Search Results (4,960)

Sustainable agriculture in arid and semi-arid regions critically depends on the interactions between soil physical properties, water dynamics, and mechanized field operations. In this context, soil physical attributes, such as texture, bulk density, aggregate stability, and soil water potential, play a crucial role in determining soil–water–machine interactions. Soil attributes such as texture, bulk density, aggregate stability, and soil water potential govern both water movement and retention, as well as traction efficiency, draft energy, and compaction under mechanized traffic. Deviations from the optimal soil moisture range in sandy or calcareous soils increase wheel slip, energy consumption, and soil structural degradation, resulting in uneven infiltration and reduced water-use efficiency. This review synthesizes recent research on these coupled processes, emphasizing how soil mechanics and hydraulics collectively influence irrigation performance and mechanization energy requirements. The novelty of this study lies in presenting an integrated soil–machine–water conceptual framework that captures the continuous interactions and interdependencies among soil physical state, machine behavior, and water movement. By highlighting these dynamic relationships, this review provides a systems-level perspective on energy and water interactions in dryland agroecosystems, offering a foundation for predicting the environmental implications of mechanized operations under arid conditions. Overall, the review demonstrates that sustainable mechanized agriculture in arid regions requires integrated management of soil physical state, machine operation, and irrigation timing, where maintaining soil moisture within an optimal operational range is the key factor for reducing energy losses, preventing soil compaction, and improving water productivity. Full article

Biochar, a carbon-rich material traditionally used to improve soil health and as a feed additive, has recently attracted attention for its potential biological activity. This study examined the effects of an aqueous biochar extract (BC-AE) on human intestinal epithelial cells (Caco-2), focusing on its influence on cell viability and apoptosis. The metabolic activity of Caco-2 cells exposed to BC-AE was first evaluated using an MTS assay. A concentration of 3 mg/mL, which promoted Caco-2 metabolic activity, was selected for further testing at 24 and 72 h. The effect of BC-AE on cell viability was assessed by epifluorescence microscopy (morphology) and flow cytometry (apoptosis profiling). The transcriptional response of cell viability-related genes (BAX, BAD, BCL-2, BCL-xL, MCL-1, P21, and P53) and microRNAs (miR-15b, miR-19, miR-21, miR-33a, miR-155, and miR-486) was analyzed by RT-qPCR. In parallel, selected proteins (BAD, BAX, BCL-2, and MCL-1) were examined by Western blotting. We showed that BC-AE decreased cell viability after 24 h via late apoptosis, while 72 h exposure increased necrosis without further viability loss. Both BAX and MCL-1 protein levels increased in Caco-2 cells after 72 h of BC-AE treatment, and miR-15b and miR-21 were upregulated, suggesting the involvement of a regulatory mechanism controlling cell survival. The obtained findings highlight the importance of considering both concentration and exposure duration when assessing biochar bioactivity and represent an additional contribution to the ongoing effort to better understand the biological role. Full article

Drought is a highly destructive natural disaster that inflicts severe economic losses. Its formation mechanisms are complex, yet existing studies have often focused on single driving factors, leaving the synergistic effects of multiple factors insufficiently explored. Based on multi-source data from Xinjiang spanning 1981–2020, this study systematically examined the combined impacts of atmospheric circulation, underlying surface conditions, and human activities on drought, using the multi-temporal-scale Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Soil Moisture Index (SSI), along with partial correlation analysis, spatial autocorrelation, and principal component analysis. The results show that Xinjiang experienced a pronounced drying trend over the past 40 years, with the seasonal SPEI and SSI both exhibiting significant declines. Drought intensity was higher in northern Xinjiang than in the south. Correlations between drought indices and circulation indices, such as Atlantic Multidecadal Oscillation (AMO), were relatively weak, indicating a limited regulatory influence of large-scale circulation on regional drought under the dual constraints of topography and an inland setting. Among underlying surface factors, slope significantly influenced drought spatial patterns. Mountainous areas and basin interiors showed positive spatial correlations, characterized respectively by high–high clustering (high slope and high drought index) and low–low clustering (low slope and low drought index). In contrast, basin margins exhibited low–high clustering (low slope surrounded by high drought index), reflecting negative spatial correlation. Aspect showed no significant effect. Vegetation cover displayed clear seasonal coupling with drought, with strong negative correlations in spring due to intensified water stress. Human activities also played a prominent role. Since the mid-1990s, the expansion of built-up land and increased agricultural water use have shifted drought–land use relationships toward low–high clustering (low drought index surrounded by high land-use intensity) in southern Xinjiang oases, and toward low–low clustering (low drought index and low land-use intensity) in eastern Xinjiang. Meanwhile, ecological restoration projects promoted a transition from low–high to high–high clustering (high drought index and high land-use intensity) in some areas, alleviating local drying trends. Principal component analysis further revealed a shift in the dominant driver: land-use change was the primary factor before 2005, whereas vegetation cover became the key driver thereafter. By clarifying the mechanisms underlying multi-factor interactions in drought in Xinjiang, this study provides scientific support for integrated water resource management, ecological conservation, and climate adaptation strategies in arid regions. Full article

