Search Results (4,414)

In this paper, we presents a case study involving the implementation experience and a methodological framework through a comprehensive comparative analysis of the YOLOX and YOLOv12 object detection models for agricultural automation systems deployed in the Jetson AGX Orin edge computing platform. We examined the architectural differences between the models and their impact on detection capabilities in data-imbalanced potato-harvesting environments. Both models were trained on identical datasets with images capturing potatoes, soil clods, and stones, and their performances were evaluated through 30 independent trials under controlled conditions. Statistical analysis confirmed that YOLOX achieved a significantly higher throughput (107 vs. 45 FPS, p < 0.01) and superior energy efficiency (0.58 vs. 0.75 J/frame) than YOLOv12, meeting real-time processing requirements for agricultural automation. Although both models achieved an equivalent overall detection accuracy (F1-score, 0.97), YOLOv12 demonstrated specialized capabilities for challenging classes, achieving 42% higher recall for underrepresented soil clod objects (0.725 vs. 0.512, p < 0.01) and superior precision for small objects (0–3000 pixels). Architectural analysis identified a YOLOv12 residual efficient layer aggregation network backbone and area attention mechanism as key enablers of balanced precision–recall characteristics, which were particularly valuable for addressing agricultural data imbalance. However, NVIDIA Nsight profiling revealed implementation inefficiencies in the YOLOv12 multiprocess architecture, which prevented the theoretical advantages from being fully realized in edge computing environments. These findings provide empirically grounded guidelines for model selection in agricultural automation systems, highlighting the critical interplay between architectural design, implementation efficiency, and application-specific requirements. Full article

Loess, a typical soil widely distributed in China, exhibits engineering properties that are highly sensitive to environmental changes, leading to increased erosion and the development of surface cracks. This article examines the influence of initial moisture content, dry density, and thickness on crack formation in compacted loess subjected to wet–dry cycles, using both laboratory experiments and numerical simulation analysis. It quantitatively analyzes the process of crack evolution using digital image processing technology. The experimental results indicate that wet–dry cycles can cause cumulative damage to the soil, significantly encouraging the initiation and expansion of secondary cracks. New cracks often branch out and extend along the existing crack network, demonstrating that the initial crack morphology has a controlling effect over the final crack distribution pattern. Numerical simulations based on MultiFracS software further revealed that soil samples with a thickness of 0.5 cm exhibited more pronounced surface cracking characteristics than those with a thickness of 2 cm, with thinner layers of soil tending to form a more complex network of cracks. The simulation results align closely with the indoor test data, confirming the reliability of the established model in predicting fracture dynamics. The study provides theoretical underpinnings and practical guidance for evaluating the stability of engineering slopes and for managing and mitigating fissure hazards in loess. Full article

Xylosalsola chiwensis (Popov) Akhani & Roalson is listed in the Red Data Book of Kazakhstan as a rare species with a limited distribution, occurring in small populations in Kazakhstan, Uzbekistan, and Turkmenistan. The aim of this study is to deepen the understanding of the ecological conditions of its habitats, the floristic composition of its associated plant communities, the species’ morphological and anatomical characteristics, and its molecular phylogeny, as well as to identify the main threats to its survival. The ecological conditions of the X. chiwensis habitats include coastal sandy plains and the slopes of chinks and denudation plains with gray–brown desert soils and bozyngens on the Mangyshlak Peninsula and the Ustyurt Plateau at altitudes ranging from −3 to 270 m above sea level. The species is capable of surviving in arid conditions (less than 100 mm of annual precipitation) and under extreme temperatures (air temperatures exceeding 45 °C and soil surface temperatures above 65 °C). In X. chiwensis communities, we recorded 53 species of vascular plants. Anthropogenic factors associated with livestock grazing, industrial disturbances, and off-road vehicle traffic along an unregulated network of dirt roads have been identified as contributing to population decline and the potential extinction of the species under conditions of unsustainable land use. The morphometric traits of X. chiwensis could be used for taxonomic analysis and for identifying diagnostic morphological characteristics to distinguish between species of Xylosalsola. The most taxonomically valuable characteristics include the fruit diameter (with wings) and the cone-shaped structure length, as they differ consistently between species and exhibit relatively low variability. Anatomical adaptations to arid conditions were observed, including a well-developed hypodermis, which is indicative of a water-conserving strategy. The moderate photosynthetic activity, reflected by a thinner palisade mesophyll layer, may be associated with reduced photosynthetic intensity, which is compensated for through structural mechanisms for water conservation. The flow cytometry analysis revealed a genome size of 2.483 ± 0.191 pg (2n/4x = 18), and the phylogenetic analysis confirmed the placement of X. chiwensis within the tribe Salsoleae of the subfamily Salsoloideae, supporting its taxonomic distinctness. To support the conservation of this rare species, measures are proposed to expand the area of the Ustyurt Nature Reserve through the establishment of cluster sites. Full article

