Search Results (7,361)

Split nitrogen (N) application is an important agronomic measure for improving wheat yield and quality, yet how rhizosphere nitrogen-transforming microbes respond to split N strategies and the underlying mechanisms remain unclear. This study investigated the effects of six N treatments, including control, basal application, jointing-stage soil topdressing, and foliar applications at booting, anthesis, and 10 days post-anthesis, on the community structure and diversity of key rhizospheric nitrogen cyclers (ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB)) in wheat. Results showed that AOB and NOB alpha diversity were significantly modified by split N application. N application at anthesis enhanced AOB richness and diversity more than the later application, while concurrently decreasing NOB diversity. Booting-stage application enriched Nitrosospira and Nitrosomonas in the AOB community, whereas anthesis application increased Nitrososphaera sp. JG1 in AOA, but decreased Candidatus Nitrospira inopinata in NOB. Redundancy analysis identified soil pH, moisture, organic carbon, and key enzyme activities as the main drivers of microbial community assembly. Although no significant differences were observed in key agronomic traits among treatments, the 10 days post-anthesis treatment showed numerically superior yield and N uptake. Notably, AOB community evenness was significantly positively correlated with grain yield, protein yield, and N uptake, whereas NOB community diversity showed negative correlations. These findings demonstrate that split N application, particularly late foliar spray at 10 days post-anthesis, can modulate soil physico-chemical properties to selectively shape nitrogen-transforming microbial communities (notably AOB) in the wheat rhizosphere. This study provides a theoretical foundation for designing precise N management strategies rooted in rhizosphere ecology, with the goal of simultaneously improving yield, grain quality, and nitrogen use efficiency. Full article

Efficient crop management requires intelligent control strategies capable of handling uncertainty, nonlinear environmental interactions and dynamic crop growth conditions. This study presents a multisensor data fusion-based intelligent crop management framework for Capsicum cultivation using both a Mamdani fuzzy inference system (MFIS) and an adaptive Mamdani fuzzy inference system (AMFIS). The Capsicum dataset from the SmartFasal platform includes temperature, humidity and soil moisture at three depths, recorded over a four-month period (March–June 2020) with a total of 7188 samples. The proposed MFIS and AMFIS models are implemented and evaluated in the simulation environment. A Capsicum yield of 60–63 t/ha (3.6–3.8 kg/plant) is predicted via a regression model built on raw sensor inputs under conventional environmental management. An expert-rule MFIS with triangular memberships improves the regulation of agricultural parameters, increasing yield to 70–73 t/ha (4.2–4.4 kg/plant), a 15–18% increase. To improve adaptability, the AMFIS model incorporates fuzzy C-means (FCM) clustering for the automatic tuning of Gaussian membership functions and enables the controller to adjust dynamically to sensor data distributions. The adaptive system achieves a predicted productivity range of 82–87 t/ha (4.9–5.2 kg/plant), a 30–35% increase over the baseline. The regression model validation metrics R² = 0.86, RMSE = 2.1 t/ha, and MAE = 1.7 t/ha confirm the reliability of the yield estimation within the simulation framework rather than experimentally measuring crop performance. A correlation analysis, histograms, scatter plots, and Bland–Altman assessments reveal that compared with the MFIS, the AMFIS results in smoother control transitions, lower variability, and higher resource-use efficiency. This study represents a data-driven simulation framework, and future work will focus on real-time implementation and experimental validation under actual greenhouse conditions. Full article

Plastic film mulching combined with raised bed–furrow irrigation is an effective technique for enhancing the seed yield, oil contents, and plant-level water use efficiency of sunflower cultivation, while also optimizing water footprint. In this study, a field experiment was carried out at the experimental station of the Department of Irrigation and Drainage during 2023–2024. The trial involved three types of raised bed–furrow irrigation (raised beds with 60, 45, and 30 cm ridges and 30 cm furrows) with and without mulching practices. The results revealed that the treatments combining mulching with raised beds showed higher soil temperature and moisture contents compared to non-mulching treatments. The highest seed yield and oil content were recorded in furrow irrigation with mulching, representing a 35% increase in yield and a 28% increase in oil content compared to the control treatment. Seed yield was positively correlated with oil content. Additionally, the highest plant-level water use efficiency was observed in a raised bed 45 cm in size with mulching, while the highest total water footprints were recorded in a raised bed with a 60 cm ridge and non-mulch treatment, both exceeding the control treatment. It is concluded that sunflower cultivation under mulching combined with raised bed–furrow irrigation significantly enhances crop and water productivity. Full article

