Search Results (1,121)

Straw removal is a method used to reduce cadmium (Cd) concentration in contaminated farmland. Experiments in Hunan Province tested different stubble heights (0, 15, 30, 45 cm) in three Cd-polluted paddy fields with different contamination levels. The results showed that lower stubble heights resulted in larger straw biomass and more Cd removed from the field, while the residual biomass and Cd returned to the field decreased accordingly. At stubble heights of 0, 15, 30, and 45 cm, the removed straw biomass accounted for 100%, 69.19%, 48.84%, and 28.17% of the total straw biomass, respectively. The corresponding Cd removal amounts were 12.89, 7.18, 4.18, and 1.83 g ha⁻¹, which constituted 100%, 54.06%, 29.85%, and 12.54% of the total Cd accumulation in straw for the season, respectively. According to the fitted curve, the biomass of returned and removed straw was equal at a stubble height of 31 cm, while at 23 cm, the Cd return and removal amounts were balanced. Rice varieties Huanghuazhan and Nongxiang 42 had better Cd removal but risked grain Cd exceeding limits. Since Cd concentration in straw determines removal efficiency, varieties with high straw Cd accumulation and low grain Cd are more suitable for remediation, rather than high-Cd-accumulating types. Full article

The ecological rice–eel co-culture system is not only beneficial for enhancing productivity and sustainability in agriculture but also plays a crucial role in promoting environmental health. In the present study, based on the long-term positioning trial of the rice–eel co-culture system that began in 2016 and was sampled in 2023, the effects of reduced nitrogen fertilizer application on soil physico-chemical properties and the bacterial community were investigated. Treatments included a conventional regular fertilization treatment (RT), rice–eel co-culture system regular fertilization (IT), and nitrogen-reduction 10%, 30%, and 50% fertilization treatments (IT90, IT70, and IT50). Our research demonstrated the following: (1) Compared to RT, IT significantly increased soil water-stable macroaggregates (R0.25), mean weight diameter (MWD), geometric mean diameter (GMD), and available phosphorus content, with the increases of 15.66%, 25.49%, 36.00%, and 18.42%, respectively. Among the nitrogen-reduction fertilization treatments, IT90 showed the most significant effect. Compared to IT, IT90 significantly increased R0.25, MWD, GMD, and available nitrogen content, with increases of 4.4%, 7.81%, 8.82%, and 28.89%, respectively. (2) Compared to RT, at the phylum level, the diversity of Chloroflexi was significantly increased under IT and IT50, and the diversity of Gemmatimonadota was significantly increased under IT90, IT70, and IT50. The diversity of Acidobacteriota was significantly higher in IT90 and IT70 compared to IT. It was shown that the rice–eel co-culture system and nitrogen fertilizer reduction could effectively improve the degradation capacity of organic matter and promote soil nitrogen cycling. In addition, redundancy analysis (RDA) identified total phosphorus, total nitrogen, and available nitrogen (p = 0.007) as the three most important environmental factors driving changes in the bacterial community. (3) The functional prediction analysis of soil microbiota showed that, compared to RT, the diversity of pathways related to biosynthesis (carbohydrate biosynthesis and cell structure biosynthesis) and metabolism (L-glutamate and L-glutamine biosynthesis) was significantly higher under IT70, IT90, IT, and IT50 (in descending order). However, the diversity of pathways associated with degradation/utilization/assimilation (secondary metabolite degradation and amine and polyamine degradation) was significantly lower under all the rice–eel co-culture treatments. In conclusion, the rice–eel co-culture system improved soil physicochemical properties and the soil microbial environment compared with conventional planting, and the best soil improvement was achieved with 10% less N fertilizer application. Full article