The priming effect (PE), a microbially mediated process, critically regulates the balance between carbon sequestration and mineralization. This study used soils from different soil depths (0–20 cm, 20–40 cm, and 40–60 cm) under Picea schrenkiana forest in the Tianshan Mountains as the research object. An indoor incubation experiment was conducted by adding three concentrations (1% SOC, 2% SOC, and 3% SOC) of ¹³C-labelled glucose. We applied ¹³C isotope probe-phospholipid fatty acid (PLFA-SIP) technology to investigate the influence of readily labile organic carbon inputs on soil priming effect (PE), microbial community shifts at various depths, and the mechanisms underlying soil PE. The results indicated that the addition of ¹³C-labeled glucose accelerated the mineralization of soil organic carbon (SOC); CO₂ emissions were highest in the 0–20 cm soil layer and decreased trend with increasing soil depth, with significant differences observed across different soil layers (p < 0.05). Soil depth had a positive direct effect on the cumulative priming effect (CPE); however, it showed negative indirect effects through physico-chemical properties and microbial biomass. The CPE of the 0–20 cm soil layer was significantly positively correlated with ¹³C-Gram-positive bacteria, ¹³C-Gram-negative bacteria, and ¹³C-actinomycetes. The CPE of the 20–40 cm and 40–60 cm soil layers exhibited a significant positive correlation with cumulative mineralization (CM) and microbial biomass carbon (MBC). Glucose addition had the largest and most significant positive effect on the CPE. Glucose addition positively affected PLFAs and particularly microbial biomass. This study provides valuable insights into the dynamics of soil carbon pools at varying depths following glucose application, advancing the understanding of forest soil carbon sequestration. Full article

Understanding the distribution patterns of soil bacterial community structure and diversity across different forest types is essential for elucidating the mechanisms underlying microbial community assembly and its ecological drivers, particularly under the pressures of climate change. In this study, we examined six forest types—including four monocultures and two mixed-species stands—to systematically evaluate the structural composition, diversity metrics, and functional potential of soil bacterial communities. Significant differences in microbial structure and functional composition were observed among forest types. Mixed forests exhibited higher soil nutrient levels, more complex structures, and greater water retention capacity, resulting in significantly higher bacterial and functional diversity compared to monoculture forests. Bacterial diversity was greater in subsurface layers than in surface layers. Surface communities in monoculture forests showed relatively high structural heterogeneity, whereas deeper communities in mixed forests displayed more pronounced differentiation. The dominant bacterial phyla were mainly related to carbon and nitrogen metabolism, compound degradation, and anaerobic photosynthesis. Surface bacterial communities were primarily influenced by catalase activity, alkali-hydrolysable nitrogen, bulk density, and pH, whereas subsurface communities were largely controlled by pH, with supplementary regulation by nitrogen and potassium availability. Therefore, forest type and soil depth jointly influence the diversity, composition, and functional attributes of soil microbial communities by modulating soil physicochemical conditions. Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

