetables and fruits. This study was conducted in the eastern of Erciyes Strato volcano, an area of 2400 km2 in Turkey. Tissue samples taken from the stomach and intestines of people living in the study area, soils, vegetables, and fruits were used as material. In the study, tissue samples of 26 people's stomach and intestines, 576 soil samples from 192 points and 3 different depths (0-30 cm, 30-60 cm, and 60-90 cm) and vegetable and fruit samples from 137 sampling points were taken. Cu, Mn, Ni, and Zn contents of human tissue samples, soil samples, vegetable and fruit samples were determined. Artificial Neural Networks method (ANN) and Fuzzy Linear Regression Analysis (FLRA) methods were used to determine the relationships between PTE contents in human tissue samples and soils, vegetables, and fruits. Root Mean squared error (RMSE) and coefficient of determination (R2) indices were used as the test criteria for goodness of fit. When compared with ANN method, it was determined that PTE values in stomach and intestinal tissue estimated by FLRA method had the lowest error and high R2 values. It was found that the most effective variable in estimating the average PTE value in stomach and intestinal tissue is PTE values in soil. It was determined that the FLRA regression analysis method has a better predictive power than the ANN method. Using FLRA and ANN regression methods, it was determined that there is a statistically high relationship between PTE contents in soils and stomach and intestinal tissues. It is recommended to make the study findings more meaningful with effective and reliable service planning by using different regression analysis methods in ecological and clinical studies.

Assessment of spatial variability in some soil properties as related to soil salinity and alkalinity in Bafra plain in northern Turkey.

The objectives of this study were to assess the variability in soil properties affecting salinity and alkalinity, and to analyze spatial distribution patterns of salinity (EC) and alkalinity (ESP) in the plain, which was used irrigation agriculture with low quality waters. Soil samples were collected from 0-30 cm, 30-60 cm, 60-90 cm and 90-120 cm soil depths at 60 sampling sites. Soil pH had the minimum variability, and hydraulic conductivity (Ks) had the maximum variability at all depths. The mean values of pH, EC, ESP and Ks increased while the mean values of CEC decreased with soil depth. Values pH, EC and ESP were generally high in the east and northeastern sides. Soil properties indicated moderate to strong spatial dependence. ESP and pH were moderately spatially dependent for three of the four depths, EC exhibited moderate spatial dependence for one of the four depths, CEC had a moderate spatial dependence at all depths, and Ks exhibited a strong spatial dependence. EC, CEC, and ESP were considerably variable in small distances. The spatial variability in small distances of EC, CEC, pH and ESP generally increased with depth. All geostatistical range values were greater than 1230 m. It was inferred that the strong spatial dependency of soil properties would be resulted in extrinsic factors such as ground water level, drainage, irrigation systems and microtopography.

Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey.

Spatial variability of salinity and alkalinity is important for site-specific management since they are the most important factors influencing soil quality and agricultural production. The objectives of this study were to analyze spatial variability in salinity and alkalinity and some soil properties affecting salinity and alkalinity, using classical statistics and geostatistical methods, in an irrigated field with low-quality irrigation water diverted from drainage canals. A field of 5 da was divided into 10 m x 10 m grids (5 lines in the east-west direction and 10 lines in the north-south direction). The soil samples were collected from three depths (0-30, 30-60 and 60-90 cm) at each grid corner. The variation coefficients of OM and sand contents were higher than other soil properties. OM had the maximum variability, with a mean of 1.63% at 0-30 cm depth and 0.71% at 30-60 cm depth. Significant correlations occurred between ESP, EC and each of Ca, Mg, K and CaCO(3) contents of the soils (p<0.01). Experimental semivariograms were fitted to spherical and gaussian models. All geostatistical range values were greater than 36 m. The soil properties had spatial variability at small distances at 60-90 cm depth. EC was variable within short distances at 30-60 cm depth. The nugget effect of ESP increased with soil depth. Kriged contour maps revealed that soils had a salinisation and alkalisation tendency at 60-90 cm depth based on spatial variance structure of the EC and ESP values. Spatial variability in EC and ESP can depend on ground water level, quality of irrigation water, and textural differences.