Search Results (464)

Facing global problems such as the energy crisis and climate change, in recent years, the bioelectrochemical system represented by plant microbial fuel cell (PMFC) has been widely studied. It is a frontier bioelectrochemical technology that combines plant photosynthesis, rhizosphere microbial metabolism, and electrochemical energy conversion. This paper focuses on the linkage application of PMFC and intelligent sensing technology in the paddy-field environment, systematically expounds the basic composition, working principle, and integration mode of this technology with paddy field ecology, and emphatically analyzes its realization path and application potential in self-powered external sensor deployment, rhizosphere biosensor, and multi-node sensor network integration. The analysis shows that PMFC has the unique advantage of in situ and continuous micro-power generation in flooded rice fields. Its output not only supports the intermittent operation of low-power sensors, but the output electrical signals can also reflect plant stress and environmental conditions, thereby possessing biosensing potential. However, the current system still faces key bottlenecks, such as low power density, easily disturbed electrical signals, and high cost of high-performance electrode materials, which restrict the actual deployment of rice fields. Through the collaborative optimization of electrode interface engineering, microbial community directional control, and low-power sensing fusion strategy, it is expected to promote the transformation of PMFC from principle verification to field intelligent monitoring application. Full article

Rice cultivation commonly employs the continuous flooding (CF) method, which depends heavily on water availability creating anaerobic conditions for methane (CH₄) emissions. Rainfed rice areas rely on precipitation for irrigation, making the system sensitive to climatic variability. This study examines associations between ENSO phases and satellite-observed atmospheric XCH₄ variability over Thailand using GOSAT as the primary long-term dataset from 2012 to 2022, with Sentinel-5P/TROPOMI used as a supporting dataset for recent spatial patterns. The analysis conducted covers three cropping seasons: (1) January–April, (2) May–August, and (3) September–December. The results indicate comparable average atmospheric methane concentrations of 1787.94 ± 11.50 XCH₄ (ppb) during El Niño, 1788.8 ± 11.22 XCH₄ (ppb) in neutral conditions, and 1793.45 ± 10.93 XCH₄ (ppb) during La Niña. The obtained data indicate a seasonal variability, with the highest satellite-observed XCH₄ values found during September–December, corresponding to the main growing period of wet-season rice. The results suggest that climate change amplifies these anomalies through altered precipitation patterns and water availability. Current rice cultivation practices warrant reconsideration, in particular the alternate wetting and drying (AWD) method, offering reduced CH₄ emissions while conserving water resources. This underscores the importance of water management strategies for sustainable rice production and resilience to climate variability. Full article

As the second most important anthropogenic greenhouse gas (GHG), methane (CH₄) has received wide attention in the mitigation of global climate change. China’s Sichuan Basin has been identified as one of the world’s hotspot regions with very high CH₄ emission intensity. Winter-flooded paddies are considered as potential significant sources of CH₄ emissions among various cropping systems in Sichuan. However, current studies are limited to the field scale, and there is a lack of research conducted over a large spatiotemporal scale. Here, we simulated CH₄ emissions from 1980 to 2023 at region scale using the Denitrification–Decomposition (DNDC) model and evaluated the associated climate impact using the radiative forcing-based climate footprint (RFCF) metric. We found that CH₄ emissions have recently decreased, from 0.53 billion tonnes in 2019 to 0.28 billion tonnes in 2023, representing a 47.20% reduction. Moreover, the climate footprint peaked in 2019 at 1.25 mW m⁻² and decreased to 1.08 mW m⁻² in 2023, and the system achieved net zero increase in radiative forcing (RF) in 2020. This means that Sichuan’s winter-flooded paddies no longer contribute to the additional RF in the atmospheric system. Overall, our findings demonstrate that the reduction in CH₄ emissions from winter-flooded paddies has been mainly attributed to a reduction in the cropping area and a decrease in average temperature during the rice growth season. These results provide a scientific basis for region-specific CH₄ mitigation policies and demonstrate how these spatiotemporal changes in CH₄ emissions from winter-flooded paddies in Sichuan can support sustainable agriculture. Full article