Understanding the detailed spatiotemporal variations in soil organic carbon (SOC) stocks is essential for assessing soil carbon sequestration potential. However, most existing studies predominantly focus on topsoil SOC stocks, leaving significant knowledge gaps regarding critical zones, depth-dependent variations, and key influencing factors associated with deeper SOC stock dynamics. This study adopted a comprehensive methodology that integrates random forest modeling, equal-area soil profile analysis, and space-for-time substitution to predict depth-specific SOC stock dynamics under climate warming in Northeast China’s forest ecosystems. By combining these techniques, the approach effectively addresses existing research limitations and provides robust projections of soil carbon changes across various depth intervals. The analysis utilized 63 comprehensive soil profiles and 12 environmental predictors encompassing climatic, topographic, biological, and soil property variables. The model’s predictive accuracy was assessed using 10-fold cross-validation with four evaluation metrics: MAE, RMSE, R², and LCCC, ensuring comprehensive performance evaluation. Validation results demonstrated the model’s robust predictive capability across all soil layers, achieving high accuracy with minimized MAE and RMSE values while maintaining elevated R² and LCCC scores. Three-dimensional spatial projections revealed distinct SOC distribution patterns, with higher stocks concentrated in central regions and lower stocks prevalent in northern areas. Under simulated warming conditions (1.5 °C, 2 °C, and 4 °C increases), both topsoil (0–30 cm) and deep-layer (100 cm) SOC stocks exhibited consistent declining trends, with the most pronounced reductions observed under the 4 °C warming scenario. Additionally, the study identified mean annual temperature (MAT) and normalized difference vegetation index (NDVI) as dominant environmental drivers controlling three-dimensional SOC spatial variability. These findings underscore the importance of depth-resolved SOC stock assessments and suggest that precise three-dimensional mapping of SOC distribution under various climate change projections can inform more effective land management strategies, ultimately enhancing regional soil carbon storage capacity in forest ecosystems. Full article

To clarify the ecological mechanisms underlying the succession of artificial grasslands to native alpine meadows and systematically reveal the patterns of ecological restoration in artificial grasslands in the Qinghai–Tibet Plateau, this study provides a theoretical basis for alpine meadow ecological restoration. In this study, artificial grassland and degraded grassland (CK) with different restoration years (20 years, 16 years, 14 years, and 2 years) in the Qinghai–Tibet Plateau were taken as research objects. We focused on the tillering characteristics, patch number, community structure evolution, and soil properties of the dominant species, C. alatauensis, and systematically explored the ecological restoration law by comparing and analyzing ecological indicators in different restoration years. The results showed the following: (1) With the extension of restoration years, the asexual reproduction ability of C. alatauensis was enhanced, the patches became large, and aboveground/underground biomass significantly accumulated. (2) Community structure optimization meant that the coverage and biomass of Cyperaceae plants increased with restoration age, while those of Poaceae plants decreased. The diversity of four species in 20A of restored grasslands showed significant increases (10.71–19.18%) compared to 2A of restored grasslands. (3) Soil improvement effect: The contents of soil organic carbon (SOC), total phosphorus (TP), nitrate nitrogen (NN), and available phosphorus (AP) increased significantly with the restoration years (in 20A, the SOC content in the 0–10 cm soil layer increased by 57.5% compared with CK), and the soil pH gradually approached neutrality. (4) In artificial grasslands with different restoration ages (20A, 16A, and 14A), significant or highly significant correlations existed between C. alatauensis tiller characteristics and community and soil properties. In conclusion, C. alatauensis in artificial grasslands drives population enhancement, community succession, and soil improvement through patch expansion. Full article

Offshore wind turbine structures (OWTs) commonly use monopile foundations for support, and long-term exposure to wind–wave cyclic loads may induce changes in foundation stiffness. Variations in foundation stiffness can significantly alter the inherent vibration characteristics of OWTs, potentially leading to amplified vibrations or resonant conditions. In this study, a numerical model considering soil–pile interaction was developed on the FLAC3D platform to analyze the natural frequency of OWTs under long-term cyclic loading. The study first validated the numerical model’s effectiveness through comparison with measured data; a degradation stiffness model (DSM) was then embedded to assess how prolonged cyclic loading affects the degradation of foundation stiffness. A series of parametric studies were conducted in medium-dense and dense sand layers to investigate natural frequency alterations induced by prolonged cyclic loading. Finally, a simplified method for evaluating long-term natural frequency changes was established, and a 3.6 MW offshore wind turbine case was used to reveal the evolution characteristics of its natural frequency under long-term cyclic loads. The data reveal that the natural frequency of the structure undergoes a downward tendency as cyclic loading and frequency increase. To ensure long-term safe operation, the designed natural frequency should preferably shift toward 3P (where P is the blade rotation frequency). Full article

