Search Results (526)

Organic micropollutants in agricultural soils pose significant ecological and health risks. This study conducted the first large-scale, integrated non-targeted screening and targeted analysis across China’s major food-producing regions. Using high-resolution mass spectrometry, 498 micropollutants were identified, including pesticides, industrial chemicals, pharmaceuticals, personal care products, food additives, natural products, and emerging contaminants. Spatial analysis revealed strong correlations in pesticide detections between Henan and Hebei, as well as between Hebei and Shandong, indicating pronounced regional similarities in pesticide occurrence patterns. Concentrations of 50 quantified micropollutants showed clear spatial variability, which was associated with precipitation, water use, and agricultural output, reflecting climate–agriculture–socioeconomic synergies. Greenhouse soils accumulated higher micropollutant levels than open fields, driven by intensive agrochemical inputs, plastic-film confinement, and reduced phototransformation. Co-occurrence patterns indicated similar pathways for personal care products, industrial chemicals, and pesticides, whereas natural products and pharmaceuticals showed lower levels of co-occurrence due to crop-specific exudates, fertilization, and rainfall-driven leaching. Among cropping systems, orchard soils had the highest micropollutant accumulation, followed by paddy and vegetable soils, consistent with frequent pesticide use and minimal tillage. Risk quotients indicated moderate-to-high ecological risks at over half of the sites. These results reveal complex soil pollution patterns and highlight the need for dynamic inventories and spatially differentiated, crop- and system-specific mitigation strategies. Full article

Uniform application of fertilizers and pesticides continues to dominate global agriculture despite significant spatial variability in soil and crop conditions. This mismatch results in avoidable yield gaps, excessive chemical waste, and environmental pressures, including nutrient leaching and greenhouse gas emissions. The integration of Artificial Intelligence (AI) and Remote Sensing (RS) has emerged as a transformative framework for diagnosing this variability and enabling site-specific, climate-responsive management. This systematic synthesis reviews evidence from 2000–2025 to assess how AI–RS technologies optimize agrochemical efficiency. A comprehensive search across Scopus, Web of Science, IEEE Xplore, ScienceDirect, and Google Scholar were used. Following rigorous screening and quality assessment, 142 studies were selected for detailed analysis. Data extraction focused on sensor platforms (Landsat-8/9, Sentinel-1/2, UAVs), AI approaches (Random Forests, CNNs, Physics-Informed Neural Networks), and operational outcomes. The synthesized data demonstrate that AI–RS systems can predict critical soil attributes, specifically salinity, moisture, and nutrient levels, with 80–97% accuracy in some cases, depending on spectral resolution and algorithm choice. Operational implementations of Variable-Rate Application (VRA) guided by these predictive maps resulted in fertilizer reductions of 15–30%, pesticide use reductions of 20–40%, and improvements in water-use efficiency of 25–40%. In fields with high soil heterogeneity, these precision strategies delivered yield gains of 8–15%. AI–RS technologies have matured from experimental methods into robust tools capable of shifting agrochemical science from reactive, uniform practices to predictive, precise strategies. However, widespread adoption is currently limited by challenges in data standardization, model transferability, and regulatory alignment. Future progress requires the development of interoperable data infrastructures, digital soil twins, and multi-sensor fusion pipelines to position these technologies as central pillars of sustainable agricultural intensification. Full article

To address the issue of low fertilizer proportioning accuracy in irrigation and fertilization systems due to neglecting the influence of target ions in raw water, this study designed a high-precision online automatic water–fertilizer mixing device that can directly mix raw water (without water purification treatment) with fertilizer stock solution. This device is capable of preparing mixed fertilizer solutions containing N, K, and Ca elements. It employs ion-selective electrodes and flow meters for online detection and feedback of target ion concentrations in the fertilizer solution and flow rate information, and adopts an online fertilizer mixing control strategy that uses a constant raw water flow rate and a fuzzy PID control method to dynamically adjust the pulse frequency of metering pumps, thereby changing the injection volume of nutrient solution. Simulation and experimental analyses show that the piping system of the device is reasonably designed, ensuring stable and smooth fertilizer injection. The temperature-compensated concentration detection models for the three target ions in the fertilizer solution, constructed using a stepwise fitting method, achieve average relative detection errors of 1.94%, 1.18%, and 2.87% for K⁺, NO₃⁻, and Ca²⁺, respectively. When preparing single-element or mixed fertilizer solutions, the device achieves an average steady-state error of no more than 4% and an average steady-state time of approximately 40 s. Compared with deionized water, the average relative errors for potassium ions, nitrate ions, and calcium ions when preparing fertilizer solutions with raw water are 1.33%, 1.12%, and 1.19%, respectively. Compared with the theoretical errors of fertilizer preparation with raw water, the fertilizer proportioning errors of this device for potassium ions, nitrate ions, and calcium ions can be reduced by a maximum of 10.55%, 66.84%, and 62.71%, respectively, which is superior to the performance requirements for water–fertilizer integration equipment specified in the national industry standard DG/T 274-2024. Additionally, the device achieves accurate and stable fertilizer proportioning with safe and reliable operation during 6 h of continuous operation. This device significantly reduces the impact of raw water on fertilizer proportioning accuracy, improves the adaptability of the device to irrigation water sources, and provides theoretical basis and technical support for water-fertilizer integration systems in cost-sensitive agriculture. Full article

