Search Results (22,535)

This perspective examines the interactions among microplastics (MPs), emerging contaminants (ECs), climate change, and extreme hydrological events. Droughts, water scarcity, heatwaves, intense rainfall, and floods can alter the occurrence, mobilisation, transport, fate, and risks of MPs and associated ECs across water, soil, and groundwater systems. The analysis focuses on the context-dependent potential of MPs to act as vectors of ECs, soil–water interactions, and the potential influence of MPs on greenhouse gas (GHG) emissions. When these stressors co-occur, their combined effects may be additive, synergistic, or antagonistic. Accordingly, the “perfect storm” framing is used here to describe the potential for mutually reinforcing and cascading risks rather than to imply that synergy occurs universally. An integrated perspective therefore helps anticipate worst-case scenarios and move beyond the fragmented assessment of individual stressors. This paper discusses sustainable mitigation and adaptation strategies, including advanced wastewater treatment, water reuse, climate-resilient water management, infrastructure adapted to increasing hydrological variability, climate-smart agriculture, and safer alternatives to conventional plastics and chemicals. Effective implementation combines technological innovation with monitoring, governance, policy action, and public awareness. By framing the microplastics–contaminants–water–soil–climate nexus as an interconnected sustainability challenge, this work aims to support environmental resilience and progress toward the Sustainable Development Goals. Full article

Ensuring food authenticity, traceability, and quality has become a critical challenge in increasingly complex and globalized food supply chains. Conventional post-harvest analytical approaches, while powerful, often operate in isolation and fail to fully capture the influence of pre-harvest conditions on food composition. In parallel, the emergence of smart farming technologies has enabled the collection of high-resolution environmental and agronomic data, offering new opportunities to establish baseline signatures linked to geographical origin and production practices. This review explores the integration of pre-harvest data from precision agriculture with advanced post-harvest analytical techniques, focusing on spectroscopic and isotopic methods for food authentication. Recent advances in vibrational spectroscopy, including near- and mid-infrared, Fourier-transform infrared, and Raman techniques, alongside complementary methods such as nuclear magnetic resonance and fluorescence spectroscopy, have enabled rapid and non-destructive food fingerprinting. In parallel, isotope ratio mass spectrometry and compound-specific isotope analysis provide robust markers of origin, climate conditions, and agricultural inputs through the analysis of stable isotopes of carbon, hydrogen, oxygen, nitrogen, and sulfur. The combination of these analytical approaches with chemometric and machine learning tools facilitates the extraction of meaningful patterns from complex datasets. A central focus of this review is the development of integrated farm-to-fork frameworks that use multi-source data, including field sensor technologies, spectral fingerprints, and isotopic signatures, to enhance traceability and authentication. Applications across a wide range of food systems, including edible oils, beverages, plant-based products, and animal-derived foods, are critically evaluated to highlight the strengths and limitations of current methodologies. Key challenges related to data standardization, system interoperability, cost, portability, miniaturization and regulatory acceptance are discussed, alongside emerging solutions such as artificial intelligence-driven models, digital twins, and blockchain-enabled traceability systems. The review underscores a paradigm shift from reactive testing toward predictive and real-time food authentication systems, driven by the convergence of smart agriculture and advanced analytical chemistry. This integrated approach has the potential to significantly enhance transparency, trust, and sustainability in the global food system. Full article

Excessive nitrogen (N) fertilization in maize (Zea mays L.) production causes environmental degradation, particularly in semi-arid regions where high chemical inputs are necessary to maintain crop production. Plant growth-promoting rhizobacteria (PGPR) could reduce the optimal N fertilization doses. This investigation aimed to isolate bacteria, screen them for plant growth-promoting traits, and evaluate their potential effects on maize grain under different chemical N fertilization doses. Isolates Stenotrophomonas maltophilia LIMN and Enterobacter roggenkampii LCMG demonstrated multifunctional growth-promoting traits in vitro, including N₂ fixation, indole-3-acetic acid and siderophore production, potassium solubilization, and desiccation tolerance, with E. roggenkampii LCMG also solubilizing inorganic phosphate. A field trial across four chemical N fertilization rates (0, 40, 80, and 120 kg N ha⁻¹) revealed that single bacterial inoculation without N fertilizer matched or exceeded uninoculated controls receiving up to 80 kg of N ha⁻¹ (the standard recommendation). Specifically, S. maltophilia LIMN combined with the recommended rate of 80 kg N ha⁻¹ achieved the maximum grain yield (4601.2 kg DM ha⁻¹), outperforming uninoculated controls (without PGPR) receiving excessive fertilization at 120 kg N ha⁻¹ (3760.4 DM ha⁻¹). Although maize plants benefited from inoculation with S. maltophilia LIMN or E. roggenkampii LCMG, achieving similar or better yields than crops fertilized with high chemical N inputs under stress factors such as deficiency of moisture, low-nutrient soils, and high temperatures, the present study did not test the pathogenicity and biosecurity of S. maltophilia or E. roggenkampii in crops; therefore, the results are not a direct recommendation of their use as biofertilizers before novel studies to assess all the limitations and the potential to reduce N dependency in order to design novel sustainable strategies for crop production. Full article

