Currently, the main optimization of pneumatic conveying seed-discharge systems targets distributors, ignoring the important role of pipelines. In this study, simulations were used to determine an improved structure of the conveying pipe. The horizontal pipe was determined to be a 300 mm straight pipe, which was connected under the vertical bellows as a transition. This study adopted the L9(34) orthogonal test method to optimize the bellows parameters, using as index the coefficient of variation of the uniformity of the bellow outlets. The indoor bench test was designed to validate different flow rate and bellows length combinations. The optimal bellows parameter combination of the corrugated circle had a radius of 8 mm, bellows length of 500 mm, corrugation distance of 40 mm and corrugation length of 16 mm, achieving a 3.46% coefficient of variation of the particle distribution in the plumbing. Under various particle mass flow rates (33.5, 67.0, 101 gs-1), the bellows length of the optimal solution was verified to be in the interval of 400-500 mm, and the consistency coefficients of the variations in row displacements of the system satisfied the requirements. This study provides guidance for the design and application of piping in pneumatic seed-discharge systems.

Straw return combined with direct-seeded rice (DSR), a furrow-ridge system, and biodegradable film mulching offers a promising alternative to puddled transplanted rice for mitigating methane emissions. However, strategies for reducing carbon dioxide (CO2) emissions and runoff in DSR systems remain unclear. Additionally, a challenge lies in developing techniques capable of translating data, simulations, and research findings into actionable farmer guidance, particularly through adaptive feedback mechanisms that enhance carbon sequestration efforts. To address these limitations, this study proposes an artificial intelligence (AI)-driven digital shadow and farmer assistant. The AI framework integrates fuzzy logic controllers (FLCs), modular artificial neural network (ANN) ensembles, Hydrus two-and three-dimensional (2D/3D) model, and generative pre-trained transformer (GPT) model. Field case studies were conducted in Babaiqiao, Nanjing, China, during the summers of 2023 and 2024. The adaptive hybrid simulated annealing-particle swarm optimization (AS-PSO) algorithm improved the performance of the FLCs (Ackley value of 2.0 & times; 10-4 and Griewank of 2.5 & times; 10-4) in controlling soil moisture and runoff. ANN ensemble improved predictions of surface flow variables, achieving coefficient of determination (R2) of 0.87 and 0.94, and mean absolute error (MAE) of 0.11 and 0.036 cm for modules 1 and 2, respectively. Hydrus 2D/3D simulated soil moisture with R2 of 0.91 and mean relative error (MRE) of 7.20 percent. Based on Likertscale ratings, the overall performance of the GPT model was 93.62 +/- 1.05 percent. Overall, the AI framework provided farmers with actionable, location-specific insights and feedback to researchers, supporting effective control of CO2 emissions and runoff risks.

To accurately predict wear locations on the rotary tillage blade surfaces operating in wet-adhesive soil, a novel discrete element modeling method of rotary tillage blade is first proposed, and an improved contact model incorporating the wear effects between wet-adhesive soil and blades is developed in this work. Model parameters are calibrated using direct shear and penetration tests, and a discrete element interaction model of the wet-adhesive soil-blade coupled system is established. The proposed model is then employed to investigate the effects of the blade shaft orientation, shaft speed and cutting-edge angle on the wear and tillage performance, evaluated through surface pressure and friction force. Additionally, the corresponding model verification tests and blade wear tests are conducted. The results show that the relative error of the blade shaft torque between the simulated value and the experimental value is 3.9%, and the simulated results align closely with the actual wear position on the blade surface. Wear is most pronounced on the front cutting edge, particularly under the forward rotation condition. Furthermore, increasing the cutting-edge angle of the blade from 60 degrees to 120 degrees leads to a 106.5% rise in cumulative pressure on the front cutting edge, indicating that the cutting-edge angle is a key factor influencing blade wear.