Rice (Oryza sativa L.) straw-return can improve soil carbon (C) sequestration, but its adoption in intensive rice systems is limited by short fallow periods (<30 days), which likely lead to incomplete straw decomposition and increase methane emissions under continuous flooding (CF). Brittle rice straw, characterized by lower recalcitrant fiber content and rapid decomposition, may overcome this constraint; however, its environmental performance under alternate wetting and drying (AWD) remains unclear, such as broader C allocation. This 150-day microcosm study evaluated the interaction of straw type (brittle vs. non-brittle) and water management (CF vs. AWD) on greenhouse gas (GHG) emissions, dissolved C production, soil C storage, and aggregate formation in two contrasting paddy soils (sandy loam vs. silty clay loam). Compared with non-brittle straw, brittle straw returns reduced net GHG emissions by approximately 28.4% under CF and 39.6% under AWD. The combination of brittle straw with AWD produced the lowest net GHG emissions (0.61 kg CO₂-eq m⁻²), indicating that intermittent oxygen input effectively mitigated the early decomposition-related emission risk. Brittle straw also increased the concentrations of dissolved inorganic C by 14.2% and nitrate by 64.3% under AWD, suggesting enhanced mineralization and potential inorganic C stabilization. Regardless of straw type, straw return improved soil C stocks by 27.3% in sandy loam and 29.6% in silty clay loam, while also promoting macroaggregate formation. Overall, this study demonstrated that coupling brittle rice straw with AWD can reduce GHG emissions while maintaining soil C benefits, offering a promising residue management strategy for intensive rice cultivation. Full article

To investigate the effects of water-saving irrigation and different straw retention methods on soil CH₄ and N₂O emissions from paddy fields in cold regions and their potential underlying mechanisms, a field experiment was conducted in Qing’an City, Heilongjiang Province. Two water management regimes were set, combined with four straw retention treatments. The static chamber-gas chromatography method was used to monitor CH₄ and N₂O emission fluxes during the entire rice growth period. Meanwhile, soil pH, oxidation–reduction potential (Eh), dissolved oxygen (DO), and dynamic changes in carbon and nitrogen substrates were measured, and the global warming potential (GWP) and greenhouse gas emission intensity (GHGI) were comprehensively evaluated. The results showed that controlled irrigation significantly increased soil dissolved oxygen content and oxidation–reduction potential. Compared with conventional flooding irrigation, total CH₄ emission decreased by more than 50%, while N₂O emission increased by 1.5–2.5 times, exhibiting an obvious divergent correlation with the two gas emission fluxes. Among different straw retention methods, organic fertilizer returning and direct straw returning significantly promoted CH₄ emission by supplying easily decomposable organic carbon. In contrast, biochar, due to its stable carbon structure and favorable pore properties, inhibited CH₄ emission without significantly stimulating N₂O emission. The treatment of controlled irrigation combined with biochar returning (CB) achieved the lowest global warming potential and greenhouse gas emission intensity at 7230.82 kg CO₂-eq/hm² and 0.8054 kg CO₂-eq/kg, respectively, while maintaining high rice yield. Path analysis based on soil physicochemical properties and emission fluxes further revealed that Eh and DO were significantly negatively correlated with CH₄ emission but positively correlated with N₂O emission. Path inference from flux and substrate data indicated that carbon and nitrogen availability were the key factors limiting the denitrification process. In conclusion, the combined application of controlled irrigation and biochar returning can realize the synergistic effect of stable yield and emission reduction in cold-region paddy fields by improving soil aeration and regulating the transformation of carbon and nitrogen substrates, providing a scientific basis for establishing a green and low-carbon rice production technology system for black soil in cold regions. Full article

Non-flooding irrigation is widely promoted as a carbon–water co-benefit strategy in paddy rice, but field-scale trials overlook return flow compensation within irrigation districts and therefore overstate water-saving potential. To reconcile this scale mismatch, we developed a semi-distributed multi-scale water balance model coupled with a carbon footprint and full-component blue–green–grey water footprint framework and applied it across field, district, and provincial scales in Heilongjiang Province—a leading cold-region japonica rice region in Northeast China—using the Qinglongshan Irrigation District on the Sanjiang Plain as the focal case, supported by two growing seasons of field observations and 35 years of provincial records. Under alternate wetting and drying, apparent field-level water savings of 50–60% converge to 33% after return flow correction, implying that field-based indicators overestimate savings by 40–50%. Carbon mitigation is decoupled from water volume: CH₄ suppression dominates total abatement and is governed by drying frequency rather than water saved. At the provincial scale, the water footprint has shifted from grey- to blue-water dominance, suggesting that blue-water efficiency now represents a principal remaining lever for further cold-region carbon–water co-benefits. Two-season coverage and fixed parameter assumptions affect magnitudes but not directions. Water-saving irrigation in cold-region paddy systems should therefore be evaluated at the district scale where data permit, rather than relying solely on field-scale indicators. Full article