Moringa oleifera has been recognized for its adaptability, nutritional richness, and multipurpose potential, particularly in resource-limited regions. While most research has focused on its leaves, moringa seeds remain underutilized despite their broad applicability in the environmental, agricultural, and food sectors. This review systematically and critically examines recent scientific literature on the use of M. oleifera seeds across these fields, emphasizing their functional value, applications, and challenges for sustainable use. The review follows the SALSA methodology (Search, Appraisal, Synthesis, and Analysis), a structured and iterative framework designed to identify, evaluate, and integrate scientific evidence from diverse sources. The analysis encompasses three main areas: (i) water treatment, where moringa seed extracts have achieved turbidity removal efficiencies above 90% and effective adsorption of dyes and potentially toxic elements; (ii) agriculture, where seed-derived fertilizers improve soil fertility, nutrient availability, and crop yield compared to conventional inputs; and (iii) the food industry, where moringa seed derivatives enhance the nutritional, functional, and antioxidant properties of bakery, beverage, and oil-based products. Overall, M. oleifera seeds emerge as a versatile and sustainable resource with proven potential as a natural coagulant, biofertilizer, and nutraceutical ingredient. By integrating findings from both English and Spanish language studies, this work highlights their contribution to sustainable water management, agricultural productivity, and food innovation, while emphasizing the need for further safety evaluation and process optimization to support large-scale application. Full article

Groundwater is one of the main sources of water supply in tropical developing countries; however, its integrated management is often constrained by limited hydrogeological information and increasing anthropogenic pressures on aquifer systems. This study presents the numerical modeling of groundwater flow in the Neogene–Quaternary aquifer system of the Middle Magdalena Valley (Colombia), focusing on the rural area of Puerto Wilches, which is characterized by strong surface–groundwater interactions, particularly with the Yarirí wetland and the Magdalena River. A three-dimensional model was implemented and calibrated in FEFLOW v.8.1 under steady-state and transient conditions, integrating both primary and secondary data. The dataset included piezometric levels measured with water level meters and automatic loggers, hydrometeorological records, 21 physicochemical and microbiological parameters analyzed in 45 samples collected during three field campaigns under contrasting hydrological conditions, 79 pumping tests, detailed lithological columns from drilled wells, and complementary geological and geophysical models. The results indicate a predominant east–west groundwater flow from the Eastern Cordillera toward the Magdalena River, with seasonal recharge and discharge patterns controlled by the bimodal rainfall regime. Microbiological contamination (total coliforms in 69% of groundwater samples) and nitrate concentrations above 10 mg/L in 21% of wells were detected, mainly due to agricultural fertilizers and domestic wastewater infiltration. Particle tracking revealed predominantly horizontal flow paths, with transit times of up to 800 years in intermediate units of the Real Group and around 60 years in shallow Quaternary deposits, highlighting the differential vulnerability of the system to contamination. These findings provide scientific foundations for strengthening integrated groundwater management in tropical regions under agroindustrial and hydrocarbon pressures and emphasize the need to consolidate monitoring networks, promote sustainable agricultural practices, and establish preventive measures to protect groundwater quality. Full article