A multi-parameter optimization-based design method for soil-mixing blades was proposed to address the issue of excessive straw residue in the seeding layer after maize straw incorporation. A discrete element model simulating the interaction between the soil-mixing blades, soil, and corn straw was established. The key structural parameters included the bending line angle (α), bending angle (β), side angle (δ), tangential edge height (h), and bending radius (r); the straw burial rate (Y₁) and straw percentage in the seeding layer (Y₂) were selected as evaluation indicators. Single-factor experiments determined the significance level (p < 0.05) and the parameter range. A Box–Behnken response surface design, combined with analysis of variance (ANOVA), was employed to elucidate the influence patterns of the structural parameters and their interactions regarding straw burial performance. Multi-objective optimization yielded an optimal parameter combination: α = 55°, β = 100.01°, δ = 130°, h = 40.05 mm, and r = 28.67 mm. The simulation results demonstrated that this configuration achieved a Y₁ of 96.04% and reduced Y₂ to 35.25%. Field validation tests recorded Y₁ and Y₂ values of 96.54% and 34.13%, respectively. This study quantitatively elucidated the relationship between soil-mixing blade parameters and straw spatial distribution, providing a theoretical foundation for optimizing straw incorporation equipment. Full article

In earthquake-prone areas such as Tokyo, accurate estimation of bearing stratum depth is crucial for foundation design, liquefaction assessment, and urban disaster mitigation. However, traditional methods such as the standard penetration test (SPT), while reliable, are labor-intensive and have limited spatial distribution. In this study, 942 geological survey records from the Tokyo metropolitan area were used to evaluate the performance of three machine learning algorithms, random forest (RF), artificial neural network (ANN), and support vector machine (SVM), in predicting bearing stratum depth. The main input variables included geographic coordinates, elevation, and stratigraphic category. The results showed that the RF model performed well in terms of multiple evaluation indicators and had significantly better prediction accuracy than ANN and SVM. In addition, data density analysis showed that the prediction error was significantly reduced in high-density areas. The results demonstrate the robustness and adaptability of the RF method in foundation soil layer identification, emphasizing the importance of comprehensive input variables and spatial coverage. The proposed method can be used for large-scale, data-driven bearing stratum prediction and has the potential to be integrated into geological risk management systems and smart city platforms. Full article

Dry jack pine forests exposed to elevated nitrogen (N) deposition do not necessarily exhibit traditional N saturation responses. Using empirical results from a five year above-canopy N deposition experiment, a simple nitrogen (N) saturation model was developed for jack pine (Pinus banksiana Lamb.) forests dominated by cryptogams. For the model, a series of differential equations using empirically derived rate constants (k) were applied to estimate changes in net N pools in biotic and abiotic components across a narrow N deposition gradient (0, 5, 10, 15, 20, and 25 kg N ha⁻¹ yr⁻¹). Critical soil C:N ratios were used as the model limit to signify saturation. We explored the saturation response time by priming the model to mineralize approximately one percent of the soil N pool after the critical C:N ratio was reached. A portion of this pool was made available to jack pine trees. Nitrogen leaching below the rooting zone occurred when the mass of N mineralized from the soil organic- and A horizon layers exceeded the theoretical mass required by jack pine, driving the mineral soil below the critical C:N ratio. The model suggests that N leaching below the rooting zone could happen around 50 (1% LFH N mineralization) years after the onset of deposition at 25 kg N ha⁻¹ yr⁻¹. In contrast, N deposition rates ≤ 20 kg N ha⁻¹ yr⁻¹ are not expected to be associated with N leaching over this timeframe. The modeled results are consistent with empirical surveys of jack pine forests exposed to elevated N deposition for several decades. Full article

