Search Results (1,864)

The increasing use of plastics in agriculture has enhanced crop productivity, water-use efficiency, and food supply stability. Nevertheless, the ongoing degradation of agricultural plastics and waste-derived materials has resulted in the widespread occurrence of microplastics (<5 mm) and nanoplastics (<1 μm) in agricultural soils, raising concerns about ecosystem functioning, food safety and human health. This review was conducted using literature obtained primarily from Web of Science, Scopus and PubMed. Publications published between 2019 and 2026 were primarily included. In addition, selected landmark studies published before 2019 were incorporated when they provided foundational concepts, methodological frameworks, or highly cited evidence that remains essential for understanding the sources, fate, and impacts of micro- and nanoplastics in agricultural systems. The review synthesizes recent scientific evidence regarding the sources, environmental fate, biological interactions, and food-chain transfer of micro- and nanoplastics within agricultural and food production systems, tracing their movement from farm to fork. Major contamination pathways include agricultural plastic materials, organic amendments, polymer-coated agrochemicals and atmospheric deposition. Mechanisms governing transport, aging, plant uptake and trophic transfer are also discussed. Current evidence suggests that agricultural soils are among the largest terrestrial reservoirs of micro- and nanoplastics; however, substantial uncertainties remain regarding environmental concentrations, plant uptake under field conditions, and human health risks due to methodological limitations and the lack of standardized analytical protocols. Future research should focus on standardized monitoring methods, enhanced risk assessment frameworks, the development of biodegradable alternatives, and integrated mitigation strategies to reduce plastic contamination. Full article

Measuring the water table level is a critical factor in irrigated agriculture in arid regions, as it can significantly influence the exchange of water and nutrients with crops. This work presents the design, implementation, and field validation of an open-source, solar-powered IoT device for autonomous groundwater level monitoring, combining long-range low-power LoRa communication, a non-contact pressure-based level sensor using the trapped-air capillary method, and an efficient power management stage that seamlessly switches between solar and battery power. Unlike existing commercial leveloggers, which are costly and lack integrated wireless telemetry and solar-based autonomy, the proposed platform is presented as a fully open-source, low-cost alternative purpose-built for unattended deployment in areas without grid power or cellular coverage. The system was validated through a multi-day field trial and dedicated communication tests, demonstrating a stable power conversion efficiency of 84–90%, a five-day autonomous operation without any deep-discharge event, high linearity ($R^2$ = 0.9998) of the level module over a 0–2 m range with a resolution of approximately 1.94 mm per ADC count, and a reliable LoRa link of up to 8.51 km in an urban/suburban environment despite non-line-of-sight conditions. With an estimated hardware cost of approximately $100 USD per unit, the device represents a low-cost, low-maintenance tool capable of generating knowledge about water resources to optimize irrigation and crop management in the face of climate change. Full article

Cyanobacterial blooms are an increasing global concern due to the release of microcystins (MCs), potent hepatotoxins that threaten aquatic ecosystems, livestock, and human health. This study investigated the efficiency of low-cost natural adsorbents—rice straw (R), corn straw (C), and sawdust (S)—compared with commercial activated charcoal (AC) for the removal of microcystins from water sources in Upper Egypt. A total of 72 water samples were collected between June and September 2022 from rivers, irrigation canals, and wastewater channels in Sohag and Assiut governorates. Samples were analyzed for intra- and extracellular MCs using ultra-performance liquid chromatography (UPLC), while adsorbents were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM), pH, moisture content, iodine number, and methylene blue adsorption. Results revealed mean total MC concentrations of 9.39, 3.18, and 11.70 µg/L in river, irrigation, and wastewater samples, respectively—exceeding the World Health Organization (WHO) guideline of 1 µg/L. Adsorption experiments demonstrated that AC exhibited the highest MC removal efficiencies (88.9% in acidified and 92.3% in neutral water), followed by sawdust (84–86.2%), corn straw (74.01–85.2%), and rice straw (75.4–74.8%). Sawdust and corn straw performed particularly well for extracellular MC removal, while AC was most effective for intracellular fractions. This study highlights the potential of agricultural by-products, particularly sawdust and corn straw, as sustainable, low-cost alternatives to activated charcoal for cyanotoxin removal. Their availability and efficiency support their application in water treatment systems without chemical pretreatment. These findings indicate that agricultural residues could serve as practical, low-cost adsorbents for mitigating cyanotoxin contamination in water, especially in resource-limited regions, while also promoting the beneficial reuse of agricultural waste. Full article