Despite its significant water-saving potential, the adoption of alternate wetting and drying (AWD) irrigation remains limited due to infrastructure constraints and intensive manual monitoring requirements. An automated precision irrigation system was developed and tested at the Bangladesh Rice Research Institute research farm in Gazipur, Bangladesh. The system combined ultrasonic water-level sensors, capacitive soil moisture sensors, an Arduino-based microcontroller, a GSM communication module, and solar-powered automatic control gates. Field performance was evaluated following a Randomized Complete Block Design (RCBD) under four irrigation treatments: IRRISAT, IRRI35, IRRI25, and continuous flooding (CF). The first three irrigation treatments were operated using scheduled daily decision windows, in which irrigation actions were automatically triggered based on predefined schedules and sensor threshold values. In IRRISAT, irrigation started when soil moisture dropped slightly below saturation and stopped at a ponding depth of 5 cm, while IRRI35 and IRRI25 were triggered at volumetric soil water contents of 35% and 25%, respectively, with the same upper cutoff of 5 cm ponding depth; CF served as the control. The IRRI35 treatment achieved a high grain yield (7.76 t ha⁻¹) while reducing water use by 28% and energy consumption by 37% compared to CF. Water use efficiency was considerably higher under IRRI35 (9.4 kg ha⁻¹ mm⁻¹) than under CF (6.7 kg ha⁻¹ mm⁻¹). The automated system proved to be reliable and precise in scheduled irrigation control, significantly reducing water use and labor requirements. The findings suggest that large-scale adoption of the system under real-world cultivation conditions could reduce irrigation energy needs and contribute to sustainable water governance in rice production. Full article

This study aims to explore the effects of micro-polluted river water on nitrogen and microbial communities of paddy field soil under different irrigation modes. The experiment was conducted in a water-saving park in Nanjing. By establishing three water quality conditions—clean water, micro-polluted river water, and alternating irrigation—and two moisture conditions—flood irrigation and controlled irrigation—this study investigates the effects of different irrigation patterns on soil nitrogen and microbial communities. The results indicate that, under flood irrigation, the input of micro-polluted river water can effectively alleviate NH₄⁺-N loss during the heading stages of rice growth by 49.3%. Moisture conditions are the primary factor influencing microbial community structure. Although the input of micro-polluted river water reduces community stability, rotation irrigation can increase microbial abundance and enhance network complexity, thereby enhancing the system’s resilience. Redundancy analysis shows that soil moisture, pH, and ion content are the key environmental factors driving microbial distribution. The clean and polluted water rotation irrigation model performs best in maintaining soil nitrogen and microbial health. Rotation irrigation promotes the enrichment of key functional groups, such as Actinobacteria, effectively increasing rice yield. This study provides a theoretical basis for promoting sustainable agricultural production through water resource management. Full article

The cocontamination of arsenic (As) and cadmium (Cd) in agricultural soils poses severe risks to ecosystem stability and food safety because of their high toxicity, mobility, and bioaccumulation potential. However, single amendments often exhibit selective immobilization, which limits their effectiveness for As–Cd-cocontaminated soils. In this study, a sepiolite-supported nanoscale zero-valent iron composite (S-nZVI) was synthesized via liquid-phase reduction, and its remediation performance and mechanisms under different moisture conditions were evaluated. The characterization results confirmed that the nZVI nanoparticles were uniformly dispersed and anchored onto the sepiolite matrix, thus mitigating aggregation and oxidative passivation while increasing surface reactivity. Soil incubation experiments demonstrated that S-nZVI reduced the bioavailability of As and Cd and promoted their transformation from labile to stable fractions under both 50% and 120% water holding capacity (WHC). Under flooded conditions (120% WHC), 0.5% S-nZVI reduced the bioavailable Cd and As concentrations by 52.3–58.7% and 67.4%, respectively, after 120 days. Mechanistically, immobilization was governed by a synergistic “adsorption–reduction–coprecipitation” pathway coupled with pH–Eh regulation. Rice pot experiments further validated the effectiveness of S-nZVI, with the grain As and Cd concentrations reduced by 73.3% and 52.3%, respectively, without impairing plant growth. Overall, S-nZVI provides an efficient strategy for simultaneous immobilization of As and Cd in As–Cd-cocontaminated soils and supports the safe use of polluted agricultural lands. Full article

