Soil Properties Research Articles

Forest ecosystem services of water-related filtration and regulation, a multi-source assessment and economic valuation in Mangla watershed

ABSTRACT Watershed forests offer crucial ecosystem services for hydrological systems. This study provides comprehensive insights into sediment retention within the Mangla watershed. We analyzed spatial layers from Sentinel-2 imagery, land use data, weather, soil properties, and terrain characteristics to identify soil erosion and sediment delivery hotspots. Using the Integrated Valuation of Environmental Services and Tradeoffs-sediment delivery ratio (InVEST-SDR) model, we quantified sediment exported to the downstream Mangla Dam. The InVEST-sediment retention (InVEST-SR) model estimated the sediment retention capacity of various land cover types. Our findings show that forests retained 20,300.70 tons of sediment in 2017 and 29,887.60 tons in 2021, making them the primary source of sediment retention. The economic value of this ecosystem service was approximately USD 2.59 trillion for 973,168.51 ha of forest in 2017 and USD 4.02 trillion for 1,023,927 ha in 2021. Understanding the dynamics and economic value of this forest ecosystem service at a large watershed scale provides essential insights for decision-making and conservation efforts aimed at protecting water resources and ecological integrity.

Soil Physicochemical Properties and Carbon Storage Reserve Distribution Characteristics of Plantation Restoration in a Coal Mining Area

The Bulianta Coal Mine is among the problematic coal mining areas in China that is still creating environmental damage, especially associated with soil destruction. Therefore, a scientific investigation was conducted to establish a scientific basis for evaluating the impact of planted forest on soil physical and chemical properties, as well as the ecological benefits following 15 years of vegetation restoration in the area. The soil physicochemical characteristics and distribution of organic carbon storage in the 0–80 cm layer soils of Pinus sylvestris forests, Prunus sibirica forests, and Hippophae rhamnoides forests restored after 5, 10, and 15 years were investigated. The immersion method was used to determine soil porosity and density followed by the determination of soil indicators, and a statistical ANOVA test was applied to examine the differential effects of different vegetation types and restoration years on soil properties. The results clearly demonstrated the following: (1) The recovery of vegetation was achieved after a period of 15 years, with the average bulk density of the 0–80 cm soil layer as follows: P. sylvestris forest (1.513 g·cm−3) > P. sibirica forest (1.272 g·cm−3) > H. rhamnoides forest (1.224 g·cm−3), and the differences among different forest types were statistically significant (p < 0.05). (2) In planted forests, soil nutrients were predominantly concentrated in the 0–20 cm layer, while soil carbon storage exhibited a decline with an increasing soil depth. (3) The soil carbon storage across the three forest types was as follows: P. sylvestris forest (45.42 t·hm−2) > P. sibirica forest (44.56 t·hm−2) > H. rhamnoides forest (41.87 t·hm−2). In summary, during the ecological vegetation restoration process in the Bulianta Core Mine, both P. sylvestris forest and P. sibirica forest exhibit superior carbon storage capacities compared to H. rhamnoides forest, as well as more effective soil improvement outcomes.

Irrigation of rangeland soils with coal seam water - A lysimeter study on soil physico-chemical properties

Groundwater extracted from coal seams may be a resource for irrigation of land in areas with low rainfall, but the effect of this water on soil properties needs to be established. A lysimeter study was conducted using intact soil cores (0.75 m diameter, 1.4 m deep) of four different soil types (Sodic Vertisol, Calcic Solonetz, Haplic Solonetz and Xanthic Lixisol) from southern Queensland, Australia, to study changes in soil physical and chemical properties under accelerated rates of irrigation with coal seam (CS) water (electrical conductivity (ECw) of 3 dS/m, pH of 8.8, and a sodium adsorption ratio (SAR) of 100). Cores were also alternately irrigated with deionised water to simulate rainfall, and either lucerne (Medicago sativa L) or Rhodes grass (Chloris gayana Kunth.) where grown in the lysimeters. The soil surface was treated with stoichiometric rates of elemental sulfur (1.4 t/ha) and gypsum (2.5 t/ha) prior to every 450 mm CS water irrigation to minimise changes in SAR and pH. Three of the soils (Vertisol, both Solonetz) had low leaching fractions (≤ 0.1 %) due to their clay texture and were initially saline in the subsoil (ECse 1.4–4.4 dS/m). Irrigation with CS water resulted in a gradual increase in salt content (EC) and SAR throughout the soil profile, but pH was not increased due to surface-applied elemental sulfur. The Lixisol had a higher hydraulic conductivity and leaching fraction (6.7 %) due to is loamy texture – in this soil, accumulated salts could be leached and no increase in salinity or pH were measured. Despite an increase in SAR for this loamy soil, no structural degradation was observed, and it could be sustainably irrigated with up to 3200 mm CS water (with cumulative irrigation volume of 5400 mm). Hence, leaching fractions rather than soil chemistry are good indicators to identify soils suitable for irrigation with CS water that is saline, alkaline, and sodic.