This study assessed six tomato (Solanum lycopersicum L.) cultivars within an integrated solar-powered closed hydroponic system in Al Dhaid, UAE (25°16′11.2″ N, 55°55′52.2″ E). The system combined an insect-proof net house, closed hydroponics, root-zone cooling, ultra-low-energy drip irrigation, and a cost-effective solar-powered reverse osmosis (RO) desalination unit to address salinity constraints. The cultivars, selected for their adaptability to controlled environments in the UAE, were evaluated for yield, water-use efficiency (WUE), and fertilizer-use efficiency (FUE). Among them, Torcida recorded the highest mean yield (0.619 kg/m²/harvest), WUE (27.1 kg/m³), FUE (26.5 kg fruit/kg fertilizer), and marketable fruit ratio (66.3%), followed by Roenza, Eviva, and SV 4129 TH; Lamina was intermediate, while Saley, a bushy type, produced the lowest yield. The top cultivars achieved cumulative yields exceeding 7 kg/m²—surpassing regional open-field benchmarks (4–5 kg/m²; 3–6 kg/m³). Compared with conventional cooled hydroponic greenhouses (3.5 kg/plant; 8 kg/m³), the system demonstrated similar productivity using three times less water. The RO unit produced water at baseline 1.05 USD/m³—58–68% below regional tariffs—while minimizing reliance on grid electricity and mechanical cooling. Overall, the integrated solar-powered hydroponic–RO model proved technically reliable, resource-efficient, and economically viable, offering a scalable solution for sustainable vegetable production in hyper-arid regions. Full article

Big data and artificial intelligence technologies are driving a paradigm shift in smart farming, yet intelligent decision-making faces critical bottlenecks. At the data level, challenges include fragmentation, high acquisition costs, and inadequate secure sharing; at the model level, issues involve regional heterogeneity, weak adaptability, and insufficient explainability. To address these, this paper systematically reviews global research to establish a theoretical framework spanning the entire production cycle. Regarding data governance, trends favor federated systems with unified metadata and layered storage, utilizing technologies like federated learning for secure lifecycle management. For decision-making, approaches are evolving from experience-based to data-driven intelligence. Pre-harvest planning now integrates mechanistic models and transfer learning for suitability and variety optimization. In-season management leverages deep reinforcement learning (DRL) and model predictive control (MPC) for precise regulation of seedlings, water, fertilizer, and pests. Post-harvest evaluation strategies utilize spatio-temporal deep learning architectures (e.g., Transformers or LSTMs) and intelligent optimization algorithms for yield prediction and machinery scheduling. Finally, a staged development pathway is proposed: prioritizing standardized data governance and foundation models in the short term; advancing federated learning and human–machine collaboration in the mid-term; and achieving real-time, ethical edge AI in the long term. This framework supports the transition toward precise, transparent, and sustainable smart agriculture. Full article

High-efficiency farmland production is essential for ensuring national food security and promoting sustainable agriculture in China. This paper aims to systematically analyze the challenges in building a new-quality farmland production system driven by innovative productive forces that emphasizes large-scale operations, optimal integration of farming components, and the application of modern technologies and intangible inputs. To achieve this aim, we conducted a comprehensive review and synthesis of the current literature, national policy documents, and agricultural statistics. Our analysis identifies key challenges, including limited water and land resources, outdated machinery and practices, a shortage of skilled farmers, insufficient innovation, and underdeveloped policy and support systems. Based on this analysis, we propose a series of integrated strategies to enhance farmland productivity. These recommendations include improving soil fertility, developing new crop varieties, promoting modern management models, training farmers in advanced technologies, innovating agricultural policies and infrastructure, and establishing accessible farm credit and insurance systems. We conclude that by integrating the six key elements of quality farmland, superior varieties, skilled farmers, modern technologies, sound policies, and supportive credit systems, China can successfully transition from labor-intensive to technology- and information-intensive farming models, thereby boosting the productivity and resilience of its farmland production systems. Full article

Nitrate in groundwater (GW) poses a public-health concern in semi-urban northeastern Saudi Arabia, where households rely on untreated wells. We measured nitrate in 45 wells spanning treated/untreated commercial stations, private domestic wells, and agricultural wells, and linked contamination severity to age-specific risks using the Nitrate Pollution Index (NPI), Chronic Daily Intake (CDI), and Hazard Quotient (HQ). Nitrate ranged from 12 to 380 mg·L⁻¹ (35% > 50 mg·L⁻¹ World Health Organization (WHO) guideline), with untreated private and agricultural wells most affected. Based on NPI, 65% of wells were “clean”, while 18% showed significant to very significant pollution. Infants and children had the highest exposure: CDI frequently exceeded the oral reference dose (1.6 mg·kg⁻¹·d⁻¹), and HQ > 1 occurred in 56% (infants) and 51% (children) of samples from untreated sources. Treated stations consistently achieved lower nitrate and HQ < 1. Sensitivity analysis identified nitrate concentration as the dominant risk driver, followed by ingestion rate, with body weight mitigating the dose. The findings suggest that monitoring based solely on compliance may underestimate risks in sensitive age groups, thereby advocating for immediate actions such as fertilizer management, septic system upgrades, extension of treatment to vulnerable households, and community monitoring. The integrated NPI–CDI–HQ framework provides a replicable methodology for associating groundwater contamination with demographic-specific health risks in arid, water-stressed regions. Full article

