Search Results (9,559)

Reliable quantification of crop evapotranspiration (ET_c) at field resolution is a prerequisite for evidence-based irrigation scheduling in agricultural systems subject to nitrate leaching constraints. This study presents and evaluates a multi-sensor data fusion framework integrating MODIS Terra (500 m, daily) and Sentinel-2 (10–20 m, 5-day revisit) imagery to generate cloud-robust, daily ET_c maps for an 87.5 ha irrigated maize field in Nyírbátor, Hungary, during the 2020 and 2021 growing seasons. Three gap-filling strategies for missing Sentinel-2 NDVI observations were systematically compared: (i) co-regionalisation with cokriging, (ii) local time series interpolation of MODIS pixel centres using ordinary kriging, and (iii) a median time series of cotemporal MODIS pixels—a novel approach developed to suppress sub-pixel spectral contamination from roads and irrigation infrastructure. For field-mean temporal reconstruction, the median approach consistently outperformed the alternatives (adjusted R² = 0.81, NRMSE = 0.15–0.17; pixel-wise correlation 0.70–0.85), effectively filtering heterogeneous landscape artefacts. Daily crop coefficients (K_c) derived from fused NDVI time series via the FAO-56 framework yielded ET_c ranging from 0.99 mm day⁻¹ (initial stage) to 6.40 mm day⁻¹ (peak crop development). Seasonal precipitation–ET_c deficit analyses revealed contrasting patterns: near balance in 2020 versus an 85 mm mid-season deficit at critical nodes in 2021, demonstrating the potential utility of spatially explicit daily ET_c monitoring for irrigation scheduling. These deficit estimates represent irrigation demand indicators; a complete water balance would additionally require measured irrigation volumes, soil water storage changes, deep percolation, and surface runoff data. The methodology provides a proof-of-concept framework for EU Nitrates Directive compliance monitoring, relying solely on freely available satellite data. Independent ET_c validation is required before operational deployment, and transferability to other crops and regions requires validation across contrasting pedoclimatic conditions. Full article

Freshwater is essential for sustaining the health of humans, animals, and ecosystems; however, agricultural activities remain a major source of water pollution globally. This review examines how crop production, livestock farming, and aquaculture contribute to water contamination, the effectiveness of current European policies, and the potential of sustainable mitigation strategies. Evidence from the research identified pesticides, herbicides, veterinary antibiotics, nutrient runoff, aquaculture effluents, and microplastics as the primary agricultural pollutants affecting surface and groundwater quality. These contaminants have been linked to ecosystem degradation, biodiversity loss, endocrine disruption, antimicrobial resistance, and adverse human health outcomes. Despite extensive regulatory frameworks, including the Water Framework Directive, Nitrates Directive, Farm to Fork Strategy, and European Green Deal, significant implementation and monitoring challenges remain. Current evidence indicates that only 40% of European surface waters achieve “good” ecological status, highlighting persistent water quality concerns across the region. The review further identified precision irrigation, Internet of Things (IoT)-enabled monitoring, biopesticides, hydroponic systems, and integrated multi-trophic aquaculture as promising solutions for reducing agricultural impacts on water resources. However, barriers, including high implementation costs, technological limitations, and inconsistent policy enforcement, continue to hinder widespread adoption. Overall, the findings demonstrate that while existing policies have improved water governance, stronger regulatory enforcement, greater investment in sustainable technologies, and increased adoption of nature-based solutions are required to reduce agricultural water pollution. An integrated approach combining technological innovation, policy support, and sustainable farming practices is essential to protect freshwater resources and ensure long-term environmental sustainability. Full article