Exploring the effect of fertilizer application on yield and decoding CO2 flux under flooded paddy conditions towards sustainable agriculture

The impact of organic and inorganic nutrient management on the emission of carbon dioxide (CO2), soil properties such as available nutrients, microbial population and soil organic carbon (SOC) were investigated in paddy (Oryza sativa L.) field (at 8o 46’ N Latitude and 77o 42?’ E Longitude) under flooded condition during late pishanam season in 2023-2024. The treatments were designed to observe the effects of applying fertilizer based on the soil test crop response (100 % STCR-based NPK) that had been modified by organic amendments, which include absolute control (unfertilized), inorganic fertilizers, sole application of organic amendments (Farm yard manure, Green leaf manure, Vermicompost and Poultry manure) and combined these organic amendments with inorganic fertilizers. The main objective of this study is to understand the intricate relationship between fertilizers and carbon flux in paddy soils, which is crucial for developing sustainable agricultural practices that minimize environmental harm while ensuring food security. The observation of the experimental field study reported that the combined application of poultry manure at the rate of 5 tonnes per hectare with 100% STCR-based inorganic fertilizer recorded maximum yield and yield attributes. The treatment combination of poultry manure + inorganic fertilizer enhanced in sequestrating the soil organic carbon (0.67%) resulted in higher grain yield (5972 kg ha-1) and also observed that this combination will limit the emission of CO2 to the atmosphere. Therefore, it could be a better choice for carbon storage and higher productivity in a sustainable rice cropping system.

Boron availability and fertilizer response of maize in soils from sub‐Saharan Africa

AbstractBackground and aimsLow boron (B) availability is associated with strongly weathered, coarse‐textured, and low organic matter soils, widespread in sub‐Saharan Africa (SSA). It is unknown to what extent B fertilization can increase maize yields in SSA. This study aims to understand the soil properties controlling B availability to field‐grown maize.MethodsBoron fertilizer omission trials with maize were executed at 15 sites in Kenya, Zambia, and Zimbabwe. Yield, B uptake, and soil parameters potentially relevant for B availability, including extractable soil B (hot water, 0.01 M CaCl2, and 0.43 M HNO3), were determined.ResultsSoil B pools were strongly intercorrelated and were positively correlated with organic carbon, suggesting the relevance of organic matter for soil B availability. Soil parameters described limited variation in B uptake and the yield response to B fertilization. Boron fertilization did not increase yields in any of the 15 sites but increased uptake in 11 sites. Yields were reduced through B fertilization in five sites, likely because B application induced toxicity. No clear critical soil or plant B concentrations indicating deficiency could be derived, but positive yield responses to B fertilization were absent with hot water B levels above 0.69 mg kg−1.ConclusionAssessing B fertilizer needs in maize grown in tropical soils based on soil or plant tissue concentrations remains challenging. Improving soil organic matter status could potentially alleviate B deficiency in crops when present. Recommendations are given to overcome the identified challenges associated with studying B availability in tropical soils.

The Comprehensive Effects of Biochar Amendments on Soil Organic Carbon Accumulation, Soil Acidification Amelioration and Heavy Metal Availability in the Soil–Rice System

