Soil science
Sh. Asghari; K. Heidari; M. Hasanpour Kashani; H. Shahab Arkhazloo
Abstract
Introduction
The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation ...
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Introduction
The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to generate helpful information required for the soil health assessment to save time and cost involved in soil analysis. Therefore, it is useful to use different models such as multiple linear regression (MLR) and intelligent models including artificial neural network (ANN) and gene expression programming (GEP) to estimate MWD of wet aggregates through easily accessible and low-cost soil properties. The objectives of this study were (1) to creating MLR, ANN and GEP models for predicting MWD from the easily measurable soil variables in forest, range and cultivated lands of the Fandoghloo region of Ardabil province, (2) to compare the precision of the mentioned models in the prediction of MWD of wet aggregates using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria.
Materials and Methods
Disturbed and undisturbed soil samples (n= 80) were nearly systematically taken from 0-10 cm depth with nearly 50 m distance in forest (n= 20), range (n= 23) and cultivated (n= 37) lands of the Fandoghloo region of Ardabil province, Iran (lat. 38° 24' 10" to 38° 24' 25" N, long. 48° 32' 45" to 48° 33' 5" E) in summer 2023. The contents of sand, silt, clay, CaCO3, pH, EC, bulk (BD) and particle (PD) density, organic carbon (OC), geometric mean diameter (GMD) of dry aggregates were determined in the laboratory using standard methods. Total porosity (n) was calculated using BD and PD data (n= 1-BD/PD). The mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles were computed by sand, silt and clay percentages. The mean weight diameter (MWD) of wet aggregates was measured in the aggregates smaller than 4.75 mm by wet sieving equipment using sieves with 2, 1, 0.5, 0.25 and 0.106 mm pore diameter. All data were randomly divided into two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with the stepwise method, MATLAB and Gene Xpro Tools 4.0 software were used to derive multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) models, respectively. A feed forward three-layer (9, 8, 6 and 6 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the ANN modeling. A set of optimal parameters were chosen before developing the best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The precision of MLR, ANN and GEP models in predicting MWD of wet aggregates were evaluated by the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics.
Results and Discussion
The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (3 to 42.18 %), OC (1.01 to 7.17 %), PD (2.00 to 2.67 g cm-3), n (0.39 to 0.87 cm3 cm-3), GMD of dry aggregates (0.8 to 1.33 mm) and MWD of wet aggregates (0.35 to 2.65 mm) showed good variations in the soils of the studied region. The studied soils had clay loam (n= 11), sandy clay loam (n= 6), sandy loam (n= 12), loam (n= 13), silty clay loam (n= 14), silty clay (n= 1) and silt loam (n= 23) textural classes. There were found significant correlations between MWD with OC (r= 0.67**), sand (r= 0.70**), GMD (r= 0.30**) and PD (r= -0.46**). Also, significant and positive correlation was found between OC and sand (r= 0.59**). Due to the multicollinearity of sand with dg (r= 0.87**), we did not use the dg as an input variable to estimate MWD of wet aggregates. Generally, four MLR, ANN and GEP models were constructed to predict MWD of wet aggregates from measured readily available soil variables. The results of MLR, ANN and GEP models indicated that the most suitable variables to estimate MWD of wet aggregates were sand, OC and GMD of dry aggregates. The values of R2, RMSE, ME and NS criteria were obtained equal 0.52, 0.48 mm, 0.13 mm and 0.48, and 0.85, 0.30 mm, 0.03 mm and 0.78, 0.79, 0.35 mm, -0.10 mm, 0.95 for the best MLR, ANN and GEP models in the testing data set, respectively. Many researchers also reported that there is a positive and significant correlation between MWD of wet aggregates and OC.
Conclusion
The results showed that sand, OC and GMD of dry aggregates were the most important and readily available soil variables to predict the mean weight diameter (MWD) of wet aggregates in the Fandoghloo region of Ardabil province. According to the lowest values of RMSE and the highest values of R2 and NS, the precision of ANN models to predict MWD of wet aggregates was more than MLR and GEP models in this study. Because ANN is more flexible and effectively captures non-linear relationships, it performed better than the other models in predicting MWD.
Saeed Saadat; leila esmaeelnejad; hamed rezaei; Rasoul mirkhani; javad seyedmohammadi
Abstract
Introduction: Soil aggregates refers to groups of soil particles which attach to each other stronger than neighbour particles. Aggregate stability shows the capability and strength of soil aggregates to tolerate breakup when disruptive stresses and destructive forces via mechanical agricultural operation ...
