Soil Indicators Research Articles

A Study On Stabilization of Soils by Using Egg Shell Powder

Using alternative materials, which have better engineering quality than traditional materials and are more cost-effective, has received a lot of attention recently. One of the most crucial components in many building projects, such as earth canals and earth dams, is soil. The fact that soil might offer all the resistant qualities required for a project highlights the value of several techniques used to enhance soil quality. The vast majority of construction projects employ clay soil. Because clay soils, especially soft clay soils, have good plastic qualities, their shear strength, compressive strength, and volume changes decrease as moisture content rises. Structures generally suffer permanent harm as a result of these issues, which emphasises how crucial soil improvement is. The use of such refuse and industrial wastes and their subsidiary products as alternatives to construction materials may effectively contribute to environmental preservation and minimize their negative effects on the Environment, especially in light of the millions of tonnes of waste produced annually across the nation, which not only poses the problem of disposal but also adds to environmental contamination and health risks. In the current study, eggshell powder was utilized as a waste to mix with soil in order to examine clay soil's index characteristics, compaction, and shear strength at various mixed proportions. The shear strength of soils that had already been tested was then contrasted with experimental specimens that had been combined with various ratios of eggshell powder.

Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security

Developing countries all over the world face numerous difficulties with regard to food security. The purpose of this research is to develop a new approach for evaluating wheat’s suitability for cultivation. To this end, geographical information systems (GIS) and fuzzy inference systems (FIS) are used as the most appropriate artificial intelligence (AI) tools. Outcomes of investigations carried out in the western Nile Delta, Egypt. The fuzzy inference system used was Mamdani type. The membership functions used in this work are sigmoidal, Gaussian, and zmf membership. The inputs in this research are chemical, physical, and fertility soil indices. To predict the final soil suitability using FIS, it is required to implement 81 IF-THEN rules that were written by some experts. The obtained results show the effectiveness of FIS in predicting the wheat crop’s suitability compared to conventional methods. The research region is split into four classes: around 241.3 km2 is highly suitable for wheat growth, and 224 km2 is defined as having moderate suitability. The third soil suitability class (low), which comprises 252.73 km2, is larger than the unsuitable class, which comprises 40 km2. The method given here can be easily applied again in an arid region. Decision-makers may benefit from the research’s quantitative findings.

Experimental Study on Repairing the Mechanical Characteristics of Oil-Contaminated Silty Clay in Ancient Dike with Modified Lime Mortar.

Flood-controlled ancient dikes play a significant role in flood control and have received widespread attention as historical and cultural symbols. Flood-controlled ancient dikes often undergo disasters, and research on their repair is receiving increasing attention from experts and scholars. This article studies the control of seepage and bank slope instability in flood-controlled ancient dikes. Starting from the repair of ancient dike materials, three types of work are carried out: a test of soil's mechanical properties, finite element numerical simulation, and repair technology research. The research results show that the soil of the ancient dike site has hardened after being contaminated with waste oil from catering. The strength index of the ancient dike soil decreases and shows brittleness when the water content is 15% and the oil content exceeds 6%. The strength index and permeability coefficient of oil-contaminated soil improved using modified lime mortar (MLM), which was achieved using the method of MLM to repair oil contaminated soil. When the MLM content was 10% and the oil content was 6%, the friction angle of the soil sample reached its maximum value. When the MLM content was the same, the higher the density of the soil sample, the greater the friction angle and cohesion and the smaller the permeability coefficient. Establishing a finite element numerical model, through comparative analysis, it was found that after MLM remediation of oil-contaminated soil, the extreme hydraulic gradient of the ancient dike decreased by 31.3%, and the extreme safety factor of the bank slope stability increased by 31.2%. MLM pressure grouting technology was used to improve the soil during the remediation of contaminated soil at the ancient dike site. Through on-site drilling inspection, the effective diffusion radius of MLM grouting was obtained, and the plane layout and grouting depth of MLM pressure grouting were determined. The on-site water injection permeability test showed that using MLM pressure grouting technology can effectively repair oil-contaminated soil in the ancient dike while reducing the permeability coefficient by 8-15%.

