Search Results (798)

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

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

Calcium alginate is an anionic polysaccharide that forms an ionically crosslinked hydrogel network with encapsulation properties to nucleic acids and nutrients for the amelioration of osmotic stress, ion toxicity and nutrient imbalance in saline–alkali soils. Traditional soil reclamation methods, including salt leaching, incorporation of organic matter, and gypsum application, are water-intensive under a changing climate, ultimately necessitating transformative bio-based solutions for food security. Calcium alginate-based biohydrogel represents a versatile platform with a tunable macromolecular architecture, ionic crosslinking via an “egg box” mechanism and potentially promising to deliver engineered co-encapsulated nutrients and genetically modified cargoes. The mannuronic (M) and guluronic (G) acid (M/G) ratios govern ion exchange capacity, rheological behavior and release kinetics in saline- and alkali-stressed environments. Recent studies on alginate-based nutrient encapsulation showed reduced oxidative damage and a 15–50% increase in plant-available water. The irrigation intervals extended from 7 to 14 days and yield gains by 24% in wheat, with comparable improvements in maize, tomato, rice and cotton. Calcium alginate hydrogels encapsulated salt tolerance genes (HKT1, SOS1, AVP1) encoding proteins mainly involved in Na⁺ retrieval from xylem, Na⁺ extrusion from root cells and vacuolar Na⁺ sequestration, which have achieved yield gains of 40 to 75% across wheat, rice and maize. Future research should focus on optimizing mechanical strength, crosslinking chemistry and smart bioencapsulation strategies for sustainable development so that crops are capable of withstanding variable climate stresses. Full article

Sustaining rice productivity under the dual constraints of freshwater scarcity and low-temperature stress represents a pressing challenge for high-latitude japonica rice systems worldwide. There is an urgent need to develop coupled irrigation–agronomic management strategies that jointly safeguard yield stability and water use efficiency (WUE) in cold-region rice production. In this study, a two-year field experiment was conducted in 2024–2025 on albic soil (Albic Luvisols, WRB; θfc 38.2% v/v, pH 5.80, clayey texture with poor permeability and a propensity for subsurface waterlogging) in the Sanjiang Plain, Heilongjiang Province, China (47°15′ N, 133°28′ E), with nine coupled “irrigation regime × auxiliary practice” treatments, comprising conventional continuous flooding, four-level controlled irrigation (CI) at lower thresholds of 60%, 70%, 75%, and 80% θfc, and their combinations with film mulching (FM) or a humic-acid-based soil amendment (SA). An interpretable machine-learning diagnostic framework was developed, with elastic net (EN) as the primary analytical model and random forest (RF) as a nonlinear control, to simultaneously identify core yield predictors and outlier treatments. The principal findings were: (i) The soil-amendment-coupled 75% θfc CI treatment (SACI) increased grain yield by 12.3% and reduced water input by 17.0% relative to conventional continuous flooding, with WUE reaching 1.801 kg m⁻³, a 35.3% gain over the control (p < 0.05); these improvements were consistent across both individual years (year × treatment interaction: p = 0.601; inter-year rank correlation ρ = 0.967). Lowering the CI threshold below 75% θfc significantly reduced grain yield through diminished effective-panicle retention. (ii) Multi-method consensus analysis (Kendall’s W = 0.871, p < 0.01) identified root volume at the milk stage as the most strongly and consistently associated statistical predictor of yield formation, with convergent mechanistic support from independent rhizosphere evidence (Eh, TTC reductive activity). Definitive causal validation awaits isotope-tracing experiments. (iii) The film-mulching × continuous-flooding treatment (FMCG) was diagnosed as a yield-response outlier (permutation test p = 0.003), three in situ rhizosphere measurements (redox potential, root TTC-reducing activity, and rhizosphere temperature) supported the proposed mechanism of hot–anoxic rhizospheric inhibition. Methodologically, this study develops a four-level evidence convergence framework that integrates intra-model self-consistency, cross-model (EN vs. RF) consensus, independent rhizosphere evidence, and distribution-free permutation testing, with Jackknife+ conformal prediction and companion Monte Carlo simulations (1000 replicates) used to quantify the reliability boundaries under small-sample conditions (n = 27). These findings provide an evidence-based irrigation–soil co-management strategy for cold-region rice production in Northeast China, and the proposed diagnostic paradigm offers a generalizable, reliability-quantified methodological template for interpretable small-sample modeling in multifactorial coupled field experiments. Full article