Large soil pores critically influence water and solute transport in soils. The presence of preferential flow paths created by soil macropores can profoundly impact water quality, underscoring the necessity of accurately assessing the characteristics of these macropores. However, it remains unclear whether variations in macropore structure exist between different altitudes and positions of terraced paddy fields. The primary objective of this research was to utilize X-ray computed tomography (CT) and image analysis techniques to characterize the soil pore structure at both the inner field and ridge positions across different altitude levels (high, medium, and low altitude) within terraced paddy fields. The results indicate that there are significant differences in the distribution of large soil pores at different altitudes, with large pores concentrated in the surface layer (0–10 cm) in low-altitude areas, while in high-altitude areas, the distribution of large pores is more uniform. Additionally, as altitude increases, the porosity of large pores shows an increasing trend. The three-dimensional equivalent diameter and large pore volume are primarily characterized by large pores ranging from 1 to 2 mm and 0 to 5 mm³, respectively, with their morphology predominantly appearing spherical or ellipsoidal. The connectivity of large pores in the surface layer of paddy soil is stronger than that in the bunds. However, this connectivity gradually weakens with increasing soil depth. The findings from this study provide valuable quantitative insights into the unique characteristics of soil macropores that vary according to the altitude and position in terraced paddy fields. Moreover, this study emphasizes the necessity for future research that encompasses a broader range of soil types, altitudes, and terraced paddy locations to validate and further explore the identified relationships between altitude and macropore characteristics. Full article

Soil organic carbon (SOC) is an important part of the global C pool and is sensitive to climate change. The SOC content and fractions of rice paddies along four elevations (250, 1150, 1600 and 1800 m) on the same slope in four seasons (spring, summer, autumn and winter) at Yuanyang Terrace in southwest China were investigated, and their relationship with environmental factors was analyzed. The contents of SOC, unprotected SOC (uPOM), physically protected SOC (pPOM) and biochemically protected SOC (bcPOM) in rice paddies at a low elevation (250 m), were significantly lower by 49–51% than those at relatively high elevations (1600 m and 1800 m). Among the SOC fractions, the highest proportion (33–50%) was uPOM, followed by pPOM and bcPOM (accounting for 17–40%), and the lowest proportion was chemically protected SOC (cPOM). In addition, there were interseasonal differences among the contents of SOC fractions, with a significantly higher content of SOC, uPOM and pPOM at an elevation of 1600 m in summer than in the other three seasons, whereas the cPOM content at an elevation of 250 m in spring was significantly higher than in the other three higher elevations. According to the redundancy analysis (RDA), total nitrogen was the key environmental factor, with an explanatory degree of 56% affecting the contents of SOC and its fractions. Thus, the SOC content increased with increasing elevation, and physical and biochemical protection were potential stabilization mechanisms responsible for their stability in the rice paddy of Yuanyang Terrace. These results provides empirical evidence for the elevational distribution patterns and seasonal dynamics of SOC fractions in rice paddies across Yuanyang Terrace. These findings highlight the importance of physical and biochemical protection mechanisms in stabilizing SOC in rice paddies, which could enhance long-term C sequestration and contribute to climate change mitigation in terraced agroecosystems. Full article

This investigation examines the influence of P. dabryanus density on the growth performance of P. nigromaculatus and the structural and functional dynamics of paddy soil microbial communities within a rice–frog–loach integrated aquaculture system. Field experiments were conducted with five density gradients of P. dabryanus (0.5, 1.0, 1.5, 2.0, and 2.5 × 10⁴ individuals/667 m²), designated as RFLS0.5, RFLS1.0, RFLS1.5, RFLS2.0, and RFLS2.5, respectively. Control treatments included rice monoculture (RM) and rice–frog co-culture (RFS). These findings demonstrated that as the density of loach increased, the weight gain ratio of P. nigromaculatus showed a unimodal pattern, reaching its peak in RFLS1. Metagenomic analysis on paddy soil revealed that the RFLS1 facilitated the enrichment of nitrogen-fixing bacteria (Proteobacteria), while concurrently suppressing proliferation of the potential pathogen Pseudomonas aeruginosa and microbial markers in metal-contaminated environments of Usitatibacter rugosus. Further, functional profiling indicated that RFLS1 group reached a peak activity in amino acid metabolism (14.52 ± 0.09%) and carbohydrate metabolism (14.44 ± 0.06%) and showed a higher proportion of glycosyltransferase (GT) abundance (41.93 ± 0.02%) than other groups. In summary, the optimal stocking density of P. dabryanus in rice–frog–loach integrated systems was determined to be 1.0 × 10⁴ individuals/667 m². This density not only promotes the growth of P. nigromaculatus but also improves the structure of paddy soil microbial communities. Full article