An important component of sustainable agriculture is the development of strategies that reduce the use of mineral fertilizers while maintaining high crop productivity. One promising approach is the application of plant growth-promoting bacteria (PGPB), which may support plant development and improve nutrient use efficiency. A field experiment with winter wheat was conducted in south-western Poland during two growing seasons, 2023–2024 and 2024–2025, to evaluate the effect of inoculation with Priestia sp. KR219 under different nitrogen fertilization regimes. The experiment included three levels of nitrogen: 70, 91, and 130 kg N ha⁻¹ (54%, 70%, and 100% of the full spring nitrogen fertilization rate) with and without bacterial application. Soil chemical and biological properties, photosynthetic pigment content, plant morphological traits, grain yield, as well as grain chemical composition and amino acid profile were evaluated. The inoculated treatments showed higher soil dehydrogenase activity in the second growing season and higher contents of selected photosynthetic pigments, particularly chlorophyll a, under reduced nitrogen fertilization. Bacterial inoculation was also associated with numerical increases in grain yield in most treatment combinations, although these differences were not statistically significant. Differences among treatment combinations involving nitrogen fertilization were more pronounced for grain chemical composition and amino acid profile than differences between inoculated and non-inoculated treatments at the same nitrogen level, with the full nitrogen rate generally resulting in the highest protein content and higher contents of several essential and non-essential amino acids. Overall, the responses observed following Priestia sp. KR219 inoculation included changes in selected soil and physiological parameters, while responses in grain yield and quality varied between growing seasons. Further studies under diverse environmental conditions are required to determine its agronomic potential. Full article

The integration of robotics into agriculture addresses challenges such as labour shortages and sustainable production. Handling delicate and irregular natural products remains difficult for conventional grippers. This paper presents a baromorphic end-effector as a proof-of-concept platform for validating a perception-sensing TCP realignment pipeline rather than as a field-ready agricultural product. The square-to-hexagonal layout choice was made iteratively through prototyping, whereas a finite-element analysis was used in prior work to optimise and characterise the hexagonal cushion unit . The materials, actuation, and robotic platforms serve as the experimental testbeds for the integrated control concept. The system uses a modular array of pneumatically actuated hexagonal cells with sparse embedded pressure sensing, vision-based object detection, a discrete heuristic visual servoing controller to bypass kinematic singularities during the approach, and a closed-loop TCP dynamic realignment algorithm. Under controlled laboratory conditions, the prototype achieved 12/12 successful linear grasps and 9/11 successful angular grasps (82%) on irregular produce, whereas a conventional rigid parallel-jaw gripper failed all attempted baseline trials under the same protocol. Full article

Brassica crops, including collard greens, are economically important vegetable crops cultivated worldwide. Among the major pests affecting these crops, the aphids Brevicoryne brassicae (Linnaeus) and Myzus persicae (Sulzer) (Hemiptera: Aphididae) are particularly relevant due to the direct and indirect damage they cause. Increasing consumer demand for sustainable agricultural practices and pesticide-free produce has intensified the search for environmentally friendly pest management alternatives. In this context, plant-derived insecticides have emerged as promising sources of bioactive compounds because of their biodegradability, selectivity, and generally low toxicity to non-target organisms and mammals. Likewise, agro-industrial residues such as avocado seeds have attracted attention as sustainable raw materials with potential bioactive and insecticidal properties. In the present study, biopolyols produced from avocado and neem seeds through a liquefaction process based on green chemistry and waste valorization principles were evaluated for their insecticidal activity against B. brassicae and M. persicae. A series of laboratory and field bioassays were conducted to assess toxicity and repellency effects on aphids. Among the tested formulations, the AAA avocado seed biopolyol (2:1/30 min) showed the highest insecticidal activity, possibly due to better preservation of bioactive compounds under the liquefaction conditions tested. Dose–response and lethal-dose (LD) analyses estimated an LD50 of 64 mg/mL and an LD90 of 429 mg/mL (p < 0.001) for the AAA biopolyol. In addition to its lethal effects, the LD90 concentration of the AAA biopolyol exhibited significant repellency against aphids and outperformed Azamax^®applied at the recommended field rate. Field bioassays further demonstrated that both the AAA biopolyol at LD90 and Azamax^® significantly reduced aphid abundance in collard greens of the ‘Manteiga’ cultivar under field conditions, compared to the control. Nonetheless, there was no difference in the efficacy of the AAA biopolyol and Azamax^® in the field study. Altogether, these findings demonstrate the potential of seed-derived biopolyols as sustainable bioinsecticides for aphid management in Brassica crops, while also highlighting the value of agro-industrial waste as a source of novel bioactive compounds for integrated pest management programs. Full article