In recent years, biochar (BC) and biochar-based soil amendments (CSAs) have been widely used in agriculture and the environment. In the present study, a two-rice-season field study was conducted to explore the comprehensive effects of applying BC (1%) and CSA (0.5% and 1%) on soil organic carbon accumulation, soil acidification amelioration and heavy metal availability in a soil–rice system. The results show that soil pH was increased by 0.5–1.7 units and 0.3–1.0 units, respectively, in the early rice season and late rice season treated by the amendments compared with CK. Soil organic contents were increased by 18–30% in the early rice season and by 15–25% in the late rice season in the amended treatments. In addition, soil available phosphorus contents were largely increased as a result of BC and CSA addition. Soil CaCl2 extractable heavy metals (Cd, Ni, Cu and Zn) were simultaneously decreased by BC or CSA amendments. In addition, Cd contents in early rice grain and late rice grain were significantly reduced by 25–48% and 52–83% in amended treatments, while Zn contents were generally not affected. The uptake of Cu and Ni was also decreased by BC and CSA. This study demonstrates that biochar application alone or combinates with inorganic amendments (limestone, sepiolite and potassium dihydrogen phosphate) can significantly improve soil properties and nutrient content and decrease the heavy metal (especially for Cd and Ni) uptake and accumulation from soil to rice grain, where the combination application is more effective.

Multi-Sensor Soil Probe and Machine Learning Modeling for Predicting Soil Properties.

We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe was engineered that contains seven sensors, each of a distinct modality, including sleeve friction, tip force, dielectric permittivity, electrical resistivity, soil imagery, acoustics, and visible and near-infrared spectroscopy. The DSC System integrates the DSC Probe, DSC software (v2023.10), and deployment equipment components to sense soil characteristics at a high vertical spatial resolution (mm scale) along in situ soil profiles up to a depth of 120 cm in about 60 s. The DSC Probe in situ proximal data are harmonized into a data cube providing vertical high-density knowledge associated with physical-chemical-biological soil conditions. In contrast, conventional ex situ soil samples derived from soil cores, soil pits, or surface samples analyzed using laboratory and other methods are bound by a substantially coarser spatial resolution and multiple compounding errors. Our objective was to investigate the effects of the mismatched scale between high-resolution in situ proximal sensor data and coarser-resolution ex situ soil laboratory measurements to develop soil prediction models. Our study was conducted in central California soil in almond orchards. We collected DSC sensor data and spatially co-located soil cores that were sliced into narrow layers for laboratory-based soil measurements. Partial Least Squares Regression (PLSR) cross-validation was used to compare the results of testing four data integration methods. Method A reduced the high-resolution sensor data to discrete values paired with layer-based soil laboratory measurements. Method B used stochastic distributions of sensor data paired with layer-based soil laboratory measurements. Method C allocated the same soil analytical data to each one of the high-resolution multi-sensor data within a soil layer. Method D linked the high-density multi-sensor soil data directly to crop responses (crop performance and behavior metrics), bypassing costly laboratory soil analysis. Overall, the soil models derived from Method C outperformed Methods A and B. Soil predictions derived using Method D were the most cost-effective for directly assessing soil-crop relationships, making this method well suited for industrial-scale precision agriculture applications.

Evaluating the impacts of area closure on soil properties in south central highland of Ethiopia

Soil degradation affects its quality and productivity of the land. To control soil degradation, various soil and water conservation (SWC) measures, including area closure are implemented. Understanding the impacts of SWC measures could support planning and implementation of land management practices. This study aimed to investigate impacts of area closure on soil properties in south central highland of Ethiopia. To acquire the necessary data, we conducted interviews with 80 households. Furthermore, nine years old area closure with physical soil and water conservation (AC-SWC), open grazing with physical SWC (OG-SWC), and open grazing without physical SWC (OG) were identified and each divided into upper, middle, and lower slope positions. In each slope position, 3 sample plots were established at 25–50 m intervals. A total of 27 composite samples and other 27 core samples for bulk density (3 treatments∗3 slope position∗3 replications) were collected and analyzed for soil properties. The data were analyzed using descriptive statistics and one-way ANOVA. The results showed that about 98 % of the respondents perceived that area closure would be an effective way to restore degraded land. Majority of the farmers (86 %) believed that area closure could reduce soil erosion and replenish soil fertility and thus, is beneficial in improving land productivity. Soil test results revealed that AC-SWC had significantly greater (P < 0.05) clay fractions, pH, available potassium, and available phosphorus than OG-SWC and OG. Variations of soil organic carbon (SOC) and total nitrogen (TN) were more pronounced. The SOC in AC-SWC was 83 % and 314 % greater than OG-SWC and OG, respectively. In the AC-SWC, TN was three and seven times higher than that of OG-SWC and OG, respectively. This could be due to vegetation restoration that reduces erosion, and enhances organic matter, moisture, and nutrient. The SOC, TN, pH, available potassium, and clay were significantly greater (P < 0.05) at lower slope position than upper in all forms of land management, which could be due to deposition at downslope. About 12 % and 11 % variations of clay fractions and SOC were, respectively, observed in between upper and lower slope positions at AC-SWC, but they varied by 25 % and 57 %, respectively, in OG. These imply area closure has had a beneficial effect on soil properties even on sloping land. AC-SWC is an important option to integrate in land management for rehabilitation of degraded soil.