This study proposes a comprehensive methodology for the design and performance assessment of infiltration ponds integrated within hybrid grey–green urban drainage systems. The scope of the ponds is twofold: (i) increase infiltration of rainwater, and hence groundwater recharge, and (ii) decrease pluvial discharge downstream. The framework is applied to the Rome Technopole district, which serves as a pilot case for testing and demonstrating the procedure. Through 30-year continuous simulations performed with the EPA Storm Water Management Model and forced with a 5 min historical rainfall, the approach enables a performance-based evaluation that captures the full hydrological variability and the hydraulic performances of urban drainage systems. The methodology relies on physically based models for both the grey stormwater drainage network and the infiltration ponds, combined with a long-term simulation and functional analysis under transient conditions. The approach explicitly represents the main hydrological processes, including runoff generation, flow routing, storage dynamics, infiltration, and soil moisture variability, enabling a quantitative evaluation of peak-flow attenuation, infiltration efficiency, groundwater recharge volumes, seasonal variability, and wet–dry cycle behaviour. The latter is used to assess the long-term evolution of pond performance and its implications for maintenance activities, including clogging development and removal. Scenario analyses explore the influence of pond geometry and storage volumes, highlighting the trade-offs between hydrological efficiency, evaporation losses, and drawdown times. Beyond the specific application to the Rome Technopole developed in this study, we propose a generalizable, practitioner-oriented design procedure suited to contexts where infiltration-based solutions are desirable but regulatory guidance is fragmented. The proposed design workflow identifies critical parameters for both the hydraulic design and the operational management of infiltration ponds, enabling a statistical evaluation of their performance. The analysis of peak-flow reduction, infiltrated volumes, and the timing and frequency of wet–dry cycles provides a robust technical basis for the proper sizing, integration, and long-term assessment of infiltration ponds within urban drainage planning. Full article

This study aims to evaluate the potential of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) based on signal-to-noise ratio (SNR) analysis for monitoring crop structure and moisture. Data were collected using a GNSS antenna placed within an experimental meadow located in NW Italy. GNSS-IR exploits the interference between direct and ground-reflected signals to derive physical parameters such as the vegetation phase center height and soil moisture. In this work, by analyzing and modeling the oscillations in SNR time series, the sensitivity to crop growth dynamics was assessed. Vegetation height and dielectric parameters were compared against corresponding ground-surveyed values collected using a ruler and buried soil moisture sensors. Results suggest that GNSS-IR can detect canopy height with a high degree of consistency (Pearson’s r = 0.89, MAPE = 18%). Results also show that changes in the amplitude and phase of the interference pattern are sensitive to biomass density and dielectric properties of the reflecting surface (r = −0.81 and r = 0.86 respectively). GNSS-IR observables were analyzed across four representative measurement campaigns capturing distinct seasonal stages of meadow development. Despite the limited temporal sampling (n = 4), the selected observations correspond to contrasting vegetation and soil moisture conditions, allowing the identification of systematic variations in crop biophysical properties. These findings open promising perspectives for the development of innovative monitoring strategies in precision agriculture, leveraging existing GNSS infrastructure to obtain key biophysical parameters with minimal additional equipment and operational complexity. Full article

Under dry sowing and wet emergence conditions in Xinjiang, cotton planting with extra-wide film mulching and sowing faced challenges including low soil moisture content and poor soil plasticity. These conditions resulted in inadequate film edge laying, seed exposure, and unstable sowing depth. This study focused on an extra-wide film mulch planter, conducting operational process analysis and parameter optimization experiments. The research first analyzed the soil layer structure required for a high-quality cotton seedbed, described the structural composition and working principle of the extra-wide film mulch planter, and examined the interaction between key components and soil during operation. The primary factors affecting machine performance were identified, and a soil-deflecting device was added to mitigate rapid soil backflow. A coupled MBD-DEM model was developed to simulate the operation of key components, and simulation experiments were conducted. The optimal parameter combination obtained through optimization was as follows: furrowing disc deflection angle of 11°, primary soil-covering disc deflection angle of 20°, operational speed of 3.5 km/h, longitudinal blade height of 16 mm, and spring stiffness of 14 N/mm. Simulation validation under these parameters yielded the following results: covering soil amount ranged from 3.22 kg/m to 3.67 kg/m, with a mean of 3.43 kg/m; seeding qualification rate ranged from 94.97% to 97.52%, with a mean of 96.3%; film hole length ranged from 43.14 mm to 46.86 mm, with a mean of 45.18 mm; and cotton seed sowing depth ranged from 29.51 mm to 31.82 mm, with a mean of 31.23 mm. These simulation results met the operational requirements for extra-wide film mulching and sowing. Field validation experiments were conducted using the optimal parameter combination. The results showed a mean soil-covering thickness of 35.1 mm, mean soil-covering width of 65.3 mm, mean film hole length of 45.7 mm, and mean cotton seed sowing depth of 29.1 mm, with coefficients of variation of 5.1%, 2.6%, 4.7%, and 5.8%, respectively. The field results were generally consistent with the simulation results, confirming the reliability of the simulation model and demonstrating improved operational performance of the extra-wide film mulch planter, making it more suitable for the dry sowing with wet emergence technique. Twenty days after sowing, the mean emergence rate reached 93.3% with a coefficient of variation of 1.0%, indicating stable emergence, which preliminarily validated the effectiveness of the constructed seedbed in promoting cotton growth. Full article

