JWSS - Journal of Water and Soil Science

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An experiment was carried out on 384 7d old commercial broiler chicks (Lohman) to study the effect of changes in source and level of dietary calcium and limestone particle size on the performance and tibial growth and calcification of broiler chicks. From day 1 to day 7, the chicks were fed with the commercial basal diet. On day 7, the chicks were weighted and randomly assigned to 64 groups, six chicks of similar body weight (82.2±5.4) per group. Each of the eight experimental diets was fed to eight groups of chicks for an experimental period of 49 days. Two calcium sources (oyster shell and limestone), two calcium levels (100% NRC and 85% NRC) and three particle sizes of limestone [ground (less than 0.15 mm), medium (0.6 to 1.18 mm) and coarse (1.18 to 4.75 mm)] were added to diets with the same energy based on a Randomized Complete Design, in which levels of calcium were nested into calcium sources. Particle sizes were nested into calcium sources and levels.

Limestone significantly increased phosphorus retention (in percentage of phosphorus ingestion) at the age of 21 and 56 days and increased tibial length, dry weight and ash weight at 56 days. Calcium level of 85% NRC significantly decreased feed intake and feed conversion, especially during the starter, and increased calcium retention (in percentage of calcium ingestion) at 21 and 42 days. Phosphorus retention and cortical thickness of tibia at 21 and 42 days, tibial dry weight, ash weight and ash percentage at 42 day, were significantly increased with calcium level of 100% NRC. Coarse and medium particle sizes of limestone as compared to ground particle size, significantly improved feed intake and feed conversion, especially during the starter. Medium particle size of limestone with calcium level of 85% NRC and coarse particle size of limestone with calcium level of 100% NRC, significantly improved tibia ossification characteristics and increased calcium and phosphorus retention. By using calcium level of 85% NRC, coarse and medium particle sizes of limestone compared to ground particle size, significantly diminished percentage of leg abnormalities.

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For the study of field wind erosion and the design and evaluation of wind erosion control techniques, detailed observations of soil particle transport and vertical destribution of eroded soil particles are needed. The objectives of this study were: 1) To describe one device for soil transport particle measurement, i. e. the BSNE sediment catcher and 2) To assess vertical distribution of wind–eroded sediment with height in eastern Isfahan. The BSNE sediment catcher is a wind erosion sampler that traps eroded material at seven heights of 0.24, 0.60, 1.08, 2.00, 3.00, and 4.00 m above the soil surface. Each trap consists of a steel container with an inlet and outlet, mounted on a wind vane that rotates about a central pole. Before using the sampler in the field, it was tested and calibrated in the wind tunnel. The results showed that the average trapping efficiency with speeds ranging from 5.2 to 7.2 m sec^-1 for 4 different wind–eroded sediments was 0.44 to 0.68. However the trapping efficiency depended on wind speed, particle size distribution, particle density and type of sediment. The sampler had the lowest efficiency for particles < 44 μm. A BSNE sediment catcher was installed in Babaii Air Base. After a sampling period, the sediment in each trap was collected and weighed. The trapped materials were a mixture of saltation and suspension particles. Vertical distribution of wind–eroded sediment showed that the amount of soil collected decreased with increased height and the percentage of fine particles (<63μm) increased with height. The amount of trapped materials for each cm2 frontal intake with increased height were 12.00, 3.42, 1.44, 1.56, 0.75, 0.21, and 0.39 g cm-2, respectively, for the one sampling period.