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Introduction: Soil aggregates refers to groups of soil particles which attach to each other stronger than neighbour particles. Aggregate stability shows the capability and strength of soil aggregates to tolerate breakup when disruptive stresses and destructive forces via mechanical agricultural operation such as tillage and water or wind erosion are applied. Wet aggregate stability shows how well a soil can withstand raindrop impact and water erosion, while size distribution of dry aggregates can be used to predict resistance to abrasion and wind erosion. Aggregate stability changes can act as the first indicators of recovery or degradation of soils. Aggregate stability is an indicator of organic matter content, biological activity, and nutrient cycling in soil. Generally, in small aggregates (< 0.25 mm), the particles are bound by older and more stable forms of organic matter. Microbial decomposition of fresh organic matter releases products (that are less stable) that bind small aggregates into large aggregates (> 2-5 mm). Although, there is not a unique acceptable methodology that serves and applies the entire world up to now, aggregate stability has been introduced as a soil physical quality indicator. Difficulties remain when comparison of aggregate stability from different methodologies are done. The objective of the present study was to assess appropriate and satisfactory aggregate stability tests that enable to distinguish the soil physical quality condition of both arid and moist medium textured soils.
Materials and Methods: A total of 120 soil samples which contained 60 wetland samples from Guilan province with a very humid climate, average annual rainfall of 1285 mm, and average annual temperature of 16°C, and 60 samples from Fars province with dry climate, average rainfall of 225 mm, and the average annual temperature of 27°C were provided. Soil sampling was performed from surface layer (0-20 cm). Each 10 soil samples with similar texture were mixed and one soil sample for each texture was finally obtained. After air drying and sieving, soil texture and organic carbon were determined by pipette and oxidation methods, respectively. Also, undisturbed samples were taken using metal cylinders from surface layer of 5-15 cm for determination of soil saturation coefficient, soil moisture curve, and soil bulk density. Also, in order to determine the aggregate stability, Kemper and Rosenau, de Leenheer and de Boodt, as well as Le Bissonnais were used.
Results and Discussion: Among different tested methods, wet sieving using the well known fast wetting methods of Kemper & Rosenau and of Le Bissonnais presented similar results in both climates. The mean weight diameter value of both methods for assessing aggregate stability can be considered as a dependable indicator of soil structure status for comparing soils. These aggregate stability tests were in correspondence with only one out of the eight soil physical quality indicators when the entire soils were used. It was concluded that the aggregate stability should be used judiciously and in accordance with other indicators for an overall assessing of the soil physical quality condition. The great differences in the estimation of aggregate stability between KRSW and LB2 with other methods confirm that aggregate stability increases with increasing soil moisture content. This involves reducing the amount of air condensed, which results in the reduction of compressive forces on the aggregates during rapid wetting. But the lack of similarity between the KRSW and LB2 methods in terms of MWD suggests that the results of these two methods are not comparable to dry and wet soils. The difference in aggregate size distribution from all three treatments of LB method was higher in dry areas than wet areas. Only dry soils based on LB (LB1 and LB3 treatments based on MWD) (P <0.05) are comparable. In dry soils, the LB3 method is very efficient. This method involves the use of ethanol that protects the aggregate structure against dryness stresses. The lack of similarity between the MWD and other soil quality indicators describes the complexity of the soil structure, which is dependent on the location. It seems that SOC can be considered as an indicator with high correlation with the aggregate sustainability index of LB and KRFW methods, at least in the studied medium-textured soils.
Conclusion: Since only a soil quality index (SOC) had a similar trend to the sustainability index derived from these two methods (LB1 and KRFW), it can be concluded that aggregate stability should be judged and recognized correctly, along with other used soil physical indicators for a general assessment of the conditions. In case of arid land soils, efficiency of pre-wetted methods of Kemper and Rosenau and of Le Bissonnais as well as pre-wetted Le Bissonnais with mechanical slaking and shaking were similar. If a simple and rapid analysis of the structure status is needed, single tests such as fast wetted Kemper and Rosenau and Le Bissonnais can be used.
Saeideh Bardsirizadeh; Isa Esfandiarpour Borujeni; Ali Asghar Besalatpour; Peyman Abbaszadeh Dahaji
Abstract
Introduction: Aggregate, as the basic unit of soil structure,represents a collection of primary particles which their adherence to each other is more than their connection to environ soilparticles. Aggregate stability is a highly complex parameter influencing a wide range of soil properties, including ...
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Introduction: Aggregate, as the basic unit of soil structure,represents a collection of primary particles which their adherence to each other is more than their connection to environ soilparticles. Aggregate stability is a highly complex parameter influencing a wide range of soil properties, including carbon stabilization, soil porosity, water infiltration, aeration, compatibility, water retention, hydraulic conductivity andresistance to erosion by water and overland flows. Maintaining high stability of soil aggregate is essential for preserving soil productivity, minimizing soil erosion and degradation and thus minimizing environmental pollution as well. Nevertheless, aggregate stability is described as one of the soil properties that can serve as an indicator of soil quality.The main purpose of this study is to determine the most important component of soil aggregate (macro and/ormicro) in estimating the soil structural stability in the Rabor region, Kerman province, using geostatistical method.
