Soil Particle Size Research Articles

Proximal sensors for modeling clay mineralogy and characterization of soil textural fractions developed from contrasting parent materials

Proximal sensors combined with X-ray diffraction (XRD) have optimized soil characterization, but scarce studies have focused on predicting the contents of minerals under this scope. The objectives herein were to: a) use the portable X-ray fluorescence (pXRF) spectrometry, diffuse reflectance spectroscopy in the range of visible and near-infrared (Vis-NIR), magnetic susceptibility (χ) and XRD to characterize the mineralogy of soils derived from representative Brazilian soil parent materials, and b) create models to quantify the minerals obtained via XRD. Twenty-two soil profiles developed from gabbro, gneiss, quartzite, mineral and organic sediments were described with 53 soil horizons sampled. Each sample had the sand, silt and clay fractions separated and analyzed with XRD, pXRF, χ, and Vis-NIR. Models were created using the Random Forest algorithm permuting the following predictor variables (separately and combined): pXRF, parent material (PM), χ, soil texture (sand, silt, and clay content), and Vis-NIR. Models’ accuracy was calculated using the leave-one-out cross-validation method. Si, Al, Fe, Ca, K, and Ti contents obtained by pXRF and the χ discriminated the soil particle size fractions according to the parent material. XRD analysis allowed the evaluation of the pedogenetic development of soils and their relation to the respective parent material. The best models for mineral contents were found for hematite (Hm) (104)+(Gt) (130) (R2 = 0.85), Hm (110) + Mh (131) (R2 = 0.76), kaolinite (Kt) (001) (R2 = 0.73), Kt (002) (R2 = 0.80), mica (Mc) (001) (R2 = 0.77), and Mc (020) + Kt (020) (R2 = 0.81). Clay mineralogy content was accurately modeled using only pXRF and parent material data. This approach can facilitate and speed up detailed soil mineralogy characterization. Further studies are encouraged to model the content of minerals found in the sand and silt fractions of soils with diverse mineralogy via proximal sensors and using larger data sets.

National-scale digital soil mapping performances are related to covariates and sampling density: Lessons from France

Accurate soil property and class predictions through spatial modelling necessitate a thoughtful selection of explanatory variables and sample size, as their choice greatly impacts model performance. Within the framework of Global Soil Nutrient and Nutrient Budget maps (GSNmap), the FAO Global Soil Partnership (GSP) launched a country-driven digital soil mapping (DSM) approach. The GSP asked the countries if they could implement the DSM prediction of ten soil properties, using their national point data and a set of widely available covariates (GSP_Cov). In this study, we examined the effect of including additional national-based covariates and soil observations on the performance of the prediction models using mainland France as a pilot. The learning soil dataset was based on a systematic 16-to-16 km grid. For a subset of soil properties, we also assessed using repeated k-fold cross-validation the effect of adding to this dataset many other irregularly spread measurements. The GSP_Cov included common widely available covariates that represented information about terrain, climate, and organisms. The second set of covariates consisted of the GSP_Cov, extended to extra covariates available at a national level, such as previously existing soil maps, geological maps, remote sensing products and others. Random Forest approach in combination with the Boruta selection method was employed for mapping ten soil properties: soil organic carbon (SOC), pH (water), total nitrogen (N), available phosphorus (P), available potassium (K), cation exchange capacity (CEC), bulk density (BD), and texture (clay, silt, and sand). The results revealed noteworthy enhancements in prediction performance for more than half of the properties, although, for some of them, the improvements were negligible. The most significant improvements were obtained for pH, CEC and texture, where geological variables and a previous pH map significantly contributed to the increase in accuracy. Adding numerous points (around 25,000) to the learning dataset improved the performance of soil particle-size fractions predictions. By broadening the spectrum of covariates and better covering the feature and geographical spaces considered in soil prediction models, this research underscores the importance of implementing a more diverse range of covariates at a national scale and of densifying soil information to enlarge the feature and geographical spaces of multidimensional soil/covariates combinations. This information should be taken into account in national and continental digital soil mapping endeavours.

