Search Results (426)

Farmland N₂O emissions exhibit significant fluctuations in subtropical regions due to notable seasonal rainfall and temperature variations. The dominant factors influencing N₂O emissions in red-soil sloping farmland, which is widely distributed and actively cultivated in the region, remain uncertain. To investigate N₂O emission characteristics of red-soil sloping farmland and responses to meteorological and soil environmental variables and tillage practices, a typical planting system (summer peanut-winter rapeseed rotation system) in southern China was selected. Two common soil micro-environments (conventional tillage, CT, n = 6; and conventional tillage with straw mulching, MT, n = 4) were established within this system, and in situ N₂O emissions were monitored over two consecutive years using the static chamber–gas chromatography method. The N₂O emission peaks across various growing seasons occurred primarily within 1 to 16 days after fertilization. The N₂O emission hotspot periods were observed during the first month following fertilization, accounting for 74.13–91.01% of the total emissions during each growing season. Significant interannual variations in seasonal N₂O cumulative emissions were observed, whereas no significant difference in cumulative N₂O emissions was observed between MT and CT. Changes in weather and soil environment jointly drive the dynamics of N₂O emissions from red soil sloping farmland. Rapeseed-season N₂O emissions were driven mainly by rainfall and air temperature, whereas peanut-season N₂O emissions were also influenced by soil temperature and NO₃⁻-N content at 0–10 cm depths. These findings provide a sound basis for developing eco-agricultural mitigation pathways in subtropical red-soil hilly regions. Full article

During rotary tillage operations, the draft force is jointly affected by operating parameters and soil conditions, exhibiting pronounced nonlinearity, time-varying behavior, and historical dependence, which all impose higher requirements on tractor operating parameter matching and traction performance analysis. A draft force prediction method that is based on a long short-term memory (LSTM) neural network jointly optimized by a genetic algorithm (GA) and the bald eagle search (BES) algorithm, termed GABES-LSTM, is proposed to address the limited prediction accuracy and stability of traditional empirical models and single data-driven approaches under complex field conditions. First, on the basis of the mechanical characteristics of rotary tillage operations, a time-series mathematical description of draft force is established, and the prediction problem is formulated as a multi-input single-output nonlinear temporal mapping driven by operating parameters such as travel speed, rotary speed, and tillage depth. Subsequently, an LSTM-based draft force prediction model is constructed, in which GA is employed for global hyperparameter search and BES is integrated for local fine-grained optimization, thereby improving the effectiveness of model parameter optimization. Finally, a dataset is established using measured field rotary tillage data to train and test the proposed model, and comparative analyses are conducted against LSTM, GA-LSTM, and BES-LSTM models. Experimental results indicate that the GABES-LSTM model outperforms the comparison models in terms of mean absolute percentage error, mean relative error, relative analysis error, and coefficient of determination, effectively capturing the dynamic variation characteristics of draft force during rotary tillage operations while maintaining stable prediction performance under repeated experimental conditions. This method provides effective data support for draft force prediction analysis and operating parameter adjustment during rotary tillage operations. Full article

To solve the problems of high resistance and blockage in stubble-breaking operations, it is necessary to reveal the interaction mechanism between disc coulters and crop root–soil composites. This study developed a discrete element method–multi-body dynamics (DEM-MBD) coupling model of the stubble-breaking operation and verified the accuracy of the model through soil bin tests (error < 20%) and field experiments (error < 32%). The model was used to investigate the effects of different design parameters (coulter type and disc radius) and operating parameters (tillage speed and depth) on the stubble-breaking operation. The results showed that due to the significant strengthening effect of roots on soil, the resistance of disc coulter stubble-breaking operation was high; the number of roots in contact with the blade edge and the amount of root deformation significantly affected the resistance of the disc coulter; irreversible deformation of roots and soil could easily lead to the holes and root hairpin effects in the seeding furrow; compared to plain disc coulters, the difference in the time of deformation and fracture of the roots made the resistance of the notched coulter lower. The wavy disc coulter with a longer edge curve made its resistance higher; the disc coulter with a greater radius, higher tillage speed, and deeper tillage depth significantly increased the tillage resistance. However, the disc coulter with a greater radius or a higher tillage speed was beneficial for improving stubble-breaking performance. This study revealed the interaction mechanism between disc coulters and maize root-soil composites, providing a theoretical basis for the optimization design of no-till stubble-breaking devices. Full article