Driven by agricultural labor shortages and rising quality requirements, ginger harvesting increasingly demands high-throughput, low-damage operations and a reliable supply chain. This review summarizes harvesting modes and harvester types used in ginger production, with emphasis on critical process modules: digging and lifting, soil disintegration and cleaning, vine cutting and anti-tangling, gentle conveying, and collection. We compare major technical routes in terms of field capacity, control of soil and foreign materials, damage mitigation, and reliability under continuous operation, and identify the conditions under which each route performs best. Drawing on advances in harvesting systems for other root and bulb crops, we outline transferable approaches for intelligent sensing, precision control, and system-level integration. We then propose an online monitoring and closed-loop regulation framework for strongly coupled conditions, such as heavy clay soils, plastic-mulch residues, and vine interference. Key bottlenecks include limited cross-regional adaptability, persistent trade-offs between low damage and high throughput, cost constraints on intelligent functions, and the lack of shared datasets and standardized evaluation protocols. Future progress should be anchored in integrated equipment sets and supporting operating specifications, guided by multi-source sensing-based quality indicators and interpretable control strategy libraries, to reduce harvest losses, stabilize marketable quality, improve operational efficiency, and enable scalable adoption. Full article

Accurate modeling of dam reservoir sedimentation is crucial for effective reservoir management. Traditional approaches for estimating sedimentation include the Hydraulic Approach (HA) and the Empirical Approach (EA). HA involves complex computations and requires substantial data, while the EA relies on equations like the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE), which use subjective parameters and lead to inaccurate estimations. This study introduces a novel approach called the hydrological approach, which integrates the sediment rating curve (SRC) and the dam reservoir elevation-capacity curve (ECC) to estimate reservoir sedimentation and evolution of the ECC. This HA leads to a newly developed equation for the estimation of the sediment rise and the corresponding sediment volume. The approach is applied to the Wadi Fatimah Dam in Saudi Arabia. By combining rainfall data from 1985 to 2022 and performing rainfall–runoff hydrological modeling combined with the proposed HA, sediment accumulation trends and reservoir capacity reductions are estimated from past to present. Validation through ground survey and geophysical investigations in 2008 confirms model accuracy. Findings reveal significant sediment buildup, with an estimated average of 7.5 m rise from 1985 to 2008. The study’s main findings highlighted the urgent need for effective sediment management strategies in arid regions, where sedimentation rates are notably higher than in other regions. Full article

Correct arch-back orientation is essential in ridge-based strawberry transplanting. Improper orientation can increase soil contact and soil-borne disease risk, leading to yield loss and reduced harvest efficiency. In current practice, arch-back orientation of bare-root seedlings is still mainly judged and corrected manually, which is labor-intensive and not always accurate under field conditions. Although plug seedlings are easier for mechanized transplanting, they are about three times more expensive than bare-root seedlings. Therefore, bare-root seedlings remain widely used for cost-effective production. However, accurate real-time orientation perception for bare-root seedlings is still challenging because stems are thin, morphology varies widely, and leaves often occlude key curvature cues. To address this gap, we propose a lightweight machine-vision method for bare-root strawberry seedlings that detects three characteristic keypoints on the new stem. The three-keypoint design is inspired by farmers’ practical judgement: farmers often determine arch-back direction by observing the stem and using manual touch to sense curvature changes. Similarly, three keypoints provide a simple geometric representation of curvature trend, enabling real-time estimation of both arch-back direction and bending angle. Physical tests on 100 bare-root seedlings achieved a 93% agronomically compliant orientation rate, with an MAE of 5.74° and an RMSE of 7.44° for bending-angle estimation. For edge deployment, the optimized model achieved real-time performance on an embedded GPU platform, reaching 152.51 FPS (FP16) and 154.26 FPS (INT8). Overall, the proposed method provides a practical perception module that can be integrated into strawberry transplanting machines to support cost-effective, orientation-aware mechanized transplanting. Full article