Desertification is a serious environmental challenge in regions with desert landscapes, such as the Khorezm Oasis in the Republic of Uzbekistan. Low precipitation rates and shortages of irrigation water have driven dynamic changes in desert-related land use and land cover (LULC) classes, threatening environmental and food security. This study aims to assess desertification safety levels in the Khorezm oasis using geospatial technologies to better understand spatiotemporal dynamics and to support sustainable agricultural management. A multi-criteria decision-making (MCDM) approach was used for desertification assessment. Annual mean values of key indicators—land surface temperature, vegetation index, groundwater (GW) depth, wind speed, soil erodibility (K-factor), precipitation, normalized enhanced sand index, maximum air temperature, and LULC classes—were analyzed for the period 2000–2023. The results indicate that the normalized enhanced sand index and LULC classes exert the strongest influence on desertification processes. Areas classified as high to very high desertification hazard are predominantly concentrated in the Republic of Karakalpakstan, covering a total area of 2345.65 km². Ongoing water shortages in the Amu Darya River basin pose a significant risk of further expansion of desertified areas. The findings provide valuable insights for regional land management and desertification mitigation planning. Full article

Cloud-dependent irrigation platforms can support remote monitoring, but their use in precision fertigation is limited when local decisions must be made quickly and reliably. Network delay, temporary disconnection, and the use of single-point measurements may all reduce the ability of a system to respond to spatial variation in soil moisture and nutrient demand. In this work, an edge-controlled precision fertigation system was developed by combining multi-parameter soil sensing, spatial task scheduling, and a 6-DOF robotic manipulator. The ESP32 controller runs a preemptive FreeRTOS scheduler, allowing sensor acquisition, inverse-kinematics calculation, and pump actuation to be handled as separate tasks. A Kalman filter was used to smooth soil moisture measurements, and a hysteresis-based control strategy was adopted to reduce false triggering and repeated pump switching. To improve fertigation safety, a hardware–software interlock was added so that fertilizer delivery is always accompanied by water delivery. Hardware-in-the-Loop simulation and a 14-day field deployment were used to evaluate the system. The controller achieved an end-to-end latency of less than 38 ms and maintained operation during network interruptions through cached local parameters. After calibration, the robotic end-effector positioning error was reduced to ±2.4 mm. The hysteresis strategy lowered daily pump cycling by 71%. Based on prototype duty-cycle data and seasonal extrapolation, the projected seasonal water use and fertilizer demand were 44% and 38% lower, respectively, than those estimated for a uniform application. These values should be interpreted as model-based projections rather than direct season-long measurements. During 72 h of continuous operation, no Modbus faults were observed, and RTOS heap fragmentation remained stable. Overall, the results suggest that edge-based deterministic control can provide a practical route for precision fertigation where both spatial variability and intermittent connectivity must be considered. Full article

Global atmospheric N₂O concentrations have risen to 335 ppb, with agricultural soils serving as a major emission source and rice paddies accounting for approximately 11% of agricultural N₂O emissions. Rice–crab co-culture has been widely adopted because of its potential to increase and stabilize crop yields; however, the underlying mechanisms of N₂O mitigation and the synergistic effects of crab bioturbation with water and nitrogen management remain unclear. Therefore, in this study, we conducted a two-year field experiment in Zhaodong, Heilongjiang Province, China, to elucidate the N₂O mitigation effects of rice–crab co-culture under water and nitrogen regulation and the associated driving mechanisms. The results showed that rice–crab co-culture significantly reduced N₂O emissions. Specifically, the N₂O flux decreased by 19.9%, while cumulative N₂O emissions decreased by 19.8%. Under the combined regulation of water and nitrogen management, the mitigation effect on N₂O emissions was further enhanced, with a reduction of up to 30.8%. Regarding environmental factors, crab activity combined with shallow wet irrigation reduced soil water content and increased surface temperature. These changes promoted the transformation of nitrogen from inorganic forms to microbially assimilable forms, increasing the microbial nitrogen content by approximately 29.5%. Meanwhile, soil enzyme activities changed significantly: the activities of urease, sucrase, and protease increased, whereas nitrate reductase activity decreased. Structural equation modeling showed that the indirect effect of management practices was much greater than the direct effect, accounting for 63% of the total effect. Nitrogen transformation was the core mitigation pathway, characterized by the conversion of inorganic nitrogen into microbial biomass nitrogen, which reduced substrate availability for nitrification and denitrification. Enzyme activity regulation served as a secondary pathway, mainly through the inhibition of nitrate reductase activity. Overall, the rice–crab system achieved sustained N₂O reduction by improving soil aeration and jointly regulating substrate limitation and weakening nitrogen transformation capacity. Full article