Tillage practices critically influence soil’s physical properties, which are fundamental to sustainable agriculture in temperate climates. This review evaluates how conventional tillage (CvT; e.g., moldboard and chisel plowing), reduced tillage (RT), and conservation tillage (CT), particularly no-tillage (NT), affect six key indicators: bulk density (BD), saturated hydraulic conductivity (Ks), wet aggregate stability (WAS), penetration resistance (PR), available water capacity (AWC), and soil organic carbon (SOC). Special emphasis is placed on differentiating topsoil and subsoil responses to inform climate-resilient land management. A total of 70 peer-reviewed studies published between 1991 and 2025 were analyzed. Data were extracted for BD, Ks, WAS, PR, AWC, and SOC across tillage systems. Depths were standardized into topsoil (0–10 cm) and composite (>10 cm) categories. Descriptive statistics were used to synthesize cross-study trends. NT showed lower mean BD in the topsoil (1.32 ± 0.08 Mg/m³) compared with moldboard plow (1.33 ± 0.09) and chisel tillage (1.39 ± 0.12); however, the effects of tillage on BD were not statistically significant, while BD was higher at composite depths under NT (1.56 ± 0.09 Mg/m³), indicating subsoil compaction. Ks improved under NT, reaching 4.2 mm/h with residue retention. WAS rose by 33.4%, and SOC increased by 25% under CT systems. PR tended to be elevated in deeper layers under NT. Overall, CT, particularly NT, improves surface soil’s physical health and SOC accumulation in temperate agroecosystems; however, persistent subsoil compaction highlights the need for depth-targeted management strategies, such as controlled traffic, periodic subsoil alleviation, or deep-rooted cover crops, to sustain long-term soil functionality and climate-resilient production systems. Full article

Soil total carbon (TC) and total nitrogen (TN) are key indicators of soil fertility and ecosystem stability, particularly in dryland agroecosystems. However, how rotational tillage combined with straw return affects aggregate formation and aggregate-associated TC and TN stabilization remains insufficiently understood. In this study, we aimed to clarify how rotational tillage affects aggregate structure, stability, and the spatial distribution of TC and TN, thereby revealing internal processes driving nutrient stabilization in dryland farming systems. A long-term field experiment was conducted at the Shenfeng site of Shanxi Agricultural University, China, including three rotational tillage systems with straw return: T1 (two years of no tillage (NT) + one year of deep tillage (DT)), T2 (two years of conventional tillage (CT) + one year of DT), and T3 (two years of DT + one year of CT). Soil aggregates were separated into total mechanical aggregate (TMA), 0.25–2 mm MA, and 2–10 mm MA, and they were further fractionated into water-stable aggregates (WM, Wm, and Wf) for TC and TN analysis. The results showed that aggregate stability, TC, and TN were positively correlated and decreased with soil depth, indicating strong surface enrichment. TC was mainly enriched in 0.25–2 mm MA, whereas TN was concentrated in 2–10 mm MA, and water-stable macroaggregates (WM) acted as the dominant reservoirs for R_C and R_N. Relative to the 2016 baseline (CK), TC in 2022 tended to be higher under rotational tillage with straw return, while NT-containing systems better maintained TN across the 0–60 cm profile. Among the treatments, T1 provided the most balanced performance, with a higher MWD and GMD, lower D, and improved aggregate-associated TC and TN retention. These findings suggest that rotational tillage with straw return, particularly the NT–NT–DT sequence, can support aggregate stability and is associated with improved aggregate-mediated TC and TN retention in the Loess Plateau dryland winter wheat system. Full article

