Soil science
Hamid Reza Matinfar; M. Jalali; Z. Dibaei
Abstract
Introduction: Understanding the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Over the past two decades, the use of data mining approaches in spatial modeling of soil organic carbon using machine learning techniques ...
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Introduction: Understanding the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Over the past two decades, the use of data mining approaches in spatial modeling of soil organic carbon using machine learning techniques to investigate the amount of carbon to soil using remote sensing data has been widely considered. Accordingly, the aim of this study was to investigate the feasibility of estimating soil organic matter using satellite imagery and to assess the ability of spectral and terrestrial data to model the amount of soil organic matter.Materials and Methods: The study area is located in Lorestan province, and Sarab Changai area. This area has hot and dry summers and cold and wet winters and the wet season starts in November and ends in May. A total of 156 samples of surface soil (0-30 cm) were collected using random sampling pattern. Data were categorized into two categories: 80% (117 points) for training and 20% (29 points) for validation. Three machine learning algorithms including Random Forest (RF), Cubist, and Partial least squares regression (PLSR) were used to prepare the organic soil carbon map. In the present study, auxiliary variables for predicting SOC included bands related to Lands 8 OLI measurement images, and in order to reduce the volume of data, the principle component analysis method (PCA) was used to select the features that have the greatest impact on quality.Results and Discussion: The results of descriptive statistics showed that soil organic carbon from 0.02 to 2.34% with an average of 0.56 and a coefficient of variation of 69.64% according to the Wilding standard was located in a high variability class (0.35). According to the average amount of soil organic carbon, it can be said that the amount of soil organic carbon in the region is low. At the same time, the high value of organic carbon change coefficient confirms its high spatial variability in the study area. These drastic changes can be attributed to land use change, land management, and other environmental elements in the study area. In other words, the low level of soil organic carbon can be attributed to the collection of plant debris and their non-return to the soil. Another factor in reducing the amount of organic carbon is land use change, which mainly has a negative impact on soil quality and yield. In general, land use, tillage operations, intensity and frequency of cultivation, plowing, fertilizing, type of crop, are effective in reducing and increasing the amount of soil organic carbon. Based on the analysis of effective auxiliary variables in predicting soil organic carbon, based on the principle component analysis for remote sensing data, it led to the selection of 4 auxiliary variables TSAVI, RVI, Band10, and Band11 as the most effective environmental factors. Comparison of different estimation approaches showed that the random forest model with the values of coefficient of determination (R2), root mean square error (RMSE) and mean square error (MSE) of 0.74, 0.17, and 0.02, respectively, was the best performance ratio another study used to estimate the organic carbon content of surface soil in the study area.Conclusion: In this study, considering the importance of soil organic carbon, the efficiency of three different digital mapping models to prepare soil organic carbon map in Khorramabad plain soils was evaluated. The results showed that auxiliary variables such as TSAVI, RVI, Band 10, and Band11 are the most important variables in estimating soil organic carbon in this area. The wide range of soil organic carbon changes can be affected by land use and farmers' managerial behaviors. Also, the results indicated that different models had different accuracy in estimating soil organic carbon and the random forest model was superior to the other models. On the other hand, it can be said that the use of remote sensing and satellite imagery can overcome the limitations of traditional methods and be used as a suitable alternative to study carbon to soil changes with the possibility of displaying results at different time and space scales. Due to the determination of soil organic carbon content and their spatial distribution throughout the region, the present results can be a scientific basis as well as a suitable database and data for the implementation of any field operations, management of agricultural inputs, and any study in sustainable agriculture with soil properties in this area. In general, the results of this study indicated the ability of remote sensing techniques and random forest learning model in simultaneous estimation of soil organic carbon location. Therefore, this method can be used as an alternative to conventional laboratory methods in determining some soil characteristics, including organic carbon.
Z. Dianat Maharluei; M. Fekri; M. Mahmoodabadi; A. Saljooqi; M. Hejazi
Abstract
Introduction: Today, soil pollution is an important environmental issue that should be taken into account. Industrial activities cause pollution and accumulation of heavy metals in the soil. Soil pollution significantly reduces the quality of the environment and threatens human health. Heavy metals are ...