Combined strategies involving straw return and water management practices, such as furrow irrigation in directseeded rice systems, show varying performance in reducing greenhouse gas (GHG) emissions in rice-wheat rotations. However, achieving a reliable functional decoupling between the mechanized shallow-incorporated straw layer and the saturated subsurface water redistribution zone remains a key challenge, thereby limiting effective suppression of conditions that exacerbate methane (CH4) emissions. Additionally, decision support tools (DSTs) for optimizing freshwater demand, runoff recycling, and energy cost, while simultaneously reducing carbon dioxide (CO2) and nitrous oxide (N2O) emissions, remain underdeveloped. Further, robust frameworks capable of interpreting and translating data, simulations, and research findings into farmer-level decision-making to enhance the management of environmental trade-offs in rice-wheat rotations are still poorly defined. Therefore, this study proposes biomimetic tillage design and artificial intelligence (AI)-based DST by integrating a coupled Hydrus 2D/3D-MPC system with the generative pre-trained transformer (GPT) model to guide straw return and optimize water-energy use under a furrow-ridge system. Data collection, experiments, and model validation were conducted during the 2023 and 2024 rice seasons in Babaiqiao, Nanjing, China. Hydrus 2D/3D simulated wetting rates and soil moisture with an R2 of 0.80 and 0.89, respectively. For the biomimetic strategy, the optimized factors for straw-incorporated depth, plow pan thickness, and subsoiling depth were 6.50, 4.80, and 20.0 cm. Predictive control regulated conditions promoting GHG emissions while simultaneously optimizing water-energy use. The AI-based DST achieved performance score of 95.71 +/- 0.68 %, translating simulations into clear guidance for farmers. Biomimetic stratification increased irrigation demand by 9.9 %, but integrating it with film mulching and runoff recycling significantly offset the increased freshwater requirement and reduced energy costs by 23.14 %. Overall, this study demonstrates the effectiveness of integrated multi-objective techniques for optimizing water-energy use, mitigating conditions that exacerbate GHG emissions, and reducing runoff-related environmental footprints in rice-wheat rotations.

Mechanical damage to wheat grains is inevitable during harvester threshing; damaged wheat grains are vulnerable to mold colonies. Selecting optimal threshing pattern is an important approach to reduce wheat storage quality loss for threshing damage. Wheat harvested by tangential flow threshing patterns (TFTP) and axial flow threshing patterns (AFTP) were used as test samples and wheat harvested manually were used as control samples. Moisture contents of all wheat grains were adjusted to 18% (wet basis) before storage, then wheat grains were stored in an artificial climate box at temperature of 30 °C and humidity of 80% RH. The mold colonies and fatty acids value of wheat harvested by TFTP increased faster than those of wheat harvested by AFTP, the dry basis 1000 grain weight, seed vigor and germinating traits of wheat harvested by TFTP decreased faster than those by AFTP during storage. After storage, there were significant differences between TFTP and AFTP in the mold colonies, seed vigor, dry basis 1000 grain weight (p < 0.05). Germination potential and rate were significantly negative correlation with mold colonies. Aberrations of seedling and mold colonies in seedling root had significantly positive correlation with the mold colonies. The storage quality traits of wheat harvested by AFTP were better than those of wheat harvested by TFTP. AFTP should be preferred for wheat harvested mechanically in terms of the storage quality of wheat.

Organic–inorganic compound fertilizer application technology is a key technology for chemical fertilizer efficiency improvement, and stable grain yield increase. However, current agricultural machinery is unable to achieve uniform application of both organic and inorganic fertilisers. This study has compared two modeling methods and optimally selected the EDEM-Fluent coupled method. It aims to investigate the mechanism by which four factors—namely inorganic fertilizer drop location (Polar angle: −80° to 80°, polar radius: 60 mm to 180 mm), organic fertilizer flow rate (875–3500 g·s−1), inorganic fertilizer proportion (10–50%), and fertilizer spreading disc rotational speed (300–700 r·min−1)—influence inorganic fertilizer uniformity. A Box–Behnken test was designed with the pole angle and pole diameter of the drop location, organic fertiliser flow rate, spreading disc rotational speed, and coefficient of variation in the uniformity of the inorganic fertilisers as indexes. The Box–Behnken test divided the fertiliser drop location into left and right parts and established a mathematical model of fertiliser drop location, rotational speed, and organic fertiliser flow rate. Finally, the predictive performance of the model was verified in the field by testing four scenarios: low speed–low flow rate, low speed–high flow rate, high speed–low flow rate, and high speed–high flow rate. The root mean square error (RMSE) between the EDEM-Fluent coupled test and the bench test is 1.53, which is better than the RMSE (2.55) between the EDEM test and the bench test. Before optimization, the coefficients of variationof inorganic fertilizer (ICV) under four operating conditions were 28.93%, 32.43%, 38.17%, and 29.32% respectively. After optimization, the corresponding values were 19.34%, 23.78%, 21.45%, and 23.10% respectively. Compared with the pre-optimization results, the organic fertilizer coefficient of variation (OCV) remained stable, while the inorganic fertilizer coefficient of variation (ICV) decreased by an average of 10.29%. This study greatly improved the uniformity of inorganic fertiliser in the organic–inorganic spreader and provides a basis for subsequent intelligent spreaders.