Adaptive multi-paddock grazing increases mineral associated soil carbon in Northern grasslands

Grassland soils play an important role in sequestering carbon (C) and are primarily used for livestock grazing. Grazing management can increase the amount of C stored in soils and the distribution of C in different soil fractions by altering soil microbial community structure, thereby influencing the persistence of soil C over time. Adaptive multi-paddock grazing (AMP), grazing cattle at high stock densities with long periods between grazing events, is considered to enhance grassland sustainability, productivity, and soil C compared to more conventional grazing practices (continuous to slow rotational). However, whether and how AMP grazing might affect the amount of C stored in different soil fractions has received little attention. Soil samples (0–15 cm depth) were collected from 24 ranches in a paired design, where 12 ranches practiced AMP grazing and 12 neighboring ranches practiced conventional grazing. Soil organic C (SOC) and total nitrogen were measured in different soil particle size [fine (<53 µm), medium (53–250 µm) and coarse (>250 µm)], and density [light (>1.6 g cm−3), and heavy (<1.6 g cm−3)] fractions. Soil bacterial and fungal biomass and abundances were obtained from phospholipid fatty acid analysis. Mean weights of soil microaggregates and heavy fractions were higher in soil exposed to AMP grazing, whereas mean weights of macroaggregates and light fractions were higher in conventionally grazed soils. In warmer and drier climatic conditions, SOC in both bulk soils and within various size and density fractions tended to decrease. Soil organic C (both concentration and stock) were significantly higher in the fine soil fractions under AMP management than conventionally grazed grasslands. Given that SOC in fine fractions, is more mineral associated and recalcitrant, our results indicate that AMP grazing increased the size of the stable SOC pool. The increased carbon pool in the fine fraction was associated with greater fungal to bacterial ratios, suggesting a possible biological mechanism for the increase. Overall, the results indicate that AMP grazing may be beneficial for sequestering more stable carbon that helps mitigate the effects of climate change.

Multifractal characteristics of soil particle size distribution of abandoned homestead reclamation under different forest management modes

In this study, fast-growing poplar reclaimed from abandoned homestead in Xixian New District, Xi’an City, Shaanxi Province, was used as the research object to explore the multi-fractal characteristics of soil particle size distribution under different management modes of abandoned land (control), irrigation, fertilizer irrigation and mixed fertilizer irrigation. The results showed that the mean values of soil clay, silt and sand in abandoned land were 14.58%, 81.21% and 4.22% respectively, 14.08%, 79.92% and 5.99% under irrigation, 15.17%, 81.19% and 3.64% under fertilizer irrigation, and 16.75%, 80.20% and 3.05% in mixed fertilizer treatment. From 40 cm, with increasing soil depth, soil clay particles increase under irrigation, fertilizer irrigation, and mixed fertilizer irrigation modes. The single fractal dimension of soil particle size distribution (D) in each treatment ranges from 2.721 to 2.808. At 60–100 cm, D shows fertilizer irrigation > mixed fertilizer irrigation > irrigation > abandoned land, indicating that fertilization and irrigation can increase the fine-grained matter of deep soil particles and reduce soil roughness. Compared with abandoned land, under irrigation, fertilizer irrigation and mixed fertilizer modes the capacity dimension (D0), entropy dimension (D1), correlation dimension(D2), shape characteristics of the multifractal spectrum (Δf) and overall inhomogeneity of the soil particle size distribution (D0–D10) indicate an uneven distribution of soil particle size; fractal structure characteristics of soil (D−10–D0) indicate a simplified soil structure, and degree of dispersion of soil particle size distribution (D1/D0) indicates that soil particle size is distributed in dense areas. Pearson correlation analysis showed that D was significantly correlated with clay, sand, D0–D10, soil organic matter (SOM) and soil available phosphorus (SAP) (P < 0.05). Stepwise regression analysis showed that clay was the main controlling factor of D and D0–D10 changes. The research results can provide some potential indicators for the quality evaluation of abandoned homestead reclamation.

Experimental study on the interface characteristics of geogrid-reinforced gravelly soil based on pull-out tests

The factors influencing geogrid–soil interface characteristics are critical design parameters in some geotechnical designs. This study describes pull-out tests performed on gravelly soils commonly encountered in the Xinjiang region and reinforced with two types of geogrids. The factors affecting the geogrid–gravelly soil interface properties are investigated with different experimental loading methods (pull-out velocity, normal stress), geogrid types, and soil particle size distributions and water contents. The ultimate pull-out force increases with the normal stress and pull-out velocity. Furthermore, with increasing coarse particle content and water content, the ultimate pull-out force increases and then decreases sharply. Based on these research results, this paper provides reasonable parameters and recommendations for the design and pull-out testing of reinforced soil in engineering structures. In reinforced soil structure design, the grid depth should be increased appropriately, and the coarse particle content of the overlying soil should be between 30 and 40%. During construction, the gravelly soil should be compacted to the maximum compaction at the optimal water content, and the structure should have a reasonable waterproofing system. According to the calculation results of the interface strength parameters, the uniaxial geogrid–gravelly soil interface has a high cohesive force csg, which should not be ignored in reinforced soil structure design.