Current sustainability discourse promotes sustainable yard practices as a means for residents to contribute to urban environmental health and soil conservation. Social–ecological research suggests that yard practices are shaped by multiscale social drivers, including social contagion, whereby visible expressions of individuality in front yard design are copied by nearby neighbors. This study evaluated residential areas within the Río Piedras Watershed (RPWS) in the San Juan metropolitan area to assess evidence of social contagion in front yard configuration and vegetation structure, and to examine whether these variables were associated with socio-demographic and economic characteristics when spatial effects were considered. A total of 6858 front yards across six highly urbanized sites were analyzed using Google Earth Street View imagery. Housing lot sizes were quantified, and yards were classified into eight landscape configurations based on green and gray cover elements. Woody vegetation structures, including trees, shrubs, and palms, were also quantified to generate estimates of functional diversity and a front yard quality index. Significant differences in yard characteristics were observed among sites. Spatial analyses revealed significant clustering at distances of 65–80 m, particularly for front yard configuration, while clustering of woody vegetation density was weaker. Local clustering patterns and the distribution of outliers varied across sites. Spatial lag models indicated that lot area positively influenced yard configuration and quality, and the density and diversity of woody vegetation. While socio-economic variables were not significant predictors of yard quality, their effects cannot be discarded. Overall, results are consistent with social contagion processes but also highlight neighborhood design as a key driver of clustering, alongside widespread conversion of green to paved front yards, with implications for soil and green infrastructure loss as well as environmental and human health in the RPWS. Full article

Soil erosion is a growing environmental problem in arid regions, where land-use changes and landscape fragmentation directly influence land degradation. This study estimated soil loss in the Tarabillas sub-basin, located in the Chihuahuan Desert, Mexico. To this end, the Universal Soil Loss Equation (USLE) was applied and integrated with Geographic Information System (GIS) tools. Landsat TM and OLI satellite imagery were classified through supervised techniques, achieving overall accuracies above 89%. The analysis was supported by comparing erosion patterns associated with land-use changes occurring during the 1990–2021 period, assessed through cross-tabulation matrices and landscape metrics. The results show that although the average erosion potential of the sub-basin remained constant at approximately 12.45 t ha⁻¹ yr⁻¹, erosion redistributed spatially, concentrating in areas where agriculture has replaced natural vegetation. Shrublands and grasslands continue to dominate the high erosion categories due to their wide spatial extent and high erodibility. These findings highlight that fragmented agricultural expansion constitutes the main driver of landscape transformation and soil vulnerability, emphasizing the importance of integrating remote sensing, GIS, and empirical models to support sustainable land management in arid regions. Full article

Clogging is the main mechanism that deteriorates the hydraulic functionality of permeable pavements, particularly in porous asphalt mixtures (PAM). This study evaluated the hydraulic impact of sediments from three peri-urban micro-watersheds in the Boyacá region of Colombia on the infiltration capacity of PAM. Road infrastructure and drainage conditions were analysed using orthophotos and field inspections to identify geomorphological factors that favour sediment transport toward the roadway. Annual erosion rates were estimated using the Universal Soil Loss Equation (USLE), and sediments were characterized both within the watersheds and at their outlet onto the road. Hydraulic performance was assessed through laboratory tests using a Falling Head Permeameter, complemented by field infiltration measurements with a Modified Cantabrian Infiltrometer (0.25 m²). Results showed erosion rates of up to 7.9 t/ha·year and infiltration losses above 90% under clogged conditions. A partial hydraulic recovery of around 40% was observed after maintenance, particularly when sediments exhibited a higher sand fraction. These findings demonstrate that combining USLE-based erosion modelling with controlled hydraulic testing provides a robust framework for evaluating clogging risks in peri-urban roads and offers new evidence on the hydraulic behaviour of PAM exposed to non-urban sediments in the design and maintenance of sustainable pavements. Full article