Accurate field-scale surface soil moisture (SSM) measures are important for agricultural water management. Conventional satellite SSM products remain too coarse for within-field applications. Here, we developed sequence-aware deep learning models for growing-season SSM estimation by fusing data from Sentinel-1 C-band SAR, harmonized Landsat-8/Sentinel-2 (HLS), and local ancillary datasets. We assembled a multi-source dataset on Sentinel-1 overpass time for 2016–2024 (May–September), yielding 1469 samples and 65 features per sample, including SAR and optical features, meteorological data, soil texture and bulk density, topography, crop labels, irrigation-likelihood flag, and irregular-time-step encoding. We compared long short-term memory (LSTM) and temporal convolutional neural network (TCN) architectures together with attention-augmented variants, including feature attention (FA), temporal attention (TA), and the combined feature–temporal attention (FTA). Models were trained and tested on seven years of data and were validated based on a temporal generalization using combined data of a wet year (2016) and a dry year (2023). The best model, FTA-TCN, achieved R² = 0.851, RMSE = 0.024 m³.m⁻³, and MAE = 0.020 m³.m⁻³ on the withheld validation years, outperforming the base LSTM (R² = 0.422; RMSE = 0.053 m³.m⁻³; MAE = 0.043 m³.m⁻³) and the base TCN (R² = 0.746; RMSE = 0.034 m³.m⁻³; MAE = 0.022 m³.m⁻³). Shapley additive explanations (SHAP) analysis indicated that antecedent precipitation and short-term rainfall accumulations were dominant forcings, while soil texture, elevation, incidence angle, and vegetation indices modulated SSM variability. Satellite-derived features accounted for ~28.5% of aggregated SHAP importance. Overall, the results show that dual-attention temporal convolution can capture field-scale SSM dynamics across wet and dry seasons when satellite signals are coupled with local soil-meteorological-management context. Full article

The aim of study was to investigate the effects of foliar application of salicylic acid on cellular damage, physiological indices, and growth of dwarf cashew cultivated under salt stress. A 5 × 4 factorial scheme, resulting from the combination of five ECiw levels (0.4, 1.2, 2.0, 2.8, and 3.6 dS m⁻¹) and four salicylic acid concentrations (control—0, 1, 2, and 3 mM), with three replications. Irrigation water salinity of 3.6 dS m⁻¹ inhibited the synthesis of photosynthetic pigments, gas exchange, chlorophyll a fluorescence, and the growth of dwarf cashew plants. Foliar application of salicylic acid at concentrations ranging from 0.1 to 2.5 mM mitigated the effects of salt stress on relative water content, stomatal conductance, internal CO₂ concentration, CO₂ assimilation rate, instantaneous carboxylation efficiency, variable fluorescence, quantum efficiency of photosystem II, stem diameter at the grafting point, and plant height, while also reducing electrolyte leakage and initial fluorescence in dwarf cashew plants at 180 days after transplanting. Salicylic acid (SA), when applied at appropriate concentrations, alleviates the deleterious effects of salt stress on the growth and physiological performance of dwarf cashew plants. Full article