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Introduction: Today, soil pollution is an important environmental issue that should be taken into account. Industrial activities cause pollution and accumulation of heavy metals in the soil. Soil pollution significantly reduces the quality of the environment and threatens human health. Heavy metals are one of the most important pollutants in the environment, which has received a lot of attention in recent decades. Heavy metal pollution is a serious problem in developing countries and urban areas. Among heavy metals, lead is found in large amounts in the Earth's crust, which has several effects on human health and the environment. Lead is an essential element for the plant and one of the most important pollutants, which is toxic even at very low concentrations. Its presence in the culture medium has a negative effect on germination rate, water status in the plant, dry root weight and aerial part of the plant, photosynthesis, absorption of nutrients and enzymatic activity. Much research has been done to use alternative and modern methods to clean the environment of heavy elements. One way to stabilize heavy metals in the soil is to use biochar. Due to its cation exchange capacity and high specific surface area, biochar is able to reduce the pollution caused by organic pollutants and heavy metals, stabilize heavy metals and improve the condition of plants and soil in terms of pollution. The aim of this study was to investigate the effect of modified biochars rice husk and almond soft husk on lead desorption kinetics in contaminated calcareous soil. Materials and Methods: To conduct this research, a sufficient amount of soil from a depth of zero to 30 cm was collected from the farm of Shahid Bahonar Agricultural College in Kerman. Physical and chemical properties of the studied soil were measured after air drying and passing through a 2 mm sieve. To prepare the biochars (rice husk and almond soft husk), the residues, after collection, were air-dried and ground and then packaged in aluminum foil to limit the oxygenation process. They were then placed in an oven at 500 0C for four hours to produce a charcoal called biochar. Also, to prepare the modified biochar (NaOH and HNO3), one gram of biochar was added to 100 ml of distilled water and then 10 ml of concentrated acid (or 10 g of alkali) was added to it. Stirring at 60 0C for 24 hours. Finally, it was filtered using a centrifuge and washed several times with distilled water to neutralize the pH. The produced powder was dried at 70 0C for 24 hours. The lead desorption kinetics experiment was studied at several times (5, 15, 30, 60, 120, 240, 480, 960, 1440 and 2880 minutes) in two levels of biochar (0 and 4 wt %) and three levels of lead (0, 300 and 600 mg kg-1), which were incubated for 5 months under field moisture in a greenhouse. Results and Discussion: The kinetics results showed that the desorption of lead has the same pattern in all the time studied. Early rapid desorption occurred in the early desorption times (initial 30 minutes) followed by low-velocity desorption (8 hours) and finally, equilibrium was observed in the treated and control samples. The significant difference between the amount of lead released from the treated soils and control indicated a positive effect of both used engineered biochars on reducing lead desorption. The highest amount of lead desorption was observed in soil without biochar, while the lowest desorption rate occurred in treatments of rice husk and almond soft husk modified by sodium hydroxide. The application of modified biochar rice husk highly reduced lead desorption, compared to modified biochar almond soft husk. Conclusion: According to the results, the modified biochar with sodium hydroxide caused a significant reduction in lead desorption compared to other treatments, and this reduction was more in biochar rice husk than the almond soft husk one. It can be stated that rice husk biochar has been more successful than almond soft husk biochar due to its more porous structure and cation exchange capacity. Among the equations used for lead desorption estimation, the two-constant rate equation was selected as the best model for data fit due to high explanatory coefficient (R2) and low standard error (SE). According to the above, the use of biochar can be recommended as a modifier in lead contaminated soils.
zahra dianat maharluei; ali akbar moosavi
Abstract
Introduction: In arid and semi-arid soils, low organic matter is one of the barriers to achieving optimal performance. The soils with more organic matter have a better structure and are more resistant to erosive factors such as water and wind. Soil organic matter has a particular importance and has significant ...
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Introduction: In arid and semi-arid soils, low organic matter is one of the barriers to achieving optimal performance. The soils with more organic matter have a better structure and are more resistant to erosive factors such as water and wind. Soil organic matter has a particular importance and has significant impact on the stability of soil aggregates, the extension of plant root system, carbon and water cycles and soil resistance to erosion. This substance acts as a cementing agent and plays an important role in soil flocculation and formation of resistant aggregates.Also, the addition of organic matter to the soil increases soil porosity and decreases soil bulk density.
Materials and Methods: In this research, the effect of the two types of organic matter (compost and the ripe fruit waste of fig) on some soil physical properties was studied. A factorial experiment based on completely randomized design, including the four levels of compost and the ripe fruit waste of fig (0, 1, 2 and 4 by weight %) and three soil types (loamy sand, loam and silty clay loam) with three replications was carried out. The soil samples were collected from the three territories of Fars Province: loamy sand soil from Shiraz, loamy soil from Maharlu and Silty clay loam soil from Zarghan area. The soil samples were air dried and passed through a 2 mm sieve. The physical properties including the bulk density, particle density, porosity, moisture content and soil crust strength was measured. In this research, the soil texture by hydrometer method, Electrical conductivity of the soil saturated paste extract by electrical conductivity meter, saturated paste pH by pH meter, seedling emergence test, soil crust strength by a pocket penetrometer (HUMBOLDT MFG.CO.) bulk density by cylindrical sample and particle density by pycnometer method were measured. The fig fruit treatments were prepared by thoroughly mixing the dried powder of ripe fig fruit passed through a 2 mm sieve (with the rates of 0, 1, 2, and 4 % by dry weight) with the air dried soils. Also, the compost treatments were prepared by thoroughly mixing the dried powder of compost passed through a 2 mm sieve (with the rates of 0, 1, 2, and 4 % by dry weight) with the air dried soils. The test measurement PVC cylinders with an inner diameter of 12.5 cm and a height of 20 cm were prepared. The bottom ends of the cylinders were closed with a screened PVC plate. These cylinders were uniformly filled with the treated soils and irrigated a few times to make a homogeneous soil column. About 3 cm of the top end of the cylinders were left empty.
Results and Discussion: The results showed that all the rates of the ripe fruit waste of fig and the compost treatments significantly decreased crust strength of all soils compared to control at 1% probability level. The results also showed nearly the greater effect of all the treatments on crust strength of loamy sand soil compared to the other soils. All the rates of the ripe fruit waste of fig and compost treatments significantly increased the moisture content of all the soils compared to control at 1% probability level. Moreover, the greater effect of all the treatments on the moisture content of silty clay loam soil compared to other soils was generally observed. All the rates of the ripe fruit waste of fig and compost treatments decreased the bulk density and particle density of all the soils compared to control. Tthe greatest impact was observed in the compost treatments at the level of 4% by dry weight and silty clay loam texture. Also, all the rates of the ripe fruit waste of fig and compost treatments increased the porosity of all the soils compared to control, and the greatest impact belonged to the compost treatments at the level of 4% by dry weight andsilty clay loam texture.
Conclusion: The results showed that the use of the ripe fruit waste of fig and compost in the soil increased moisture content and decreased crust strength significantly compared to the control. Also, the ripe fruit waste of fis and compost in the soil increased porosity and decreased bulk density and particle density compared to the control, but this increase and decrease were not significant.Reduction in crust strength caused by the ripe fruit waste of fig application was more than compost application. However, the effect of compost application on the soil bulk density, particle density, porosity and moisture content was more than the ripe fruit waste of fig application.