Environment, plant genetics, and their interaction shape important aspects of sunflower rhizosphere microbial communities.

Associations with soil microorganisms are crucial for plants' overall health and functioning. While much work has been done to understand drivers of rhizosphere microbiome structure and function, the relative importance of geography, climate, soil properties, and plant genetics remains unclear, as results have been mixed and comprehensive studies across many sites and genotypes are limited. Rhizosphere microbiomes are crucial for crop resistance to pathogens, stress tolerance, nutrient availability, and ultimately yield. Here, we quantify the relative roles of plant genotype, environment, and their interaction in shaping soil rhizosphere communities, using 16S and ITS gene sequencing of rhizosphere soils from 10 genotypes of cultivated sunflower (Helianthus annuus) at 15 sites across the Great Plains of the United States. While site generally outweighed genotype overall in terms of effects on archaeal, bacterial, and fungal richness, community composition, and taxa relative abundances, there was also a significant interaction such that genotype exerted a significant influence on archaeal, bacterial, and fungal microbiomes in certain sites. Site effects were attributed to a combination of spatial distance and differences in climate and soil properties. Microbial taxa that were previously associated with resistance to the fungal necrotrophic pathogen Sclerotinia were present in most sites but differed significantly in relative abundance across sites. Our results have implications for plant breeding and agronomic microbiome manipulations for agricultural improvement across different geographic regions.IMPORTANCEDespite the importance of plant breeding in agriculture, we still have a limited understanding of how plant genetic variation shapes soil microbiome composition across broad geographic regions. Using 15 sites across the Great Plains of North America, we show that cultivated sunflower rhizosphere archaeal, bacterial, and fungal communities are driven primarily by site soil and climatic differences, but genotype can interact with site to influence the composition, especially in warmer and drier sites with lower overall microbial richness. We also show that all taxa that were previously found to be associated with resistance to the fungal pathogen Sclerotinia sclerotiorum were widespread but significantly affected by site, while a subset was also significantly affected by genotype. Our results contribute to a broader understanding of rhizosphere archaeal, bacterial, and fungal community assembly and provide foundational knowledge for plant breeding efforts and potential future microbiome manipulations in agriculture.

Mapping Tropical Dry Forest Gradients in an Andean Region with High Environmental Variability

Tropical Dry Forest (TDF) is one of the most threatened terrestrial environments in the neotropics because of high rates of conversion to agriculture. Despite this high degree of threat, many regions lack detailed maps on the actual extent and boundaries of their TDFs, which is fundamental information for their conservation. We developed a methodological framework to map TDF at 10 m in regions where they grade into other forest types. The approach uses climate variables, altitude, soil properties, and remote sensing data (multispectral and SAR − Synthetic Aperture Radar-SAR imagery) to predict TDF in the Department of Caldas, Colombia. Accuracy of the resulting map was confirmed with field observations (Overall Accuracy = 0.88, Kappa = 0.73, Area Under the Receiver Operating Characteristics Curve = 0.87, and True Skill Statistic = 0.73). We estimated ∼ 54 km2 of TDF, which represents 9.2 % of its potential area of occurrence in the study area. TDF gradually transitions to Tropical Moist Forest (TMF) from two main low altitude river valleys to higher altitudes in the Andes Mountains. With modification, our methods could be applied for mapping TDF in other tropical regions.

