Search Results (86)

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

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

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

Water-level monitoring in rice paddies supports sustainable farming, responsible water management, and greenhouse gas emission mitigation. SAR-based remote sensing is an effective alternative for estimating water levels, especially in regions where optical observations are limited. This study evaluates ten ALOS-2/PALSAR-2 L-band SAR-derived polarimetric parameters for their contribution and effectiveness in water-level estimation across rice-growing phases using random forest regression in the Subang District, which is one of the largest rice-yield areas in West Java, Indonesia. Overall, L-band polarimetric information is clearly related to water-level dynamics throughout the rice-growing cycle, confirming its strong potential for quantitative water-level retrieval. The highest estimation accuracy was achieved by integrating all polarimetric parameter groups (MAE = 1.37 cm, RMSE = 1.79 cm, R² = 0.52, r = 0.73), indicating that no single group can adequately represent the complex scattering mechanisms governing water-level variability across an entire cropping season. Variable importance analysis shows a relatively uniform contribution (7.63–12.90%), suggesting synergies across parameters in water-level estimation. Phase-specific evaluation further reveals that Phase 2, corresponding to the vegetative-to-generative transition, is the optimal temporal window for L-band SAR-based water-level retrieval due to enhanced double-bounce scattering and reduced signal saturation. While Phase 2 data maximizes physical sensitivity and correlation, whole-phase modeling provides greater robustness and lower absolute errors, making it more suitable for L-band SAR-based operational water-level monitoring applications. Full article

Alternate Wetting and Drying (AWD) is a proven water-saving irrigation technique that reduces irrigation water use and methane emissions from rice cultivation. The emission reduction achievable through AWD irrigation practices represents a significant opportunity for credits generation, particularly for the major rice-producing countries. To capitalize on this opportunity, a scalable, reliable, and cost-effective information system for AWD irrigation monitoring, reporting, and verification (MRV) is urgently needed. However, most existing MRV systems depend on manual data collection or software systems driven by field-based observation. Satellite remote sensing, derived from different tools and techniques, has achieved considerable traction in agriculture monitoring. This study attempts to develop a remote sensing and Internet of Things (IoT)-based system for large-scale AWD irrigation detection and monitoring as a potential tool for the MRV system. IoT sensor-based water level measurement, L-band PALSAR-2 full polarimetric data, and intensive field survey data were integrated and analyzed. Three study sites in the Naogaon District of Bangladesh, one of the major rice-growing regions, were selected as the study area. The PALSAR-2 full-polarimetric data were collected, radiometrically and geometrically corrected, and converted into the backscattered coefficient (Sigma-naught) value. Using the full-polarimetric channel of VV, VH, HH, and HV, the Freeman–Durden three-component decomposition, surface scattering, double-bounce, and volume scattering were constructed to assess the irrigation water condition of the rice paddy field. IoT sensors data, field survey data, and three-component data on 8 different dates and a total of 704 fields during the rice growing period were subsequently analyzed and cross-calibrated. The results showed that surface scattering and double bounce are more sensitive to irrigation water status, while volume scattering primarily responds to plant height changes. By leveraging the backscatter characteristics of these three components, a Random Forest classifier was applied to classify AWD and non-AWD irrigated paddy fields. Classification accuracy achieve 94% in early crop growth stages and declined to 80% during dense canopy stages. These findings offer a reliable and scalable approach to documenting water regime management with direct applicability to carbon emissions reduction verification and carbon credits claims. Full article

Arsenic (As) accumulation in rice (Oryza sativa L.) is considered a major environmental and food safety concern, particularly in flooded agroecosystems where reducing conditions mobilize As from soils. Portugal is one of Europe’s rice producers, especially in the Tejo, Almansor, and Sorraia valleys. As such, this study evaluates As pathways across 5000 ha of rice fields in the Tagus, Sorraia, and Almansor alluvial plains by combining soil, water, and plant analyses with a geostatistical approach. The soils exhibited consistently elevated As concentrations (mean of 18.9 mg/kg), exceeding national reference values for agricultural soils (11 mg/kg) and forming a marked east–west gradient with the highest levels in the Tagus alluvium. Geochemical analysis showed that As is strongly correlated with Fe (r = 0.686), indicating an influence of Fe-oxyhydroxides under oxidizing conditions. The irrigation waters showed low As (mean of 2.84 μg/L for surface water and 3.51 μg/L for groundwater) and predominantly low sodicity facies, suggesting that irrigation water is not the main contamination vector. In rice plants, As accumulation follows the characteristic organ hierarchy roots > stems/leaves > grains, with root concentrations reaching up to 518 mg/kg and accumulating progressively in the maturity phase. Arsenic content in harvested rice grains was 266 μg/kg (with a maximum of 413.9 μg/kg), being close to EU maximum limits when considering typical inorganic As proportions, assuming 60 to 90% inorganic fraction. Together, the findings highlight that a combined approach is essential, and identify soil geochemistry (and not irrigation water) as the primary source of As transfer in those agroecosystems, due to the flooded conditions that trigger the reductive dissolution of Fe oxides, releasing As. Additionally, the results also identified the need for targeted monitoring in areas of elevated As content in soils and support future mitigation through As speciation analysis, cultivar selection, improved fertilization strategies, and water-management practices such as Alternate Wetting and Drying (AWD), to ensure the long-term food safety. Full article