The development of high-salinity geothermal resources is hindered by corrosion, scaling, and high water treatment costs, posing severe challenges for conventional hydrothermal systems. Deep borehole heat exchanger (DBHE) technology, which extracts heat without water production and avoids contact with high-salinity fluids, offers a promising alternative. In this study, field experiments on a coaxial DBHE were conducted in well SQ-1 (over 3000 m deep) in the Xining Basin, targeting its dual structure: a shallow high-salinity aquifer and a deep high-temperature low-permeability basement. Results show that the deep Proterozoic metamorphic basement has extremely low permeability (10⁻⁸ cm/s), with a bottom hole temperature of 113 °C and an average geothermal gradient of 3.39 °C/100 m, confirming it as a stable solid heat source. Under steady-state operation, the heat extraction rate averaged 150 W/m (144–155 W/m, with an uncertainty of approximately ±3 W/m). A marginal effect of flow rate was observed: increasing flow from 40 to 50 m³/h increased heat extraction by only 1.5%, indicating a threshold flow-rate range beyond which continued flow increases yield diminishing returns. No groundwater extraction, corrosion, or scaling was observed during the 13-day test, confirming the short-term operational reliability of the system under the tested conditions. This study validates shifting heat extraction to deep low-permeability basements to avoid high-salinity issues, providing a scientific basis for clean geothermal utilization in similar regions globally. Full article

The solid-state landscape of pharmaceutical compounds is often characterized by the occurrence of polymorphs, hydrates, and solvates, which may significantly influence their physicochemical and biopharmaceutical properties. In contrast, some active pharmaceutical ingredients exhibit a remarkable resistance to crystal form diversification, despite extensive experimental investigation. In the present work, vinpocetine was subjected to an extensive solid-form screening campaign aimed at exploring its propensity to generate alternative polymorphs, hydrates, and solvates. Mechanochemical experiments were performed under neat grinding and liquid-assisted grinding conditions using a broad range of organic solvents and water, including two-step milling procedures and formulations containing surfactants. Additional investigations included high-energy planetary milling, high-pressure compaction, exposure to controlled humidity, thermal cycling, slurry-bridging experiments in various media, and crystallization after mechanochemical neutralization of vinpocetine salts. The resulting solids were systematically characterized by powder X-ray diffraction, and thermal and morphological analyses. In all cases, the recovered solid corresponded to the commercially available crystalline form of vinpocetine, with no evidence of alternative polymorphs, solvates, or hydrates. These results demonstrate the unusual robustness of vinpocetine crystal structure across a wide range of mechanical, thermal, and solvent-mediated conditions. Notably, this behavior contrasts with the well-established ability of vinpocetine to form numerous salts and salt cocrystals, suggesting that solid-state diversification in this compound is primarily driven by proton-transfer processes rather than by neutral polymorphism or solvent incorporation. The present study provides experimentally defined boundaries for the solid-state landscape of vinpocetine and contributes valuable data for future crystal-form prediction and pharmaceutical development studies. Beyond the specific findings reported herein, the systematic documentation of both successful and unsuccessful experimental outcomes represents a valuable source of experimentally validated positive and negative data that may support the future development and validation of AI-assisted crystal-form prediction tools. Full article

