IntroductionThe PENETRATION RESISTANCE (PR) of the SOIL shows the mechanical RESISTANCE of the SOIL against the PENETRATION of a conical or flat probe; it is important in terms of seed germination, root growth and tillage operations. In general, if the PR value of a SOIL exceeds 2.5 MPa, the growth and expansion of roots in the SOIL will be significantly limited. The direct measurement of PR is also a laborious and costly task due to instrumental errors. Therefore, it is useful the use of different models such as multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) to estimate PR through easily accessible and low-cost SOIL characteristics. The objectives of this research were: (1) to obtain MLR, ANN and GEP models for estimating PR from the easily accessible SOIL variables in forest, range and cultivated lands of Fandoghloo region of Ardabil province, (2) to compare the accuracy of the aforementioned models in estimating SOIL PR using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria. Materials and MethodsDisturbed and undisturbed samples (n = 80) were nearly systematically taken from 0-10 cm SOIL depth with nearly 50 m distance in forest (n = 20), range (n = 23) and cultivated (n = 37) lands of 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 density (PD), organic carbon (OC), gravimetric field water content (FWC), mean weight diameter (MWD) and geometric mean diameter (GMD) were measured in the laboratory. Relative bulk density (BDrel) was calculated using BD and clay data. Mean geometric diameter (dg) and geometric standard deviation (σg) of SOIL particles were computed by sand, silt and clay percentages. The PENETRATION RESISTANCE (PR) of the SOIL was measured in situ using cone penetrometer (analog model) at 5 replicates. Data randomly were divided in two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with 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 (2, 5 and 6 neurons in 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 a best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, as they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The accuracy of MLR, ANN and GEP models in estimating PR were evaluated by coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics. Results and Discussion 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. The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (2.95 to 42.18 %), OC (1.01 to 7.17 %), FWC (11.58 to 50.47 mass percent), BD (0.84 to 1.43 g cm-3) and PR (1.03 to 5.83 MPa) showed good variations in the SOILs of the studied region. There were found significant correlations between PR with FWC (r = - 0.45**), silt (r = - 0.36**) and σg (r = 0.36**). Due to the multicollinearity of silt with σg (r = -0.84**), the σg was not used as an input variable to estimate PR. Generally, 3 MLR, ANN and GEP models were constructed to estimate PR from measured readily available SOIL variables. The results of MLR, ANN and GEP models showed that the most suitable variables to estimate PR were FWC, silt and BDrel. The values of R2, RMSE, ME and NS criteria were obtained equal 0.44, 1.19 MPa, 0.19 MPa and 0.36, and 0.92, 0.41 MPa, -0.05 MPa and 0.92,  0.79, 0.91 MPa, 0.13 MPa, 0.63 for the best MLR, ANN and GEP models, respectively. The former researchers also reported that there is a negative and significant correlation between PR with FWC. Conclusion The results indicated that field water content (FWC), silt and relative bulk density (BDrel) were the most important and readily available SOIL variables to estimate PENETRATION RESISTANCE (PR) in the studied area. According to the lowest values of RMSE and the highest values of NS, the accuracy of ANN models to predict SOIL PR was higher than MLR and GEP models in this research.    

One of the most important issues in agricultural machinery section is tyre-SOIL interactions. In this study, a single wheel tester was used to follow experiments in controlled conditions in a SOIL bin. A Goodyear 12. 4-28, 6 ply tractor drive tyre was operated at three vertical loads of 6, 9 and 12 kN, three inflation pressures of 80, 120 and 160 kPa and three moisture content of SOIL: 11. 20, 14. 86 and 18. 68 % d. b to investigate the effect of the variables on these parameters: contact area, contact pressure, compaction, and SOIL apparent electrical conductivity. It was found that medium contact pressure had a direct relation with vertical load, inflation pressure and moisture content. A regression model with R-square of 0. 946 was achieved to predict contact pressure. SOIL electrical conductivity changes was predicted with acceptable determination coefficient of 0. 850 by using of vertical load, inflation pressure and moisture content. Determination coefficient magnitude for models to predict RESISTANCE to SOIL PENETRATION (cone index) using SOIL apparent electrical conductivity, decreased when moisture content was increased. The vertical load and inflation pressure were found two factors controlling the SOIL apparent electrical conductivity changes in low and high moisture content, respectively. Error percentage in using SOIL apparent electrical conductivity parameter to estimate the PENETRATION RESISTANCE increased with increasing moisture content.