This study considers the potential of utilizing waste glass powder as a sustainable additive to improve the characteristics of clay subgrade soils. A comprehensive experimental program was designed, wherein a selected clay soil was amended with four distinct contents of glass powder that were finely ground: 0%, 3%, 6%, and 9% by weight. The primary objective was to evaluate the resultant improvements in soil strength and the enhanced interfacial bond between the treated subgrade and an overlying Type B granular subbase layer, which was further reinforced with an SS2 Geogrid. To characterize these effects, a suite of laboratory tests was performed, including the Modified Proctor Test, Atterberg Limits Test, California Bearing Ratio (CBR) test, and a large-scale direct shear test. A specially made large-scale instrument for direct shear was employed for the interface testing. The results demonstrate a clear positive correlation between the proportion of glass powder and the improvement in geotechnical properties. The most significant enhancement was observed at the 9% inclusion rate, which yielded a 6.6% increase in the maximum dry density and a substantial 49% improvement in the CBR value. Concurrently, this optimal mix design resulted in a 14% reduction in optimum moisture content, alongside notable decreases in the swelling and plasticity indices by 33% and 39%, respectively, confirming the efficacy of glass powder in stabilizing the clay subgrade. Full article

Single-species hedges can help mitigate a range of urban and climate change-related issues, such as slowing stormwater flow and reducing rainfall runoff, particularly during the growing season. There is, however, little information on the service delivery of mixed hedges and their comparison to single-species, year-round, as well as on the practicality of functional rather than ornamental plant mixing. Here, we report on an initial case study to address this. Chosen hedge taxa (Crataegus monogyna, Elaeagnus × submacrophylla ‘Gilt Edge’, Ligustrum ovalifolium, Thuja plicata ‘Atrovirens’) represented a range of plant characteristics. These were trialled outdoors in Reading (SE England, UK) as treatment groupings of either single-species or mixed-species (‘evergreen’ and ‘broadleaf’ mix), along with a bare soil control, in 110 L troughs. We applied 5 min simulated rainfall onto each treatment twice in every meteorological season and assessed canopy throughfall. We also monitored substrate moisture content change as a proxy for evapotranspiration and substrate storage capacity of subsequent rainfall. During summer, the deciduous taxa and mixed hedges had the highest evapotranspiration rates, suggesting their potential to influence soil water storage, but in our experimental setup, that did not translate into significant differences in substrate moisture between treatments. During autumn and winter, the single-species Thuja treatment had the highest rainfall interception rate, followed by both mixed species treatments. In winter, canopy and leaf characteristics rather than physiological activity correlated with increased rainfall attenuation. However, by the end of the experiment (spring 2023), Crataegus, Thuja and both mixed hedge treatments had significantly lower throughfall (higher interception) compared to bare soil. We are continuing to test these treatments in a longer-term field experiment. Management of mixed-species hedges for rainfall attenuation is practically achievable, despite some differences in individual species’ growth rates and plant habits. Full article