Having reliable tools for characterizing rainfall-induced soil erosion is fundamental to the effective management of agroforestry systems in order to increase resilience against climate change. Physics-based models provide a robust, comprehensive and widely applicable framework to quantify runoff generation and soil erosion during intense rainfall events in agroforestry catchments. In this work, we propose a novel hydro-erosive model to simulate hydrodynamical flow and bed mobilization, movement and deposition. This hydro-erosive model solves the two-dimensional shallow water equations (SWE-2D) with hydrological source terms for runoff generation, coupled with the 2D depth-averaged solid transport and the soil surface evolution equations. The partial differential system is solved using a finite volume method. Alternative Integral/Differential Bed Slope and explicit upwind/implicit pointwise friction term discretization options can be used to improve performance in terms of numerical stability and conservation. The behavior of different discretization options in this hydro-erosive model is evaluated through an analytical hillslope verification, a benchmark V-catchment rainfall–runoff test and a laboratory dam-break experiment over an erodible bed. The results show that the Differential Bed Slope formulation combined with the upwind friction discretization provides the most accurate and conservative predictions. Also, an Upwind Bed Updating method for integrating soil surface elevation change is compared with the cell-centered integration of the bed change term by suppressing non-physical oscillations without compromising computational efficiency. Overall, the proposed open-source hydro-erosive model provides a reliable and computationally efficient framework for high-resolution simulations of rainfall-induced soil erosion and represents a valuable tool for environmental and agroforestry applications, but appropriate calibration and mesh resolution are required to ensure reliable predictions. Full article

Microbially induced calcium carbonate precipitation (MICP) is a promising biotechnology for environmental remediation; however, the high cost of conventional chemical-grade calcium sources limits its large-scale scalability. This study evaluated the feasibility of utilizing an aqueous extract of natural attapulgite clay as a sustainable, low-cost calcium source for MICP-mediated arsenic (As) immobilization in both aqueous and soil systems. Among the tested minerals, Baiyin attapulgite (group B) exhibited the highest calcium content (62,808.94 mg kg⁻¹) and minimal toxic metal impurities, providing a favorable chemical matrix for biomineralization. At an optimal solid-to-liquid ratio of 1:10, Lysinibacillus fusiformis LF and Enterococcus LZU-1 successfully induced calcite precipitation driven by the attapulgite extract. In batch aqueous remediation experiments (20 days), the attapulgite extract significantly enhanced As removal efficiency compared to the controls; As removal rates peaked at 66.4% for strain LZU-1 (with LZ1 extract) and 65.8% for strain LF (with group B extract), drastically outperforming the standard CaCl₂ groups (31.2–37.3%) and blank controls (21.8–24.5%). Concurrently, soil incubation experiments (30 days) demonstrated that the combined application of attapulgite and MICP bacteria reduced the highly bioavailable exchangeable As fraction from 0.115 to approximately 0.03 mg kg⁻¹, while effectively driving its transformation into more stable carbonate-bound and organic-bound fractions without causing secondary soil salinization. Morphological and mechanistic analyses revealed that, compared to the well-defined euhedral crystals in the CaCl₂ control, the precipitates mediated by the clay extract exhibited distinctly irregular, defect-rich rhombohedral structures. This structural disruption was governed by the natural matrix effect of attapulgite, which simultaneously supplied dissolved Ca²⁺ and provided an abundance of fine clay fragments, calcite micro-grains, and associated amorphous Fe/Al/Mn-bearing phases. These constituents acted as physical scaffolding and heterogeneous nucleation sites that became embedded in the growing CaCO₃ lattice, driving the formation of highly reactive, defect-rich clay-calcite-arsenic composite precipitates that efficiently encapsulated arsenate. Mantel analysis further revealed that the remediation efficiency was significantly correlated with key environmental variables including Ni, V, Ca. These findings highlight the dual-system potential of natural attapulgite as an inexpensive, eco-friendly calcium alternative for sustainable MICP-based remediation of As-contaminated water and agricultural soils. Full article