The Temperature-Vegetation-Precipitation Drought Index (TVPDI) performs poorly in complex terrain due to Normalized Difference Vegetation Index (NDVI) saturation and land surface temperature (LST) retrieval inaccuracies. To address this, we adopted an improved TVPDI (ITVPDI) by incorporating Leaf Area Index (LAI) and the land surface–air temperature difference (LST−T). By using multi-source data from 2000 to 2022 in Xinjiang, China, we validated ITVPDI and analyzed drought dynamics. Results show: (1) ITVPDI correlates better with solar-induced chlorophyll fluorescence (SIF) (r = 0.17) and the moisture index (MI) (r = 0.22) than the traditional TVPDI, demonstrating superior performance in densely vegetated and topographically complex areas. (2) Drought frequency ranked as follows: severe (31.55%) > moderate (29.04%) > extreme (23.44%) > mild (15.94%). Mild and moderate droughts occurred in Northern Xinjiang and the Tianshan Mountains, while severe and extreme droughts clustered around the Tarim Basin and Eastern Xinjiang desert margins. As drought intensity increases, its center of gravity shifts “from north to south” and “from mountains to basins.” (3) ITVPDI showed a slight upward trend over the 23-year period, with autumn experiencing the most severe drought (mean ITVPDI = 0.293). (4) A mean Hurst index of 0.468 indicates weak anti-persistence, suggesting the current wetting trend may reverse, and increasing future drought risk. The ITVPDI proves to be a robust tool for drought monitoring in arid and semi-arid regions with complex terrain. This study provides crucial scientific support for regional water resource allocation, precision irrigation, and collaborative drought resistance and disaster mitigation in Northwest China. Full article

Rice cultivation is a major source of methane (CH₄) emission in the agricultural sector, with a significantly higher global warming potential than carbon dioxide. Accurate and scalable quantification of CH₄ from rice paddies is essential for carbon accounting. This study presents an automated framework for estimating rice CH₄ emissions from irrigated paddies in the central plain of Thailand, integrating multi-sensor Synthetic Aperture Radar (SAR) observations with the IPCC methodology. The framework combines Sentinel-1 C-band SAR time series for phenological detection, ALOS-2 PALSAR-2 L-band full-polarimetric SAR for water regime classification, and IPCC water-scaling factors corresponding to Continuous Flooding, Single Drainage, or Multiple Drainage regimes. Evaluated across five stratified holdout sets, the phenology detection algorithm achieved planting and harvesting date Mean Absolute Errors of 6.1 ± 1.4 and 8.3 ± 1.7 days, with a 97.0% ± 2.7% operational detection rate. Water regime classification employed rice growth stage-specific Support Vector Machine classifiers with Radial Basis Function kernels (SVM-RBF), achieving per-stage test Balanced Accuracy ranging from 0.59 to 0.89. End-to-end integration using a four-track counterfactual decomposition yielded a full-pipeline mean absolute error of 18.5 ± 4.5 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$ (21.4% of the mean ground-based CH₄ calculation) and a mean bias of 3.5 ± 5.8 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$. Water level classification was confirmed as the dominant algorithmic uncertainty source, while the IPCC Tier 1 emission factor structural range (−32% to +48% of the default) exceeded all algorithmic errors combined. The proposed framework provides a spatially explicit approach for integrating multi-frequency SAR data into IPCC-compliant methane estimation, supporting Monitoring, Reporting, and Verification applications. Full article

Drought stress significantly constrains broccoli (Brassica oleracea L.) productivity by impairing growth, photosynthesis, and yield. Seed priming with ascorbic acid (AsA) has shown promise in enhancing early seedling performance; however, its effects on head development and yield under water deficit remain limited. This greenhouse pot experiment evaluated four seed treatments: non-primed control, water-primed control, 1 mg L⁻¹ AsA, and 10 mg L⁻¹ AsA under two irrigation regimes: 100% and 50% field capacity. Growth, physiological traits, biochemical responses, and yield were assessed. AsA priming significantly (p < 0.05) enhanced plant height, net photosynthesis, and chlorophyll content under both water regimes. Under 100% FC, water priming significantly increased canopy length, whereas under 50% FC, only AsA priming produced a significant increase relative to the non-primed control (p < 0.05). Biochemical responses further showed that 10 mg L⁻¹ AsA significantly (p < 0.05) increased chlorophyll a and chlorophyll b under 50% FC compared with the non-primed control. Proline accumulation was reduced by 10 mg L⁻¹ AsA, but this reduction was significant (p < 0.05) only under 100% FC. Under 100% FC, 10 mg L⁻¹ AsA significantly (p < 0.05) increased total phenolic content compared with the non-primed control. Total flavonoid content was significantly (p < 0.05) increased by 1 and 10 mg L⁻¹ AsA compared with the control, while both water priming and AsA priming significantly (p < 0.05) increased carotenoid content and reduced H₂O₂ accumulation relative to the non-primed control, irrespective of watering regime. Total yield per plant, measured on a fresh weight basis, significantly (p < 0.05) increased with increasing AsA concentration, with 10 mg L⁻¹ AsA enhancing yield by 37.8% relative to the water-primed control and by 70.5% relative to the non-primed control, independent of water regime. Percentage dry weight was unaffected by AsA treatment. Overall, AsA seed priming potentially enhanced physiological resilience and fresh yield of broccoli under water-limited conditions, indicating its potential as a low-cost strategy for drought mitigation. Full article