Hydrochar has emerged as a promising carbonaceous amendment to enhance soil quality, yet its short-term effects on soil carbon (C) and nitrogen (N) dynamics and microbial functioning remain poorly understood. Here, a 77-day greenhouse pot experiment was conducted using a Cambisol cultivated with sunflower (Helianthus annuus L.) under two irrigation regimes simulating well-irrigated (WI) and water-deficit (WD) scenarios. Two doses of chicken-manure-derived hydrochar (3.25 and 6.5 t ha⁻¹, corresponding to 2.35 and 4.69 g kg⁻¹ of dry soil, respectively) and mineral fertilizer (MF) treatments providing equivalent N inputs were evaluated. Hydrochar promoted microbial growth and enhanced enzymatic and respiratory activities despite its low apparent C and nutrient input. After 77 days under WI, the addition of 6.5 t ha⁻¹ hydrochar enhanced the activity of phenol oxidase (POA) and acid phosphomonesterase (AcPA). Concomitantly, the availability of soluble C and N increased, whereas total organic C (TOC) and N decreased relative to the initial values. These responses may suggest enhanced mineralization potentially related to early-stage priming processes. The increase in POA relative to β-glucosidase is in line with a functional shift from a predominant degradation of labile compounds towards an increased oxidation of more complex structures. This interpretation is supported by solid-state ¹³C NMR data, revealing a higher degradation index of the soil organic matter. Under WD, the overall effects of hydrochar were attenuated or suppressed, particularly those related to C and N dynamics, emphasizing the interactive influence of moisture and amendment dose. Overall, our results show that hydrochar can modulate short-term soil biochemical processes, partly through enhanced microbial responses. Full article

Genomic selection (GS) may improve the adaptation of white lupin to drought or moderately calcareous soil, enabling to realize its potential as a high-protein crop. This study aimed to (a) verify breeders’ ability to identify the top-, mid-, and bottom-performing genotypes of published GS models of breeding lines and landrace genotypes for adaptation to drought and moderately calcareous soil; and (b) compare the top-performing materials produced by GS and phenotypic selection. Twelve selected genotypes were evaluated in four managed environments obtained through combining two soils (non-calcareous; moderately calcareous) with two water treatments (moderate terminal drought; moisture-favorable). GS based on the genotyping-by-sequencing of independent material was challenged by validation conditions that were partly different from the training ones and an imposed similarity of genomically predicted genotype phenology (to exploit drought resistance rather than drought escape). Grain yield reduction relative to favorable conditions averaged 19% for drought and 23% for calcareous soil. GS correctly identified the top-performing material for drought-prone or moderately calcareous soil, except for one model based on a small training set. The best GS lines performed comparably to the best phenotypically selected material. A higher harvest index was associated with better adaptation to drought and calcareous soil. Crossover genotype × water treatment interaction underpinned the selection for adaptation to drought. Full article

Climate change poses a significant threat to water resources and agricultural sustainability, particularly in semi-arid and socio-economically vulnerable regions such as South Africa. This review synthesizes empirical, modelling, and policy-based evidence on the impacts of climate change on water availability, crop production, and adaptation strategies in the country, drawing on approximately 162 peer-reviewed studies and institutional reports published between 2010 and 2025. The findings indicate that rising temperatures, shifting rainfall patterns, and an increasing frequency of extreme events, such as droughts and floods, are intensifying water stress and disrupting agricultural systems. Hydrological models consistently project declines in runoff, soil moisture, and streamflow, while crop simulation models predict reductions in the yields of major staple crops, including maize, wheat, and sorghum, particularly under high-emission scenarios. Although localized improvements in water availability and crop productivity may occur, these tend to be limited and highly context-specific. In response, South Africa has implemented a range of adaptation strategies, including climate-smart agriculture, water-efficient irrigation, ecosystem-based approaches, and policy-driven interventions. However, their effectiveness remains constrained by institutional fragmentation, limited financial capacity, and persistent socio-economic inequalities, particularly among smallholder farmers. The review underscores the need for integrated, inclusive, and context-specific adaptation strategies that strengthen governance, enhance the science–policy interface, and improve access to climate finance. The insights provided offer valuable guidance for advancing climate resilience in South Africa and other vulnerable regions across the Global South. Full article

Cover crops in woody crops as a sustainable land management alternative to conventional tillage induce changes in soil properties that improve ecosystem functioning. Soil is highly dynamic, and disturbances in environmental conditions affect soil microorganisms, particularly in gypsiferous soils, where microbiological activity remains poorly understood. This study evaluated the effects of three cover crop systems: spontaneous permanent vegetation cover (SVE), annual legume cover (VIC), and permanent grass cover (BRA), compared with conventional tillage (TIL), on soil physicochemical and biological properties in an olive grove over two crop seasons. Overall, cover crops promoted higher microbial activity and carbon storage than tillage, with responses being more pronounced during the wetter year. Conventional tillage consistently exhibited the lowest levels of enzyme activities and carbon stocks, whereas permanent covers showed stronger positive effects on soil functioning. These findings indicate that the benefits of cover crops on soil processes are reinforced under favorable moisture conditions but also remain under drier years, highlighting their stabilizing role. The improvement of soil health induced by cover crops contributes to enhancing soil ecosystem services, including soil fertility, in olive groves, supporting their adoption as a sustainable management strategy in Mediterranean agroecosystems, even under lower rainfall conditions. Full article

