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Interaction of Sugarcane Bagasse Biochars and Salinity on Availability and Fraction of Cadmium in a Clay Loam Calcareous Soil
E. Mirzakhani, H. Motaghian, A. Hosseinpur,
Volume 25, Issue 4 (3-2022)
Abstract
Pollution of the environment by heavy metals, especially soil pollution with cadmium (Cd), is one of the most important environmental problems. Also, salinization of soils due to a decrease in irrigation water quality reduces plants growth. To investigate the effect of sugarcane bagasse biochars and salinity on Cd available and Cd fractions in a contaminated soil (15 mg kg-1 Cd), an experimental factorial design in a completely randomized design including (1) biochar factor with control, 1% (w/w) bagasse, 1% (w/w) biochar 400 °C and 1% (w/w) biochar 600 °C, and (2) salinity factor with control, 20, and 40 mmol kg-1 as sodium chloride were performed in 3 replications. The amount of available Cd was determined by the DTPA-TEA method and the Cd fractions were determined by Tessier et al. (1979). The results showed that biochar and salinity had no significant effect on soil pH (P > 0.05) but increased soil EC (P < 0.05). Interaction of biochar and salinity was not significant (P > 0.05) on available Cd and Cd fractions. Biochar application reduced Cd -DTPA-TEA (P < 0.05), whereas salinity increased Cd -DTPA-TEA (P < 0.05). Application of biochar prepared at 600 °C reduced (P < 0.05) exchangeable Cd (23.8%) and increased (P < 0.05) Cd associated with iron and manganese oxides (25.2%) and residual (15.6%) compared to the control. The results showed that salinity had no significant effect on the Cd fractions (P > 0.05) and soil treated with sugarcane bagasse biochar can reduce Cd available due to changing the Cd distribution from unstable forms to stable forms.
The Effect of Soil Amendments and Precipitation on the Amount of Soil Nutrients in Different Time Periods
A. Balvaieh, L. Gholami, F. Shokrian, A, Kavian,
Volume 26, Issue 4 (3-2023)
Abstract
Changes in nutrient concentrations of soil can specify optimal management of manure and prevent environmental and water resources pollution. The present study was conducted with the objective of changing macronutrients concentrations of Nitrogen, Phosphorus, and Potassium with amendments application of polyvinyl acetate, bean residual, and a combination of polyvinyl acetate + bean residual for time periods of one, two, and four months. The results showed that the application of soil amendments had various effects on changing Nitrogen, Phosphorus, and Potassium. The maximum amount of Nitrogen related to the treatment of bean residual at the time period of four months before simulation (with a rate of 44.62 percent) and minimum amount of nitrogen related to Polyvinyl acetate treatment at the time period of one month (with a rate of -1.92 percent). The minimum rate of Phosphorus was measured at the treatment of bean residual at the time period of one month before simulation (with a rate of 0.95 percent). The maximum amount of Potassium related to the treatment of Polyvinyl acetate at the time period of four months before simulation (with a rate of 189.35 percent) and the minimum amount of Potassium related to the combination of bean residual + Polyvinyl acetate at the time period of one month after simulation (with a rate of 40.66 percent). Therefore, the application of amendments has various effects on changing soil macronutrients at different time periods.

Evaluation of Erosion Sensitivity of Lithological Units in Vaz Watershed, Mazandaran Province Using Fingerprinting
D. Khatibi Roudbarsara, A. Khaledi Darvishan, J. Alavi,
Volume 27, Issue 2 (9-2023)
Abstract
Soil erosion followed by sediment production is the most important phenomenon that causes soil and environment degradation in many areas and is increasing. Sediment fingerprinting is a method to identify sediment sources and determine the contribution of each source to sediment production. The present research was carried out to evaluate the relative erosion sensitivity of lithological units and to determine the contribution of each unit in bed sediment production using geochemical properties in the Vaz River located in Mazandaran province. The 33 soil samples were taken from the whole watershed and one sediment sample at the outlet of the watershed. Then, five tracers of B, Al, Sc, Mo, and Sn were selected as the optimal combination using three statistical tests range tests, Kruskal-Wallis, and discriminant function analysis. Finally, using optimal tracers and a combined multivariate model, the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were obtained using FingerPro statistical package and R software. The results showed that the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were 24.23, 50.77, 15.62, and 9.36%, respectively. Then, the specific contribution of each sensitivity class was also calculated to remove the effect of area on the results. The Qal lithological unit including the Quaternary sediments in the river bed and banks with very high sensitivity to erosion (A) and a specific contribution of 0.0807 % per hectare had the maximum contribution in bed sediment production in Vaz River.

Application of Minimal Data Sets for Quantitative Assessment and Investigation of Spatial Autocorrelation of Soil Quality in Southwestern Lands of Urmia Plain
A. Barikloo, S. Rezapour, P. Alamdari, R. Taghizadeh Mehrjardi,
Volume 27, Issue 4 (12-2023)
Abstract
Soil quality is one of the most crucial factors determining crop productivity and production stability. The soil's physical, chemical, biological, and ecological characteristics affect its quality. Numerous researchers have concentrated the evaluation on a small number of soil quality indicators because measuring all soil quality indicators would be time-consuming and expensive. This study looked at the spatial autocorrelation of soil quality in the southwest areas of the Urmia Plain to establish the minimal data set for quantitative assessment. To accomplish this, 120 composite soil samples were collected from a depth of 0 to 60 cm, and the soil quality index was then calculated using the IQI method in 4 modes: Total-Linear (IQIwL-TDS), Total-Nonlinear (IQIwNL-TDS), Minimum-Linear (IQIwL-MDS), and Minimum nonlinearity (IQIwNL-MDS). 22 physical and chemical characteristics were used to choose the data set. The characteristics of sand percentage, sodium absorption ratio, cation exchange capacity, Available phosphorus, active calcium carbonate, and nickel concentration were chosen as the minimum data set (MDS) using the decomposition method into principal components. The linear IQIMDS mode produced the greatest soil quality index result, whereas the non-linear IQIMDS mode produced the lowest. The non-linear mode of the IQI index has a greater correlation coefficient (R2=0.85) than the linear mode of the IQI index (R2=0.73), according to an analysis of the linear and non-linear correlation coefficient between the soil quality index with the total category and minimum data. The findings of computing the global Moran's index for study sets of IQI soil quality index data revealed that the soil quality data are not independent of each other and are spatially autocorrelated, distributed in clusters, and have spatial autocorrelation. Getis-ord GI statistics indicated that the eastern and southeastern parts of the research region comprise clusters with poor soil quality, salt marshes produced by Lake Urmia's drying up, and surrounding arid plains.

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