Diluted solar saltworks effluent, applied via fertigation, can contribute to circular economy strategies by recycling nutrients and reducing the environmental impact associated with the disposal of hypersaline effluents. However, its adoption in drip irrigation systems is still limited, as are its effects on emitter performance. This study investigated whether electronic pulses could mitigate emitter clogging by applying dilution of saltworks bittern. Three systems (freshwater + saltworks bittern + electronic pulses; freshwater without electronic pulses; and freshwater + saltworks bittern without electronic pulses) were evaluated in Mossoró, Brazil, using three emitter designs over 0–320 h. Water physicochemical properties and hydraulic performance were monitored, and deposits were characterized by SEM—EDS and FTIR. Electronic pulses did not change bulk water chemistry but were associated with lower total suspended solids. Clogging risk was mainly related to alkaline pH, high electrical conductivity, and elevated Ca²⁺ and Mg²⁺ concentrations, which kept effluent dilutions within a high-risk range. Untreated effluent reduced irrigation uniformity, whereas treated effluent performed similarly to supply water. Electronic pulses reduced deposit complexity and the severity of critical events but did not eliminate clogging, and responses dependent on the emitter labyrinth’s geometry. Full article

A field experiment was conducted at the Agronomy Field Laboratory of Bangladesh Agricultural University to evaluate the effects of arbuscular mycorrhizal fungi (AMF) inoculation and foliar supplementation of nitrogen (N) and phosphorus (P) on the performance of maize (Zea mays L.) under irrigated and rainfed conditions. The experiment followed a randomised complete block design with two levels of AMF (inoculated and non-inoculated) and four foliar treatments (no N and P, N only, P only, and combined N + P). The recommended dose of fertiliser (RDF) was applied as a soil application to all treatments. AMF inoculation significantly increased grain yield by 8.1% under rainfed and 10.0% under irrigated conditions compared with non-inoculated plants. Foliar application of N and P, especially when they were applied together, significantly improved yield components, including cob length, number of grains per cob, and 1000-grain weight. The highest grain yield (9.08 t ha⁻¹ under rainfed and 10.91 t ha⁻¹ under irrigated conditions) was obtained from the combined treatment of AMF inoculation and foliar N + P application. Redundancy analysis (RDA) and linear mixed-effects modelling (LMM) confirmed that water availability was the dominant factor controlling maize productivity, while AMF inoculation exhibited a stronger independent effect than foliar fertilisation. Under rainfed conditions, the treatment responses were reduced, and maize responded better to foliar N application in combination with AMF than combined N + P application. These findings indicate that the integrated use of AMF and foliar nutrient management enhances maize productivity, but optimal combinations depend strongly on moisture regimes. Full article