Rice is a vital staple food crop worldwide and also one of the major sources of greenhouse gas (GHG) emissions, generating substantial methane (CH₄) and nitrous oxide (N₂O). As one of the key management practices for rice production, the GHG mitigation potential of water management has attracted extensive attention, whereas its global scalability remains to be further investigated. Based on 15,458 global observations of field experimental data, we employed advanced machine learning methods to quantify the GHGs and soil carbon sequestration of global rice systems around 2020. Furthermore, we identified the optimal spatial distribution of GHG mitigation for five rice water management practices (continuous flooding (CF), flooding–midseason drainage–reflooding (FDF), alternate wetting and drying irrigation (AWD), flooding–midseason drainage–intermittent irrigation (FDI), and rainfed cultivation (RF)) through scenario simulation, under the premise of no yield reduction. The results of machine learning simulation showed that optimizing water management could reduce global rice greenhouse gas emissions by 39.17%, equivalent to 340.46 Mt CO₂ eq, while increasing rice yields by 3.55%. This study provides valuable insights for the optimization of agricultural infrastructure and the realization of agricultural sustainable development. Full article

Methane emissions from rice paddies account for over 11% of global atmospheric CH₄, making water management practices such as Alternate Wetting and Drying (AWD) critical for climate change mitigation. Remote sensing offers an objective approach to monitoring AWD implementation and improving greenhouse gas estimation accuracy. This study investigates the backscattering mechanisms of L-band SAR for inundation/non-inundation classification in paddy fields using full-polarimetric ALOS-2 PALSAR-2 data. Field surveys and satellite observations were conducted in Ryugasaki (Ibaraki) and Sekikawa (Niigata), Japan, collecting 1360 ground samples during the 2024 growing season. Freeman–Durden decomposition was applied, and relationships with plant height and water level were analyzed. The results indicate that plant height strongly influences backscatter, with backscattering contributions from the surface decreasing beyond 70 cm, reducing classification accuracy. Random forest models can classify inundated and non-inundated fields with up to 88% accuracy when plant height is below 70 cm. However, when using this method, it is necessary to know the plant height. Volume scattering proved robust to incidence angle and observation direction, suggesting its potential for phenological monitoring. These findings highlight the effectiveness of L-band SAR for water management monitoring and the need for integrating crop height estimation and regional adaptation to enhance classification performance. Full article

The System of Rice Intensification which promotes agro-ecological practices like alternate wetting and drying (AWD) to enhance root growth and resource efficiency, relies on the genotypic capacity of rice varieties to undergo physiological adaptation. This study elucidates the molecular basis of such adaptation by investigating the transcriptomic profile of four rice varieties to continuous flooding (CF) and AWD at 50 days after transplanting. Our analysis revealed distinct, organ-specific acclimation strategies. Roots underwent extensive transcriptional reprogramming, underscoring their role as the primary site of plasticity. Under CF, a conserved response involving cell wall reinforcement was accompanied by variety-specific strategies, ranging from sustained growth to enhanced anaerobic metabolism. Under AWD, roots shifted toward water stress management, with varieties employing distinct defensive (e.g., diterpenoid biosynthesis) and metabolic programs. Associated transcription factors (TFs) enriched under CF included Dof and MYB, whereas bZIP, HSF, and WRKY factors predominated under AWD. In leaves, acclimation to AWD involved more targeted adjustments, including modulation of nitric oxide signaling and photoprotective pathways, regulated by TFs such as WRKY, NAC, and HSF. Varieties with robust TF responses, such as IR64 and Hitachi hatamochi, showed comprehensive regulatory shifts, while others exhibited more constrained profiles. Overall, this study provides a molecular framework for understanding variety-specific adaptation to SRI-relevant water management practices and identifies key TFs as promising candidates for breeding climate-resilient rice. Full article