Materials and Methods: Ninetysurface soil samples (0 to 10 cm) were taken on a 200 m square sampling grid in the study area for the geostatistical studies.After air drying the soil samples and passing them through a 4 mm sieve, the percentage of aggregates belong tothree parts of total, macro, and micro classes and aggregate staility were calculated in both dry and wet conditions.Some stability indices were calculated and their spatial variabilities were investigated using two variography and estimation stages methods. Finally, the kriged map of each aggregate stability indicator was produced. To determine the compatibility of kriged maps of the soil aggregates stability indices calculated for the macro and micro aggregates with aggregates stability index (i.e., AS index) calculated forthe total aggregates, the overall accuracy related to each aggregate component (i.e., macro and micro) was calculatedafter creating an error matrix.
Results and Discussion: The results showed that total aggregate stability in the dry condition and macro aggregate stability in the wet condition had the lowest and highest coefficients of variability,respectively. The highest percentage of total aggregate stability (i.e., 89.90 %)was observed in the north and southeast positions of the study areain the dryconditionwhich had the highest amount of organic matter(i.e., 2.30 %). Also, the variograms of all investigated variables were exponentially and their ranges were varied between 380 to 450 m. Although the obtainedranges were different, a sampling distance more or less equal to 420 m is reasonable to study the most of the variables in the area. This can be a good indicator to decrease the sampling tasks for monitoring of these parameters in future.An overall look at the obtained root mean square standardized error (RMSSE) values indicated a high correlation between the measured and estimated values of all investigatedvariables (except for macro aggregate stability in the wet condition). However, all variables had a strong spatial correlation class. The percentage of overall accuracy obtained from crossing the total and macro aggregate kriged maps in the dry condition (i.e., 51.75 %), was more than its percentage for similar maps in the wet condition (i.e., 32.17 %). In return, the percentage of overall accuracy obtained from crossing the total and micro aggregate kriged maps in the wet condition (i.e., 17.31 %)was greater than its percentage for the mentioned maps in the dry condition (i.e., 10.93 %). Because of macro aggregate sensitivities to the amount of pressure imposed on them (as in the wet sieving method, the aggregates are under pressure caused by water energyin addition to tensions related to mechanical motion of sieving), the conformities of above two mentioned maps were less than those in the dry sieving method.
Conclusions: In general, the soil aggregates stability depends strongly on the amount of pressure imposed on them. Besides, the study of spatial variability of macro and micro aggregate stabilities and relative effects of each on the soil structure stability can be useful for choosing proper land management activities in future studies. According to theeffect of aggregation on nutrient cycling, capture, storage and water movement, and also other soil characteristics affecting plant growth and sustainable agriculture on one hand, and the effect of organic matter on aggregation on the other hand, it can be concluded thatall human activities that have a role in reducing or removing organic matter from the soil (e.g., grazing, deforestation, and intensive cultivation etc.) may reduce soil aggregate stability and finally can jeopardize human life in a near future.
P. Mohajeri; P. Alamdari; A. Golchin
Abstract
Introduction: Topography is one of the most important factors of soil formation and evolution. Soil properties vary spatially and are influenced by some environmental factors such as landscape features, including topography, slope aspect and position, elevation, climate, parent material and vegetation. ...
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Introduction: Topography is one of the most important factors of soil formation and evolution. Soil properties vary spatially and are influenced by some environmental factors such as landscape features, including topography, slope aspect and position, elevation, climate, parent material and vegetation. Variations in landscape features can influence many phenomena and ecological processes including soil nutrients and water interactions. This factor affects soil properties by changing the altitude, steepness and slope direction of lands. In spite of the importance of understanding the variability of soils for better management, few studies have been done to assess the quality of soils located on a toposequence and most of these studies include just pedological properties. The aim of this study was to investigate physical and chemical properties of soils located on different slope positions and different depths of a toposequence in Deilaman area of Gilan province, that located in north of Iran.
Materials and Methods: The lands on toposequence that were same in climate, parent material, vegetation and time factors but topographical factor was different, were divided into five sections including steep peak, shoulder slope, back slope, foot slope and toe slope. In order to topsoil sampling, transverse sections of this toposequence were divided into three parts lengthways, each forming one replicate or block. 10*10 square was selected and after removing a layer of undecomposed organic residues such as leaf litter, three depths of 0 to 20, 20 to 40 and 40 to60 cm soil samples were collected. physical and chemical characteristics such as soil texture, bulk density, aggregate stability, percent of organic matter, cation exchange capacity, available phosphorous and total nitrogen were measured.