Conversion of Natural Soil to Paddy Promotes Soil Organic Matter Degradation in Small-Particle Fractions: δ13C and Lipid Biomarker Evidence

The stabilization mechanism of soil organic matter (SOM) has received considerable attention. It is widely accepted that mineral sorption/protection is important for SOM stabilization. However, it remains unclear which organic carbon component is beneficial for mineral protection. We collected soil samples from a paddy field (TP) to compare with natural soil (NS). To illustrate the behavior of different SOM pools and their protection by particles, we separated the soils into different particle-size fractions and then removed the active minerals using an acid mixture (1 M HCl/10% HF). The different carbon pools were analyzed using stable carbon isotopes and lipid biomarkers. Our study showed that acid treatment evidently increased the extractability of free lipids, usually over 60%, which confirmed the predominant role of minerals in SOM protection. For NS, the δ13C values increased with decreasing soil particle sizes and soil depths, indicating that 13C-enriched SOM was selectively preserved. However, this trend disappeared after cultivation, which was mainly attributed to the combined effects of the input of 13C-depleted fresh SOM and decomposition of the preserved 13C-enriched SOM. Meanwhile, based on the degradation parameters of the overall lipid biomarkers, SOM showed higher degradation states in clay and silt fractions than in the sand fraction before cultivation. It is possible that the small particle-size fractions could selectively absorb highly degraded SOM. The clay-associated SOM showed a low degradation state, but its carbon content was low after cultivation. We propose that the previously protected SOM was degraded after cultivation and was replaced by relatively fresh SOM, which should be carefully monitored during SOM management.

Estimating soil water content from thermal images with an artificial neural network

Data of soil water content measured at regular time intervals could be used to set an irrigation schedule for farmland. Changes in soil water content could also provide an early warning of potential slope slippage. An artificial neural network is proposed for detecting soil water content from five variables: soil and water temperature changes after sunlight exposure, plant coverage rates, fine-grained soil content, and effective soil particle size. Temperature changes were detected using thermal images taken using an unmanned aerial vehicle equipped with a thermal camera in the morning and at noon. Plant coverage was estimated using visible light photograph, and the fine-grained soil content, effective particle size, and soil water content were determined from laboratory tests of soil samples. An optimized neural network was established by analyzing the performance of various neural network parameters. The mean square error of the optimized neural network reached a minimum value of 0.10061 in the validation data set at the 12th epoch, the training was stopped to avoid overfitting. The correlation coefficients for the training, validation, testing, and overall data sets were 0.880, 0.772, 0.810, and 0.847 respectively. The target values and the predicted values of the neural network are highly correlated. Thus, the proposed neural network is effective for predicting soil water content. A relative importance analysis revealed that soil and water temperature changes after sunlight exposure had the greatest influence on the neural network’s results.

Elevation-related variations of soil disintegration and its driving forces in the water level fluctuation zone of the Three Gorges Reservoir, China

Soil disintegration is a key process of the early stages of soil erosion. The water level fluctuation zone (WLFZ) in reservoirs undergoes seasonal changes involving periodic alternations in inundation and exposure that can affect soil disintegration. In this study, we conducted experiments on pre-wetted undisturbed soil samples obtained from different elevations ranging from 155 to 180 m a.s.l. and different soil depths (0–10 and 10–20 cm) in the WLFZ of the Three Gorges Reservoir (TGR), upper Yangtze River, China. We investigated how soil disintegration varies depending on elevation within the WLFZ and used principal component analysis (PCA) and stepwise regression to identify the dominant variables affecting soil disintegration. Results show the following: (1) The disintegration ratio, which is a measure of the amount of soil disintegration that occurs during experiments, varied in the range of 0.45 %–4.79 % over 60 min, with 79 %–100 % of the disintegration occurring within the first 30 min. The disintegration ratio increases with decreasing elevation in the WLFZ. Soil samples from a depth of 0–10 cm disintegrated 0.43 % less on average than those from a depth of 10–20 cm. The relationship between disintegration rate and elevation can be expressed using an exponential function with R2 > 0.80. (2) The main variables loading onto the first three principal components (explain 91.4 % of the variation in all variables) identified by PCA were those involving soil aggregates, the plant root system, and soil particle-size, respectively. (3) Stepwise regression identified >0.25 mm water-stable aggregate content (Ws0.25) and root mean diameter (Droot) as the strongest predictors of soil disintegration and yielded a linear regression equation with R2 = 0.88. Ws0.25 and Droot were the most influential variables on the elevation-dependent occurrence/degree of disintegration. Such information is essential for understanding the occurrence and prevention of bank erosion in reservoir areas.