High-Precision Mapping of Soil Organic Matter Based on UAV Imagery Using Machine Learning Algorithms

Soil organic matter (SOM) is a critical indicator of soil nutrient levels, and the precise mapping of its spatial distribution through remote sensing is essential for soil regulation, precise fertilization, and scientific management and protection. This information can offer decision support to agricultural management departments and various agricultural producers. In this paper, two new soil indices, NLIrededge2 and GDVIrededge2, were proposed based on the sensitive spectral response characteristics of SOM in Northeast China. Nine parameters suitable for SOM mapping and modeling were determined using the competitive adaptive reweighted sampling (CARS) method, combined with spectrum reflectance, mathematical transformations of reflectance, vegetation indices, and so on. Then, utilizing unmanned aerial vehicle (UAV)-based multispectral images with centimeter-level resolution, a random forest machine learning algorithm was used to construct the inversion model of SOM and mapping SOM in the study area. The results showed that the random forest algorithm performed best for estimating SOM (R2 = 0.91, RMSE = 0.95, MBE = 0.49, and RPIQ = 3.25) when compared with other machine learning algorithms such as support vector regression (SVR), elastic net, Bayesian ridge, and linear regression. The findings indicated a negative correlation between SOM content and altitude. The study concluded that the SOM modeling and mapping results could meet the needs of farmers to obtain basic information and provide a reference for UAVs to monitor SOM.

A New Idea to Improve the Test Method of Soil Aggregate Stability for Soils with a Texture Gradient

It is of great significance to determine soil aggregate stability in predicting agricultural production conditions and soil erosion risk. However, the problem exposed in the process of evaluating soil aggregate stability cannot be ignored: Can the effects of different mechanisms on the degree of soil aggregate breakdown be distinguished by selecting ethanol and water as dispersion media? Based on this question, natural soils with a gradient in soil textures of silty loam to loamy clay were used as the test materials. Deionized water, ethanol and hexane were employed as soaking solutions to quantitatively analyze the extent to which the aggregates were dispersed in static disintegration experiments. The results suggested that the soil hydrophilicity (SH) of six soils with a texture gradient were >1 by comparing the aggregate breakdown index (ABI) of soils undergoing ethanol and hexane dispersion. This indicated that the hydrophilic group (-OH) contained in ethanol interacted with the hydrophilic surfaces of the soil particles. Therefore, the soil hydrophilicity (hydration) should be determined by comparing the ABI values undergoing hexane and water dispersion. From silty loam to loamy clay, the average contribution of hydration to aggregate fragmentation decreases, and the process of aggregate breakdown with different textures is characterized by size selectivity. When the soil aggregates were fragmented into 2–0.25 mm aggregate fractions, for silty loam and sandy clay loam, 0.002–0.02 mm and <0.002 mm particles were preferentially moved; for clay loam and loamy clay, >0.002 mm particles were preferentially moved. When the soil aggregates were fragmented into <0.25 mm aggregate fractions for soils with different textures, the 0.002–0.02 mm and <0.002 mm particles all exhibited preferential migration characteristics. This work provides an idea for improving the methods of aggregate stability measurements in the future.

Robust models to predict the secondary compression index of fine-grained soils using multi objective evolutionary polynomial regression analysis

Robust models to predict the secondary compression index of fine-grained soils using multi objective evolutionary polynomial regression analysis

STATUS OF SOIL QUALITY ON RECLAIMED LAND IN AN ARID REGION

The study was conducted in Egypt’s El Minya Governorate, where 16 soil samples were taken from reclaimed land and analyzed in the USA using a variety of indices. The study revealed that the soil was moderately alkaline, calcareous, and had salinities ranging from not salty to relatively salty. Most of the soil samples had a clay texture, with varying mineral compositions. The study also found that phosphate fertilizers had been used to improve soil fertility, but it was cautioned against using them due to the low soil fertility and potential for heavy metal contamination. The study also compared the quality index of soil, the ratio of sodium absorption, and the percent of base saturation to determine soil quality and fertility. Finally, the study found that agriculture was more extensive in 2018 and 2020 than in 2022, which could indicate a lack of farming in the current season.

Influence of acid rain and root reinforcement coupling factors on disintegration characteristics of expansive soil.