Weed management is crucial for the sustainable production of rice (Oryza sativa L.), although herbicides such as Imazamox (IZX) can persist in soils, posing risks to soils and water resources. This two-year study evaluated the effects of soil physicochemical properties under different irrigation and tillage practices, with and without compost derived from olive mill waste, on IZX behavior. The treatments implemented were as follows: no-tillage and sprinkler (NT-S), conventional tillage and sprinkler (T-S), conventional tillage and flooding (T-F), and the corresponding regimes with compost amendment (NT-SC, T-SC, and T-FC). Sorption–desorption, dissipation, and leaching of the herbicide were assessed. The IZX adsorption was lower under soil collected from sprinkler irrigation, especially in NT-S, while compost reduced the adsorption under T-SC and T-FC. Dissipation was faster in NT-S and T-S soils, in which the half-life of IZX declined up to 30% relative to T-F. Furthermore, compost further accelerated herbicide dissipation, correlating with higher organic carbon content and microbial activity. The IZX losses via leaching were significantly reduced in soils irrigated by sprinkler in combination with compost, with values ≤ 48.5% of the IZX applied. These results indicate that the irrigation regime and organic amendment strongly influence soil physicochemical properties, then influencing the environmental fate of IZX. Integrated management using sprinkler irrigation and compost can mitigate IZX persistence and leaching, improve soil health, and reduce the risk of water contamination, representing a sustainable strategy for rice cultivation. Full article

Maintaining ballast performance in seasonal frozen regions is essential for resilient and sustainable railway infrastructure because freeze–thaw-driven fouling can shorten service life and increase maintenance-related material consumption. To investigate the deterioration mechanisms of fouled railway ballast in seasonal frozen regions, freeze–thaw cycle tests and cyclic loading model tests were conducted in sequence using a custom low-temperature geotechnical system. The test results processed by Origin software indicate that unfrozen water migrates toward the freezing front under temperature gradients and forms ice lenses during freezing. During thawing, meltwater is retained above the underlying frozen soil. Repeated freeze–thaw cycles therefore promote progressive water accumulation in the upper soil layers, eventually forming a clay layer with high water content. Under cyclic loading, interlayer thickening exhibited clear moisture thresholds relative to the clay liquid limit (LL = 24%). Below the LL (18–24%), ballast penetration and fines migration were limited and thickness increased slowly. Above the LL, rapid strength loss accelerated penetration and upward transport. At an initial water content of 32%, fines migration surpassed the ballast surface and the ballast became fully fouled, meaning that the fouled interlayer thickness equaled the full 100 mm ballast-layer thickness. Fouling severity increased sharply with moisture: the void contaminant index exceeded the maintenance criterion (VCI > 40%) at 28% water content and evolved into severe mud pumping at higher concentrations. Excess pore water pressure developed stratification with depth, maintaining an upward hydraulic gradient near the interface and yielding a net water loss of 2.24–6.91% in the upper fine-grained layer. These quantified thresholds and mechanistic insights provide actionable trigger points for condition-based maintenance and climate-adaptive design, helping extend track-bed service life and reduce resource-intensive ballast renewal in seasonal frozen regions. Full article

Polyethylene (PE) is one of the most persistent pollutants in the environment. Here, we enriched a microbial consortium (PEH) and isolated a bacterial strain, Bacillus cereus PE-1, capable of degrading PE from landfill soil using PE as the sole carbon source. Scanning electron microscopy revealed significant surface erosion, while weight loss reached up to 4.57% after 30 days. TGA showed a 5.88% decrease in onset degradation temperature, and contact angle measurements indicated increased hydrophilicity. Elemental analysis confirmed oxygen incorporation into the polymer matrix. Genome sequencing revealed genes associated with biofilm formation (epsA, epsB, pgaC), oxidation (laccase, copper oxidase), hydrolysis (esterase, lipase, PHB depolymerase), and β-oxidation pathways. While these genomic findings indicate a predicted capacity for assimilation, no transcriptomic or proteomic validation was performed in this study. These findings suggest that PE-1 can colonize PE, initiate oxidative cleavage, and potentially assimilate breakdown products. This study provides new insights into the microbial degradation of polyolefins and identifies a promising bacterial candidate for plastic bioremediation. Full article

