Search Results (1,677)

Using our terahertz sensor, we addressed the agricultural challenge of nondestructively and cost-effectively detecting internal plant moisture. For plant health assessment, we developed a low-cost nanobolometer imaging sensor array. The proposed terahertz imaging system can detect changes in leaf moisture content under stress, even at low moisture levels. The system enables terahertz imaging of living plant tissues to assess moisture and nutrient distribution in leaves. Because terahertz radiation is non-ionizing and strongly interacts with water molecules, it can reveal internal plant processes. Plant development can also be monitored using time-series imaging. In addition, specialized software was used to enhance the quality of terahertz images and to fuse them with conventional images. This feature enables a more comprehensive assessment of plant health. Such an approach may support future applications, such as disease detection and evaluation of fertilizer effects. Full article

Maize production in the black soil region of Northeast China is highly vulnerable to drought and flood stress, yet stage-specific mechanisms under rain-fed conditions remain unclear. Daily meteorological records from 1951 to 2024 were used to calculate the Crop Water Surplus Deficit Index (CWSDI) for four maize phenological stages, and 2025 in situ soil moisture and temperature observations were used to derive root-zone soil water storage (SWS), soil water depletion rate (SWDR), and the soil temperature–moisture coupling index (STMI). The growing season showed a persistent water deficit (mean CWSDI = −39.19%). Drought risk was greatest during sowing–jointing (S1; CWSDI = −64.73%; drought frequency = 73.0%) and milk–maturity (S4; CWSDI = −49.84%; drought frequency = 58.1%), whereas jointing–tasseling (S2) had the highest flood frequency (13.5%). Soil hydrothermal indicators showed that S1 drought was evaporation-driven, S2 involved potential hot-wet compound stress, tasseling–milk (S3) had rapid root-zone water depletion, and S4 drought was driven by insufficient late-season precipitation. These findings show that maize water stress is a sequence of stage-specific mechanisms rather than a uniform seasonal phenomenon. We therefore propose a regulation strategy combining soil moisture conservation, rainwater harvesting, precision supplemental irrigation, and field drainage to improve maize resilience. Full article

Kiwifruit (Actinidia deliciosa cv. Hayward) is a high-demand crop due to its nutritional value. Climate change increasingly challenges its cultivation, particularly under Mediterranean conditions, due to limited water resources. Therefore, the early detection of water stress onset is crucial for optimizing irrigation water use and enhancing kiwi productivity. In this context, advanced sensors capable of continuously monitoring critical hydrodynamic parameters, combined with machine learning approaches, offer a promising solution for reliable prediction of plant water status, supporting irrigation decision-making systems. This study develops and evaluates machine learning (ML) models to predict trunk water potential (Ψtrunk), integrating soil moisture, climatic variables, and plant-based measurements, including sap flow. Various machine learning models were evaluated including Ridge Regression, Lasso Regression, Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), using soil moisture, trunk water potential (Ψtrunk), sap flow, and microclimatic variables (relative humidity, wind speed, temperature, solar radiation, vapor pressure deficit, and reference evapotranspiration). Among the tested models, XGBoost demonstrated the best performance, achieving an accuracy of approximately 0.80, followed by Ridge, Lasso and SVM, which showed similar accuracy. Full article

Despite extensive research on concrete pavement performance, integrating early-age mechanical behavior with multidimensional sustainability assessment remains limited, particularly in tropical environments where rapid moisture loss increases the risk of cracking. Existing approaches often focus on long-term performance or isolated indicators, lacking a unified framework that links early-age reliability to economic, environmental, and social outcomes. This study proposes a reliability-based framework to evaluate early-age performance and sustainability across curing methods. Stress–strength ratio (SSR) relationships (R² > 0.96) were derived from HIPERPAV simulations under tropical conditions, with SSR expressed as a function of structural reliability (75–99%). Mechanical performance was linked to economic costs, environmental impacts (kg CO₂-eq), and a social index, and integrated through a multicriteria approach. The results show that the selection of the curing method strongly influences both early reliability and sustainability. Cotton blankets maintain an SSR of about 70% even at 99% reliability, whereas the no-curing condition exceeds the failure threshold (>100%) at high reliability levels (≥95%). The single-layer curing compound provides the best cost–performance balance, while plastic sheeting and no curing perform worst. The main contribution is a transferable framework that integrates early-age cracking risk with sustainability indicators, enabling consistent evaluation of curing strategies across varying reliability levels in tropical contexts. Full article