The effect of soil fixation and anti-scour instability of slope vegetation generally depends on the strength and anti-disintegration ability of slope soil due to increase of root system. Therefore, it is particularly necessary to study the disintegration characteristics of expansive soil related to slope instability under acidic conditions (simulated acid rain). In this paper, the response surface method (RSM) was used with the pH value, root diameter, root length, root coefficient, and distribution as independent variables, and the disintegration amount of root-soil (DARS) after 60min as the response value. Then X-ray diffractometer (XRD) was used to analyze the mineral composition changes of the sample under this environment. Simultaneously, the plasticity index of expansive soil at different values of pH was studied to discuss the disintegration mechanism of root compound expansive soil in an acid environments. The results show that the root system improves the anti-disintegration characteristics of the root-soil, and the effects of various factors on the amount of disintegration were as follows: root length > pH value > root distribution > root amount > root diameter. The DARS with a length of 20mm increased by 26.67% and 41.56% compared to the 30mm and 40mm. Compared to the horizontal distribution and horizontal + slant distribution, the DARS with slant distribution was increases by 11.39% and 20.24% respectively. The DARS with 2 roots is increased by 9.92% and 16.75% compared to 4 and 6 roots respectively. The 1mm diameter DARS is 6.65% and 15.49% higher than the 2mm and 3mm, respectively. In addition, an acidic environments can lead to an increase in the amount of disintegration or rate of disintegration. The disintegration at pH = 4.2 was increased by 11.4% and 22.4% compared to pH = 5.6 and pH = 7, respectively. The acidity affects soil disintegration is due to the hydrophilic minerals in the expansive soil react with H+ ion in the acid solution to form soluble salts. Due to the dissociation and leaching of free quartz and metal oxides in the soil to varying degrees, the ability of expansive soil to accumulate is reduced. The intensity of erosion and leaching decreases with increasing pH. In addition, the pH value can affects the plasticity index of the soil, which increases with the increasing pH, thus affects the disintegration properties of the expansive soil.

A Research on Groundnut Shell Ash's Impact on Lateritic Soils' Soil Stabilization

This study aims to provide information on the engineering characteristics of laterite soil, which is frequently used as a building material in civil engineering projects. The significance of subsoil investigations has grown significantly in light of the recent trend of civil construction collapses. In non-industrial nations like Nigeria, minimal residual soil has long been a problem for civil infrastructure, including buildings, culverts, dams, and highways. Also, there has been a lot of global research into using lateritic soil for engineering reasons due to the rising costs of conventional stabilizing agents and the need to utilize industrial and agricultural waste in cost- effective ways for engineering applications. As implied by the research project's topic, this is accomplished through a comprehensive field inquiry and intensive laboratory testing (the effect of groundnut shell ash on lateritic soil properties). The index property test categorized the soil into the A-2-4 subgroup in accordance with the AASHTO standard. As a result, the substance is deemed unfit for use as a foundation or sub-base for paving roads. Tests on the soil's index and geotechnical characteristics after adding groundnut shell ash show significant changes in the parameters. The tests performed for this study adhered to BS 1377:1975 standards. An analysis of the data shows that GSA can be used as a binding agent in the absence of cement, even if it does not have the same binding strength as cement. 4% G.S.A. was also discovered to be the optimal content concentration. All tests and analyses are shown in chapters three and four.

Flow index-liquid limit relationship by fall-cone tests in clay-sand mixtures

The Fall-cone test is a useful method which can be used in evaluation of many soil index and strength identifiers. In this regard, the flow index is calculated as the slope of the plot of water content against natural logarithm of the penetration depth. This is also a fruitful method used to determine the liquid limit of soils, and evaluation of test results may lead to many parameters related to soil plasticity, i.e. using the flow index. In this study, the changes in the liquid limit and plasticity index of a soil as a function of the flow index were investigated. Later, a simple correlation between the plasticity index and the flow index was obtained, and as a result, the plasticity index was directly calculated. The Fallcone test results show that there is an excellent relationship between the plasticity index and the flow index in soils within a wide range of plasticity level and this relationship is significantly affected from mineralogical properties of components of sand-clay mixtures. A linear relationship with R2 = 0.97 (n = 44) was obtained. As a result, both the liquid limit and the plasticity index of the soils are calculated directly based on the results of the Fall-cone test. In addition, this study compared the results of the standard plasticity chart with the new plasticity chart proposed by Vardanega et al. (2022) for the classifying fine-grained soils. It was shown that the new plasticity chart proposed by Vardanega et al. (2022) can also be used in the classification of both fine-grained soils and clay-sand mixtures. The new plasticity chart by Vardanega et al. (2022) provided modifications on standard plasticity chart. The usefulness of the new chart is also verified by the results of this study, experimental results showed that soil classes -for 115 specimens of 125 total- obtained using Fall-cone tests are in accordance with classifications proposed by Vardanega et al. (2022). According to experimental results, the highest flow index was obtained in %100 bentonite soil at 146.47, while the lowest flow index at 7.20 was obtained in a mixture of 90% sand (SW) −10% bentonite. In 100% pure kaolin clay, the liquid limit was 56.09%, the plasticity index was 27.52% and the flow index was 34.55.