Desiccation cracking in expansive soils on slopes accelerates soil erosion and reduces water retention capacity, posing significant threats to agricultural sustainability. This study investigates the combined effects of organic fertilizer (OF), slow-release fertilizer (SRF), and rice straw (RS) on crack inhibition in expansive soil under wet–dry (W-D) cycles. A three-factor Box–Behnken design (BBD) was used with OF at 5–15%, SRF at 0.3–0.9 kg/m³, and RS at 0.25–0.75%, and crack development was followed through 20 W-D cycles. The quadratic response-surface model fitted to the BBD crack-ratio data was significant (R² = 0.952, adjusted R² = 0.865, p = 0.008), with significant linear effects of OF, SRF, and RS, whereas the two-factor interaction terms were not statistically significant as a group (p = 0.701). The lowest observed crack ratio in the BBD matrix was 1.7% at 10% OF + 0.9 kg/m³ and SRF + 0.75% RS; this is therefore reported as an observed low-response combination rather than evidence of a statistically confirmed SRF–RS interaction. An LSTM model was retained as a complementary dynamic predictor and yielded R² = 0.927, MAE = 0.325, and RMSE = 0.478 for the evaluated dataset; however, divergence between training and validation losses indicated overfitting, so external generalizability remains to be established. The results support agricultural-waste-based amendment as a promising crack-control strategy while emphasizing the need for independent replication and field validation. Full article

Cadmium (Cd) contamination in paddy soils poses health risks, yet the role of aggregate-scale Cd binding remains poorly understood under interactive agricultural management. Unlike primary textural separates that are fixed by parent material, aggregates are dynamic and manageable. This study investigates the interactive effects of parent material, water regime shifts in annual tobacco–rice rotation, and chlorine-containing fertilizers on aggregate stability, carbon/nitrogen sequestration, and cadmium (Cd) adsorption in paddy soils from subtropical paddy fields of Hunan Province, South China. Two paddy soils, Masaniutan (granite-derived sandy loam) and Shanniutan (slate/shale-derived clayey soil), were divided into four size classes. Selective removal of soil organic carbon (SOC) and free iron oxides (Fe_d), followed by Cd adsorption experiments. Shanniutan had greater aggregate stability than Masaniutan. Water regime shifts did not significantly alter aggregate structure. Chlorine fertilizers disrupted aggregates, increasing finer fractions. Cd adsorption rose as aggregate size decreased. SOC removal reduced the maximum adsorption capacity (q_m) by 36.8%, while Fe_d played a supporting role. Partial least squares structural equation modeling (PLS-SEM) revealed that parent material had a strong positive direct effect on aggregate stability (path coefficient = 2.346), while chlorine fertilization (−0.750) and water regime shifts (−0.344) had negative effects. Parent material, water regime shifts, and fertilization jointly influence aggregate stability and the distribution of cementing agents, thereby controlling Cd adsorption capacity—with SOC as the dominant factor. These findings provide a basis for sustainable paddy soil management by promoting SOC retention and avoiding excessive chloride inputs. Full article