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To obtain soil-moisture characteristic curve experimentally is time-consuming and usually subject to considerable errors. So, many investigators have tried to predict soil-moisture characteristic curve by different models. One of these models predicts soil moisture characteristic curve based on soil particle size distribution and bulk density. In this model, soil particle size distribution curve is divided into a number of segments, each with a specific particle radius and cumulative particle mass greater than that of the radius. Using these data, soil-moisture characteristic curve was estimated. In this model, a scale factor, α, is used which may be considered as a constant, or obtained by logistic or linear procedures. The average values of α for clay, silty clay, sandy loam, two loam soils, and two silty clay loam soils were 1.159, 1.229, 1.494, 1.391, 1.393, 1.253 and 1.254, respectively. For most conditions, soil particle size distribution curve is not available, but only the percentages of clay, silt, and sand could be obtained using soil textural data, which is not enough to draw a precise soil particle size distribution curve. In this situation, a precise soil particle size distribution curve must be initially developed on the basis of which the soil moisture characteristic curve can be predicted. In this study, using soil textural data of seven different soils, soil moisture characteristic curve of each was estimated. In these estimations, logistic and linear methods were used to obtain the α value. Then, the results were compared with those of measured soil moisture characteristic curve. For estimation of soil particle size distribution curve, two extreme values for soil particle radius, 125 and 999 m, were used. The results indicated that using particle radius of 999 µm is more appropriate. On the other hand, it was found that for clay, silty clay, and sitly clay loam texture, it is more appropriate to employ a linear equation to determine for estimating soil-moisture characteristic curve while the logistic equation can be more appropriately used for loam and sand loam textures.

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  Soil particle size distribution and bulk density are used for estimating soil-moisture characteristic curve. In this model, soil particle size distribution curve is divided into a number of segments, each with a specific particle radius and cumulative percentage of the particles greater than that radius. Using these data, soil-moisture characteristic curve is estimated. In the model a scale factor, a , is used which may be considered as a constant, or obtained by logistic or linear procedures. F or most conditions, soil particle size distribution curve is not available, but only the percentages of clay, silt and sand could be obtained using soil textural data. In this situation, at first a precise soil particle size distribution must be developed, based on which the soil-moisture characteristic curve can be predicted. According to the previous studies, using particle radius of 999 µ m is more appropriate than radius 125 µ m. Also, adjusted coefficients for estimating soil particle size distribution curve for radii 1 to 20  µ m was obtained. In this study, using the soil textural data of 19 different soils from UNSODA database, soil-moisture characteristic curve of each was estimated with logistic and linear methods based on initial and adjusted soil particle size distribution estimation. The estimated values were compared with the measured data. The results indicated that for most soils, using the combination of logistic and adjusted particle size distribution estimation procedures is more appropriate than the previous methods.

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Despite the existence of highly silty soils in southern Mashhad, there is no information about the aeolian and /or in situ formation of these soils. The main objective of this study was to determine the source of silt generation in this area. Granitic hilly lands in southern Mashhad have been covered by silty deposits. Based on the soil origin, four profiles including a residual soil covered by a silty layer, a residual soil with low amount of silt, a highly silty soil and an alluvial soil as well as a deep profile containing a succession of silty and alluvial materials were studied. Cumulative particle size distribution curve (CPSDC), depth distribution curves of silt/sand ratio (Si/S), Folk inclusive graphic standard deviation, Folk inclusive graphic skewness (SKI) and sand grain morphology analyzed by scanning electron microscopy (SEM) were determined and used to identify the source of the silty materials. Based on the results obtained, silty (L), residual-silty (R-L), residual (R), alluvial (A) and alluvial-silty (A-L) horizons were identified. CPSDC of L horizons is sigmoidal in shape and is easily distinguishable from that of the other horizons. In contrast, the CPSDC of alluvial and residual horizons is spherical in shape. CPSDCs for R-L and A-L horizons are neither sigmoidal nor spherical, but something in between. The L horizons have the highest SKI (very skewed to fine particles) and the lowest Folk inclusive graphic standard deviation (very badly sorted). In this regard, alluvial and residual horizons are intermediate. Because of the silt addition to R-L and A-L horizons, these horizons have a nearly zero SKI (symmetrical) and the highest Folk inclusive graphic standard deviation (very badly sorted). Particle size distribution histograms of R-L and A-L horizons are bimodal, a mode for sand and a mode for silt, suggesting two different sources. Depth distribution of Si/S, SKI and Folk inclusive graphic standard deviation of highly silty and other horizonz show a drastic change between L horizons and the other horizons-an indication of lithologic discontinuity and difference in origin. In conclusion, despite the possible contribution of granitic parent rocks to silt generation in the area, loess deposits recognized appear to have mostly been transported by aeolian movement.