Soil moisture prediction is essential for precision irrigation in water-limited agricultural systems. This study presents a deep learning-driven irrigation framework for winter wheat, integrating a novel Informer–UNet model with a Comprehensive Irrigation Index for adaptive water management. The Informer–UNet combines ProbSparse self-attention mechanisms with UNet’s multi-scale feature fusion, enabling simultaneous prediction of soil moisture at 27 monitoring points across three depths, 10, 30, and 50 cm, while quantifying prediction uncertainty through Monte Carlo Dropout. A Comprehensive Irrigation Index incorporating moisture deviation, spatial variance, and confidence interval width was developed, with weights optimized via genetic algorithm. Field experiments were conducted in Chengdu, China, over two winter wheat growing seasons. The Informer–UNet achieved superior prediction accuracy, R² greater than 0.98, RMSE less than 0.65, compared to LSTM, Transformer, and standard Informer models, with the fastest convergence and lowest validation loss. The proposed DeepIndexIrr strategy maintained soil moisture within the target range, 55% to 75%, for over 81% of the irrigation period, reducing water consumption by 38.2% compared to fixed-threshold control and 19.2% compared to expert manual scheduling. These results demonstrate that integrating spatially distributed deep learning predictions with uncertainty-informed decision rules offers a promising approach for sustainable precision irrigation. Full article

Urban wetlands are assumed to contribute to nitrous oxide (N₂O) emissions; however, the microbial mechanisms underlying enhanced N₂O fluxes in urban wetlands and differences in microbial responses between aquatic and soil compartments have not been clearly identified. Here, we characterized the nitrogen (N) cycling microbial communities and their functional metabolic pathways in urban and rural wetlands using metagenomics and N₂O flux measurements. Results showed that urbanization drove a 6~8-fold increase in N₂O fluxes from urban wetlands compared to rural wetlands. Structural equation modeling (SEM) confirmed that urbanization intensity was a primary driver (standardized coefficients: 0.72 for soil and 0.92 for water). In wetland water, N₂O emissions were negatively correlated with inorganic nutrient concentrations (coefficient = −0.62). Aquatic microbial communities exhibited substantial taxonomic shifts but preserved network connectivity, indicating adaptive strategies for surviving urban perturbations at the cost of reduced functional redundancy. In wetland soil, microbial communities maintained stability under urbanization, which was attributed to environmental buffering from heterogeneous microenvironments. Soil N₂O emissions were positively linked to microbial alpha diversity (coefficient = 0.79). Furthermore, urban wetlands enriched genes mediating nitrification and denitrification while depleting genes associated with N fixation and organic N metabolism. This functional shift reflects microbial specialization in processing elevated reactive N (Nr) inputs from urban sources, trapping urban wetlands in an “N loss loop” that reinforces high N₂O fluxes. This study elucidates the microbial mechanisms governing wetland N₂O emissions under urbanization, thereby enhancing understanding of microbially mediated N cycling in the urban wetland ecosystem. Full article

Apples in China are planted mainly in nutrient-poor mountain soil, and a large amount of fertilizer input results in resource waste and a decrease in nutrient utilization efficiency. Controlled-release fertilizer (CRF) has been shown to be environmentally friendly and increase crop yield, but nutrient release cannot be precisely synchronized with apple demand. Here, a suitable secondary fertilization method was established by a two-year apple field experiment with CRF and common compound fertilizer (CF) at various ratios under a 25% reduction in application. The application of CF and CRF changes the temporal and spatial distributions of soil NPK nutrients, decreasing NPK losses and NH₃ emissions. The NH₃ emissions under CF and CRF decreased by 17.98–44.86%, as N loss decreased by 11.59–29.81% and by 4.45–8.19%, with respect to those under CF alone, while the soil pH and electrical conductivity increased by 8.28–17.12% and 10.73–18.29%, compared with those under CF alone. The increase in soil P and K also decreased losses by 8.28–17.12% and 10.73–18.29%. The combined application of CF and CRF can increase soil microbial diversity and functional taxa and nutrient cycling genes, resulting in efficient nutrient transformation and supply for apple trees. The regulation of nutrients and microbes by the secondary application of CF and CRF drives an increase in apple yield of 23.71–54.32%, resulting in high economic benefits. In total, the application ratio of CF and CRF at 3:7 in March and July was an effective way to balance apple productivity and the soil ecological environment, providing a sustainable solution for mountainous orchard ecosystems globally. Full article