Longitudinal distributions of CO2-fixing bacteria in forest soils and their potential associations with soil multifunctionality

Autotrophic microorganisms can fix carbon dioxide (CO2) into organic carbon (C), potentially offering a natural mechanism to mitigate global climate change. Forest soils, recognized as vast and critical C repositories with significant microbial CO2 fixation rates, remain understudied, particularly regarding the spatial variations of autotrophic bacteria and their relationship to soil functions in arid regions. In this study, we systematically investigated soil multifunctionality, along with the spatial distribution of autotrophic bacterial communities identified by the RubisCO cbbL and cbbM genes, and the driving factors across a longitudinal gradient in the Loess Plateau forest soils. The investigation spanned an ∼850 km west-east transect with precipitation below 600 mm. The alpha diversity of cbbL-containing bacteria, as measured by the Chao1 index, was correlated with climatic variables such as precipitation and elevation instead of local soil characteristics. In contrast, the alpha diversity of cbbM-containing bacteria was associated with soil properties. The community composition of autotrophic bacteria, based on cbbL and cbbM genes, showed greater similarity in soils from the eastern Loess Plateau and was distinct from those in the western region. The cbbL- and cbbM-containing generalist taxa were subject to differential selection and promotion between the eastern and western regions. Temperature, soil pH and spatial variables were key drivers influencing the community composition of cbbL- and cbbM-containing bacteria. The diversity and communities of soil autotrophic bacteria significantly affected soil multifunctionality. The study demonstrates that soil autotrophic bacteria in forest soils are intricately connected to climatic conditions, soil pH and spatial factors, significantly impacting soil multifunctionality. These insights provide evidence that can be instrumental in predicting and potentially enhancing the functional capacity of forest ecosystems in the Loess Plateau.

The Response of Inorganic and Organic Fertilizers on Growth, Yield and Quality of Cluster Bean [Cyamopsis tetragonoloba (L.) Taub.] in the Village Chikkenahalli of Challakere Taluk, Chitraduraga District

Cluster bean is one of the significant yet underutilized leguminous vegetables belonging to family fabaceae. It is known by various names across the country such as gaur, chavli kaayi, gori kaayi, khutt, govar, and kothavare. A field experiment on cluster bean was carried out during the summer season of the year 2024 at the farm of P. L. Dodda Rangegowda in Chikkenahalli of Challakere taluk, Chitradurga district, Karnataka. The primary objectives of the study are to examine the effects of organic and inorganic fertilizers on the productivity and growth characteristics of cluster bean; to identify the advantages and disadvantages of these fertilizers in relation to productivity, soil fertility, and environment and further to review the effects of mixed organic and inorganic fertilizers on yield and soil fertility. The experiment was laid out in a randomized block design with four replications and five treatments which comprised of 100 percent organic (FYM and chicken manure), 100 percent inorganic (NPK), 50 percent organic + 50 percent inorganic, 100 percent organic + jeevamruta and control. The results revealed that, treatment T3 outperformed the others, showing the highest values for plant height, number of branches per plant, days to first flowering, days to first vegetable harvest, pod length, pod width, yield per plant, yield per plot, and yield per hectare, while the control recorded the lowest values. Soil properties such as pH, EC, SOC and NPK levels improved when combination of organic and inorganic fertilizers were applied together. Based on these results, it can be concluded that, the application of organic manures, along with chemical fertilizers, positively enhanced the vegetative growth, reproductive growth, yield, quality of cluster bean and soil parameters.

Soil Properties Regulate Soil Microbial Communities During Forest Succession in a Karst Region of Southwest China

Natural vegetation restoration has emerged as an effective and rapid approach for ecological restoration in fragile areas. However, the response of soil microorganisms to natural succession remains unclear. To address this, we utilized high-throughput sequencing methods to assess the dynamics of soil bacterial and fungal communities during forest succession (shrubland, secondary forest, and primary forest) in a karst region of Southwest China. Our study revealed that bacterial α-diversity was significantly higher in secondary forest compared to both shrubland and primary forest. Intriguingly, the soil bacterial community in primary forest exhibited a closer resemblance to that in shrubland yet diverged from the community in secondary forest. Conversely, the soil fungal community underwent notable variations across the different forest stages. Furthermore, analysis of the microbial co-occurrence network revealed that, within these karst forests, the relationships among soil fungi were characterized by fewer but stronger interactions compared to those among bacteria. Additionally, soil properties (including pH, soil organic carbon, total nitrogen, moisture, and available potassium), soil microbial biomass (specifically phosphorus and nitrogen), and plant diversity were the drivers of soil bacterial community dynamics. Notably, soil pH accounted for the majority of the variations observed in the soil fungal community during karst forest succession. Our findings provide valuable insights that can inform the formulation of strategies for ecological restoration and biodiversity conservation in karst regions, particularly from a microbial perspective.