Germinated Andean lupin whole flour (GAL) is rich in protein, dietary fiber, essential amino acids, and bioactive compounds, representing a promising alternative for the development of sustainable plant-based foods. This study investigated the feasibility of partially replacing soy protein isolate (SPI) with GAL in high-moisture extruded meat analogues. A central composite design was applied to evaluate the effects of the GAL ratio (0:100–50:50) and feed moisture content (50–70%) on the technological properties of the extrudates. The Response Surface Methodology was used to model and optimize the process. The incorporation of GAL significantly affected the (p < 0.10) water solubility index (WSI), oil absorption capacity (OAC), cooking loss (CL), yellowness (b*), cohesiveness, and adhesiveness, generating predictive models with satisfactory goodness-of-fit (R² > 0.75). Increasing GAL levels increased the WSI from 6.21 to 18.79% and cooking loss from 1.01 to 3.84%, while reducing OAC from 239.42 to 166.57%, indicating substantial modifications in matrix organization and hydration behavior. Numerical optimization identified an optimal formulation containing 12% GAL, 88% SPI, and 65.5% feed moisture, with a desirability of 77.82%. Model validation showed relative deviations lower than 10% between predicted and experimental values. The optimized meat analogue exhibited high protein content (84.44%), favorable techno-functional properties, and improved nutritional quality, with higher levels of branched-chain amino acids (17.34 g·100 g⁻¹ protein), essential amino acids (33.32 g·100 g⁻¹ protein), and in vitro protein digestibility (90.1%) compared with the control formulation. Multivariate analyses confirmed that phenylalanine, histidine, methionine, and leucine were the main variables that discriminated between the protein sources and the extruded products. Overall, GAL demonstrated strong potential as a sustainable functional ingredient to produce nutritionally enhanced high-moisture meat analogues. Full article

Water quality analysis plays an essential role in maintaining the health and sustainability of river ecosystems, especially in semi-arid regions like the Arroyo Colorado Watershed in South Texas. Since the river is a vital source of water supply for local communities, agriculture, and wildlife, it faces significant challenges and pollution from land use changes, climate variation, and agricultural runoff. Continuous monitoring and assessment of water quality parameters and their temporal variability are essential to ensure the drinking water supply and aquatic ecosystem health. However, comprehensive laboratory-based water quality investigations are often constrained by higher costs, logistical complexity, and limited manpower. As a result, monitoring datasets are often not available for all water quality parameters, or the datasets may be incomplete. To address such challenges, the objective of this study was to evaluate the potential of water quality index (WQI)-based assessment supported by machine learning algorithms as an alternative decision-support tool for water quality evaluation. The analysis compared four monitoring stations in the Austin and Arroyo Colorado Watersheds, with particular emphasis on one gauging station at Port Harlingen. Datasets were collected from the Texas Commission of Environmental Quality (TCEQ). A complete exploratory data analysis (EDA) was performed to understand the TCEQ water quality datasets containing sixteen parameters, and seven water quality parameters were selected based on multicollinearity checks. It was observed that seven independent water quality parameters (dissolved oxygen, ammonia, nitrate, phosphorus, temperature, fecal coliform, and residual non-filterable material concentrations) were identified as sufficient to define the WQI of the Austin monitoring stations. Moreover, U.S. Environmental Protection Agency (EPA)-based guidelines were utilized to scale individual parameters to a range of 0–100 to remove their magnitude and correlation-based bias. These parameters were further analyzed using machine learning techniques, i.e., principal component analysis, K-means, and one-class support vector machine, to compute the relative importance based on their fluctuation within the temporal dataset. Finally, the mean WQI model was developed for Port Harlingen and achieved a strong agreement with the National Sanitation Foundation (NSF) WQI (R² = 0.91). These findings demonstrate the applicability of the proposed data-driven WQI framework for regional water quality assessment and comparative analysis across watersheds. Full article