Sweet sorghum is a promising crop for bioethanol production in semi-arid regions, due to its tolerance to drought and salinity, where conventional energy crops face limitations. This study aimed to evaluate the agronomic performance of sweet sorghum irrigated with treated domestic wastewater (TDW) and its application as a substrate for bioethanol production under high-gravity (HG) and very-high-gravity (VHG) fermentation conditions. Field experiments were conducted in the Brazilian semi-arid using a 5 × 5 full factorial design consisting of five irrigation depths (40–160% crop evapotranspiration, ETc) combined with five potassium fertilization doses (0–80 kg·ha⁻¹), totaling 25 treatments. Agronomic performance, biomass production, and total reducing sugar accumulation were evaluated in both plant cane and ratoon crops. Sweet sorghum juice was subsequently combined with sugarcane molasses and fermented using Saccharomyces cerevisiae in batch and fed-batch processes. Irrigation with TDW associated with moderate potassium fertilization enhanced plant development, biomass yield, and sugar accumulation, particularly at irrigation depths between 100% and 130% of ETc, reaching up to 1908 kg·ha⁻¹ of TRS. Bioethanol production achieved fermentation efficiencies of 91.83% and 84.80% and productivities of 4.63 and 4.21 g·L⁻¹·h⁻¹ under HG and VHG conditions, respectively. These findings indicate that sweet sorghum irrigated with TDW is a promising feedstock for bioethanol production under high-gravity fermentation conditions while supporting the use of alternative water resources in semi-arid environments. Full article

Introduction: Agricultural water scarcity and cadmium (Cd) contamination threaten global food security. Reclaimed water (RW) and partial root-zone alternate irrigation (PRA) offer possible solutions, but their synergistic effects on Cd-contaminated soils remain unclear. Objective: This study evaluated the impacts of PRA with RW on Cd-polluted tomato-growing soils. Methods: A pot experiment was conducted with 5 Cd levels (0.30–2.74 mg/kg, 5 replicates each). Soil properties, enzyme activities, Cd fractions, and 16S rRNA microbiome were analyzed. Results: PRA with RW increased rhizosphere pH by 0.42 units (p < 0.01), decreased EC by 18.7% (p < 0.05), and available Cd by 12.3% (p < 0.05). Catalase activity rose by 27.47% (p < 0.05), while sucrase and urease decreased by 32.1% and 28.5% (p < 0.01). Beneficial Actinobacteria (+8.26%) and Proteobacteria (+4.64%) were enriched, and Bacillus was reduced by 11.8%. Flavisolibacter (r = 0.802, p < 0.001) and Nocardioides (r = 0.572, p < 0.001) were key genera. Conclusions: PRA with RW reduces Cd bioavailability and ecological risks, providing a sustainable strategy for mildly/moderately polluted farmland soil. Full article

Groundwater is one of the basic requirements for life, economic and social developments in the Bazo River catchment, Rift Valley, Southern Ethiopia. In the study area, availability of water is faced with several problems, such as quality issues due to high levels of fluoride in some samples, spring scarcity in the lowlands, unprotected river water used for drinking, and high demand for good quality water. The aim of this study was to investigate the hydrogeochemical characteristics and to evaluate groundwater quality for domestic and irrigation uses. Thirty-four primary groundwater samples were collected from the field and analyzed in the water quality lab of Arba Minch University. Two water quality indices (WQI and EWQI), a variety of irrigation water quality indices, and GIS-based spatial analysis were utilized in this study. Cations were present in the descending order of Na > Ca > Mg > K > Fe, and anions were HCO₃⁻ > Cl > SO₄ > NO₃⁻ > F. Excepting two samples (BH8 and SP3), the water samples were acceptable for drinking. Sodium, TDS, and fluoride levels were over the limit of drinking water in BH8 and SP3. Rock–water interaction, cation exchange, and silicate mineral weathering were the main hydrogeochemical reactions that controlled groundwater composition in the area, based on Gibb’s diagram, chloro-alkaline indices, and major ions ratios. Groundwater facies were identified as Ca.HCO₃, Na.HCO₃ and mixed Ca-Na/Ca.Mg.Na.HCO₃ types using a Piper plot. The water quality index was computed, and its spatial variations were mapped using GIS. About 82.35% of groundwater samples were excellent for drinking use and 94.12% (SAR) of groundwater were acceptable for irrigation. These study results are useful to help develop inclusive strategies and interventions to address groundwater quality aspects in the study area, underlining the significance of managing and monitoring water resources. The findings underscore the need for effective management and monitoring strategies to ensure sustainable groundwater resources in the Bazo River catchment. Full article