Rotational tillage is considered a potential option to improve soil organic carbon (SOC) stock and mitigate climate change. However, the mechanisms underlying SOC sequestration under rotational tillage remain poorly understood due to insufficient data on SOC concentration and mineralization within soil aggregates. A 12-year field experiment was conducted in Northwest China to evaluate the effects of tillage on SOC stocks, soil aggregate stability, aggregate-associated OC concentrations and mineralization. The results showed that rotational tillage had more crop residue and less soil disturbance, thus improving soil aggregate stability, aggregate-associated OC concentrations and SOC stocks. The highest MWD and SOC stocks were found in no-tillage rotated with subsoiling (NS), which were 36.0–69.7% and 16.3% higher than plowing, respectively. Macroaggregates had higher cumulative OC mineralization and lower OC mineralizability, due to physical protection. Rotational tillage treatments with higher soil aggregation contributed to decreasing OC mineralizability and increasing SOC sequestration. Meanwhile, rotational tillage decreased OC mineralization loss, mineralizability, and decomposition rate within microaggregates and silt–clay fractions. Among all treatments, NS treatment had the lowest total OC mineralization, which was lower by 5.94–27.3% than plowing at 0–40 cm depths. Considering soil structure stability, SOC mineralization and sequestration, NS treatment was a promising strategy in semiarid regions. Full article

Weeds pose a significant threat to crop yields, both in quantitative and qualitative terms. Modern agriculture relies heavily on herbicides; however, their excessive use can lead to negative environmental impacts. As a result, recent research has increasingly focused on Integrated Weed Management (IWM), which employs multiple complementary strategies to control weeds in a holistic manner. Nevertheless, large-scale adoption of this approach requires a solid understanding of the underlying tactics. This systematic review analyses recent studies (2013–2022) on herbicide alternatives for weed control across major cropping systems in the EU-27 and the UK, providing an overview of current knowledge, the extent to which IWM tactics have been investigated, and the main gaps that help define future research priorities. The review relied on the IWMPRAISE framework, which classifies weed control tactics into five pillars (direct control, field and soil management, cultivar choice and crop establishment, diverse cropping systems, and monitoring and evaluation) and used Scopus as a scientific database. The search yielded a total of 666 entries, and the most represented pillars were Direct Control (193), Diverse Cropping System (183), and Field and Soil Management (172). The type of crop most frequently studied was arable crops (450), and the macro-area where the studies were mostly conducted was Southern Europe (268). The tactics with the highest number of entries were Tillage Type and Cultivation Depth (110), Cover Crops (82), and Biological Control (72), while those with the lowest numbers were Seed Vigor (2) and Sowing Depth (2). Overall, this review identifies research gaps and sets priorities to boost IWM adoption, leading policy and funding to expand sustainable weed management across Europe. Full article

Improving fuel and energy efficiency in agricultural tillage is critical for sustainable farming and reducing environmental impacts. In this study, the effects of forward speed and tillage depth on the fuel efficiency parameters of a tractor–chisel plough combination were investigated under controlled field conditions on clay soil. Specific fuel consumption (SFC), fuel consumption per unit area (FCPA), and overall energy efficiency (OEE) were evaluated at four forward speeds (0.6, 0.95, 1.2 and 1.4 m·s⁻¹) and four tillage depths (15, 19.5, 23 and 26.5 cm). SFC ranged from 0.519 to 1.237 L·kW⁻¹·h⁻¹, while OEE varied between 7.918 and 18.854%. Higher forward speeds significantly reduced fuel consumption and improved energy efficiency, whereas deeper tillage increased fuel use and reduced efficiency. Optimal operation occurred at speeds of 1.2–1.4 m·s⁻¹ and shallow to medium depths. Five machine learning algorithms: Polynomial Regression (PL), Random Forest Regressor (RFR), Gradient Boosting Regressor (GBR), Support Vector Regression (SVR), and Decision Tree Regressor (DTR), were applied to model fuel efficiency parameters. RFR achieved the highest accuracy for predicting SFC, while PL performed best for FCPA and OEE, with the mean absolute percentage error (MAPE) below 2%. Models such as PL and RFR excel in data structures dominated by nonlinear relationships. These results highlight the potential of machine learning to guide data-driven decisions for fuel and energy optimization in tillage, promoting more sustainable mechanization strategies and resource-efficient agricultural production. Full article