Modern agriculture’s integration of Internet of Things (IoT), Industrial Control Systems (ICSs), and data analytics boosts productivity but introduces significant cybersecurity and data governance challenges. Existing scholarship is divided between policy-focused governance and technical attack analyses, hindering the development of comprehensive, enforceable defenses. This paper introduces an integrated framework that bridges normative data governance in smart farming (SF) with empirical, honeynet-derived threat intelligence. Drawing on the authors’ previous systematic review of SF data governance and a honeynet simulating agricultural IoT/ICS, the study maps governance challenges to quantitative attack indicators from honeynet logs, classifying each pairing as directly supported by telemetry, indirectly supported by telemetry, or not observable using the current methodology. The findings show that the services flagged as governance concerns face sustained attack pressure: the honeynet recorded brute-force attempts against SSH/Telnet on simulated irrigation controllers (149,000 events), connection and login attempts targeting SMB (Server Message Block) and MQTT (Message Queuing Telemetry Transport) on automated machinery (67,156), credential-guessing attempts against management services (14,937), and ICS protocol probes (11,532). Geographic and protocol distributions reveal that legacy industrial protocols and weakly authenticated management interfaces, both highlighted as governance concerns, constitute the primary attack surface. This evidence supports a tiered governance model integrating protocol-level controls, identity governance, and data-sharing policy, demonstrating that effective SF cybersecurity requires empirically calibrated rather than purely policy-driven frameworks. The proposed framework offers actionable guidance for aligning technical defenses with data governance obligations. This work contributes a new methodological protocol (cross-evidentiary mapping), an empirically calibrated tiered framework, and a coherent research agenda at the intersection of governance and measurement, serving as a template for similar analyses in other critical infrastructure sectors. Full article

Wind erosion poses a serious threat to land stability and agricultural sustainability across global arid and semi-arid zones. This study was conducted in Tuoksun County, China’s sole county situated below sea level; its unique low-elevation landform generates distinctive wind–sand movement processes, forming a representative research platform for elucidating shelterbelt functional mechanisms under extreme arid environments. In this work, we systematically monitored wind field characteristics, shelterbelt windbreak performance, and soil wind erodibility and quantitatively analyzed the regulatory effects of different shelterbelt configurations on sand-fixing efficiency and soil anti-wind erosion capacity. The results revealed an obvious decoupling between wind velocity and wind direction frequency within the study area: the maximum wind speed (≈5.5 m s⁻¹) occurred in the NNW direction, whereas the W and WSW directions exhibited the highest wind occurrence frequency. Shelterbelt height showed an extremely significant positive correlation with wind speed reduction efficiency (r = 0.817 ***), while ambient wind speed was significantly negatively correlated with windproof benefit (r = −0.690 ***). Among forest types, F2 and PF achieved significantly higher efficiency and lower wind speeds than F1. Intact shelterbelts reached >85% efficiency, while degraded belts fell below 40%. Soil texture acted as the dominant factor controlling soil erodibility: clay, fine sand, and very fine sand increased soil wind erodibility, while coarse sand and gravel suppressed erodibility. Hierarchical clustering analysis of vertical wind speed profiles confirmed that shelterbelts can substantially reduce near-ground wind velocity; compared with shelterbelt types, spatial position (windward side, leeward side, and central zone) exerted a stronger influence on wind field regulation. This study elucidates the internal correlations among shelterbelt spatial configuration, sand-fixing efficiency, and soil wind erodibility, providing scientific support for the optimization of shelterbelt layout in low-elevation arid ecological regions. Full article

The mounting requirement for sustainable construction materials has augmented the development of geopolymer binders incorporating agricultural wastes. Unlike the previous studies on individual agricultural ashes, this study investigates the viability of combined use of sugarcane bagasse ash (SCBA) and jackfruit leaf ash (JLA) in fly ash-ground granulated blast furnace slag (GGBFS)-based geopolymer binders under ambient curing conditions. Five mixtures with varying proportions of SCBA and JLA were evaluated for their fresh (flow, setting time, fresh density and rise in temperature), hardened (compressive strength and flexural strength) and microstructural characteristics (FESEM-EDS, XRD, FTIR and TG/DTG analyses). The incorporation of 10% SCBA and 10% JLA of the total binder (M3 mixture) was found to produce best performing performance, resulting in a maximum 28-day compressive strength of 64.83 MPa and flexural strength of 7.25 MPa, corresponding to increments of 36.5% and 73.0%, respectively, over the control mix. The formation of a dense reaction matrix along with enhanced geopolymerization and thermal characteristics were also observed for the best performing mixture through microstructural studies. The outcome of this investigation reveals that the utilization of agricultural ashes (SCBA and JLA) can be an efficient supplementary aluminosilicate precursor to develop high-performance geopolymer binders. Full article