Results and Discussion: The results showed that, because of high organic matter content and fine textured soils on the lower slope positions including foot slope and toe slope, aggregate stability, cation exchange capacity, available phosphorous and total nitrogen were maximum in these positions, whereas, bulk density had a reverse trend and was higher in the upper slope positions than the lower slope positions. The high content of organic carbon, phosphorus and total nitrogen in the soil of foot and toe slope positions, can be attributed to soil erosion and transferred from top of the slope and their accumulation in these situations. The results also revealed that, with increasing depth, aggregate stability, organic carbon content, cation exchange capacity, available phosphorous and total nitrogen content of soils decreased, whereas, clay content and bulk density had a reverse trend and increased with increasing the depth. Reducing the amount of organic carbon with increasing depth was because of the remains of plants and roots in the surface horizons and the presence of more organic carbon. Since phosphorus and nitrogen in the soils are highly dependent on organic matter, Thus, changes in these indicators are mainly obeys from this materials.
Conclusion: In general, it became appears from this study, that the topography factor had important effect on studied soil properties. The changes observed in the quality of soils located on different slope positions can be attributed to the differences of the soil in erosion rate and moisture content and different sediment receptions in different positions of toposequence as affected by the amount and distribution of rainfall. Considering the effect of the position of the landscape on the physical and chemical properties of soil, recommended analysis of the landscape is better to be done in the sustainable land management and also for soil and water conservation programs. Because of the different management practices in different parts of landscape is difficult and perhaps impossible, in order to maintain soil, conservation management must be done based on soil quality in areas with maximum damage and minimum quality.
Sh. Asghari; S. Dizajghoorbani Aghdam; Abazar Esmali
Abstract
Knowledge of the spatial distribution of soil properties is the major issues in identifying, program planning, management and utilization of soil and water resources. This study was carried out to investigate the spatial variability of some important soil physical quality indices including sand, silt, ...
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Knowledge of the spatial distribution of soil properties is the major issues in identifying, program planning, management and utilization of soil and water resources. This study was carried out to investigate the spatial variability of some important soil physical quality indices including sand, silt, clay, mean weight diameter of aggregates (MWD), organic carbon (OC), saturated hydraulic conductivity (Ks), saturated water content (θs) and bulk density (Db) in the three adjacent land uses i.e. forest, agriculture and range land located at Fandoghlou region of Ardabil. Totally, 100 soil samples were systematically (100 × 100 m grade) taken from 0-15 cm depth in spring 2013. At first, the accuracy of Kriging and inverse distance weighting (IDW) geostatisticaly methods in mapping of studied parameters was evaluated then the final map was presented. The values of nugget effect to sill ratio for clay, sand and silt were 0.5, 0.47 and 0.49, respectively so these parameters have an average spatial structure. The values of above mentioned ratio for OC, Db, θs, Ks, and MWD were obtained 0.002, 0.014, 0.0007, 0.05 and 0.008, respectively, indicating strong spatial structure. According to the R2 criteria, Kriging method in estimating clay, sand and silt and IDW method in estimating MWD, OC, Ks ،θs and Db had the highest accuracy. The final map indicated that forest land had higher OC, MWD and Ks and lower Db compared with agriculture and range land. The results of this research showed that soil physical quality of the studied region in agriculture and range land uses was lower than forest lands.
H.R. Samaei; A. Golchin; Mohammad Reza Mosaddeghi; Sh. Ahmadi
Abstract
Organic matter improves soil structure and any factor that decreases soil organic matter content causes soils structural instability. In soils with low organic matter content, soluble polymers can be used to increase the soil structural stability. In order to study the effects of polymer type and concentration ...
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Organic matter improves soil structure and any factor that decreases soil organic matter content causes soils structural instability. In soils with low organic matter content, soluble polymers can be used to increase the soil structural stability. In order to study the effects of polymer type and concentration on physical properties of soils with different texture, factorial experiment ..was ..conducted.. within ..completely ..randomized design ..with ..three replication. Three types of polymer (R790, TC108 and NC218) and three polymer concentration (1:1, 1:3 and 1:10 V/V polymer: water) were used in factorial combinations. Samples from soils with different texture were sprayed with different concentrations of the polymers and physical properties of polymer- treated soil samples were measured and compared with the control. Polymers application significantly enhanced the physical conditions of the soils. It increased the soil saturated hydraulic conductivity and dry and wet structural stabilities of the polymer-treated samples when compared with the control. The application of polymers decreased the dispersible clay and soil density of the polymer-treated soil samples. Increase of the soil saturated hydraulic conductivity and structural stability of the polymer-treated samples was greater for high polymer concentrations. The TC108 and R790 polymers were more effective than the NC218 polymer in improving the physical properties of the soils.