A two-year (2024–2025) field experiment was conducted in southern Xinjiang to alleviate soil compaction and severe salinization in saline–alkali soils and to evaluate the combined effects of tillage depth and subsurface drain spacing on soil improvement. Six treatments were established with three deep tillage depths, 70 cm (W1), 50 cm (W2), and 30 cm (W3), and two subsurface drain spacings, 20 m (S1) and 40 m (S2). Treatment effects on soil water–salt dynamics, soil physical properties and structure, ionic composition, and subsurface drainage and salt removal were analyzed. This study provides mechanistic and practical evidence that coupling deep tillage with subsurface drainage creates a more effective leaching–drainage pathway than either measure alone and enables robust optimization of design parameters (drain spacing × tillage depth) for saline–alkali land improvement in arid regions. Deep tillage in combination with subsurface drainage significantly increased soil profile water content, total porosity, and cumulative subsurface drainage and salt export, all of which reached their maxima under S1W1; it also significantly reduced bulk density, total salinity, and the concentrations of Na⁺, K⁺, Mg²⁺, Ca²⁺, Cl⁻, and SO₄²⁻, which reached their minima under S1W1. After two spring irrigation–leaching events (in 2024 and 2025), surface salt accumulation in the soil profile was markedly alleviated, and the mean salinity in the 0–20 cm layer decreased by 45.68% across treatments. The S1W1 treatment achieved the best desalinization performance in both leaching events, with reductions of 41.36% and 44.68%, respectively. Pearson correlation analysis indicated that the desalinization effect was significantly negatively correlated with porosity and significantly positively correlated with bulk density and ionic concentrations. Overall, coupling deep tillage with subsurface drainage effectively reduced soil salinity and harmful ions, improved soil structure, and enhanced drainage-mediated salt removal, with the 70 cm tillage depth combined with a 20 cm drain spacing delivering the best performance. Full article

Crop root development, and in turn crop growth, is strongly influenced by soil strength and the mechanical impedance of compacted layers, which restrict root elongation and exploration. Because the depth and thickness of compacted layers vary across a field, their identification is essential for site-specific tillage and sustainable root-zone management. A sensing approach that can support future real-time identification of compacted layers after soil-specific calibration, which would enable variable-depth tillage, reducing mechanical impedance and improving energy-use efficiency while maintaining crop yields. This study aimed to develop and evaluate prediction models that can support future real-time identification of compacted soil layers using soil electrical conductivity (EC) and moisture content as non-destructive indicators. A sandy clay soil (48.6% sand, 29.3% clay, 22.1% silt) was tested in a soil-bin laboratory under controlled conditions at three moisture levels (13, 18, and 22% db.) and six depth layers (C1–C6, 0–30 cm) identified from the penetration-resistance profile to measure penetration resistance, shear resistance, and EC. Penetration and shear resistance increased toward the most resistant depth layer and decreased with increasing moisture content, whereas EC generally increased with both depth layer and moisture content. Linear regression models relating penetration resistance ($R^2=0.893$) and shear resistance ($R^2=0.782$) to EC and moisture content were developed and evaluated. Field validation in a paddy field of similar texture showed that predicted penetration resistance differed from measured values by 3–6% across the three compaction treatments evaluated. Root length density and root volume decreased with increasing machine-induced compaction, confirming the agronomic relevance of the modeled patterns and supporting the suitability of the proposed indicators. Together, these results demonstrate that EC and moisture content can potentially be used as non-destructive proxies for compacted-layer identification and provide a calibration basis for future on-the-go sensing systems to support site-specific, variable-depth tillage in agricultural fields. Full article