Effective management of organic and inorganic fertilizers is vital for sustaining productivity in intensive cropping systems. This four-year study (2012–2015) assessed the immediate and residual effects of cattle corralling combined with mineral fertilizer on maize in northern Benin using a strip-plot design with five corralling levels No corralling(NM), immediate application (C0) and residual effects one (C1), two (C2), and three (C3) years after the initial corralling and three fertilizer rates F0 (no fertilizer), F1 (50% of the recommended rate) and F2 (the recommended rate). Cattle corralling doubled maize yield from 2.0 to 4.0 t ha⁻¹ and increased net profitability from 384 to 1000 USD ha⁻¹ compared to non-manured plots. Water-use efficiency increased from 3.4 to 6.8 kg ha⁻¹ mm⁻¹, and soil organic carbon increased nearly fourfold (3.0 to 11.2 g kg⁻¹). Residual effects declined over time without mineral inputs (C0 > C1 > C2 > C3 > NM); however, these benefits were sustained or enhanced when combined with fertilizer (C3 > C2 > C1 > C0 > NM). Fertilizer responses were minor in C0 and C1 but significant in C2 and C3, demonstrating a strong organic–inorganic synergy. Nutrient recovery efficiency was initially lower in recently corralled plots but surpassed non-manured levels after two years. These results confirm that integrating livestock corralling with optimized fertilizer use strengthens soil fertility, resource efficiency, and profitability, providing a sustainable intensification pathway for maize systems in sub-humid, low-fertility regions. Full article

The sustainable operation of hydroponic systems depends on maintaining the chemical stability of circulating nutrient solutions and preventing the accumulation of toxic compounds. The accumulation of phytotoxic ammonium, heavy metals, and organic metabolites in recirculating nutrient solutions remains one of the key challenges limiting the efficiency, sustainability, and scalability of hydroponic cultivation. This review provides a comprehensive comparative analysis of zeolites, activated carbons (ACs), and their functionalized and composite forms as key sorbents for nutrient management, contaminant removal, and environmental safety in hydroponic cultivation. Natural zeolites, with their well-defined crystalline structure and high ion-exchange selectivity toward ammonium and heavy metal cations, enable effective NH₄⁺/K⁺ balance regulation and phytotoxicity mitigation. ACs, characterized by high specific surface area and tunable surface chemistry, complement zeolites by offering extensive adsorption capacity for organic compounds, root exudates, and pesticide residues, thereby extending the operational lifespan of nutrient solutions and improving overall system performance. Further advancements include the integration of zeolites and ACs with two-dimensional (graphene, g-C₃N₄) and three-dimensional (MOF, COF) frameworks, yielding multifunctional materials that combine adsorption, ion exchange, photocatalysis, and nutrient regulation. Transition-metal modification, particularly with Fe, Mn, Cu, Ni, and Co, introduces redox-active centers that enhance sorption, catalysis, and phosphate stabilization. The comparative synthesis reveals that the combined application of zeolite- and carbon-based composites offers a synergistic strategy for developing adaptive and low-waste hydroponic systems. From a techno-economic and environmental standpoint, the judicious application of these materials paves the way for more resilient, efficient, and circular hydroponic systems, reducing fertilizer and water consumption, lowering contaminant discharge, and enhancing food security. This systematic review was conducted according to the PRISMA 2020 guidelines. Relevant studies were identified through Scopus, Web of Science, and Google Scholar databases using specific inclusion and exclusion criteria. Full article

Agricultural non-point source pollution (AGNPSP) is one of the core challenges facing global water environment management. Existing research mainly focuses on post-event estimation of pollution loads and source analysis, while studies on proactive risk warning for watershed non-point source pollution are relatively limited, especially those that integrate with agricultural production practices. Therefore, this study takes the River Tongyang Watershed as the research object and establishes a fertilization warning and regulation model based on short-term meteorological data. First, it simulates the migration and transformation processes of pollutants within the watershed under different meteorological conditions and analyzes their spatiotemporal evolution characteristics. Then, combined with real-time water quality monitoring data at the lake inlet, it calculates the residual environmental capacity for pollutants in the river water. Finally, based on this environmental capacity and the farmland area, it back-calculates the maximum safe fertilization amount for each plot under different meteorological scenarios to achieve precise fertilization management. When the planned fertilization amount does not exceed this maximum safe value, environmental risks are within a controllable range; if exceeded, fertilization should be proportionally reduced to prevent non-point source pollution. The results indicate that this model can accurately predict the concentration trends of non-point source pollutants and can develop differentiated fertilization strategies based on rainfall scenarios. The “fertilization determined by water” decision-making framework established in this study provides a technically significant pathway for shifting watershed agricultural non-point source pollution management from passive treatment to active prevention. Full article