Sustainable rice production requires management strategies that reduce drainage-related nitrogen export while maintaining grain yield under increasingly constrained water and labor conditions. This study evaluated a controlled-irrigation-based integrated management regime in direct-seeded and mechanically transplanted rice under production-field conditions in the lower Yangtze River region, China. The optimized regime combined threshold-based controlled irrigation, functional basal fertilizer, and key-stage foliar regulation, whereas the traditional treatments followed local conventional flooding and fertilization practices. Drainage-related total nitrogen (TN) export was mainly associated with rainfall or irrigation-overflow events after fertilization. Compared with the corresponding traditional treatments, optimized management reduced irrigation input by 28.5% and 26.4%, cumulative drainage volume by 54.8% and 46.5%, and monitored-event TN export load by 63.6% and 60.0% in mechanically transplanted and direct-seeded rice, respectively. Grain yields reached 10,088 and 9870 kg ha⁻¹ in Opt-MT and Opt-DS, increasing by 6.5% and 7.2%, respectively. The optimized treatments also reduced chalky grain rate and chalkiness degree, although head rice rate did not improve synchronously. These findings provide field-based evidence that integrated management may help coordinate monitored drainage-related nitrogen-export mitigation, water-saving irrigation, and yield maintenance under similar production-field conditions. Full article

Rice production is under increasing threat from adverse climatic trends that exacerbate water scarcity and compromise food safety. The need to transition toward water-saving irrigation is urgent, as is the requirement of addressing the dual burden of selenium (Se) deficiency and arsenic (As) toxicity. This 3-year field study (2020–2022) is the first to evaluate the effects of integrated water-saving irrigation. Permanent flood irrigation (Flood) or alternate wetting and drying was used, in which fields were reflooded when the soil matric potential reached −20 kPa (Reflood-20) and −70 kPa (Reflood-70); the effects of foliar Se biofortification at 15 g Se ha⁻¹ with sodium selenate (15-Se) or no Se (No-Se) on rice production and Se and As accumulation were also investigated. The results identified the Reflood-20 regime as the optimal strategy, achieving 36% water savings without significant grain yield penalties while enhancing grain quality. Foliar Se application successfully increased the dehulled grain Se content by 10.7-fold, effectively meeting human dietary requirements. The As contents were decreased by 27.6% due to water restriction, and an additional 10% loss was observed because of Se supplementation. Analysis of the straw also showed a 23.5% decrease in As and a 5.7-fold increase in Se. Consequently, the synergy between moderate deficit irrigation and Se biofortification provides a robust, cost-effective framework for the large-scale production of safer, nutrient-dense rice, reconciling resource efficiency with food security. Full article

The quality of rice grain impacts milling yield, market acceptance, and product value. Physical quality is determined by many traits, such as chalkiness, whiteness, vitreous whiteness, caryopsis length, and width. Breeding for these traits is challenging due to their quantitative nature, environmental effects, and time and labor requirements to evaluate these traits. The digital grain analyzer (S21) equipment determines rice grain physical quality by image-based analysis; however, its use remains restricted. Thus, here we aimed to evaluate S21 efficiency to determine the physical quality of rice grains and estimate the genetic diversity of the trait using a Brazilian panel of 152 irrigated rice genotypes as a working model. We accessed total whiteness, vitreous whiteness, chalkiness degree, chalky grain rate, white belly, grain length, width, and length/width ratio. Our results demonstrated that S21 allowed the characterization of the genotypes according to physical traits, facilitating grouping and separation of accessions and correlation analyses between quality traits. It was also possible to estimate the heritability of quality traits. S21 was efficient in characterizing the physical quality of rice grains and determining their genetic diversity. The equipment is an effective tool exhibiting potential application by breeder programs. Full article