Climate change influences crop prices through its impacts on agricultural production, costs, consumer and producer behavior, and the market equilibrium. Therefore, this study aims to examine the dynamic relationship between climate variability and date palm producer prices in Saudi Arabia utilizing annual time-series data from 1991 to 2024 and applying a Vector Autoregression (VAR) method to investigate dynamic responses over shorter and longer horizons. The analysis incorporates impulse response functions (IRFs), forecast error variance decomposition (FEVD), and historical decomposition (HD). The empirical findings indicate that date palm producer prices exhibit strong persistence and are predominantly explained by their own innovations in the short run. At horizon 10, date-palm producer-price innovations account for 94.82% of the forecast-error variance, while climatic variables jointly account for approximately 5.18%. Although climate factors’ shocks exert measurable short-run effects on producer prices, these responses diminish over time, indicating that the market effectively absorbs climate-related changes while maintaining persistence. However, FEVD and HD results reveal that the contribution of temperature and relative humidity to producer price fluctuations increases steadily over time, highlighting the growing importance of climate variability in shaping long-term market dynamics. The findings highlight the relevance of considering climate-smart agricultural practices, drought-tolerant date-palm varieties, and climate adaptation and risk-management strategies in the date-palm sector. While these measures were not directly evaluated in the present model, they may contribute to strengthening the sector’s resilience to climatic variability, supporting price stability, and promoting sustainable agricultural development. Their specific effects on price volatility and food security, however, require further empirical investigation. Full article

Cereal–legume forage mixtures provide sustainable agronomic and environmental benefits for arid Mediterranean agricultural systems, but their productivity is often limited by within-field soil spatial variability. Site specific management practices are required to address the yield gaps. This study aimed to identify management zones in a no-till Triticale–Avena–Pea mixture by integrating apparent electrical conductivity (ECa) and NDVI measurements. ECa was mapped using an EM38-MK2 sensor, while NDVI was derived from UAV and Sentinel-2 imagery at four key growth stages. Plant biomass data and soil samples were collected for evaluating and explaining the yield gaps. Using K-means clustering, three management zones were delineated using ECa and NDVI data. Results showed a yield gap of 46% in fresh biomass between high- and low-productivity zones, associated with strong gradients in soil organic matter and total nitrogen availability. The delineation of management zones enabled targeted agronomic interventions, such as adjusting seeding rates in the high-productivity area and prioritizing soil improvement strategies in the low-productivity zone, thereby enhancing input-use efficiency. Full article

Timely computation of vegetation indices from remote sensing imagery would assist in sustainable agriculture monitoring through quick analysis of vegetation state and surface water. However, high-resolution multispectral imagery can be computationally expensive to process, especially on embedded systems. In this research work, we evaluate heterogeneous approaches that aim to enhance the computation of the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) through sequential C++, OpenMP, CUDA and OpenCL on desktop and embedded CPU–GPU platforms. We compare multicore and GPU-based computations while also exploring optimizations of the OpenCL kernels with respect to memory management, loop unrolling and work-group settings. OpenMP increased the image-processing throughput from 211.24 to 500.85 images/s on the desktop platform and from 55.30 to 145.11 images/s on the Odroid XU4. These results correspond to speedups of 2.37× and 2.62×, respectively. These results demonstrate that heterogeneous processing can accelerate vegetation index calculation and provide a computational basis for timely, locally available agricultural monitoring. This capability may support precision agriculture applications, including vegetation stress assessment and water management decisions. Nevertheless, the experiments used offline multispectral images; energy consumption, energy per image, water savings, and onboard UAV performance were not measured. Full article

Biotope mapping provides an essential spatial framework for biodiversity conservation, ecosystem management, and sustainable landscape planning. However, a standardized and transferable GIS-based methodological framework for biotope identification and mapping is still lacking in Türkiye, limiting the systematic integration of biodiversity considerations into spatial planning processes. This study develops an integrated GIS-based biotope mapping framework for Çınarcık District, Yalova Province, Türkiye, integrating Digital Elevation Model (DEM), CORINE Land Cover 2018, Forest Management Plans, stand characteristics, vegetation, floristic, and hydrological data through spatial analyses. Additionally, 30 national and 15 international studies were systematically reviewed to identify the common indicators, data sources, and methodological components used in biotope mapping and to establish the proposed GIS-based framework. The proposed approach identified four main biotope groups (forest, aquatic, agricultural, and urban). Based on ecological similarity and growing environment characteristics, 12 sub-biotope types were identified within the forest biotopes. Forest biotopes were the dominant ecological units, mainly characterized by broadleaved communities dominated by Fagus orientalis, Castanea sativa, Tilia tomentosa, and Quercus petraea. A total of 72 forest stand types were identified, with Fagus orientalis-dominated forests in plateau environments representing the largest sub-biotope type (36.40%). The proposed framework provides a repeatable and transferable, inventory-based methodology that can serve as a preliminary decision-support tool for biodiversity assessment, conservation planning, and sustainable landscape management in forested landscapes with similar ecological characteristics, pending future field-based validation. Full article