Study on the Temperature and Water Distribution of Hot Air in Red Loam Based on Soil Continuous Cropping Obstacles

In recent years, the problematic circumstances of the constant cropping problem in facility crops have become increasingly serious. Compared to chemical disinfection, soil steam disinfestation offers the benefits of environmental protection and being pollution-free, which can effectively reduce the problem of constant cropping in crops. However, during the steam disinfection procedure, a large quantity of liquid water is formed due to the condensation of high-temperature steam, which causes soil pore blockage, seriously affecting the mass and heat transfer efficacy of steam and, thus, affecting the disinfection efficiency. Therefore, to solve this problem, this paper proposes the use of hot air dehumidification to remove excess water from soil pores and achieve the goal of dredging the pores. However, further exploration is needed on how to efficiently remove excess water from different pore structures through hot air applications. Therefore, this paper first used CFD simulation technology to simulate and analyze the hot air flow field, mass, and heat transfer in soil aggregates of different sizes (&lt;2 mm to &gt;8 mm). Then, based on the soil hot air heating experimental platform, research was conducted on the mass and heat transfer mechanism of hot air under diverse soil pore conditions. The results show that as the soil particle size increases from &lt;2 mm to &gt;8 mm, the number of soil macropores also increases, which makes the soil prone to the formation of macropore thermal currents, and the efficiency of hot air heating for dehumidification first increases and then decreases. Among them, the 4–6 mm treatment has the best dehumidification effect through hot air heating, with a deep soil temperature of up to 90 °C and a water content reduction of 6%. The 4–6 mm treatment has a high-temperature heating and dehumidification area of 15–20 cm deep. The above results lay the theoretical foundations for the parameters of hot air heating and dehumidification operations, as well as the placement of the hot air pipe. This paper aims to combine hot air dehumidification technology, for the removal of excess water from soil, and dredging soil pores, ultimately achieving the goal of improving soil steam disinfection efficiency.

Exploring a path of vegetation restoration best suited for a photovoltaic plant in the Hobq desert

To investigate the soil improvement effects of different vegetation restoration measures during the operation and maintenance of photovoltaic power plants in the Hobq Desert. This study determined the soil grain size composition and soil nutrient content of 0–5 cm under four vegetation restoration measures and within the mechanical sand barriers by laser diffraction techniques and chemical experiments. The results showed that: (1) Soil particle size composition in the study area is predominantly sandy, with 1.02%, 6.63%, 5.34% and 2.61% less sand in Leymus chinensis (YC), Glycyrrhiza uralensis (GC), Artemisia ordosica Krasch (YH) and Hedysarum scoparium (HB), respectively, compared to mechanical sand barriers (CK). Soil particle distributions of YC, GC, and HB showed better sorting and more concentrated patterns, and all four vegetation restoration measures had higher fractal dimensions than CK. (2) AN (Alkali-hydrolyzable Nitrogen) content performance: The content of YC, GC, and HB was significantly higher than that of YH and CK, AP (Available Phosphorus) content did not differ significantly between measures, AK (Available Potassium) content was higher than that of CK in all measures, with YC content being the highest and SOM content being the highest for GC. (3) Soil total nutrient is unstable across vegetation restoration measures. Overall, the performance showed that the three vegetation restoration measures, YC, GC, and HB, were more evident in the soil total nutrient content improvement. Each particle size characteristic parameter and soil nutrient response vegetation restoration measures ameliorate sandy soil in PV power plants during operation and maintenance. YC and GC have the most apparent effect on soil amelioration.

