Showing 3 results for M. H. Saleh
M. H. Salehi, H. Khademi, M. Karimian Eghbal,
Volume 7, Issue 1 (spring 2003)
Abstract
Clay minerals have considerable effects on physico-chemical properties of soils. Using different techniques, mineralogy of silicate clays and their formation were investigated in selected soils from Chaharmahal and Bakhtiari Province. The study area is about 1300 ha and its soil moisture and temperature regimes are xeric and mesic, respectively. Geomorphologically, the area consists of different landforms including pediments, outwash, hills and piedmont plain. After field and laboratory studies, five representative pedons were selected in previously determined mapping units and samples were taken for the analyses required. Clay particles from two surrounding rock formations and selected soil samples were separated and examined by electron microscopy (SEM and TEM), X-ray diffraction and infrared techniques.
Illite, smectite, chlorite, palygorskite and kaolinite were present in all the soils. Considering the fact that palygorskite was not observed in nearby rock formations, this mineral is probably formed by pedogenic processes. Smectite, on the other hand, has been inherited from parent materials and also transformed from palygorskite. Other minerals had been probably inherited from parent materials. Infrared spectra confirm the X-ray diffraction and submicroscopic results.
H. Alinezhad Jahromi, A. Mohammadkhani, M. H. Salehi,
Volume 16, Issue 60 (Summer 2012)
Abstract
Nowadays, due to drought and water shortage, use of unconventional waters, particularly sewage, has become usual in agriculture whereas they often contain heavy metals. The present study was employed to evaluate the effect of urban wastewater of Shahrekord on growth, yield and accumulation of heavy metals (lead and cadmium) in balm (Melissa officinalis) as a medicinal plant with five treatments (0, 25, 50, 75 and 100 percent wastewater) and three replications in a completely randomized experimental design. The results showed that the highest shoot length, stem diameter and stem number, number of leaves and tillers are achieved in the treatment of 100 percent. The wet and dry weight of shoots and roots was highest in 100 % of wastewater. Oil percentage of the leaves was also the highest amount (1.23 %) in 100 % of wastewater. Accumulation of lead in roots and aerial parts and its transmission factor was not significant for the treatments. However, the highest concentration of lead in root (0.057 mg/kg) and shoots (0.013 mg/kg) was observed in 100 % of wastewater and the lowest one was related to zero percent of wastewater treatment. The lead concentration was less than the critical limit for all the treatments. The amount of cadmium was undetectable in all the plant samples. The results of this study demonstrated that urban wastewater of Shahrekord, in addition to providing water, increases plant growth and essential oil.
M. Bagheri Bodaghabadi, M. H. Saleh, I. Esfandiarpoor Borujeni, J. Mohammadi, A. Karimi Karouyeh, N. Toomanian,
Volume 16, Issue 61 (fall 2012)
Abstract
Discrete Models of Spatial Variability (DMSV) have limitations for soil identification in traditional soil maps. New approaches, generally called digital soil mapping (DSM), using continuous methods (CMSV), try to predict soil classes or soil properties based on easily-available environmental variables. The objective of this study was to map the soil classes of the Borujen area, Chaharmahal-va-Bakhtiari province, using digital elevation model (DEM) and its attributes and Soil-Land Inference Model (SoLIM). To do this, eighteen terrain attributes were derived from the DEM of the area. The primary analysis showed seven attributes are the most important derivatives. These derivatives as well as three dominant soil subgroups and seven soil families of the region (41 profiles from 125 profiles) were used to construct the input data matrix of the model. Then, output fuzzy soil maps of SoLIM were converted to polygonal soil map, using ArcGIS. Results showed that different combinations of DEM attributes have different accuracy rates for soil prediction. The accuracy of the interpolation was twice that of the extrapolation. Although SoLIM had an acceptable accuracy for soil nomination, and identification of soil map units’ types, it did not have enough accuracy for the location of soil classes. It seems that using other data like parent material and geomorphic surface maps will increase the accuracy of the model prediction.