Rice–fishery integrated farming has expanded rapidly in China, yet its implications for arsenic (As) accumulation remain insufficiently understood. This study evaluated As bioavailability and enrichment in a rice–crayfish farming system (RCFS) by establishing controlled field plots with soil As concentrations ranging from 5 to 40 mg/kg under three water-management regimes: alternating wetting and drying (AWD), continuously flooded (CF), and RCFS. Soil–water physicochemical variables and As accumulation in both rice organs and crayfish tissues were systematically analyzed, followed by human health risk assessment. Inorganic As in brown rice increased linearly with soil As, following Y = 0.0117X + 0.0598 (R² = 0.96), and the estimated soil safety thresholds were 26.48 mg/kg for AWD, 11.98 mg/kg for RCFS, and 9.24 mg/kg for CF. AWD consistently exhibited the lowest As risk due to its ability to elevate soil Eh and maintain a more favorable pH, thereby suppressing As mobilization. Compared with CF, RCFS reduced As bioavailability through crayfish-induced bioturbation, which increased Eh, enhanced SOM and CEC, and improved soil aeration. As accumulation in crayfish tissues also rose with soil As, with abdominal muscle As fitting Y = 0.0085X + 0.0553 (R² = 0.8588). Although abdominal muscle met safety limits, the hepatopancreas accumulated substantially higher As and exceeded carcinogenic risk thresholds, even at 5 mg/kg of soil As, indicating a potential health concern for consumers. This work elucidates As dynamics and enrichment mechanisms in RCFS, providing guidance for safer rice–crayfish production in As-impacted areas. Full article

Extensive practice has demonstrated that the continuous pursuit of high yields in the black soil region of Northeast China resulted in imbalances in soil nutrients and declines in both soil quality and water use efficiency. Alternate wetting and drying (AWD) irrigation offers a promising solution for increasing rice yield and maintaining soil fertility. However, the success of this irrigation method largely depends on its scheduling. This study examined the threshold effects of AWD on rice growth, yield, and soil nutrient availability in the Sanjiang Plain, a representative black soil region in Northeast China. A two-year trial was conducted from 2023 to 2024 at the Qixing National Agricultural Science and Technology Park. “Longjing 31”, a local cultivar, was selected as the experimental material. The lower limit of soil water content under AWD was set as the experimental factor, with three levels: −10 kPa (LA), −20 kPa (MA), and −30 kPa (SA). The local traditional irrigation practice, continuous flooding, served as the control treatment (CK). Indicators of rice growth and soil nutrient content were measured and analyzed at five growth stages: tillering, jointing, heading, milk ripening, and yellow ripening. The results showed that, compared to CK, AWD had minimal impact on rice plant height and tiller number, with no significant differences (p > 0.05). However, AWD affected leaf area index (LAI), shoot dry matter (SDM), yield, and soil nutrient availability. In 2023, control had little effect on rice plant height and tiller number among the different irrigation treatments. The LAI of LA was 11.1% and 22.5% higher than that of MA and SA, respectively, while SDM in LA was 10.5% and 17.2% higher than in MA and SA. Significant differences were found between LA and MA, as well as between LA and SA, whereas no significant differences were observed between MA and SA. The light treatment is beneficial to the growth and development of rice, while the harsh growth environment caused by the moderate and severe treatments is unfavorable to rice growth. The average contents of nitrate nitrogen (NO₃⁻-N), available phosphorus (AP), and available potassium (AK) in LA were 11.4%, 8.4%, and 9.3% higher than in MA, and 16.7%, 11.5%, and 15.0% higher than in SA, respectively. Significant differences were observed between LA and SA. This is because the light treatment facilitates the release of available nutrients in the soil, while the moderate and severe treatments hinder this process. Although panicle number per unit area and grain number per panicle in LA were 7.5% and 2.3% higher than in MA, and 10.8% and 2.2% higher than in SA, these differences were not statistically significant. Seed setting rate and thousand-grain weight showed little variation across irrigation treatments. The yield of LA was 10,233.3 kg hm⁻², 9.1% and 14.1% higher than that of MA and SA, respectively, with significant differences observed. Compared with the moderate and severe treatments, the light treatment increases indicators such as the number of panicles per unit area, grains per panicle, thousand-grain weight, and seed setting rate, resulting in significant differences among the treatments. Water use efficiency (WUE) decreased as the control level increased. The WUE of all AWD irrigation treatments was significantly higher than that of the control treatment (CK). Compared with CK, AWD reduces evaporation, percolation, and other water losses, leading to a significant decrease in water consumption. Meanwhile, the yield remains basically unchanged or even slightly increases, thus resulting in a higher WUE than CK. The trends in rice growth, soil nutrient indicators, and WUE in 2024 were generally consistent with those observed in 2023. In 2024, the yield of LA was 9832.7 kg hm⁻², 14.9% and 17.3% higher than that of MA and SA, respectively, with significant differences observed. Based on the results, the following conclusions are drawn: (1) AWD irrigation can affect the growth of rice, alter the status of available nutrients in the soil, and thereby cause changes in yield and WUE; (2) LA is the optimal treatment for increasing rice yield, improving the availability of soil available nutrients, and improving WUE; (3) Both MA and SA enhanced WUE; however, these practices negatively impacted rice growth and the concentration of soil available nutrients, leading to a concurrent decline in yield. To increase rice yield and maintain soil fertility, LA, with an irrigation upper limit of 30 mm and a soil water potential threshold of −10 kPa, is recommended for the Sanjiang Plain region. Full article