As a critical link connecting groundwater and vegetation, the vadose zone’s lithological structural heterogeneity directly influences soil water distribution and vegetation growth. A comprehensive understanding of the ecological effects of the vadose zone can provide scientific evidence for groundwater ecological protection and natural vegetation conservation in arid regions. This study, taking the Minqin Basin in the lower reaches of China’s Shiyang River as a case, reveals the constraining effects of vadose zone lithological structures on vegetation water supply, root development, and water use strategies through integrated analysis, field investigations, and numerical simulations. The findings highlight the critical ecological role of the vadose zone. This role primarily manifests through two mechanisms: regulating capillary water rise and controlling water-holding capacity. They directly impact soil water supply efficiency, alter the spatiotemporal distribution of water deficit in the root zone, and drive vegetation to develop adaptive root growth patterns and stratified water use strategies, ultimately leading to different growth statuses of natural vegetation. During groundwater level fluctuations, fine-grained lithologies in the vadose zone exhibit stronger capillary water response rates, while multi-layered lithological structures (e.g., “fine-over-coarse” configurations) demonstrate pronounced delayed water release effects. Their effective water-holding capacities continue to exert ecological effects, significantly enhancing vegetation drought resilience. Full article

This study investigates the effect of pile diameter on the seismic performance of single piles using the kinematic interaction framework outlined in Method III of the Turkish Building Earthquake Code TBEC-2018. Pile diameters of 65 cm, 80 cm, and 100 cm were analyzed under four different soil profiles—soft clay, stiff clay, very loose sand-A, and very loose sand-B. The methodology integrated nonlinear spring modeling (P-y, T-z, Q-z) for soil behavior, one-dimensional site response analysis using DEEPSOIL, and structural analysis with SAP2000. The simulation results showed that increasing the pile diameter led to a significant rise in internal forces: the maximum bending moment increased up to 4.0 times, and the maximum shear force increased 4.5 times from the smallest to the largest pile diameter. Horizontal displacements remained nearly constant, whereas vertical displacements decreased by almost 50%, indicating improved pile–soil stiffness interaction. The depth of the maximum moment shifted according to the soil stiffness, and stress concentrations were observed at the interfaces of stratified layers. The findings underline the importance of considering pile geometry and soil layering in seismic design. This study provides quantitative insights into the trade-off between displacement control and force demand in seismic pile design, contributing to safer foundation strategies in earthquake-prone regions. Full article

Expansive soils, characterized by the presence of surface and subsurface cracks, over-consolidation, and swell-shrink properties, present significant challenges to slope stability in geotechnical engineering. Despite extensive research, preventing geohazards associated with expansive soils remains unresolved. This study investigates shallow sliding failures in slopes of highly expansive soils induced by rainfall, using model tests to explore deformation and mechanical behavior under cyclic wetting and drying conditions, focusing on the interaction between soil properties and environmental factors. Model tests were conducted in a wedge-shaped box filled with Nanyang expansive clay from Henan, China, which is classified as high-plasticity clay (CH) according to the Unified Soil Classification System (USCS). The soil was compacted in four layers to maintain a 1:2 slope ratio (i.e., 1 vertical to 2 horizontal), which reflects typical expansive soil slope configurations observed in the field. Monitoring devices, including moisture sensors, pressure transducers, and displacement sensors, recorded changes in soil moisture, stress, and deformation. A static treatment phase allowed natural crack development to simulate real-world conditions. Key findings revealed that shear failure propagated along pre-existing cracks and weak structural discontinuities, supporting the progressive failure theory in shallow sliding. Cracks significantly influenced water infiltration, creating localized stress concentrations and deformation. Atmospheric conditions and wet-dry cycles were crucial, as increased moisture content reduced soil suction and weakened the slope’s strength. These results enhance understanding of expansive soil slope failure mechanisms and provide a theoretical foundation for developing improved stabilization techniques. Full article