Tillage practices regulate soil health by influencing soil’s physico-chemical qualities and its capacity to sequester organic carbon. Maintaining soil health contributes to ecosystem stability and fluidity in the soil–plant–atmosphere relationship. This study aimed to evaluate soil porosity (SP), aeration limit (SAL), soil capillary capacity (SCC), soil total capacity (STC), soil temperature (Ts), air temperature (Ta), nutrient availability, soil organic carbon (SOC), and soil organic matter (SOM) under three different tillage systems: no-tillage (NT), minimum tillage (MT), and conventional tillage (CT), based on a short-term field experiment. This research was conducted on Cambic Chernozem soil using a randomized complete block design with three replications. The results revealed a significant effect of tillage systems on all evaluated properties. SP reached a higher value under MT (60.01%), NT (56.74%) and CT (53.58%), respectively. This observation is similar with regard to SAL, SCC, and STC. It might be due to the reduced soil disturbance characteristics of conservation systems, thereby maintaining the soil’s natural state. There is a positive regression between these two properties across all three systems, with the highest R² = 0.8308 observed under MT. The highest carbon stocks were recorded in NT (2.82%) and MT (2.91%) compared to 2.01% in CT at surface depths of 0–5 and 5–10 cm. This can be explained by the accumulation of organic residues and a reduction in their oxidation. Nutrient availability (TN, P, and K) increased at depths of 0–5 cm and 5–10 cm, with the highest values in conservation systems. Furthermore, the results demonstrate a significant relationship and positive synergy between soil depth, tillage practices, and key physical and chemical soil properties, especially carbon stock, across the two cropping seasons. Full article

Long-term human cultivation activities are the key factors of the vertical distribution and storage dynamics of soil organic carbon (SOC) in cropland. Based on a 45-year long-term field experiment, this study systematically compared SOC dynamics and carbon storage characteristics in soil profiles (0–200 cm) between cultivated land and adjacent natural forest. The findings reveal the hierarchical regulatory effects of tillage management on the soil carbon pool. The results show that: (1) Under both land use types, SOC content decreased exponentially with depth, but values in cultivated soils were 0.35–1.54% lower than in forest soils at each layer. SOC content in surface soil (0–78 cm) was significantly higher than in the subsoil (78–158 cm) and substratum layers (158–200 cm) (p < 0.01). At equivalent depths, SOC in cultivated land was significantly lower than in forest land (p < 0.01). Over 45 years, the SOC accumulation rate in the surface soil of cropland (0.07 g·kg⁻¹·yr⁻¹) was only half that of forest land (0.14 g·kg⁻¹·yr⁻¹). (2) The controls of soil physicochemical properties on SOC differed with land use: in forest soils, SOC correlated positively with clay content (r = 0.63, p < 0.01), whereas in cultivated soils, SOC was primarily regulated by total nitrogen (r = 0.94, p < 0.01) and sand content (r = 0.60, p < 0.01) and negatively correlated with bulk density (r = −0.55, p < 0.01) and pH value (r = −0.45, p < 0.05). (3) Long-term tillage significantly reshaped soil profile structure, thickening the plough layer from 20 cm to 78 cm. Surface carbon storage reached 20.76 t·ha⁻², an increase of 11.13 t·ha⁻² compared with forest soil (p < 0.01). However, storage decreased by 4.99 t·ha⁻² and 7.60 t·ha⁻² in the subsoil and substratum layers, respectively (p < 0.01). The SOC storage increment rate was 50.95 t·ha⁻²·yr⁻¹ higher than that of forest soil in the surface layer but 46.81 t·ha⁻²·yr⁻¹ and 11.12 t·ha⁻²·yr⁻¹ lower in deeper layers. These results confirm that cultivation alters soil structure and material cycling, enhancing carbon enrichment in surface soils while accelerating depletion of deeper carbon pools. This provides new insights into the vertical differentiation mechanisms of SOC under long-term agricultural management. Full article