Big-sized trees and higher species diversity improve water holding capacities of forests in northeast China

High water-holding forests are essential for adapting to drought climates under global warming, and a central issue is which type of forests could conserve more water in the ecosystem. This paper explores how forest structure, plant diversity, and soil physics impact forest water-holding capacities. We investigated 720 sampling plots by measuring water-holding capacities from 1440 soil and litter samples, 8400 leaves, and 1680 branches and surveying 18,054 trees in total (28 species). Water-holding capacities were measured as four soil indices (Maxwc, maximum water-holding capacity; Fcwc, field water-holding capacity; Cpwc, soil capillary water-holding capacity; Ncpwc, non-capillary water-holding capacity), two litter metrics (Maxwcl, maximum water-holding capacity of litters; Ewcl, effective water-holding capacity of litters), and canopy interception (C, the sum of estimated water interception of all branches and leaves of all tree species in the plot). We found that water-holding capacity in the big-sized tree plots was 4–25 % higher in the litters, 54–64 % in the canopy, and 6–37 % in the soils than in the small-sized plots. The higher species richness increased all soil water-holding capacities compared to the lowest richness plot. Higher Simpson and Shannon-Wiener plots had 10–27 % higher Ewcl and C than the lowest plots. Bulk density had the strongest negative relations with Maxwc, Cpwc, and Fcwc, whereas field soil water content positively affected them. Soil physics, forest structure, and plant diversity explained 90.5 %, 5.9 %, and 0.2 % of the water-holding variation, respectively. Tree sizes increased C, Ncpwc, Ewcl directly (p < 0.05), and richness increased Ewcl directly (p < 0.05). However, the direct effects from the uniform angle index (tree distribution evenness) were balanced by their indirect effect from soil physics. Our findings highlighted that the mixed forests with big-sized trees and rich species could effectively improve the water-holding capacities of the ecosystem.

Variability Analysis of the Behaviors of a Lateritic Soil Profile as a Structural Material

The desideratum of determining the behavior of the underlying soil on which the foundations will be laid is indisputable. This study evaluates the strength characteristics of lateritic soil material at a new construction site opposite College of Engineering and Engineering Technology (CEET), Michael Okpara University of Agriculture, Umudike (MOUAU). A trail pit was dug taking disturbed soil samples at a depth of 1m, 2m, and 3m for experimental analysis. Laboratory tests on specific gravity, grain size distribution, moisture content, atterberg limits, and triaxial tests were carried out on each sample by the procedure highlighted in BS1377 1990. Inspecting visually, the soil profile was observed to consist of three layers; light reddish, reddish, and whitish at the top, middle, and bottom respectively. The natural water content of the soil samples varied as 9.06+0.00 %, 7.98+0.00 %, and 9.32+0.03 %, while the specific gravity obtained from the test results was 2. 630+0.00 %, 2.634+0.00 % and 2.647+0.00 % at depths 1m, 2m, and 3m respectively. Using the unified soil classification system (USCS), the top, middle and bottom layers were classified as cloud sand (SC). The soil samples have a liquid limit (LL) of 24.5%, 28.8%, 31.0%; plastic limit (PL) of 19.4%, 17.2%, 18.5%; and plasticity index (PI) of 5.1%, 11.6%, and 12.5% at depths 1m, 2m, and 3m respectively. It was observed that the soil index properties vary and are enhanced as the depth of the excavation increases. Furthermore, the value of the cohesion property of the soil is 74.62 kN/m2, 29.70 KN/m2, and 24.65 KN/m2 for samples at 2m, 3m, and 3m depth respectively. The greatest and least cohesion value was noted to be 74.62 kN/m2 and 24.65 kN/m2 for samples at 2m and 3m depth respectively; the maximum and minimum angles of internal friction were 25.52o and 13.67o at depths 1m and 2m respectively. The outcome of this paper showed that the analyzed soil samples are suitable for civil engineering works.