Field versus laboratory measurements of PFAS sorption by soils and sediments

Sorption by soils and sediments is an important process that influences the distribution, transport, and fate of per and polyfluoroalkyl substances (PFAS) in the environment. Many laboratory studies have been conducted to quantify magnitudes of PFAS sorption as a function of the properties of the PFAS, solutions, and porous media. A critical question is how representative are laboratory-measured sorption magnitudes for field applications. To address this question, log Koc data were compiled from the literature for a range of PFAS of different chain lengths and functional groups. The aggregated field-based data consisted of two types, in-situ measurements comprising paired soil/sediment and water samples and ex-situ measurements obtained from laboratory desorption experiments employing field-contaminated media. These two sets of field-based measurements were compared to a comprehensive data set of standard laboratory batch-type measurements. The compiled data sets represent an extremely wide range of soil and sediment properties. One important novel outcome is the observation that the enhanced sorption of short-chain PFAS observed in several prior laboratory studies is also observed for the field data. This differential enhanced sorption should be accounted for in site investigations and modeling studies. Another relevant outcome is the observation of consistency between measurements obtained with standard batch adsorption experiments and those from desorption studies employing either field-contaminated or artificially-contaminated media. The mean log Koc values determined for the in-situ measured field data were generally larger than the mean laboratory-determined values, particularly for the short-chain PFAS. Notably, however, values for subsets of the laboratory data representing measurements for lower aqueous concentrations or for soils with low organic-carbon contents (<1 %) compared well to the in-situ field data. Measurements compiled for anionic-polyfluoroalkyl, neutral, and cationic PFAS compared well to those for PFCAs and PFSAs. Overall, the results indicate that the laboratory measurements of PFAS sorption were generally representative of the field-derived magnitudes when compared on a consistent basis.

Detection of morphometric indicators of the soil surface of a grape plantation using spectral bands of satellite images

Introduction. Soils play an important role in the approximately 30-year period of operation of a grape planting, influencing plant growth, their yield and the quality of the grapes. In this study, the morphometric parameters of the surface soil layer of a grape plantation were studied using spectral channels of satellite images.Methodology. The methodology included the use of a “random forest” algorithm to classify soil cover using spectral channels and normalized satellite image indices and analyze the main physicochemical properties of soils. Accuracy was assessed using RMSD and confidence intervals calculated via bootstrapping.Results. The study revealed significant differences in the spectral reflectivity of different site options, which was due to carbonate content, humidity levels and the amount of humus. Areas with high carbonate and moisture content showed higher standard deviation values in the spectral channels. Studying the spectral characteristics of the soil surface makes it possible to effectively classify different areas based on remote sensing data. Analysis of combinations of spectral channels revealed an optimal set of three channels (B12, B11, B8A) with a minimum standard deviation when classifying an image into six soil variants of areas. For classification, a composition of five normalized indices can also be used, but in this case the calculation time increases significantly with a larger standard deviation and a larger confidence interval range. Using machine learning, six distinct soil surface types were segmented, demonstrating the complexity of the field›s soil mosaic. These results are critical for improving vineyard management and productivity

Effectiveness of Zeolite [LTA] amendment in improving the growth of cherry tomato (Solanum lycopersicum) and its physicochemical properties of soil

Effectiveness of Zeolite [LTA] amendment in improving the growth of cherry tomato (Solanum lycopersicum) and its physicochemical properties of soil

Using Biochar to Improve Soil Fertility and Productivity of Drought-Tolerant Sweet Potatoes in Thanh Hoa Coastal Sandy Soil