Background and Objectives: The ways of dealing with density include control of SOIL moisture during tillage, the control of vehicle's traffic on the SOIL, weight reduction and vehicle's contact pressure with SOIL and changing of SOIL structure by adding organic material.Materials and Methods: In order to study the effect of organic materials and zeolite and their mutual effect at different moisture stages on RESISTANCE to pentrometer PENETRATION, organic material factor in four levels (0, 0.5, 1 and 1.5 percent), zeolite factor in four levels (0, 8, 16 and 24 tons per hectare), also SOIL moisture levels which are in two dry and wet stages at five levels (saturation, capillary crack, final crack, return final crack to capillary crack and when the crack have destroyed) were examined in three replicates as the factorial based on complete randomized blocks design in Rice Research Institute.Results: The results showed that adding plant residues has increased RESISTANCE to pentrometer PENETRATION in SOIL to 37 percent, the reason of increased RESISTANCE to pentrometer PENETRATION in treatments containing plant residues, is the levels of plant residues which aren' t decomposed. While adding plant residues causes reduced RESISTANCE to pentrometer PENETRATION will accelerate in wet process. It was also found that RESISTANCE to pentrometer PENETRATION with subsidence of SOIL, volume shrinkage of SOIL, bulk density and SOIL moisture content highly correlated (0.7811-0.9916).Conclusion: Finally it's recommended that in order to reduce of the RESISTANCE to pentrometer PENETRATION, plant residues must be added to the SOIL for long time.

Tillage systems and organic manures could affect SOIL physical and mechanical properties. This study was conducted to investigate the impacts of two tillage systems including conventional tillage by moldboard plowing (plowing depth, 30 cm) and reduced tillage by disk plow (plowing depth, 15 cm) and three rates (0, 30 and 60 ton ha-1) of farmyard manure (FYM) on the SOIL PENETRATION RESISTANCE under corn cropping in a split block design with 3 replications. The cone index (CI) decreased with increase of the tillage depth. It is attributable to SOIL disturbing and loosening of the deeper layers under conventional tillage compared to reduced tillage. This trend, however, was observed only in the first (after treatments’ application and before cropping) and second (the highest rate of vegetative growth) samplings. In the third sampling (after harvest), there were not significant differences between the CI values under two tillage systems in different SOIL depths. It might be due to SOIL re-compaction (approaching the pre-tillage state) as well as disappearance of the tillage effects seven month after commencement of the experiment. In fact, the SOIL mechanical RESISTANCE increased with the time indicating SOIL re-compaction over the growing season. Adding FYM to the surface layer (i.e. 0-10 cm) of ridge SOIL resulted in significant decrease of SOIL mechanical RESISTANCE compared to control treatment. The CI decreased significantly in the 30 ton ha-1 treatment up to the stage of highest rate of vegetative grow, but the effect on CI was diminished after harvest. However, the decreasing effects of the 60 ton ha-1 treatment on the CI continued to the harvesting time. There were no significant effects of FYM in the SOIL deeper than 10 cm from the ridge surface and in all of the layers in furrow. The CI did not decrease significantly in the furrow due to negligible effect of manure application for the inter-row position.

Assessment and management of the environmental impacts of forest harvesting operations have become increasingly critical factors in practicing commercial forestry. This study investigated SOIL disturbance from a forest logging system operation on an 8-hectare mixed broadleaved stand in compartment no. 309 in Gorazbon district in Kheyrud educational and research forest. The objective of this study was to assess SOIL disturbance from ground-based skidding system operation contribute to statistically significant changes in bulk density and PENETRATION RESISTANCE at various depths below the SOIL surface and changes in bulk density and PENETRATION RESISTANCE related to different traffic intensities. A systematic predetermined grid that was laid out prior to harvesting to measure SOIL disturbance, and pre-and post SOIL disturbance were recorded by a visual assessment. SOIL compaction and PENETRATION RESISTANCE were measured by using a double sampling method consisting of a hammer driven hand corer and a hand-held SOIL penetrometer. Bulk density and SOIL strength measurements were taken at three depths: 10, 20 and 30 cm. Detrimental compaction was recorded for the SOIL bulk density results. Detrimental compaction was recorded for the SOIL penetrometer after medium and intense machine passes. Post-harvest detrimental SOIL disturbance wasn’t exceeded the USFS maximum allowable area that can be detrimentally impacted. SOIL RESISTANCE results demonstrated no detrimental compaction in area to the skid trail center and wheel ruts.