The Relationship Between the Above-Ground Biomass and the Vegetation Cover Indices at Different Salinity Levels

The current study was carried out to find out the relationship between the Above-Ground Biomass and the spectral vegetative indices (Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Difference Vegetation Index) (NDVI, SAVI, DVI) for soils with different salinity levels. Al Salamiyat Project was chosen as a study area located at an altitude of 34 m above sea level and within the geographical coordinates (E 44°.09´13.65´´ N 33°.25´ 07.87´´ and E 44°.17´ 46.03´´ N 33°.2l´40.72´´), with a total area of 14265 Dunum. Surface and subsurface soil samples were chosen from the study area and according to the previously defined salinity units, except for the salinity map that was updated based on the soil samples of the current study. After updating the salinity map of this project, 12 Pedons (two Pedon for each salinity unit) were excavated and morphologically described. Then, the soil samples were taken from each horizon to estimate the physical and chemical properties and biomass values for each site. The study showed that the soil salinity Ece in the study Pedon ranged from 1.1 dS/m in the C2 horizon for the twelfth Pedon to 41.6 dS/m in the upper Az horizon of the ninth Pedon. It also showed that there is a high correlation (r = 0.553) between the values of soil salinity and the biomass of plants growing in it, which confirms that the biomass was increasing with the increase in soil salinity. Furthermore, the (NDVI) showed a variation in the study area, ranging from 0.386 to 0.473, while the values of this index ranged from 0.1568 to 0.4093, as it was observed that there is a direct relationship between them (r = 0.643). The values of (SAVI) showed a difference between the studied Pedon sites, the values of this index ranged from 0.0581 to 0.7100, and it was also ranged from 0.1087 to 0.6213 for the same Pedon value. Whereas the values of the (DVI) index ranged between -0.0023 to 0.0942 and from 0.0197 to 0.0874 for the study Pedon, this index showed a highly significant relationship with the above-ground biomass (r = 0.825).

Application of global mapping indices for changedetection in coal mining areas of Salanpur block ofPaschim Bardhaman district, West Bengal

The article is about the application of global mapping indices for detecting changes in vegeta-tion cover, water bodies, bare soil, and built-up areas using the Normalized Difference Vegeta-tion Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Soil Index (NDSI), Normalized Difference Water Index (NDWI) and the Global Environment Moni-toring Index (GEMI). In this study, Landsat remote sensing imagery was used to quantify change detection in coal mining areas of the Salanpur block. The aim was to analyze different landcover types using Landsat imagery with a twenty-year interval from 2001 to 2021. The mineral-bearing areas have been identified as one of the global sources of income but the research carried out from such resource-rich areas revealed that these areas experienced a rapid loss of vegetation cover and other environmental degradation due to the gigantic expansion of mining projects. These indices are used to extract information concerning land issues due to anthropo-genic activities. The results obtained from these indices in this study show conversions of vegetation land when the land was put to some excavation activities or other developmental work. This study shows an effort to monitor major entities like water bodies, vegetation cover, bare ground, and urban areas. It also shows the suitability of these mapping indices for detecting changes concerning the mining environment.

Effect of Moisture Content on Subgrade Soils Resilient Modulus for Predicting Pavement Rutting

The subgrade soil stiffness, which depends on the in-situ moisture content and soil index characteristics, is a key factor in pavement rutting. Due to variations in the compaction process used during construction and seasonal changes, the subgrade soil moisture content may deviate from the desired condition. The resilient modulus (MR), an important parameter of the Mechanistic-Empirical (M-E) pavement design process, is used to specify the subgrade soil stiffness. Repeated load triaxial tests, which can be challenging and time-consuming to execute, are often used to determine MR. As a result, correlations between MR and more accessible stiffness metrics and index qualities are frequently used. California bearing ratio (CBR) and repeated load triaxial tests were carried out in this investigation. Soil specimens were fabricated at moisture levels that were both above and below the optimum moisture content (wopt). The results of the two tests were correlated, and statistical models were created to correlate the parameters of the generalized constitutive resilient modulus model with the characteristics of the soil index. Additionally, utilizing the MR found for subgrade soils compacted at wopt and ±2%wopt, pavement rutting was analyzed for three base layer types. The results demonstrated that a laboratory-measured MR (MR(Lab)) decreases as the moisture content increases. Specimens compacted at −2%wopt showed higher MR(Lab) than specimens compacted at wopt. Specimens compacted at +2%wopt showed lower MR(Lab) than specimens compacted at wopt. Results also indicated that the MR(Lab) predicted higher pavement rutting compared to field measured MR (MR(Lab)). If a stabilized aggregate foundation layer was employed instead of an untreated granular base, subgrade soil moisture condition showed a significant impact on rutting.