Landslides are a critical environmental hazard in mountainous regions like eastern Uganda, posing serious threats to lives, infrastructure, and ecosystems. While recent advances in geospatial technology have improved hazard assessment, existing research often lacks high-resolution, cloud-based analysis for dynamic landscapes such as the Mount Elgon region. This study addresses that gap by developing a landslide susceptibility map (LSM) using Google Earth Engine (GEE), which integrates remote sensing and geospatial data for scalable analysis. The main objective is to identify landslide-prone zones by analyzing eight conditioning factors, namely slope, elevation, vegetation cover, rainfall, land use land cover, soil type, soil moisture, and groundwater levels using the weighted overlay method (WOM). The methodology produced a classified LSM with zones of high (37.7%), moderate (58%), low (2%), and very low (2.3%) susceptibility, with validation via historical landslide data and ROC analysis yielding an AUC of 0.76, confirming strong predictive performance. The study underscores the value of GEE in hazard modeling and provides actionable insights for targeted risk mitigation, sustainable land use planning, and early warning system development in landslide-prone areas. Full article

Soil adhesion and abrasive wear severely degrade the performance and service life of soil-covering rollers in no-tillage seeders, particularly in the heavy clay black soil regions of Northeast China. To address the critical issues of soil adhesion and wear on soil-covering rollers used in no-tillage seeders within black soil regions, this study presents a surface engineering strategy that integrates a bionic micro-texture with a functional composite coating. Inspired by the crescent-shaped pits on the body surface of Procambarus clarkii, a bionic texture was designed and combined with a PTFE/PDMS/TiO₂ composite coating. Key parameters were optimized using response surface methodology, yielding a TiO₂ mass fraction of 6%, coating thickness of 40 μm, remaining texture depth of 50 μm, and texture spacing of 250 μm. A prototype was fabricated and evaluated through orthogonal field experiments in two distinct soil environments. In clay soil (15–25% moisture content), soil moisture and vertical load significantly influenced anti-adhesion performance, with recommended operating parameters of 600 N vertical load and a speed range of 10.8–14.4 km·h⁻¹. In sandy soil (8–18% moisture content), vertical load and operating speed had significant effects on wear resistance, with optimal parameters identified as 600 N vertical load and 10.8 km·h⁻¹. Verification tests confirmed stable low-adhesion and low-wear performance under varying moisture conditions. Compared to conventional and PTFE-coated rollers, the bionic roller reduced soil adhesion by 82.62% and 74.02%, respectively, in high-moisture clay soil, and reduced wear loss by 36.81% and 28.97%, respectively, in dry sandy soil. These results demonstrate that the synergistic “structure–material” design, which leverages stress dispersion and storage from the bionic texture alongside low surface energy and enhanced wear resistance from the composite coating, offers a promising approach for improving the durability and performance of soil-engaging agricultural components. Full article

Pinus cembroides is among the pine species best adapted to arid and semi-arid ecosystems in the Americas, and its potential distribution is projected to expand under climate change. However, the success of this expansion will depend on belowground processes, particularly the role of soil fungal communities, which in subtropical forests are key for nutrient cycling and plant resilience to environmental stress. Yet their vertical stratification and responses to forest management remain poorly understood, especially in semi-arid systems. Here, we characterized fungal communities from mineral soil and litter associated with P. cembroides across a forest management gradient (mature forests, disturbed stands, and pine plantations) at the southern limit of the species’ distribution. We evaluated the influence of climatic, edaphic, vegetation structure, and microbial activity variables (soil moisture, precipitation, pH, tree density, vegetation cover, temperature and extracellular enzyme activity) on fungal community composition. We found strong vertical stratification between litter and mineral soil. When both substrates were analyzed together as an integrated soil profile, forest condition had no significant effect on alpha diversity; however, substrate-specific analyses revealed higher richness in mineral soil of mature forests compared to disturbed and plantation sites, while litter communities showed no significant differences among conditions. Litter communities were characterized by saprotrophic and endophytic fungi, whereas mineral soil communities were enriched in ectomycorrhizal and other root-associated taxa. Distance-based redundancy analysis indicated that fungal community composition was primarily associated with moisture content, precipitation, pH, tree density, and carbon-degrading enzyme activity. These results highlight the importance of substrate differentiation and environmental gradients in shaping fungal communities in semi-arid pine forests, and provide a baseline for understanding how management and climate change influence soil fungal diversity and ecosystem functioning. Full article