We present an active pulsed system (APS) designed for the long-term monitoring of plant photosynthetic efficiency. The specific design features and technical specifications of the system are described in detail. Experimental evaluations, conducted using both a model fluorophore and live plants, demonstrated the instrument’s robust performance across a broad range of illumination, temperature, and humidity conditions. Furthermore, the results confirm the validity and reliability of the acquired data. The system’s capability to detect the onset and progression of plant stress induced by moisture deficit was successfully verified. Full article

In order to design suitable heat-dissipating clothing for people engaged in high-temperature conditions, the vapor-dominated moisture transfer and heat dissipation properties of polyester fabric (Coolmax) with irregular cross-section in sweat-wicking protective clothing were analyzed by establishing a three-dimensional thermal–moisture coupled numerical model. In this study, moisture transport was mainly considered as water vapor transport within the porous fabric domain under a prescribed vapor-input boundary condition, rather than as a complete liquid-sweat-wicking, condensation, and re-evaporation process. The effects of convective heat transfer coefficient, ambient temperature, fabric thickness, and porosity on the thermal and moisture regulation behavior of the fabric were analyzed. The results show that Coolmax fabric can realize more efficient vapor transfer and heat diffusion under different ambient conditions due to its irregular grooved fiber structure, and its skin-side temperature is lower, and the relative-humidity distribution is more uniform than that of cotton material. Through the comparative analysis of temperature and relative humidity under different parameter combinations, the reasonable structural parameter range considering heat dissipation efficiency and perspiration ability is determined as follows: a fabric thickness of 0.8–1.2 mm and a porosity of 0.70–0.80, which can effectively improve the heat and moisture regulation performance of fabrics. This study provides a theoretical basis and numerical simulation reference for material selection and structure design of sweat-protective clothing and functional sportswear, which is helpful to improve wearing comfort and reduce thermal stress. Full article

This study aims to quantify the response of sunflower root water uptake to stratified soil water and salinity stress. Based on field observations, the root water uptake function in the existing model was improved by developing a new equation for the root water uptake rate that accounts for spatial differences in root response. Field experiments were conducted in 2021 and 2022 using irrigation water with four salinity levels: CK (0.87 g/L), S1 (1.0 g/L), S2 (1.5 g/L), and S3 (2.0 g/L). Soil moisture and salinity in five soil layers (0–100 cm) were continuously monitored using sensors. The actual crop water requirement (ET_a) was estimated using the soil water balance method, while the actual (T_a) and potential (T_p) plant transpiration rates were calculated based on the canopy-scale water consumption principle. Results indicated that with increasing irrigation water salinity, both soil moisture content and electrical conductivity exhibited an overall increasing trend. Significant differences were observed in the combined soil moisture and salinity conditions across soil depths. In particular, salt accumulation in the surface layer reduced root water uptake in the upper soil profile. Based on the differential root response to soil water and salinity stratification, the root water uptake function was further optimized, and the parameters representing water and salinity conditions in each soil layer were calibrated using the least squares method. Model validation with 2021 and 2022 data demonstrated good agreement between simulated and observed T_a values, with RMSE = 11.41 mm and MRE = 0.32%, R² ranging from 0.66 to 0.98, NSE between 0.52 and 0.96, and regression slope b between 0.90 and 1.10. This enhancement in the root water uptake rate formulation significantly improves model simulation accuracy and provides a robust basis for optimizing irrigation management in saline–alkali environments. Full article

China boasts abundant straw resources but grapples with notable challenges in straw processing: returning straw to fields can lead to soil compaction and aggravated pests/diseases, while baled straw for off-field storage and transportation tends to scatter. Additionally, domestic netting technology for square bales remains underdeveloped, and imported equipment is ill-suited for small-scale farmers. To tackle these issues, this study developed an integrated straw baling and netting machine by modifying the 9YFSG-2.2 square straw baler. It integrates a conveying mechanism, an offset crank–connecting rod compression mechanism (300 mm crank, 885 mm connecting rod), a two-stage gear-driven net-wrapping mechanism (with hollowed-out large gears for weight reduction), and a sensor-controlled net-cutting device, forming a complete workflow of “straw pick-up–shredding–conveying–compaction–net wrapping–net cutting”. Via coupled simulation using RecurDyn 2019, EDEM 2020, and ANSYS Workbench 2018, straw particles were modeled as 28-mm-long segments (composed of three 7 mm spheres). Simulations showed straw compaction in 0.48 s, with the compression chamber and plate having equivalent stresses of 0.2767 MPa and 173.44 MPa and maximum deformations of 0.0012 mm and 0.66 mm—both well below structural steel’s yield strength. Field tests in Xinxiang, Henan (straw moisture 30.03%), yielded results exceeding standards: 99.4% bale formation rate, 96% regular bale rate, 93% drop resistance rate, 170 kg/m³ bale density, and 12 s per bale efficiency. Controlling netting time further boosted efficiency and reduced consumption, successfully realizing integrated straw baling and netting. Full article