Introduction: Over the last few years, due to the depletion of Lake Urmia located in the northwest of Iran, the proportion of surrounding saline agricultural lands increased at a fast pace. Digital mapping of regional SOILs affected by salt is essential when monitoring the dynamics of SOIL salts and planning land development and reclamation schemes. The SOIL hydraulic and mechanical parameters are very important factors that affect water and chemical transport in SOIL pores. In the salt-affected SOILs, saturated hydraulic conductivity (Ks) is very low due to the high contents of sodium and weak aggregate stability. PENETRATION RESISTANCE (PR) indicates SOIL mechanical strength to PENETRATION of a cone or flat penetrometer; it is important in seedling, root growth and tillage operations. Generally, PR values exceed 2. 5 MPa, while root elongation is significantly restricted. The analysis of spatial variability of Ks and PR is essential to implement a site-specific SOIL management especially in the salt-affected lands. The objective of this study was to evaluate the influence of two different bare and agricultural land uses on the spatial variability of Ks and PR in the salt-affected SOILs around Lake Urmia. Materials and Methods: This study was conducted in the agricultural and bare lands of Shend Abad region located at the 15 km of Shabestar city, northwest of Iran (45° 36ʹ 34ʺ to 45° 36ʹ 38ʺ E and 38° 6ʹ 37ʺ to 38° 7ʹ 42ʺ N). Totally, 100 geo-referenced samples were taken from 0-10 cm SOIL depth with 100×100 m intervals (80 ha) in agricultural (n=49) and bare (n=51) land uses. Sand, silt, clay, organic carbon (OC), mean weight diameter of aggregates (MWD), sodium adsorption ratio (SAR) and electrical conductivity (EC), were measured in the collected SOIL samples. The EC and SAR were measured in 1: 2. 5 (SOIL: distilled water) extract. Ks was measured using constant or falling head method. Bulk density (BD) and field water content (FWC) were measured in the undisturbed SOIL samples taken by steal cylinders with 5 cm diameter and height. Total porosity calculated from BD and particle density (PD). PR was directly measured at the field using a cone penetrometer. The best fit semivariograms model (Gaussian, spherical and exponential) was chosen by considering the minimum residual sum of square (RSS) and maximum coefficient of determination (R2). Ordinary Kriging (OK) and inverse distance weighting (IDW) interpolation methods were used to analyze the spatial variability of Ks and PR. Spatial distribution maps of SOIL variables were provided by Arc GIS software. The accuracy of OK and IDW methods in estimating Ks and PR was evaluated by mean error (ME), mean absolute error (MAE), root mean square error (RMSE) and concordance correlation coefficient (CCC) criteria. The CCC indicates the degree to which pairs of the measured and estimated parameter value fall on the 45° line through the origin. Results and Discussion: According to coefficient of variation (CV) from the study area, the most variable SOIL indicator was Ks (CV=155. 6%), whereas the least variable was PD (CV= 3. 05%) both in bare land use. The Lognormal distribution was found for Ks data in the studied region. The Pearson correlation coefficients (r values) indicated that there are significant correlations between Ks and OC (r=0. 36), sand (r=0. 60), SAR (r=-0. 35), EC (r=-0. 22), BD (r=-0. 52), TP (r= 0. 31), silt (r=-0. 60), and clay (r=-0. 43). Also, significant correlations were obtained between PR and FWC (r=-0. 32), BD (r=0. 21), and TP (r=-0. 21). The spatial dependency classes of SOIL variables were determined according to the ratio of nugget variance to sill expressed in percentages: If the ratio was >25% and <75%, the variable was considered moderately spatially dependent; if the ratio was >75%, variable was considered weakly spatially dependent; and if the ratio was <25%, the variable was considered strongly spatially dependent. The strong spatial dependences with the effective ranges of 2443m were found for Ks. The PR and PD variables had the least (335 m) and the highest (2844 m) effective range, respectively. The range of influence indicates the limit distance at which a sample point has influence over another points, that is, the maximum distance for correlation between two sampling point. The models of fitted semivariograms were spherical for Ks and exponential for PR. According to RMSE and CCC criteria, there was not found significant difference between Ks estimates by OK and IDW interpolation methods. The high CCC and low RMSE values for OK compared with IDW indicated the more precision and accuracy of OK in estimating PR in the studied area. Generally, the spatial maps showed that from agricultural to bare land use by nearing to Lake Urmia, the BD and PR increased and consequently TP and Ks decreased. Conclusion: The results showed that Ks negatively related to the SAR, EC, BD, silt and clay and positively related to the OC, sand, MWD and TP in the study area. Also, PR negatively related to the FWC and TP and positively related to the BD and silt. The spatial dependency was found strong for Ks. The PR revealed the smallest effective range (335 m) among the studied variables. As a suggestion, for subsequent study, SOIL sampling distance could be taken as 335 m instead of 100 m in order to save time and minimize cost.

Recently, biochar has been considered as a SOIL conditioner. In research, the effect of the type and amount of biochar on SOIL properties has been emphasized. This field study was conducted to investigate the combined effect of type, amount and size of biochar particles on total porosity (TP), PENETRATION RESISTANCE (PR), mean weight diameter of aggregates (MWD) in a sandy loam texture. A Factorial experiment was performed as a randomized complete block design with three factors of type, amount and biochar particles size in three replications. Wheat straw, vermicompost and apricot firewood biochar were added to the SOIL in 0. 5, 1. 5 and 3% and particle sizes of 0. 5, 0. 5-1 and 1-2 mm. All three biochar increased TP significantly and decreased PR significantly compared to control. Biochar type had the largest contribution in TP and PR changes. The highest TP was obtained in wheat straw biochar treatment with 3% and particle size of 1-2 mm. The greatest decrease in PR was observed in wheat straw biochar with a value of 3% and a particle size of 0. 5-1 mm. Interaction of type, amount and size of biochar particles had the largest contribution in MWD change. The largest MWD (1. 22 mm) was observed in wheat straw biochar with biochar amount of 0. 5% and particle size of 0. 5 mm. The results showed that the amount and size of biochar particles had different effects on SOIL properties depending on the type of biochar.