Correlation analysis of physical and mechanical parameters of inland fluvial-lacustrine soft soil based on different survey techniques

Abstract Based on the collected soil property index test data of more than 2,500 groups of inland fluvial-lacustrine soft soil, the correlation of physical and mechanical parameters of this soft soil was systematically analyzed. The results show that the physical indexes of inland fluvial-lacustrine soft soil are close to that of marine soft soil, while its mechanical indexes are higher. However, the variation coefficient of its mechanical indexes is much larger than that of the physical indexes. In addition, it is found that the cone penetration parameters of this soft soil are significantly correlated with its physical and mechanical indexes by establishing a series of empirical relationships between the static point resistance and the natural unit weight, the liquidity index, the quick shear cohesion, and vane shear strength. On the basis of the previous research results, the disturbance strength of inland fluvial-lacustrine soft soil can be converted into in situ strength by deriving the theoretical formula between the vane shear strength and the disturbance degree. The calculation process of the above conversion relation is explained in detail through an engineering case, which indicates that the theoretical formulas have good applicability for inland fluvial-lacustrine soft soil.

Short-Term Co-Application of Organic and Chemical Fertilizer Benefits Topsoil Properties and Maize Productivity in a Medium-Productivity Meadow-Cinnamon Soil

Co-application of organic-chemical fertilizer (CAOFCF) has attracted wide attention in China in recent years. However, its short-term effect on topsoil quality and maize yield in a medium-productivity meadow-cinnamon soil is not clear. In order to address this problem, a 3-year (2019–2021) field trial was established by arranging the following five treatments: (1) CF, applying chemical fertilizer alone; (2) OFCF1, 15% organic fertilizer + 85% chemical fertilizer; (3) OFCF2, 30% organic fertilizer + 70% chemical fertilizer; (4) OFCF3, 45% organic fertilizer + 55% chemical fertilizer; (5) OFCF4, 60% organic fertilizer + 40% chemical fertilizer. The results showed that short-term CAOFCF treatments were beneficial to the topsoil aggregate stability by increasing the percentage and mean weight diameter of macro-aggregate in topsoil. In addition, lower soil bulk density and higher soil organic carbon sequestration in topsoil were observed under the CAOFCF treatments. There was no difference in rhizosphere microbial diversity among all treatments. Compared to CF, OFCF1 and OFCF2 improved the activities of some key enzymes, including sucrase, urease, and acid phosphatase. Moreover, higher relative abundance of Actinobacteria and Chloroflexi were observed under the CAOFCF treatments. The root-shoot dry matter and maize grain yield were obviously higher in OFCF1 and OFCF2 than in CF; however, no significant difference was found in the OFCF3 and OFCF4 treatments compared to CF. The analysis of correlation suggested that there were no direct correlations between maize yield and various soil indexes measured. Nevertheless, root dry weight and root-shoot ratio were positively correlated with the activities of urease and sucrase. Meanwhile, the relationships between root dry weight, root-shoot ratio, shoot dry weight, and grain yield were all significant. In conclusion, short-term co-application of organic and chemical fertilizer (i.e., replacing 15–30% chemical fertilizer with organic fertilizer with an equal N rate) was beneficial to soil properties and maize grain yield in a medium-productivity meadow-cinnamon soil. The higher grain yield was associated with a strong maize root system, which was driven by the improved rhizosphere urease and sucrase activities.

Effect of geographical factors on reference values of creatine kinase isoenzyme.

The aim of this study was to investigate the geographical spatial distribution of creatine kinase isoenzyme (CK-MB) in order to provide a scientific basis for clinical examination. The reference values of CK-MB of 8697 healthy adults in 137 cities in China were collected by reading a large number of literates. Moran index was used to determine the spatial relationship, and 24 factors were selected, which belonged to terrain, climate, and soil indexes. Correlation analysis was conducted between CK-MB and geographical factors to determine significance, and 9 significance factors were extracted. Based on R language to evaluate the degree of multicollinearity of the model, CK-MB Ridge model, Lasso model, and PCA model were established, through calculating the relative error to choose the best model PCA, testing the normality of the predicted values, and choosing the disjunctive kriging interpolation to make the geographical distribution. The results show that CK-MB reference values of healthy adults were generally correlated with latitude, annual sunshine duration, annual mean relative humidity, annual precipitation amount, and annual range of air temperature and significantly correlated with annual mean air temperature, topsoil gravel content, topsoil cation exchange capacity in clay, and topsoil cation exchange capacity in silt. The geospatial distribution map shows that on the whole, it is higher in the north and lower in the south, and gradually increases from the southeast coastal area to the northwest inland area. If the geographical factors are obtained in a location, the CK-MB model can be used to predict the CK-MB of healthy adults in the region, which provides a reference for us to consider regional differences in clinical diagnosis.