The growing global population and water scarcities are putting pressure on researchers to develop new techniques for food production that require less water. In agriculture, sustainable irrigation methods considerably improve water-use efficiency (WUE), economic returns, and crop productivity. A field trial was carried out during 2022 and 2023 to examine the impact of different irrigation techniques—furrow irrigation (FI), alternate wetting and drying (AWD), and continuous flooding (CF)—on water-use efficiency, economic benefits, cost of production, and productivity of different high-yielding rice varieties (i.e., V₁: Super gold 2019, V₂: Super basmati 2019, V₃: Kissan basmati 2016, V₄: Punjab basmati 2016, V₅: Chenab basmati 2016). Findings showed that yield and yield parameters were statistically higher in AWD than FI and CF. Chenab basmati 2016 was superior in productivity as compared to the remaining varieties in both years. Water-use efficiency, net income, and cost/benefit ratio were highest in AWD as compared to CF and FI. AWD irrigation methods coupled with Chenab basmati 2016 were the most effective combination of treatments for obtaining more grain yield with maximum water savings, net income, and cost/benefit ratio. Full article

Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, and mitigate greenhouse gas (GHG) emissions. This study introduces Farmdee-Mesook, a mobile-first smart agriculture platform designed specifically for Thai rice farmers. The platform leverages AquaCrop simulation, open-access satellite data, and localized agronomic models to deliver real-time, field-specific recommendations. Usability-focused design and no-cost access facilitate its widespread adoption, particularly among smallholders. Empirical results show that platform users achieved yield increases of up to 37%, reduced agrochemical costs by 59%, and improved water productivity by 44% under alternate wetting and drying (AWD) irrigation schemes. These outcomes underscore the platform’s role as a scalable, cost-effective solution for operationalizing climate-smart agriculture. Farmdee-Mesook demonstrates that digital technologies, when contextually tailored and institutionally supported, can serve as critical enablers of climate adaptation and sustainable agricultural transformation. Full article

Heavy metal contamination in paddy fields poses serious risks to food safety and crop productivity. This study evaluated the potential of native soil fungi as bioinoculants to reduce metal uptake in rice cultivated under contaminated conditions. Eight fungal strains—four indigenous and four allochthonous—were selected based on their plant growth-promoting traits, including siderophore production and phosphate solubilization. Additional metabolic analysis confirmed the production of bioactive secondary metabolites. In a greenhouse experiment, three rice cultivars were grown under permanent flooding (PF) and alternate wetting and drying (AWD) in soil enriched with arsenic, cadmium, chromium, and copper. Inoculation with indigenous fungi under AWD significantly reduced the arsenic accumulation in rice shoots by up to 75%. While AWD increased cadmium uptake across all cultivars, fungal inoculation led to a moderate reduction in cadmium accumulation—ranging from 15% to 25%—in some varieties. These effects were not observed under PF conditions. The results demonstrate the potential of native fungi as a nature-based solution to mitigate heavy metal stress in rice cultivation, supporting both environmental remediation and sustainable agriculture. Full article

Given the worsening global climate change that drives drought frequency and irrigation water shortages, implementing water-conserving practices like alternate wetting and drying (AWD) is now critically urgent. Biochar is widely used for soil carbon sequestration. However, there is limited information on the effects of biochar on soil organic carbon (SOC) and its labile fractions in paddy fields, especially under AWD. A two-year field experiment was conducted with two irrigation regimes (CF: continuous flooding irrigation; AWD) as the main plots and 0 (B₀) and 20 t ha⁻¹ (B₁) biochar as sub-plots. AWD had no effect on the SOC and particulate organic carbon (POC) content, but increased the dissolved organic carbon (DOC), microbial biomass carbon (MBC), easily oxidizable organic carbon (EOC), light fraction organic carbon (LFOC), and carbon pool management index (CPMI) at 0–10 cm depths, by 24.4–56.4%, 12.6–17.7%, 9.2–16.8%, 25.6–28.1%, and 11.3–18.6%, respectively. Biochar increased SOC while also increasing DOC, MBC, EOC, LFOC, POC, and CPMI at 0–20 cm depths, by 18.4–53.3%, 14.7–70.2%, 17.4–22.3%, 10.2–27.6%, 95.2–188.3%, 46.6–224%, and 5.6–27.2, respectively, making SOC more labile under AWD. Our results highlight that biochar still holds great potential for improving soil quality and carbon sequestration under AWD, and the combination of biochar and AWD can achieve the synergistic optimization of the food–water–carbon sequestration trade-off, which is beneficial to sustainable agricultural production. Full article