Straw return is essential for improving soil fertility, recycling organic matter, and sustaining productivity in rice–wheat systems. This study focuses on the conceptual design and systematic analysis of the spatial and temporal variability of straw return methods and their classification. We proposed and analyzed 36 technical models for straw return by integrating spatial distribution (depth and horizontal placement) with temporal variability (decomposition period managed through mulching or decomposers). The models of straw return were categorized into five classes: mixed burial, even spreading, strip mulching, deep burial, and ditch burial. Field experiments were conducted in Babaiqiao Town, Nanjing, China, using clay loam soils typical of intensive rice–wheat rotation. Soil properties (bulk density, porosity, and moisture content) and straw characteristics (length and density) were evaluated to determine their influence on decomposition efficiency and nutrient release. Results showed that shallow incorporation (0–5 cm) accelerated straw breakdown and microbial activity, while deeper incorporation (15–20 cm) enhanced long-term organic matter accumulation. Temporal control using mulching films and decomposer agents further improved moisture retention, aeration, and nutrient availability. For the rice–wheat system study area, four typical straw return modes were selected based on spatial distribution and soil physical parameters: straw even spreading, rotary plowing, conventional tillage with mulching, and straw plowing with burying. This study added to the growing body of literature on straw return by providing a systematic analysis of the parameters influencing straw decomposition and the incorporation. The results have significant implications for sustainable agricultural practices, offering practical recommendations for optimizing straw return strategies to improve soil health.

Side-deep fertilization in paddy fields is key to improving nitrogen use efficiency (NUE) and reducing surface water pollution. However, conventional applicators are overly heavy and incompatible with paddy machinery’s limited horsepower, restricting the technology’s popularization. To solve this, this study had two core goals: develop a lightweight, low-power centrifugal distribution-type side-deep fertilizer applicator matching paddy machinery’s load and horsepower limits; design a dedicated control system to enhance fertilization uniformity and fertilizer adaptability. First, the bulk density-based fertilizer model was improved through theoretical analysis of the external grooved wheel fertilizer discharging device, and its performance was validated in bench experiments. Simultaneously, the centrifugal distribution principle was analyzed, with dispenser rotational speed and discharge rotational speed selected as key factors and uniformity across rows chosen as the response variable. The optimum rotational speed-matching and optimal speed-matching models of the dispenser and distributor were established through CCD testing. The control system of the overall machine integrated both the bulk density-based fertilizer discharge and optimal speed matching models and performed tests in the field. The results showed that the average error in total fertilizer discharge is 4.84%, with a maximum error value of 7.93%, the average coefficient of variation for fertilizer discharge across rows was 5.47%, with a maximum coefficient of variation of 7.03%. Furthermore, comparative analyses revealed that the control system adapted well to different fertilizers and maintained stability between static and dynamic tests, thereby indicating strong dynamic adaptability. Compared with other fertilizer applicators for paddy field machinery, this device offers evident advantages in terms of quality, cost, and horsepower requirements, highlighting its potential for widespread adoption.