Traditional intensive agricultural system impedes ecological functions, such as nutrient cycling and biodiversity conservation, resulting in excessive nitrogen discharge, CH₄ emission, and ecosystem service losses. To enhance critical ecosystem services and mitigate environmental externalities in paddy fields, we developed a multi-objective agricultural system (MIA system), which combines two eco-functional units: paddy wetlands and Beitang (irrigation water collection pond). Pilot study results demonstrated that the MIA system enhanced biodiversity and inhibited pest outbreak, with only a marginal reduction in rice production compared with the control. Additionally, the paddy wetland effectively removed nitrogen, with removal rates of total nitrogen and dissolved inorganic nitrogen ranging from 0.06 to 0.65 g N m⁻² d⁻¹ and from 0.02 to 0.22 g N m⁻² d⁻¹, respectively. Continuous water flow in the paddy wetland reduced the CH₄ emission by 84.4% compared with the static water conditions. Furthermore, a simulation experiment indicated that tide flow was more effective in mitigating CH₄ emission, with a 68.3% reduction compared with the drying–wetting cycle treatment. The emergy evaluation demonstrated that the MIA system outperformed the ordinary paddy field when considering both critical ecosystem services and environmental externalities. The MIA system exhibited higher emergy self-sufficiency ratio, emergy yield ratio, and emergy sustainable index, along with a lower environmental load ratio. Additionally, the system required minimal transformation, thus a modest investment. By presenting the case of the MIA system, we provide a theoretical foundation for comprehensive management and assessment of agricultural ecosystems, highlighting its significant potential for widespread application. Full article

Investigating the factors influencing rice grain yield (GY) is critical for optimizing nitrogen (N) management and enhancing resource use efficiency in rice cultivation. However, few studies have comprehensively investigated the factors affecting rice GY, considering an entire influence chain encompassing rice N uptake, growth indicators, and GY components. In this study, field experiment with six different N fertilizer rates (0, 60, 120, 180, 225, and 300 kg N ha⁻¹, i.e., N0, N60, N120, N180, N225, and N300) was conducted in the Jianghan Plain in the Middle Reaches of the Yangtze River, China, to comprehensively elucidate the factors influencing rice GY from aspects of rice N uptake, growth indicators, and GY components and determine the optimal N fertilizer rate. The results showed that rice GY and N uptake initially increased and then either stabilized or declined with higher N fertilizer rate, while apparent N loss escalated with increased N fertilizer rate. The application of N fertilizer significantly promoted the increase in straw N uptake, which was significantly positively correlated with growth indicators (p < 0.05). Among all GY components, panicle number per hill was the most significant positive factor influencing rice GY, and it was significantly positively correlated with all rice growth indicators (p < 0.05). In addition, N180 was the optimal N fertilizer rate, ensuring more than 95% of maximum GY and reducing N loss by 74% and 39% compared to N300, respectively. Meanwhile, the average N balance for N180 remained below 60 kg N ha⁻¹. In conclusion, optimizing the N fertilizer application in paddy fields can effectively maintain stable rice GY and minimize environmental pollution. Full article

Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects of the RC systems on soil physicochemical characteristics and microbial dynamics in paddy fields of southern Henan Province, China, over the 2023 growing season and subsequent fallow period. Using a randomized complete design, rice monoculture (RM, as the control) and RC treatments were compared across replicated plots. Soil and water samples were collected post-harvest and pre-transplanting to assess soil properties, extracellular enzyme activity, and microbial community structure. Results showed that RC significantly enhanced soil moisture by up to 30.2%, increased soil porosity by 9.6%, and nearly tripled soil organic carbon compared to RM. The RC system consistently elevated nitrogen (N), phosphorus (P), and potassium (K) throughout both the rice growth and fallow stages, indicating improved nutrient availability and retention. Elevated extracellular enzyme activities linked to carbon, N, and P cycling were observed under RC, with enzymatic stoichiometry revealing increased microbial nutrient limitation intensity and a shift toward P limitation. Microbial community composition was significantly altered under RC, showing increased biomass, a higher fungi-to-bacteria ratio, and greater relative abundance of Gram-positive bacteria, reflecting enhanced soil biodiversity and ecosystem resilience. Further analyses using the Mantel test and Random Forest identified extracellular enzyme activities, PLFAs, soil moisture, and bulk density as major factors shaping microbial communities. Redundancy analysis (RDA) confirmed that total potassium (TK), vector length (VL), soil pH, and total nitrogen (TN) were the strongest environmental predictors of microbial variation, jointly explaining 74.57% of the total variation. Our findings indicated that RC improves soil physicochemical conditions and microbial function, thereby supporting sustainable nutrient cycling and offering a promising, environmentally sound strategy for enhancing productivity and soil health in rice-based agro-ecosystems. Full article