Conventional agricultural practices, based on intensive irrigation and heavy fertilizer and pesticide inputs, are increasingly incompatible with climate change, soil degradation, and sustainability goals. Hydrogels have emerged as promising soil amendments to improve water and nutrient management, and fall broadly into two categories: synthetic polyacrylate/polyacrylamide-based systems and natural biobased hydrogels derived from polysaccharides such as alginate, cellulose, and chitosan. The latter, often obtained from agro-industrial residues, offer biodegradable and potentially lower-impact alternatives to persistent synthetic matrices. This review analyzes recent advances in the design and application of nanocomposite hydrogels in agricultural crops, with emphasis on high-value systems such as tomato, chili pepper and maize. Representative studies show that hydrogel–nanofertilizer formulations can increase soil water retention in tomato from ~55–56% to ~78–79%, nearly double swelling capacity in wheat, reduce irrigation requirements by around 15% in legumes, and improve plant biomass by ~30–40% under drought conditions. In parallel, nanocomposite hydrogels loaded with micronutrients, phytochemicals or biostimulants can enhance nutrient uptake, provide 36–80% protection against Fusarium wilt, and reduce postharvest pathogen growth by up to ~90%, while in some cases improving the nutraceutical quality of fruits. These outcomes illustrate a dual mechanism of action in which the hydrogel matrix acts as a micro-reservoir that buffers water and nutrients, whereas nano- and phytochemical components operate as physiological eustressors that modulate plant defense and metabolism. Finally, we discuss environmental and translational challenges, including hydrogel biodegradation pathways, the long-term fate and ecotoxicity of released nanoparticles, regulatory uncertainty, and market and field acceptance. Addressing these gaps through integrative agronomic, ecotoxicological, and regulatory studies is essential to ensure that nanocomposite hydrogels evolve into truly sustainable smart carriers for fertilizers, pesticides, and biostimulants in future cropping systems. Full article

Water and nitrogen are fundamental factors for maintaining yield stability and achieving efficient resource utilization in wheat–maize rotation systems. Based on 131 publications indexed in the Web of Science Core Collection from 2010 to 2025, this review systematically synthesizes current knowledge on how irrigation, nitrogen application, and soil management jointly regulate water–nitrogen migration and transformation processes during wheat and maize growth. The results indicate that irrigation practices influence nitrogen transformation and availability by altering the temporal and spatial distribution of soil moisture; optimized nitrogen application strategies align nitrogen release with crop demand at critical growth stages; and the use of soil amendments improves soil physicochemical and biological conditions, thereby enhancing water retention and nitrogen stability. These three management measures exhibit strong complementarity and synergistic effects. Integrating irrigation, fertilization, and soil management can not only improve wheat and maize yields but also harmonize resource use efficiency with ecological sustainability. This review highlights the potential and pathways of integrated management practices for enhancing water and nitrogen use efficiency and ensuring food security, providing theoretical support and practical guidance for developing efficient and sustainable region-specific water–nitrogen management systems. Full article

Foxtail millet (Setaria italica L.), a typical dryland crop, has a high nutrient uptake capacity, which can lead to rapid soil nutrient depletion. Establishing soil conservation strategies compatible with the high yield traits of hybrid millet is crucial. Although organic fertilization and deep tillage are proven measures for maintaining soil productivity, their effects on dryland crops like millet remain understudied. This study investigated Zhangzagu 10 under five treatments: rotary tillage without fertilization (RT), rotary tillage with compound fertilizer (RTC), rotary tillage with organic fertilizer (RTO), deep tillage with organic fertilizer at 20–30 cm (DT1O), and deep tillage with organic fertilizer at 30–40 cm (DT2O). Soil physicochemical properties were measured at seven sampling periods and four tillage layer depths in a two-year field experiment. Compared to RT, RTO increased organic carbon and total nitrogen in mechanically stable macro-aggregates (0–20 cm) by up to 141.2% and 135.14%, respectively. Corresponding increases in water-stable aggregates reached 105.9% for organic carbon and 193.33% for total nitrogen. RTO also enhanced the pH buffering capacity of the topsoil while reducing soil bulk density and solid volume fraction in the surface layer during the late growth stages of foxtail millet. Combining organic fertilization with deep tillage (DT1O and DT2O) further optimized subsoil (20–40 cm) structure, increasing macro-aggregate content and stability, with effects intensifying at greater tillage depths. The integration of organic fertilization and deep tillage synergistically improved soil structure and nutrient distribution, offering a sustainable approach for dryland foxtail millet production. Full article