Characteristics of Soil Particle Sizes and Fractal Parameters under Different Plantation Types of Populus alba

Vegetation plays a leading role in restoring desert ecosystems and increasing productivity. In this study, we elucidate the improvement effects of different restoration areas of Populus alba on the soil particle distribution, sedimentation environment, and fractal characteristics. We selected the restoration areas of P. alba × Caragana korshinskii (YN), P. alba × Hedysarum leave (YY), and P. alba × Hedysarum scoparium (YH), which have a history of twenty-one years. We analyzed the soil nutrients, soil particle size, soil particle size parameters, soil fractal dimension (D) values, and soil multifractal parameters at soil depths of 0–80 cm. We found that the YN, YY, and YH significantly increased the soil nutrients and soil fine particles (p &lt; 0.05) and changed the deposition pattern of the soil particles in the sandy area. The YN, YY, and YH promote soil particle refinement and reduce the sorting performance of the soil particles. The vegetation promotes extremely positive-skewed and very leptokurtic soil particle distributions. The D values in the YN, YY, and YH restoration areas increased by 7.62%–27.94%, 7.36%–26.28%, and 7.10%–17.92%, respectively, relative to those of the LS. The construction of the different restoration areas of P. alba has made the distribution of the soil particles nonuniform. Compared with the YY and YH plantations, the distribution range of the soil particles in the YN plantation is wider, and the distribution heterogeneity is greater. In addition, we found that the fractal parameters are influenced by the soil physicochemical properties, the depositional environment, and vegetation factors. Therefore, we believe that D values and multifractal parameters are necessary as additional information for desert soil texture improvement. The results of this study provide a scientific and theoretical basis for the future revegetation of deserts.

A green approach to efficient soil decontamination using supercritical carbon dioxide and ethanol

As the need for global decommissioning and site remediation of aging and shut-down nuclear power plants continues to grow, it becomes increasingly crucial to efficiently treat contaminated soil while minimizing waste generation. This study explores an innovative soil decontamination approach that utilizes supercritical carbon dioxide (SCCO₂) as the primary solvent, along with ethanol as a co-solvent and specific additives, including a chelate ligand (catechol ligand) and a co-ligand (NEt₄PFOSA). The advantages of SCCO₂, such as its penetration and solubility, coupled with its ability to separate from radioactive waste, are harnessed in this research. The study demonstrates that the combination of SCCO₂, ethanol, and additives significantly enhances decontamination efficiency, particularly for cesium (Cs), strontium (Sr), and uranium (U) contamination. Results indicate that decontamination efficiency varies with soil particle size, with smaller particles presenting greater challenges. This study presents a promising eco-friendly soil decontamination technology using SCCO₂ containing ethanol and specific additives to efficiently reduce radioactive contamination in soil.

Unraveling soil filling and transport in fissures on karst slopes using multiple tracers

The fragile ecological environment and unique surface–subsurface geological duality of karst regions have led to complex processes and rates of underground soil loss, which is subject to much controversy. However, to ensure the ecological sustainability of karst areas, it is imperative to address this issue systematically using innovative study methods. With focuses on ten fissures and fivecross-sections in a typical karst area in southwestern China, this study applied unmanned aerial vehicles for field surveys and indoor modeling techniques to investigate the distribution density of fissures in typical karst areas, which is crucial for calculating underground soil loss. By measuring magnetic susceptibility, organic carbon content, and particle size of fissure soils, the primary sources of soil in the fissures were identified. Additionally, the rate of soil loss passing through karst fissure was calculated using 137Cs tracing and 14C dating techniques. Results indicate that (1) the proportion of fissure area per square kilometer of land is 1.59 %; (2) the soil in the fissures is mainly filled with the topsoil outside the fissures, and (3) the average rate of soil filling into the fissures is 16.13 t km−2 yr−1, account for only 5.8 % of the total soil erosion modulus. The study shows that soil filling into fissures is the main process of underground soil loss on karst slopes, and the rate of soil loss through fissures is very small. This study offers valuable insights into soil movement processes and quantification of soil erosion in karst regions, thus aiding in the preservation and sustainable management of these unique ecosystems.