Alternate wetting and drying (AWD) irrigation reduces CH₄ emissions from flooded rice but amplifies N₂O pulses; identifying candidate phenological windows for the remote screening of greenhouse gas (GHG) fluxes remains challenging with small datasets. In a single-site, single-season exploratory study at INIA Vista Florida (Lambayeque, Peru), eight UAV flights were paired with eight PlanetScope SuperDove scenes ($|\Delta |\le 1$ d) and closed-chamber CH₄, N₂O and CO₂ fluxes under four water regimes (CF, AWD₅, AWD₁₀, AWD₂₀; 96 sub-plot × date observations). Multivariate explanatory power was assessed by bootstrap Ridge regression on each sensor’s native predictors (VI + GLCM + $T_{\mathrm{mean}}$ for the UAV, VI for PlanetScope). Maximum tillering (79 DAS) emerged as a candidate UAV window, ranking in the top three for all gases through GLCM textures, whereas PlanetScope peaked at Mid-boot and Late-boot (103–107 DAS), with median ${\widetilde{R^2}}_{\mathrm{UAV}}$ at $0.34$–$0.71$ and ${\widetilde{R^2}}_{\mathrm{Planet}}$ at $0.20$–$0.60$. Nested Leave-One-Plot-Out (LOPO) validation gave $R_{\mathrm{CV}}^2$ between $+0.57$ and $+0.69$ for four of six platform × gas combinations (UAV-CH₄ and Planet-N₂O stayed weak), and $T_{\mathrm{mean}}$ was decisive for N₂O on the UAV ($\Delta R^2=+0.48$). Repeating the stage selection inside every LOPO fold preserved the leading combinations and their ranking. These exploratory windows and sensor-native descriptors need multi-site, multi-season validation before operational use. Full article

Given the mounting pressure on agricultural water resources in China, which poses a threat to agricultural production safety, this study focuses on Hunan Province and analyzes five major crops over the period 2012–2022. Using a water footprint (WF) accounting method, it quantifies grey water from non-point source pollution and optimizes planting structures under 5%, 10%, and 15% water-saving scenarios. The results indicate that crop water footprints per unit mass follow the descending order: oilseeds, leaf tobacco, rice, fruits, and vegetables. Regarding water footprint components, green water footprint accounts for the largest proportion, playing a dominant role in crop water use, followed by grey water footprint. Blue water footprint and irrigation losses contribute the least. After optimization, under the 5% and 10% water-saving scenarios, the cultivated areas for rice, oilseeds, and leaf tobacco decreased compared to 2021, while those for vegetables and fruits increased. Under the 15% water-saving scenario, all crop planting areas were reduced relative to 2021. The optimized crop planting structure enhanced water use efficiency by 0.35%, 0.58% and 0.77%, respectively, under water-saving scenarios of 5%, 10% and 15%. These results provide a scientific basis for sustainable agricultural water management in Hunan Province. 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

Rice cultivation in climate-sensitive regions necessitates adaptive irrigation and nutrient management strategies to enhance resource utilization efficiency and mitigate operational uncertainty. This study investigated the operational feasibility of an Internet of Things (IoT)-based monitoring and recommendation system for real-time soil moisture and nutrient-related operational monitoring in large-scale rice farming environments in Thailand. An integrated IoT-assisted monitoring and recommendation framework comprising sensing, communication, analytics, and recommendation components was developed and evaluated under practical field-deployment conditions. The system incorporated soil moisture monitoring and nutrient-related operational sensing, cloud-based data processing, machine learning-assisted prediction, and mobile notification services to support irrigation and fertilizer management. A comparative evaluation between conventional and IoT-assisted management conditions revealed lower irrigation water use (947.38 vs. 7638.38 m³/ha), reduced fertilizer utilization (41.40 vs. 347.56 kg/ha), and lower production costs (4230.88 vs. 30,664.69 THB/ha) under IoT-assisted conditions. Average profit also increased from 2357.68 to 23,920.00 THB/ha. User evaluation indicated high overall satisfaction (mean = 4.28/5.00). The findings suggest that integrating IoT-based sensing, machine learning-assisted prediction, and optimization-driven recommendation workflows within a unified field-deployment framework may improve adaptive irrigation management, resource-allocation efficiency, and operational decision support under climate-sensitive rice cultivation environments. Full article