Accurate and real-time detection of rice shelling rate (SR) and brown rice breakage rate (BR) is crucial for intelligent hulling sorting but remains challenging because of small grain size, dense adhesion, and uneven illumination causing missed detections and blurred boundaries in traditional YOLOv8n. This paper proposes a high-precision, lightweight solution based on an enhanced YOLOv8n with improvements in network architecture, feature fusion, and attention mechanism. The backbone’s C2f module is replaced with C2f-Faster-CGLU, integrating partial convolution (PConv) local convolution and convolutional gated linear unit (CGLU) gating to reduce computational redundancy via sparse interaction and enhance small-target feature extraction. A bidirectional feature pyramid network (BiFPN) weights multiscale feature fusion to improve edge positioning accuracy of dense grains. Attention mechanism for fine-grained classification (AFGC) is embedded to focus on texture and damage details, enhancing adaptability to light fluctuations. The Detect_Rice lightweight head compresses parameters via group normalization and dynamic convolution sharing, optimizing small-target response. The improved model achieved 96.8% precision and 96.2% mAP. Combined with a quantity–mass model, SR/BR detection errors reduced to 1.11% and 1.24%, meeting national standard (GB/T 29898-2013) requirements, providing an effective real-time solution for intelligent hulling sorting. Full article

The black-spotted frog (Pelophylax nigromaculatus) is a common economic species in the rice–frog ecological cropping mode. The present study investigated microbial community structures in paddy water and black-spotted frog’s guts across rice monoculture and low-/high-density rice–frog co-cropping systems at four rice growth stages. Proteobacteria dominate in paddy water, while frog guts are enriched in Firmicutes and Actinobacteriota. The frog density shows no impact on the α-diversity, but rice growth stages significantly alter the Shannon, Simpson, and Pielou_e indices (p < 0.01). Co-cropping may promote amino acid synthesis, elemental cycling, and stress tolerance in paddy water microbiota, which are more diverse than gut microbiota. Strong correlations exist between paddy water and gut microbiotas, with Limnohabitans being linked to gut diversity (p < 0.05). Low-density co-cropping enhances Xenorhabdus, which is beneficial for pest control and stabilizes gut microbiota. The results of this study offer insights for managing rice–frog systems based on rice growth stages. Full article

Reclaimed fields have a low soil fertility and low productivity compared to conventional arable land, necessitating research on productivity enhancement. The rice–frog co-culture model is an ecologically intensive practice that combines biodiversity objectives with agricultural production needs, offering high ecological and economic value. However, there is a lack of research on this model that has focused on factors other than soil nutrient levels. The present study evaluated the rice–frog co-culture model in a reclaimed paddy field across three experimental plots with varying frog stocking densities: a rice monoculture (CG), low-density co-culture (LRF), and high-density co-culture (HRF). We investigated the effects of the frog density on greenhouse gas emissions throughout the rice growth. The rice–frog co-culture model significantly reduced methane (CH₄) emissions, with fluxes highest in the CG plot, followed by the LRF and then HRF plots. This reduction was achieved by altering the soil pH, the cation exchange capacity, the mcrA gene abundance, and the mcrA/pmoA gene abundance ratio. However, there was a contrasting nitrous oxide (N₂O) emission pattern. The co-culture model actually increased N₂O emissions, with fluxes being highest in the HRF plots, followed by the LRF and then CG plots. The correlation analysis identified the soil nosZ gene abundance, redox potential, urease activity, nirS gene abundance, and ratio of the combined nirK and nirS abundance to the nosZ abundance as key factors associated with N₂O emissions. While the co-cultivation model increased N₂O emissions, it also significantly reduced CH₄ emissions. Overall, the rice–frog co-culture model, especially at a high density, offers a favorable sustainable agricultural production model. Full article