Assessment of Saturated Hydraulic Conductivity with Using Soil Particle Size Distribution: A Comparative Study of Constant Head and Falling Head Methods

&lt;p&gt;The purpose of soil hydraulic conductivity is to retain soil water contents, and soil water pressure. In this study investigates two different methods to understand the soil hydraulic conductivity of loam and clay soils. The present research conducted a laboratory experiment to measure the saturated hydraulic conductivity (Ksat) using two different methods: the constant head and falling head methods. The constant head method utilized a soil column with a length of 8.5 cm, and three soil columns were occupied with various soil texture classes (%). The study results demonstrate that the classification of soil texture was predominantly sandy loam with porosity varying between 35%, 43%, and 50% within the clay soil category. Furthermore, the average value of Ksat for the soil samples using the constant head method was 0.00142 cm/sec, while the falling head method provides average values of 0.00123, 0.00172, and 0.00144 for sandy loam and 0.0000146 cm/sec for clay soil. It is concluded that the falling head method indicates greater accuracy, particularly evident in the concurrent analysis of three samples. This study suggested that determination of Ksat through laboratory method is suitable due to cost effectiveness and simplicity.&lt;/p&gt;

Electroosmosis and electrophoresis in soft clay under direct current electric field

The demand for innovative and cost-effective in-situ consolidation technologies in soft clay stimulated the effort to employ electrokinetic phenomena in soils under an electric field. This work explains the principles of electrophoresis and electroosmosis in soft clay under an electric field and discusses the implacations of these results for field implementation of the technique. The experimental work reported here was carried out to shed light on the principles by considering various influencing factors. The results show that there is a threshold current (about 15 mA) for electroosmosis and electrophoresis in soft clay. Below the threshold current, electrophoresis plays a major role and is accompanied by weak electroosmosis. The particle size, dry density, and boundary rise height of electrophoretic soil in anode chamber are mainly affected by soil moisture content, electrode in electrolyte length, and bottom of electrode to soil surface distance. The closer the soil moisture content is to the average value of the liquid limit and plastic limit, the denser the electrophoretic soil will be. Above the threshold current, almost only electroosmosis occurs. The greater the current, the greater the electroosmosis. In practical engineering application, electrodes are usually directly inserted into the soft clay. This results in the current usually being much greater than the threshold current, meaning the electrophoretic phenomenon in the soil can be negligible.

Geochemical background and geopedological interactions of selenium in soils from Piauí state, Northeastern Brazil

ABSTRACT Although Selenium (Se) plays a role as a micronutrient for humans through vegetable consumption, it is also recognized as toxic when present in excessive quantities. Therefore, quantifying Se contents in soils can prevent diseases influenced by crop Se deficiency or excess. We aimed to measure background contents, establish quality reference values (QRV) for Se in soils from two Brazilian biomes (Cerrado and Caatinga), and assess how geopedological factors affect Se content and spatial variability. Two hundred and eight composite topsoil samples were analyzed for Se content, covering an area of about 251,578 km². Sampling sites were under the minimal anthropogenic influence to represent Se background contents. Selenium contents were determined by hydride generation atomic absorption spectroscopy (HGAAS), ranging from 0.002 to 4.78 mg kg -1 . Most soils had contents below the world average of 0.44 mg kg -1 but still above the soil content that causes human Se deficiency (0.125 mg kg -1 ). Soils from Cerrado and Caatinga biomes showed similar average contents of Se, 0.41 and 0.47 mg kg -1 , respectively. Organic carbon content and soil particle size (clay fraction) were the main factors governing Se content in the soils. Our results contribute to understanding the Se content and spatial distribution in tropical soils and the factors governing them. They also provide a tool for agriculture and environmental decision-makers to plan public policies regarding the management of Se levels in these and similar tropical soils in the world.

The state-of-the-art use of X-Ray and infrared for evaluating soil attributes

Ensuring food supply to society is crucial. Therefore, understanding the specificities of soils and climates in different countries becomes indispensable. Assessing and quantifying soil attributes play a fundamental role in the sustainable management of natural resources, promoting increased crop productivity and soil and biodiversity resilience. This review aims to analyze the main instrumental methods (NIRS, XRF, XRD, and FTIR), exploring their mode of action, challenges in implementing these methods, and emerging trends for sustainable soil management. Scientific articles indexed in two databases, Web of Science and Scopus, were searched using the keywords "soil attributes" and NIRS or "near-infrared spectroscopy" or XRF or "X-ray fluorescence spectrometry" or DRX or "X-ray diffraction" or FTIR or "Fourier-transform infrared spectroscopy", without restrictions in the field of research. Instrumental methods, when properly calibrated, provide rapid, accurate, and non-destructive information crucial for making agricultural decisions and sustainable soil management. However, challenges such as high equipment costs, complexity of analyses, and calibration dependence are faced. Nevertheless, current trends indicate promising prospects, with the pursuit of technological innovations and the integration of artificial intelligence and machine learning to simplify complex data analysis and mitigate the challenges faced. Therefore, we conclude that the instrumental methods discussed, such as NIRS, XRF, DRX, and FTIR, stand out as an indispensable set of tools in the analysis of soil particle size, chemical, and mineralogical properties, emerging as an innovative and essential response to contemporary challenges related to food security, environmental sustainability, and efficient management of natural resources.