Nitrous oxide (N₂O) is recognized as a potent greenhouse gas, and 60% of atmospheric N₂O emissions come from cropland soils. Potassium (K) is an important fertilizer for rice paddy fields. K fertilizer decreased the abundance of functional genes mediating nitrification and denitrification processes, thereby mitigating N₂O emissions. However, few studies have explored the effect of K fertilization rates on N₂O emissions and grain yields, as well as the associated soil properties and aboveground N accumulation in paddy fields under different irrigation regimes. This study aimed to propose an optimum combination of K fertilization rate and irrigation regime to increase grain yield while reducing N₂O emissions. Here, a 2-year field experiment using a split-plot design with three replicates was conducted to assess the effect of three K fertilization rates (K₀: 0 kg ha⁻¹, K₇₅: 75 kg ha⁻¹, K₁₅₀: 150 kg ha⁻¹) on N₂O emissions, grain yield, aboveground N accumulation, and soil properties, including soil redox potential (Eh), NH₄⁺, NO₃⁻, soil gene abundance of AOA, AOB, nirK, nirS, nirK/nirS, and nosZ, under continuous flooding irrigation (I_CF) and alternate wetting and drying irrigation (I_AWD). The soil physicochemical properties, the gene abundance and the aboveground N accumulation were evaluated and used to explain how irrigation and K fertilization affect grain yield and N₂O emissions. We found that I_AWD significantly increased N₂O emissions by 38% compared to I_CF, and K fertilizer significantly reduced N₂O emissions by 15% relative to K₀. The effects of I_AWD and K fertilizer on N₂O emissions can be attributed to the combined impact of soil physicochemical properties and the abundance of functional genes governing N₂O emissions. Both irrigation regimes produced equivalent grain yield and aboveground N accumulation. Shifting from I_CF to I_AWD, the increase in N₂O emissions can be mitigated by K fertilization. Moreover, K₇₅ and K₁₅₀ had similar effects in reducing N₂O emissions and yield-scaled N₂O emissions, while K₇₅ had a lower K fertilizer cost and higher K partial factor productivity. Therefore, applying K fertilizer at 75 kg ha⁻¹ under I_AWD is identified as a potentially suitable rate to secure grain yield while effectively mitigating N₂O emissions. Full article

Weed management is crucial for the sustainable production of rice (Oryza sativa L.), although herbicides such as Imazamox (IZX) can persist in soils, posing risks to soils and water resources. This two-year study evaluated the effects of soil physicochemical properties under different irrigation and tillage practices, with and without compost derived from olive mill waste, on IZX behavior. The treatments implemented were as follows: no-tillage and sprinkler (NT-S), conventional tillage and sprinkler (T-S), conventional tillage and flooding (T-F), and the corresponding regimes with compost amendment (NT-SC, T-SC, and T-FC). Sorption–desorption, dissipation, and leaching of the herbicide were assessed. The IZX adsorption was lower under soil collected from sprinkler irrigation, especially in NT-S, while compost reduced the adsorption under T-SC and T-FC. Dissipation was faster in NT-S and T-S soils, in which the half-life of IZX declined up to 30% relative to T-F. Furthermore, compost further accelerated herbicide dissipation, correlating with higher organic carbon content and microbial activity. The IZX losses via leaching were significantly reduced in soils irrigated by sprinkler in combination with compost, with values ≤ 48.5% of the IZX applied. These results indicate that the irrigation regime and organic amendment strongly influence soil physicochemical properties, then influencing the environmental fate of IZX. Integrated management using sprinkler irrigation and compost can mitigate IZX persistence and leaching, improve soil health, and reduce the risk of water contamination, representing a sustainable strategy for rice cultivation. Full article

Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ET_lys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature and biophysical inputs (e.g., NDVI and fractional cover) to derive spatially explicit ET, while AquaCrop provided continuous daily simulations between flight dates. Direct lysimeter-based validation indicated high agreement for AquaCrop (R² = 0.85; RMSE = 0.26 mm d⁻¹; MBE = 0.01 mm d⁻¹) and moderate agreement for UAV–TSEB (R² = 0.66; RMSE = 0.81 mm d⁻¹; MBE = 1.01 mm d⁻¹). Model intercomparison further showed consistent temporal dynamics of ET (R² = 0.70; RMSE = 1.35 mm d⁻¹) and robust partitioning of crop transpiration (R² = 0.79; RMSE = 0.99 mm d⁻¹) and soil evaporation (R² = 0.76; RMSE = 1.03 mm d⁻¹) while revealing a systematic divergence under near-complete canopy cover: AquaCrop tended to suppress evaporation, whereas UAV–TSEB detected residual evaporation from the flooded surface. Overall, the results highlight the complementarity of both approaches—UAV–TSEB as a spatial diagnostic tool and AquaCrop as a temporally continuous simulator—providing a robust framework for ET monitoring, flux partitioning, and water-use-efficiency assessment in water-scarce rice systems. Full article