Traditional irrigation management for tomatoes in solar greenhouses relies heavily on empirical manual experience and single soil moisture indicators, often leading to irrigation scheduling that lacks crop-specific physiological evidence and results in suboptimal water-use efficiency. To address these challenges, this study developed an intelligent, plant-centric irrigation decision-making framework for greenhouse tomatoes in the arid region of Xinjiang. Central to this framework is the precise identification of irrigation timing—the most critical first step and a fundamental prerequisite for achieving true on-demand irrigation. By monitoring the high-frequency dynamics of stem diameter (SD) and integrating soil moisture data, the physiological responsiveness of tomatoes to water stress was systematically analyzed. A hybrid predictive model, STL-LSTM, was constructed by coupling Seasonal-Trend decomposition using Loess (STL) with Long Short-Term Memory (LSTM) networks to forecast 24-h SD trends. Furthermore, an innovative dual-threshold irrigation mechanism was established, utilizing a physiological trigger (Maximum Daily Shrinkage, MDS > 70 μm) and a soil moisture constraint (Volumetric Water Content, VWC ≤ 17%). Results demonstrated that tomato SD exhibited distinct diurnal rhythms, with MDS and Daily Increment (DI) identified as highly sensitive indicators of plant water status. The proposed STL-LSTM model achieved superior predictive performance during the peak fruiting stage, with a coefficient of determination (R²) of 0.9184, representing an improvement of 14.8% and 27.56% over standalone LSTM and ARIMA models, respectively. The validation of the dual-threshold mechanism confirms its ability to balance real-time crop water demand with conservation requirements, effectively mitigating the risks of premature or delayed irrigation inherent in traditional methods. This research provides scientific rationale and technical support for the transition of greenhouse agriculture in arid regions towards precision irrigation and optimised water resource management. Full article

Urban plazas in hot-humid climates face severe heat exposure risks due to high sky view factors and limited shading, yet conventional thermal mitigation strategies predominantly rely on plaza-wide performance metrics that misalign with actual pedestrian exposure patterns. This study proposes a pedestrian-oriented microclimate optimization framework that integrates agent-based pedestrian movement simulation (PedSim) with coupled CFD microclimate modeling to enhance outdoor thermal comfort precisely where people walk and congregate. A representative urban plaza (32,300 m²) in a hot-humid climate was analyzed under extreme summer design conditions. Three scenarios were systematically compared: (1) baseline configuration, (2) plaza-wide greening optimization (uniform distribution), and (3) pedestrian-oriented optimization guided by exposure-weighted movement hotspots. Microclimatic variables were simulated using urbanMicroclimateFoam (OpenFOAM), incorporating coupled airflow, heat/moisture transport, radiation, and vegetation modules. Thermal comfort was quantified using Mean Radiant Temperature (MRT) and the Universal Thermal Climate Index (UTCI) at both plaza-wide and pedestrian hotspot scales. Winter simulations were further conducted to assess seasonal trade-offs. Results demonstrate that under identical green coverage ratio (6.6%), the pedestrian-oriented strategy achieves substantially greater thermal comfort improvements in high-use areas. Compared to the baseline, hotspot MRT and UTCI were reduced by up to 5.0 °C and 3.0 °C, respectively, whereas the plaza-wide scheme yielded only marginal improvements (ΔUTCI < 1 °C). Notably, the pedestrian-oriented layout outperformed plaza-wide optimization within hotspots by 0.8 °C UTCI reduction without compromising winter thermal comfort, maintaining 100% thermally comfortable area ratios in both scenarios. This research reveals that the spatial configuration of vegetation is equally critical as coverage quantity for pedestrian thermal exposure. By explicitly linking tree placement to movement patterns, the proposed framework offers a human-centered, resource-efficient pathway for climate-responsive urban design, providing actionable insights for mitigating heat stress in densely populated open spaces without increasing green infrastructure costs. Full article

Monitoring boreal above-ground biomass (AGB) change requires approaches that are both measurement-based and spatially explicit. We integrated permanent sample plots from Quebec and Ontario with Landsat-7 spectral trajectories (1999–2023) to quantify non-fire-related AGB change after excluding wildfire-affected intervals and to evaluate whether annualized AGB change can be predicted from spectral change at the plot-interval scale. Tree height was estimated using a multilayer perceptron model (R² = 0.83) and combined with species-specific allometry to derive plot-level AGB and interval ΔAGB. These estimates were aggregated to ecodistricts using effective sample sizes and confidence intervals. Across well-sampled ecodistricts, mean annualized ΔAGB ranged from −0.82 to +3.54 t ha⁻¹ yr⁻¹, with lower or negative changes mainly occurring in eastern regions. Spectral indices derived from NIR–SWIR bands showed relatively stronger associations with ΔAGB than greenness-based indices, consistent with the sensitivity of moisture- and disturbance-related metrics to canopy stress, including defoliation. An XGBoost ensemble correctly predicted the direction of change in 77% of intervals. These results provide a measurement-constrained and scalable framework for monitoring non-fire-related biomass change and supporting greenhouse-gas reporting across boreal forest landscapes. Full article