Temporal remote sensing based soil salinity mapping in Indo-Gangetic plain employing machine-learning techniques

Soil salinization is one of the most active land degradation processes, affecting predominantly arid, semi-arid, and dry sub-humid regions and leading to decreased agricultural yields. The Indo-Gangetic plain, which includes the irrigated command areas with arid and semi-arid climatic conditions are severely affected by secondary soil salinization. Assessing the spatial and temporal extent as well as the severity of salinization is an important step for adoption of proper reclamation measures to boost agricultural productivity in the salt affected areas. The study was conducted with this background to evaluate the extent and severity of soil salinization in alluvial plains of Mathura district of Uttar Pradesh, India. In this study, the satellite data of 6 months from January 2019 to June 2019 were pre-processed and various spectral indices were generated in Google Earth Engine. Remote sensing techniques provides an ideal platform for addressing this problem at larger scales and thus we employed Sentinel-2 derived vegetation and salinity spectral indices for distinguishing temporal change in severity of soil salinization and map the salinity as a function of these indices for the entire study area. The time series salinity analysis showed that among the various spectral indices Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Soil Index (NDSI) had a clear differentiation between slight, moderate and severe salinity class in the first three months of the study period and the Salinity Index II (SI_II) could differentiate for the first four months. Further, two machine learning algorithms namely Random Forest (RF) and Support Vector Machine (SVM), were used to create soil salinity prediction models making use of the soil Electrical Conductivity (EC) values of 115 ground-sampling sites as the predictand variable and the optimal spectral indices as the predictor variables. Further, we evaluated the prediction ability of different models using 12 and 24 variables combination using R2 and RMSE values. The prediction accuracy of the RF model was found to be slightly higher than that of the SVM model, and the spatial distribution pattern of soil salinity predicted by the two models were comparable. We concluded that spectral indices combined with machine learning techniques have the potential for low cost reliable spatial and temporal soil salinity distribution mapping for planning and implementation of salinity reclamation measures.

Spatial distribution characteristics and risk assessment of soil heavy metal pollution around typical coal gangue hill located in Fengfeng Mining area.

The pollution of heavy metals in soil caused by exposed coal gangue and its prevention and control has become a hot issue restricting the green mining of coal in China. Nemerow integrated pollution index (NIPI), potential ecological risk index (RI) and human health risk assessment model were used to evaluate the pollution and risk of heavy metals (Cu, Cr, As, Pb) in the soil around the typical coal gangue hill in Fengfeng mining area of China. The results show that: firstly, the accumulation of coal gangue leads to the enrichment of four heavy metals in the surrounding shallow soil, and NIPI and RI were 1.0-4.4 and 21.63-91.28, respectively. The comprehensive pollution level of heavy metals in soil reached the warning line and above, and the potential ecological risk level reached slightly and above. When the horizontal distance exceeded 300m, 300m and 200m, respectively, the influence of coal gangue hill on the heavy metal content in shallow soil, the comprehensive pollution level of heavy metals and the potential ecological risk level basically disappeared. In addition, based on the potential ecological risk assessment results and main risk factors, the ecological risk configuration of the study area was divided into five categories: "strong ecological risk + As," "intermediate ecological risk + As + Cu," "intermediate ecological risk + As + Cu or Pb," "minor ecological risk + As + Cu" and "minor ecological risk + As + Cu or Pb." The hazard index (HI) and total carcinogenic risk (TCR) of shallow soil polluted by heavy metals in the study area were 0.24-1.07 and 0.41 × 10-4-1.78 × 10-4, respectively, which posed non-carcinogenic and carcinogenic risks to children, but the risks were controllable. This study will help to take strategic measures to accurately control and repair the heavy metal pollution in the soil around the coal gangue hill and provide a scientific basis for solving the safe use of agricultural land and realizing the construction of ecological civilization.