The coastal area of Thanh Hoa province has a large proportion of sandy soil and is suffering negative impacts from climate change that affect crop productivity. The aim of this study is to investigate the use of biochar to improve the soil fertility and productivity of drought-tolerant sweet potatoes. The effect of biochar contents on the productivity of three sweet potatoes VC 04-24, KL C3, and VC 68-2 in the coastal sandy soil area of Thanh Hoa province was examined. The results indicated that the yield of sweet potatoes was the highest when applying five tons of biochar per hectare, equivalent to using 10 tons of manure. With the same biochar content, the productivity and other factors related to the product quality of these sweet potatoes such as the number of tubers per plant and the average mass of tuber were the highest. In detail, the estimated commercial productivity of VC 04-24, KL C3, and VC 68-2 were 25.46, 24.92, and 21.76 ton/ha, respectively. With the least significant difference at the probability of 0.05% (LSD0.05), the VC 04-24 and KL C3 showed high productivity. The economic efficiency of the sweet potatoes-growing model at Hai An commune, Tinh Gia district, Thanh Hoa province showed that the productivity of the model was 24 tons/ha, higher than the actual productivity of the control model (20.2 ton/ha). The productivity and the economic efficiency of the model were 18.8% and 31.38% higher than those of the control model, respectively. In addition, the test results showed that using 5-6 ton/hectare of biochar can improve the physical and chemical properties of soils.

Validation of a new road and contact model for vehicle–soft soil terrain interaction through an elaborate modelling of the FED-Alpha vehicle

Employing multibody dynamic simulations with semi-empirical tyre models is widely recognised as a cost-effective approach. A recent development introduces a novel road and tyre–soil contact model that is not only swift and memory-efficient but also addresses limitations in classical semi-empirical models. This study conducts a thorough validation of the new road and contact model by creating a detailed multibody model of the four-wheeled vehicle, Fuel Efficiency Demonstrator – Alpha, integral to NATO’s Next-Generation reference mobility model. The comprehensive model encompasses the chassis, suspension, tyres, engine, transmission and various other components. Through simulations of various driving scenarios, accounting for complex terrain geometries, spatially varying soil properties and multi-pass phenomena, the model’s performance is evaluated. The simulation results are compared with physical measurements, providing a detailed assessment of the tyre–soil model’s predictive accuracy for wheeled vehicle mobility on deformable terrains.

Levee Soil Stratification Based on PAM Cluster Analysis of Measured Soil Samples from Multiple Probe Drilling Sites

Accurate soil stratification is crucial for levee safety evaluation, yet limited field sampling often hinders comprehensive analysis. This study applies the Partitioning Around Medoids (PAM, also known as K-Medoids) clustering approach for levee soil stratification using data from multiple probe drilling sites. Focusing on a Yellow River levee section in China as a study case, the PAM clustering approach effectively identifies its distinct soil types and reconstructs its soil stratification by analyzing key soil properties relevant to levee seepage and stability characteristics, including coefficient of permeability, angle of internal friction, and cohesion. The resulting soil stratification, when applied to seepage and stability analyses of the levee section, yields relatively high safety factors, indicating low failure risks under design flood conditions. These analytical results align with recent monitoring records, validating the effectiveness of the approach. A sensitivity analysis on the number of clusters, the key parameter in the PAM clustering approach, demonstrates the typical existence of an optimal value balancing computational accuracy and practical interpretability. A comparison with a hierarchical clustering approach further confirms the robustness of the PAM clustering approach. This study contributes to improving levee soil stratification methodology and enhancing levee safety evaluation, particularly when dealing with limited and spatially distributed sampling data.

Effects of Soil Properties on the Accumulation and Bioavailability of Copper in the Orange Growing Soil in Cao Phong, Hoa Binh

This study focuses on investigating the crucial influence of some soil properties on the adsorption capacity and fractions of Cu in the citrus-growing soil in Cao Phong district, Hoa Binh province. Batch experiments were conducted by adding 0, 100, 500, and 1000 mgCu/L to soil samples with different characteristics. In the 100 mgCu/L added experiment, we found the highest Cu adsorption rate (&gt; 93.76%) in soil samples with loamy texture, high pHKCl, %OC, and low nutrients. Conversely, the lowest Cu adsorption rates (78.32-79.23%) were observed in soil samples with lower pH, and higher %OC and nutrient availability. Noting that the total adsorbed Cu has a negative correlation with the amount of Cu added to the soil, gradually decreasing from (78.32-95.67%) to (26.67-34.19%) and the lowest (22.48-28.56%) in soil samples with the added levels of 100, 500, and 1000 mgCu/L, respectively. In soil samples with total Cu &gt; 200 mg/kg, pHKCl 4.79-5.32, and OC 1.34-2.06%, the bioavailable Cu ranged from 2.29-4.29 mg/kg, which is safe for the soil environment and ecosystem, and sufficient as a micronutrient for citrus plants. It is necessary to find the best solutions for managing Cu-polluted soils.