Mechanical behaviour of saline soil under triaxial compression

Soluble salts in soil cause changes in soil behaviour, the extent of which varies depending on salinity levels. Salt-induced soil deformation leads to various engineering problems. Na2SO4 is among the most widespread and influential salts. This study focuses on Na2SO4 and investigates its effects on soil strength via a series of triaxial tests performed in the laboratory. The study examines different levels of salt and moisture content. Additionally, the study investigated the soil mechanism through its meso and micro structure. The research indicates that the impact of salinity on soil strength is modulated by moisture content. In situations where moisture content is low, salinity markedly affects the soil strength; however, as moisture content increases, the impact of salinity on soil strength decreases. Salinity alters the shape, size and orientation of soil particles, resulting in modifications to the interparticle and charge forces. This ultimately leads to changes in the soil strength parameters.

Effects of hillslope aspect on erosion rate of alpine meadows in the Three-River Headwater Region, China

Soil erosion causes serious grassland degradation in the Three-River Headwater Region (TRHR) of the Qinghai-Tibet Plateau. Identifying source areas of erosion is important, including understanding the influences of hillslope aspect on soil erosion. However, the effect of hillslope aspect on soil erosion is a much-debated process, wherein contrasting results were previously reported. We hypothesized that aspect-induced differences in environmental variables will be related to differences in erosion magnitude and spatial pattern, and that these differences will impact soil physiochemical characteristics as well. To test this hypothesis, soil samples were collected at conjoined south- and north-facing hillslopes along elevational profiles in a small watershed in Yushu County, with measurements of soil water content (SWC), soil organic carbon (SOC), soil organic matter (SOM), soil particle size distribution, soil total nitrogen (STN) and phosphorus (STP). Soil erosion rate was estimated using 137Cs technology. The results showed that soil erosion rates of the two hillslopes ranged from 0.073 to 10.83 t ha-1 yr-1, and were 3 times greater on the south-facing hillslope. Soil water content ranged from 7.6% to 76.8% on the two hillslopes with lower values on the south-facing hillslope due to the greater solar radiation. By Spearman correlation analysis and path analysis, we concluded that lower soil water content on the south-facing hillslope restricts vegetation growth, and hence resulting in greater soil erosion under the case where vegetation growth is dominantly controlled by water availability. Greater soil erosion on the south-facing hillslope caused greater surficial accumulation of coarser materials and greater loss of soil nutrients, which are expected to complicate the hydrological erosion process. Moreover, the downslope increased soil erosion rate should be fully considered in conservation practices. These results will improve our understanding of the interaction and feedback mechanisms between soil characteristics, vegetation function, and soil erosion in the TRHR.

Determination of soil organic carbon content of agricultural soils for proper soil management in Matazu and Musawa, Katsina State, Nigeria

Soil organic carbon is a significant parameter for estimating the global carbon cycle, which makes great sense in soil management and future climate scenario prediction. This work uses 30 heterogeneous soil samples from agricultural and non-agricultural farmlands and soil erosion areas in Matazu and Musawa LGAs to determine soil organic carbon content at the field level in Matazu and Musawa Local Government Areas, Katsina State, Nigeria. Soil samples were meticulously collected from the 0-10cm depth using a hand auger. These samples were obtained from three distinct clusters: agricultural and non-agricultural farmlands and soil erosion areas. The selection of sample locations considered the varied soil types, historical land use, and management practices. Ten soil samples were randomly gathered within each cluster, ensuring a representative and diverse set of samples for analysis. The Warlkey and Black and Hydrometer methods were used to determine the soils' organic carbon contents and particle size distribution, respectively. The data obtained were analyzed using SPSS 23 software. Two-sample t-tests and analysis of variance (ANOVA) were carried out. The soil organic carbon contents of the studied area were 0.29 ± 0.16 g/kg (0.16 – 0.34 g/kg) and 0.28 ± 0.14 g/kg (0.14 - 0.36 g/kg) for Matazu and Musawa, respectively. The study concludes that the organic carbon content helps improve sustainable agricultural productivity due to proper and efficient land use management practices.