Background: This study investigates a novel alginate–gelatin hydrogel incorporating polyphenol-rich grape skin extract as a multifunctional therapeutic system for diabetic wound healing. The extract was obtained by ultrasound-assisted extraction and formulated into a biopolymer hydrogel designed to combine optimal moisture retention with the controlled release of bioactive compounds. Methods: A streptozotocin-induced diabetic rat model was used to evaluate wound contraction, collagen deposition, oxidative stress parameters, and systemic inflammatory markers over a 15-day period. Animals were assigned to four groups: untreated control, silver sulfadiazine (SSD), empty hydrogel (EH), and extract-loaded hydrogel (LH). Results: The LH formulation demonstrated superior wound closure, reaching 97.1% by day 15, significantly outperforming SSD and other groups. Hydroxyproline levels were markedly elevated in LH-treated tissues, indicating enhanced collagen synthesis and extracellular matrix formation. Redox analyses revealed substantial reductions in TBARS and significant increases in SOD, CAT, and GSH, confirming the strong antioxidative activity of the incorporated extract. Moreover, LH treatment produced pronounced decreases in IL-6 and TNF-α, restoring inflammatory balance and facilitating timely progression from the inflammatory to proliferative phase. Conclusions: These effects are attributed to the synergistic actions of grape skin polyphenols which exerted broad biochemical and structural benefits essential for diabetic wound repair. Overall, this sustainable, bioactive hydrogel represents a promising alternative for advanced wound care. Full article

Epidermal barrier dysfunction, driven by disorganization and altered composition of the stratum corneum (SC) lipid matrix, underlies multiple inflammatory dermatoses, namely atopic dermatitis (AD). The lipid fraction derived from Black Soldier Fly larvae (BSFL) biomass has emerged as a promising biomaterial for skin health applications, particularly for restoring barrier function. Following previous work on the development of solid lipid nanoparticles (SLNs) incorporating BSFL lipid extract, the present study focused on the mechanistic evaluation of the occlusive, moisturizing and skin reinforcement potential of these nanoformulations (NFs), by exploring both in vitro and in vivo models. The compatibility assays showed no adverse effects after patch testing on healthy or atopic individuals, nor alterations on skin hydration, transepidermal water loss (TEWL), or redness. In vitro studies confirmed the ability of these NFs to form an occlusive lipid film, hampering moisture loss, with 39% reduction of water loss compared to the control. Efficacy assays in human volunteers revealed a statistically significant improvement in epidermal conditions at treated sites, evidenced by enhanced SC hydration. The plastic occlusion stress test (POST) revealed a trend toward a reduced evaporation half-life, suggesting a modulation of the epidermal water dynamics, although the effect did not reach statistical significance. Overall, BSFL-based lipid nanoparticles emerge as emollient agents with broad potential for incorporation into next-generation cosmetic and pharmaceutical products for the management of AD. 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

Expansive clay slopes are vulnerable to progressive strength loss induced by repeated wetting and drying, a mechanism that drives shallow failure in active moisture zones. Reproducing this degradation experimentally is time-consuming and resource-intensive. This study evaluates whether Fully Softened Strength (FSS) can serve as a practical substitute for five wet–dry cycles in expansive clay slope stability assessment. Direct shear tests were conducted on wet–dry-cycled and reconstituted FSS specimens across fourteen experimental water contents. Strength parameters were incorporated into homogeneous and heterogeneous limit equilibrium slope models, considering degraded layer thicknesses of 1–5 m and suspended water table conditions. Equivalence was assessed using root mean square error (RMSE), prediction bias, and physical representativeness. Five wet–dry cycles produced a dominant cohesion reduction of 70.4% with minor changes in friction angle, reaching a quasi-stationary degraded state. FSS reproduced an equivalent system response through mechanical compensation between cohesion and friction—not through equality of strength parameters—under shallow failure conditions. The best statistical fit was obtained at w = 43.5% (RMSE = 0.314); however, w = 42.0%, coinciding with the liquid limit, provided a physically more robust interpretation with near-zero bias. Equivalence was found to be valid only for normal stresses ≤ 50 kPa, representative of shallow failure depths of 1–4 m. Full article