Reducing the fuel consumption of tractors has consistently been a critical challenge that the agricultural machinery industry must address. To investigate the energy consumption during the plowing process of tractors and enhance their economic efficiency, this study conducted comparative experiments under varying plowing speeds and depths. In this experiment, the CAN bus protocol was utilized for the collection of engine operational data, such as rotational speed and fuel flow. A GPS positioning system was adopted to measure the plowing speed of the tractor and combined with the data from the tractor coasting test, and then the energy consumption for operating the plow was determined. In addition, a tension sensor was installed on the three-point hitch to measure the horizontal pull force exerted by the five-share plow during plowing, thereby facilitating the calculation of the energy consumption of agricultural machinery. The findings indicate that when the tractor’s plowing speed is maintained at 5.7 km/h, both the average fuel consumption and the fuel consumption per unit area increase as the plowing depth increases. If the plowing depth is fixed at 23 cm, the average fuel consumption rises with an increase in plowing speed, whereas the fuel consumption per unit area decreases. The experimental data show that during the actual tillage operation of the tractor, the brake thermal efficiency of diesel engines ranges from 21.76% to 28.57%. The energy consumed by agricultural implements accounts for only 11.79% to 17.04% of the total fuel energy. The energy consumed in operating the tractor-drawn plow accounts for merely 7.87% to 13.66% of the diesel engine output energy. Approximately 23.24% to 38.69% of the effective power of the diesel engine is lost during the transmission process. This study provides valuable insights for optimizing the performance of tractors during operation. Full article

Aeschynomene indica L. has become a problematic weed in the upland direct-seeding rice fields of the lower Yangtze River region, China, leading to substantial yield reductions. A comprehensive understanding of its seed germination ecology and response to herbicides is crucial for developing effective control strategies. This study examined the effects of major environmental factors including temperature, light, pH, salt stress, osmotic potential, and burial depth on seed germination of A. indica and assessed the efficacy of 20 commonly used herbicides in rice under controlled conditions. Results revealed that germination was highly sensitive to temperature, with optimum constant and alternating temperatures of 35 °C and 40/30 °C (day/night), respectively, both achieving germination rates above 90%. The seeds were non-photoblastic, maintaining a high germination rate of 83.33% under complete darkness. Germination remained consistently high across a broad pH range from 4 to 9, with rates ranging from 83.33% to 96.67%. Salt and osmotic stresses markedly suppressed germination, with EC₅₀ values of 195.08 mmol·L⁻¹ NaCl and −0.43 MPa, respectively. Seedling emergence decreased significantly with increasing burial depth, with no emergence occurring at depths greater than 7 cm. The EC₅₀ for emergence was 4.21 cm. Among the herbicides screened, saflufenacil and mesotrione were the most effective pre-emergence treatments, with GR₅₀ values of 5.38 and 12.02 g ai ha⁻¹, respectively. Florpyrauxifen-benzyl and fluroxypyr-meptyl exhibited the highest post-emergence activity, with GR₅₀ values of 0.20 and 19.69 g ai ha⁻¹, respectively. These results underscore the high ecological adaptability of A. indica to paddy fields conditions and provide a scientific foundation for integrating chemical control with cultural practices such as deep tillage into sustainable weed management systems for paddy fields. Full article

Asoil loosening device is designed to overcome the poor soil disturbance performance observed during residual film recovery, thereby effectively improving residual film recovery rates. Based on soil properties measured in cotton fields, a discrete element method was developed to simulate the interaction between the soil and the soil loosening device. A comparative analysis of the soil angle of repose and soil firmness was conducted to validate the accuracy of the soil discrete element model. Simulation experiments were conducted to analyze the effects of forward speed on soil particle velocity, soil particle forces, and forces on the soil loosening device. A theoretical analysis was performed to examine how forward speed and soil penetration depth affect the soil disturbance coefficient. Using this coefficient as the evaluation metric, a Central Composite Design experiment was carried out. Using the soil disturbance coefficient as the evaluation criterion, a central composite design experiment was carried out to identify the optimal parameter set: a forward speed of 6 km/h and a tillage implement penetration depth of 108 mm. Under these optimized conditions, the standard deviation of the soil disturbance coefficient was measured at 1.92%, which satisfies the operational requirements. The results offer useful insights for the design improvement of tillage implements. Full article