As climate change worsens, irrigation modernization has become critical for better water distribution and maintaining rice production in the face of increasing water constraints. However, there remains a gap in quantification regarding the environmental trade-offs between pump-managed and gravity-based irrigation systems, especially in integrated assessments that relate economic performance, carbon emissions, and water use. This study used an integrated framework of water productivity (WP), consumptive water footprint (WF), carbon footprint, and eco-efficiency to compare gravity-based and pump-managed systems in the Don Chedi Operation and Maintenance Project, Thailand, from 2021 to 2023. The results showed no significant differences in WP and WF between systems. WP averaged 0.39 kg m⁻³ during the wet seasons and 0.54 kg m⁻³ during the dry seasons, while the WF averaged 2517 m³ t⁻¹ and 1854 m³ t⁻¹, respectively. These findings indicate that pump-managed irrigation enhanced operational flexibility and yield stability but did not substantially improve water use efficiency. However, compared with the gravity-based system, the pump-managed system produced much greater carbon emissions, with total carbon footprints ranging from 1.252 to 1.333 tCO₂eq t⁻¹, or five times higher in the irrigation process. Eco-efficiency metrics rose by up to 8.11% despite this environmental burden, indicating enhanced economic resilience amid fluctuating water conditions. These results show a recurring trade-off between low-carbon agricultural development and irrigation modernization. The study therefore emphasizes the importance of integrating renewable energy and low-carbon technologies into pump-based irrigation systems to support climate-resilient and sustainable agricultural transitions. Full article

Alternate wetting and drying (AWD) is a crucial water-saving irrigation strategy in rice production, yet its regulatory mechanisms during drought–rewatering cycles remain unclear, particularly across recovery stages. Using a polyethylene glycol (PEG-6000) hydroponic system, we analyzed physiological, metabolomic, and transcriptomic responses of Oryza sativa L. ssp. japonica under control, continuous drought, and rewatering treatments. The net photosynthetic rate (P_n) recovered within one day after rewatering, and subsequently exceeded control levels, indicating a photosynthetic compensatory effect. In contrast, instantaneous water-use efficiency (WUE) showed only a transient increase before declining thereafter and remaining lower than under continuous drought, revealing an asynchronous recovery in which carbon assimilation precedes the recovery of transpiration. Metabolomic analysis indicated a shift from drought-induced accumulation to recovery-driven metabolic reprogramming, with coordinated up-regulation of central carbon metabolism and chlorophyll biosynthesis. Decreases in citrate, malate, and glutamate suggested their sustained utilization to support nitrogen assimilation and chlorophyll synthesis. Transcriptomic data further revealed large-scale reprogramming during late recovery, including up-regulation of nitrogen assimilation genes (e.g., NIA, NiR), linking carbon–nitrogen coordination with photosynthetic compensation. Overall, these results demonstrate that stage-specific integration of physiological recovery, metabolic restructuring, and transcriptional regulation underlies AWD-induced efficiency and identify early rewatering as a critical window for optimizing WUE. Full article

Reclaiming saline–alkaline soil is critical for food security and land expansion. While paddy rice is the key pioneer crop for remediation, the soil fertility–yield relationship remains poorly understood. To optimize remediation strategies, this study evaluated soil fertility under 16 agronomic treatments—integrating irrigation quality, fertilizer regimes, and soil amendments—across three rice growth stages (tillering, heading, and maturity) in the Yellow River Delta using the minimum data set (MDS), integrated soil fertility index (SFI), and random forest models. Saline water irrigation increased soil salinity by 24.6%, while straw returning and desulfurization gypsum reduced salinity by 18.3% and 22.7%, respectively. Straw, biochar, and desulfurization gypsum significantly influenced soil organic carbon (SOC), total nitrogen (TN), inorganic nitrogen (NH₄⁺-N, NO₃⁻-N), and available phosphorus (AP), with effects varying across growth stages. Growth-stage-specific MDS indicators were significantly correlated with SFI based on the total data set (R² = 0.70, 0.65, and 0.81, p < 0.01), and stage-specific SFI was significantly positively related to rice yield. Notably, heading-stage SFI, although relatively low, explained the highest yield variance (R² = 0.51, p < 0.01) and prediction accuracy (%IncMSE = 25.22), especially under conventional NPK combined with full straw incorporation and desulfurization gypsum. These findings highlight the critical role of heading-stage soil fertility in regulating rice production, providing a targeted nutrient management blueprint for saline–alkaline paddy fields in the Yellow River Delta. Overall, this study offers a reliable scientific template to enhance yield and promote sustainable agriculture in comparable saline–alkaline paddy fields globally. 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