Arsenic (As) and cadmium (Cd) in rice grains are major global food safety concerns. Iron (Fe) can help reduce both, but current Fe treatments suffer from poor stability, low leaf absorption, and fast soil immobilization, with unclear underlying mechanisms. To address these issues, an Fe-based metal–organic framework (MIL-88) was modified with sodium alginate (SA) to form MIL-88@SA. Its stability as a foliar inhibitor and its leaf absorption were tested, and its effects on As and Cd accumulation in rice were compared with those of soluble Fe (FeCl₃) and chelating Fe (HA + FeCl₃) in a field study on As–Cd co-contaminated rice paddies. Compared with the control, MIL-88@SA outperformed or matched the other Fe treatments. A single foliar spray during the tillering stage increased the rice yield by 19% and reduced the inorganic As and Cd content in the grains by 22.8% and 67.8%, respectively, while the other Fe treatments required two sprays. Its superior performance was attributed to better leaf affinity and thermal stability. Laser ablation inductively coupled plasma–mass spectrometry (LA–ICP–MS) and confocal laser scanning microscopy (CLSM) analyses revealed that Fe improved photosynthesis and alleviated As–Cd stress in leaves, MIL-88@SA promoted As and Cd redistribution, and Fe–Cd co-accumulation in leaf veins enhanced Cd retention in leaves. 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

The DNDC-Rice model effectively simulates yield and greenhouse gas emissions within a paddy system, while its performance under upland conditions remains unclear. Using data from a long-term cover crop experiment (fallow [FA] vs. rye [RY]) in a soybean field, this study validated the DNDC-Rice model’s performance in simulating soil dynamics, crop growth, and C-N cycling processes in upland systems through various indicators, including soil temperature, water-filled pore space (WFPS), soybean biomass and yield, CO₂ and N₂O fluxes, and soil organic carbon (SOC). Based on simulated results, the underestimation of cumulative N₂O flux (25.6% in FA and 5.1% in RY) was attributed to both underestimated WFPS and the algorithm’s limitations in simulating N₂O emission pulses. Overestimated soybean growth increased respiration, leading to the overestimation of CO₂ flux. Although the model captured trends in SOC stock, the simulated annual values differed from observations (−9.9% to +10.1%), potentially due to sampling errors. These findings indicate that the DNDC-Rice model requires improvements in its N cycling algorithm and crop growth sub-models to improve predictions for upland systems. This study provides validation evidence for applying DNDC-Rice to upland systems and offers direction for improving model simulation in paddy-upland rotation systems, thereby enhancing its applicability in such contexts. Full article

Barnyard grass is a major noxious weed in paddy fields. Accurate and efficient identification of barnyard grass is crucial for precision field management. However, existing deep learning models generally suffer from high parameter counts and computational complexity, limiting their practical application in field scenarios. Moreover, the morphological similarity, overlapping, and occlusion between barnyard grass and rice pose challenges for reliable detection in complex environments. To address these issues, this study constructed a barnyard grass detection dataset using high-resolution images captured by a drone equipped with a high-definition camera in rice experimental fields in Haicheng City, Liaoning Province. A lightweight field barnyard grass detection model, YOLOv8n-SSDW, was proposed to enhance detection precision and speed. Based on the baseline YOLOv8n model, a novel Separable Residual Coord Conv (SRCConv) was designed to replace the original convolution module, significantly reducing parameters while maintaining detection accuracy. The Spatio-Channel Enhanced Attention Module (SEAM) was introduced and optimized to improve sensitivity to barnyard grass edge features. Additionally, the lightweight and efficient Dysample upsampling module was incorporated to enhance feature map resolution. A new WIoU loss function was developed to improve bounding box classification and regression accuracy. Comprehensive performance analysis demonstrated that YOLOv8n-SSDW outperformed state-of-the-art models. Ablation studies confirmed the effectiveness of each improvement module. The final fused model achieved lightweight performance while improving detection accuracy, with a 2.2% increase in mAP_50, 3.8% higher precision, 0.6% higher recall, 10.6% fewer parameters, 9.8% lower FLOPs, and an 11.1% reduction in model size compared to the baseline. Field tests using drones combined with ground-based computers further validated the model’s robustness in real-world complex paddy environments. The results indicate that YOLOv8n-SSDW exhibits excellent accuracy and efficiency. This study provides valuable insights for barnyard grass detection in rice fields. Full article