This study evaluated oxidative damage, antioxidant-related, and nitric oxide (NO)-related chemical markers in commercial bee pollen using two extraction systems. For this purpose, a total of 30 bee pollen samples from different brands and/or manufacturers were examined; each sample was subjected to aqueous extraction and ethanol/water (80:20, v/v). The levels of reduced glutathione (GSH), malondialdehyde (MDA), and NO metabolites, comprising nitrite and nitrate and expressed as total NOx, were determined in pollen extracts using spectrophotometric methods. The data were analyzed using descriptive statistics, group comparisons, and Spearman correlation analysis. The findings showed that ethanol/water (80:20, v/v) extraction provided significantly higher measured GSH equivalents and total NOx levels than aqueous extraction. Mean GSH equivalents were 79.12 ± 25.54 µmol/g in the aqueous extracts and 189.77 ± 45.09 µmol/g in the ethanol/water extracts, and the difference was found to be statistically significant (p < 0.001). NO metabolite levels were determined as 5.97 ± 8.34 and 366.70 ± 85.10 µmol/g, respectively, and the difference between the extraction methods was found to be statistically significant (p < 0.001). In contrast, MDA levels did not show a significant difference between the two extraction systems (p = 0.391). A significant positive correlation was observed between GSH and NO metabolites in the combined dataset (r = 0.660, p < 0.001). The findings suggest that 80% ethanolic bee pollen extract may represent a promising source of NO metabolites for future investigation as a natural alternative to synthetic sodium nitrite in processed meat products. However, this hypothesis requires validation through microbiological, technological, sensory, and shelf-life studies. Full article

The chlorophyll fluorescence parameter Fv/Fm, representing the maximum photochemical efficiency of photosystem II, is an important indicator for evaluating plant photosynthetic performance and stress responses. However, rapid and non-destructive monitoring of Fv/Fm at the leaf scale remains challenging because conventional fluorescence measurements are time-consuming and require specialized equipment. Although spectral techniques provide an efficient alternative, existing spectral-based models mainly rely on single-source information and often lack sufficient integration of environmental conditions and physiological interpretability. Therefore, this study aimed to develop an explainable multi-source information fusion framework by integrating leaf spectral characteristics and environmental variables for accurate and interpretable estimation of grape leaf Fv/Fm. The grape cultivar ‘Queen Nina’ grown under protected cultivation was used as the experimental subject in this study. Visible–near-infrared reflectance spectra, measured Fv/Fm values, and environmental variables were synchronously collected under different water-stress conditions. Sensitive wavelengths were extracted by multiplicative scatter correction (MSC), competitive adaptive reweighted sampling (CARS), and the successive projections algorithm (SPA), and an XGBoost model incorporating both spectral and environmental features was established. The results demonstrated that: (1) the proposed multi-source fusion strategy effectively integrated spectral and environmental information for Fv/Fm prediction, with 12 sensitive wavelengths identified by MSC-CARS-SPA; (2) the XGBoost-EF model achieved R², RMSE, and MAE values of 0.906, 0.0432, and 0.0352, respectively, under vine-level five-fold cross-validation, outperforming the spectral-only XGBoost model; and (3) SHAP analysis provided an interpretable explanation of model predictions by quantifying the contributions of key spectral and environmental features, highlighting the importance of leaf temperature and red-edge wavelengths. It is concluded that the accuracy, robustness, and interpretability of non-destructive Fv/Fm monitoring in grape leaves can be substantially improved through multi-source information fusion. Full article

Water-intensive industries in the Mediterranean face supply stress and decarbonisation pressure simultaneously. We develop an operations-research decision-support framework that treats the firm as one node of a small industrial resource cluster and prices the cost and carbon-equivalent emissions of five alternative supply trains—municipal water, river water, groundwater, rainwater harvesting and brewery wastewater reuse—within a multi-objective Linear Program. Each train carries engineering-grounded expenditures, energy intensities and grid emissions, and a weighted-sum scalarisation is solved daily for 365 days under three managerial scenarios. On a Cretan microbrewery whose 2022 demand of 5250 m³ is met from the municipal network, the balanced and cost-focused scenarios coincide on a single optimum that cuts the Levelised Cost of Water by 25.3% and emissions by 40.7%, while the eco-friendly scenario yields a 19.3% cost and 51.7% emissions reduction. LP duality, shadow prices and an extended sensitivity programme (diversification, capacity, grid factor, discount rate, RO recovery and demand profile) turn the optimisation into a decision-support package: optimal daily allocations, shadow-price signals on capacity and demand, and robustness diagnostics for capital planning, dispatch and risk management. Results are site-specific, but the framework and its diagnostics transfer in structure to clusters sharing the same convex-polytope source geometry; transposition to energy cooperatives is future work. Full article