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Selecting an appropriate particle size distribution (PSD) model for a particular soil may be important for a precise estimation of soil hydraulic properties. Various models have been proposed for describing soil PSDs. The objective of this study was to compare the quality of fitting of eight PSD models (Fredlund, Gompertz, van Genuchten, Jaki, Logarithmic, Exponential, Logarithmic-Exponential and Fractal) in 71 soil samples collected from Lordegan and Saman in Charmahal-va-Bakhtiari province, Iran. Coefficient of determination ( ) and Akaike’s information criterion ( ) were used to compare the goodness-of-fit of the models to the experimental data. Results showed that Fredlund model is best for describing PSD of silt loam, silty clay loam, silty clay and sandy loam soil textures. While Fractal, Exponential and Logarithmic-Exponential models produced the poorest-fit in silt loam, silty clay loam and silty clay, they had the best performance in sandy loam texture. The performance of Fredlund and Gompertz models improved with an increase in clay and silt content from 25 and 40 percentage, respectively. The performance of Fractal, Exponential and Logarithmic-Exponential models improved by increasing the sand content. Reverse correlation was observed between silt content and the performance of the Fractal model.

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Texture fractal dimension is a physical index to describe soil particle size distribution having a variety of applications. Fractal dimension may be calculated from three relations of mass-time, mass-diameter and modified mass-diameter (Kravchenko-Zhang) with two linear and nonlinear options for fittings. The aim of the present study was to compare methods and select an appropriate one and fitting option for determining the fractal dimension using hydrometer data. Sixty soil samples were collected from four fields of Taqanak, near Shahrekord. After removal of organic matter and other initial treatments, hydrometer readings were obtained at 0.67, 1, 2, 5, 15, 30, 60, 120, 180, 1440 and 2880 minutes and were converted to mass-time or mass-diameter data. Nonlinear fitting of the Kravchenko-Zhang mass-diameter relation was selected as the most appropriate method of calculating the fractal dimension of solid particles, due to its highest coefficient of determination and smallest mean square error and lowest Akaike Information Criteria. Error analysis also confirmed this conclusion. There was a significant, though not very strong, relationship between the fractal dimension obtained by linear and nonlinear fitting of mass- diameter and Kravchenko-Zhang mass-diameter methods. These relationships can be used to correct the fractal dimension determined by other methods and fitting options.

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The aim of this work was to study distribution of some heavy metals in different soil particle-size fractions and to assess their spatial distribution. The study was carried out in Kafe Moor (Kerman, Iran) where the Gol-Gohar Iron Mine is located. One hundred twenty composite soil samples were randomly collected and transferred to the laboratory in bags. After air-drying, the samples were fractionated into six classes including 2- 0.5, 0.5-0.25, 0.25-0.125, 0.125- 0.075, 0.075-0.05 and <0.05 mm. Elemental concentrations (Fe, Mn, Cu, Zn, Pb and Ni) were determined using acid digestion method (HNO₃, 4.0 N) and an atomic absorption spectrophotometer in each class. Ordinary Kriging technique was used for predicting spatial distribution of heavy metals. The results showed that content of metals in soil increased with decreasing particle size. The results also showed that the concentration of Fe, Mn, Cu, Zn, Pb and Ni in <0.05 mm size fraction were 2.13, 1.70, 4.79,2.43, 1.42, and 3.47 times higher than in 2-0.05 mm size fraction, respectively. In addition, mapping the concentrations of heavy metals with kiriging showed that metals pollution decreased with increasing distance from mines area.
 

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