This study addresses the challenges of coordinating spatio-temporal water allocation to optimize water productivity and reduce carbon emissions in water resource management, particularly the lack of high-resolution, integrated optimization frameworks capable of simultaneously tackling water scarcity and greenhouse gas (GHG) emissions. We propose a modeling approach for large-scale regional rice irrigation that explicitly represents the physical-process-based relationships among irrigation water, yield, and methane (CH₄) emissions. Using GIS, a grid-based simulation domain was constructed at a 500 m × 500 m resolution, and the GIS-DSSAT and GIS-DNDC models were employed to simulate yield and CH₄ emissions under varying irrigation amounts. The Random Forest algorithm—selected for its ability to capture complex nonlinear interactions—was used to establish the response surfaces linking irrigation water, yield, and CH₄ emissions. A spatio-temporal irrigation optimization model was then developed to simultaneously reduce CH₄ emissions and enhance water productivity. This methodology was applied to the Sanjiang Plain in Heilongjiang Province, where the NSGA-II algorithm was used to derive optimal irrigation schemes for rice cultivation across 408,264 grid cells. The results revealed quadratic nonlinear relationships between irrigation water amount, yield, and CH₄ emissions. Compared to the conventional irrigation practice in the region, which typically involves 15–20 flood irrigation events per season, the optimized irrigation schedule comprised 7–14 events—with 12 events accounting for 42% of the cases—and an irrigation duration ranging from day 137 to 256. This led to a 10.3% reduction in total irrigation volume, a 9.6% decrease in CH₄ emissions per unit yield, and a 21.8% increase in water productivity. This study provides valuable decision support for optimizing regional water allocation and developing rice cultivation strategies that improve productivity while reducing emissions. Full article

Anaerobic germination tolerance (AGT) is a critical adaptive trait for rice establishment in flood-prone environments and direct-seeded systems. Here, we identified and validated the quantitative trait locus qAG2.1 for AGT and introgressed it into the elite lowland rice variety CR Dhan 801 through marker-assisted backcross breeding. The introgressed lines exhibited significantly improved germination under anaerobic conditions, demonstrating the effectiveness of qAG2.1 in a high-yielding genetic background. While CR Dhan 801 showed a low anaerobic germination percentage (17.6%), the donor ARC10424 exhibited 82.6%, and the best-performing introgressed line (22009-3) achieved 49.2%. Importantly, the improved lines maintained agronomic performance comparable to CR Dhan 801 under non-stress conditions, indicating minimal yield penalty. To gain mechanistic insight, the qAG2.1 interval was dissected in silico to prioritise candidate genes putatively associated with AGT. This analysis highlighted genes linked to ethylene biosynthesis and signalling (e.g., OsACO3, OsERF109), abscisic acid biosynthesis (OsNCED1), gibberellin homeostasis (OsGA2ox9), trehalose metabolism (OsTPS5, OsTPP1), detoxification of anaerobic by-products (OsALDH2A), and water transport (OsPIP1;3). Collectively, these results validate qAG2.1 as a further deployable locus for improving anaerobic germination in elite rice backgrounds and provide a set of putative candidate genes for future functional characterisation. Full article

Nitrogen (N) application rates and irrigation regimes are key factors determining rice yield and N use efficiency. To evaluate the effects of different irrigation regimes and N application rates on rice yield and N uptake, a four-year field experiment was conducted from 2021 to 2024 at the Qing’an National Irrigation Experimental Station in Heilongjiang Province. The experiment included two irrigation regimes (C: Controlled irrigation and F: Flooded irrigation) combined with four N application rates (N0: 0 kg N·ha⁻¹, N1: 82.5 kg N·ha⁻¹, N2: 110 kg N·ha⁻¹, and N3: 137.5 kg N·ha⁻¹). The results showed that, considering the same N application rate, C promoted dry matter accumulation by 3% to 9% and total N accumulation by 4.1% to 25.5% in the aboveground parts of rice compared to F. Under the same irrigation regime, total N accumulation in the aboveground parts of rice increased with N application rate and then plateaued. Regarding the distribution of N among organs, the proportion of panicle N relative to total N in the aboveground parts of rice followed an initial increase and subsequent decline as N input increased, resulting in the nitrogen harvest index (NHI) reaching its maximum under the moderate N treatment (N2). Overall, controlled irrigation significantly improved the NHI and AE, whereas the moderate N treatment (N2) further increased the NHI and promoted greater N allocation to panicles. Therefore, combining C with a moderate N application rate can enhance N use efficiency and markedly improve the internal N partitioning pattern. Full article