Single-use pyrotechnic and compressed-gas actuators currently meet industrial safety tasks that demand rapid response and high force. An integrated hydrogen production and combustion-driven actuation system is proposed as a clean and reusable alternative. Hydrogen is generated on demand inside the unit by water electrolysis. It is stored in a metal hydride module and burned with air under controlled conditions to drive a double-piston mechanism. A combined approach of modeling, such as thermodynamic analysis, ideal gas laws, and Engineering Equation Solver (EES) simulations, was used to predict the hydrogen demand and system performance. In addition, the combustion behavior and chamber pressure distribution were investigated using COMSOL Multiphysics. It was shown that hydrogen–air combustion allows for more stable and controllable operating conditions than hydrogen–oxygen combustion, while still satisfying the required in-cylinder pressure of about 350 bar. The designed proton exchange membrane (PEM) electrolyzer consumes about 221 W of power from a 24 V DC power source and produces 0.16 g of hydrogen in 135 s, which is sufficient for a high-force actuation stroke. Unlike conventional pyrotechnic cartridges and pneumatic and hydraulic actuators, the suggested system generates no solid combustion residues and does not require single-use consumables. It is reusable for many cycles, with water vapor as the main combustion product. Overall, the findings support hydrogen-powered actuation on demand as a viable and clean option for high-force safety tasks, ranging from closing emergency shut-off valves at oil and gas facilities to pressurizing fire protection and other safety systems, making it particularly attractive for remote facilities without a continuous grid power supply. Full article

The increasing pressure on water resources is one of the most critical challenges of the 21st century. Demographic, industrial, and climatic factors are drastically reducing the availability of fresh water, with particularly pronounced effects in arid regions and the Mediterranean basin. Agriculture, which accounts for about 70% of global water withdrawals, is at the centre of this crisis, making it essential to explore unconventional sources such as brackish water. Desalination emerges as a key technology to address this challenge. Electrodialysis offers an attractive alternative, particularly suitable for moderately salty water (1000–5000 mg/L of total dissolved solids), thanks to its energy efficiency within specific salinity ranges and the ability to precisely control the quality of the produced water. At the same time, agrivoltaic systems that integrate energy production and agriculture are spreading, requiring compact, modular treatment devices that can be integrated with renewable sources. This research objective is the design and building of an affordable and reproducible electrodialysis (ED) prototype, equipping the system with automated sensor-based control, validating the device performance on brackish water and analyzing the feasibility of integration in agrivoltaic contexts. Full article

The black soil region of Northeast China is a key grain-production area where cropland water erosion threatens soil fertility and sustainability. We diagnosed cropland soil loss across six diagnostic years/time slices (2001, 2005, 2010, 2015, 2020, and 2024) using a Revised Universal Soil Loss Equation (RUSLE)-based remote-sensing workflow implemented in Google Earth Engine (GEE). Rainfall erosivity was derived from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily precipitation, soil erodibility from SoilGrids, topography from the Shuttle Radar Topography Mission digital elevation model (SRTM DEM), vegetation cover from the Landsat normalized difference vegetation index (NDVI), and cropland extent from ESA WorldCover; alternative rainfall sources, cropland masks, and P-factor settings were used for sensitivity analyses. Under the slope-graded P-factor scenario, mean annual soil loss ranged from 1.60 to 3.07 t ha⁻¹ yr⁻¹, and the proportion of cropland exceeding T = 2 t ha⁻¹ yr⁻¹ ranged from 25.2% to 52.9%. Soil loss fluctuated among years because rainfall erosivity and cover-management effects partly counteracted each other. Risk was concentrated in sloping piedmont and hilly cropland, whereas broad plains were dominated by very slight and slight erosion. P-factor parameterization represented the largest structural uncertainty. The workflow provides regional screening evidence for field verification and conservation-practice assessment, rather than direct site-specific engineering prescriptions. Full article