This study contradicts the discrepancy between limited greenhouse spaces and substantial volumes of organic fertiliser utilised. Using EDEM numerical simulation software, we analysed the contact between the centrifugal side-throw organic fertiliser-spreading disc and the organic fertiliser particles. The factors examined included fan inclination angle, disc speed, and angle of guide vanes. The coefficient of variation was used as the measure. A three-factor, three-level Box-Behnken Design (BBD) response surface test was performed to procure response surface plots, fit the data, and determine the optimal values. To validate our findings, a specific test was conducted to evaluate the efficiency of the guide vanes. The superiority of the fertiliser-spreading structure was verified by repeating it three times in field trials. Our simulation indicated the optimal values for the rotational speed of the fertiliser-spreading disc and the inclination angle of the fan blade to ensure uniform fertiliser distribution. We discovered that an excessive number of guide vanes can hinder the smooth application of organic fertilisers. In addition, the guide vanes set at wider angles demonstrated superior dispersion. Precise optimisation identified a disc rotational speed of 417 r.min-1, fan inclination of 16.67 degrees, and guide vane angle of 20 degrees. With these settings, the ideal coefficient of variation for the lateral distribution of organic fertiliser was 15.73%, and below 16.48% in the field operation. In conclusion, we designed an adjustable centrifugal side-throw organic fertiliser-spreading disc to address the challenges of organic fertiliser distribution in greenhouses. This offers a foundational model for mechanising organic fertiliser application in agricultural facilities.

Intensified rice-wheat rotations increase greenhouse gas emissions through straw incorporation and puddled transplanted rice. While combining rotary straw return with furrow-irrigated, directly dry-seeded rice (DDR) shows promise in mitigating emissions, a decision support tool to guide such practices remains underdeveloped. Such a tool is essential for optimizing energy and water footprints, methane (CH4) emission risks, and tailwater reuse. Moreover, the mechanistic basis for integrating these optimizations with water conservation practices remains unclear. Therefore, this study proposes a finite element (FE)-model predictive control (MPC) framework, developed by coupling Hydrus 2D/3D with a closed-loop optimal model. The system is designed to optimize energy costs and water use in DDR under straw return and varying field conditions, including bare soil, biodegradable film mulching, and tailwater reuse. Experimental validation, data collection, and field case studies were conducted in Babaiqiao, Nanjing, China, during 2023 and 2024 seasons. These activities included rotary straw incorporation, furrow-ridge layouts, dry-seeded rice cultivation, soil hydraulic experiments, tailwater recovery and reuse, and relevant agronomic management. Hydrus 2D/3D effectively simulated wetting rates and soil moisture content for bare and film-mulched ridges, at R-2 of 0.79 and 0.89, and 0.80 and 0.90, respectively. Predictive control and tailwater reuse had statistically significant (p < 0.05) effects on energy and water consumption. Integrating film mulching with the FE-MPC framework reduced cumulative water use by 38.0 %. When applied with tailwater reuse, the system offset up to 34.9 % of freshwater demand. In bare furrow-ridge, the controller achieved energy cost savings of up to 32.8 and 41.8 % without and with tailwater reuse, respectively. Film mulching increased energy savings by 53.7 and 62.7 % compared to conventional alternating wetting and drying. The study provides practical strategies, which optimize energy costs and mitigate soil anoxia and tailwater-related pollution risks, thereby reducing the environmental footprint of rice-wheat rotations.

Soil tillage is essential for improving soil structure, enhancing fertility, promoting crop growth, and increasing yield. However, precise and efficient standardized methods for quantitatively evaluating post-tillage soil structure are still absent. This study aims to develop a general quantitative evaluation method for post-tillage soil structure using close-range photogrammetry. Six soil surface sample plots of different scales were selected, and two image acquisition methods and three platforms were chosen for image capture and 3D reconstruction. Geomagic Wrap was used for post-processing the models, with indicators such as clod sizes, surface flatness, and cumulative percentage used for quantitative description. Model accuracy was validated using traditional needle plate and vernier caliper measurements. The most effective combinations of image acquisition methods and 3D reconstruction platforms were identified based on modeling efficiency and quality. The results showed that combining image acquisition, 3D reconstruction platforms, and post-processing software enables high-precision 3D reconstruction and accurate digital information retrieval. Image Acquisition Method One and the AgisoftMetashape platform demonstrated the best combination in terms of model completeness, texture detail, and overall quality. This combination is recommended for the 3D reconstruction and digital information retrieval of soil surfaces. This study provides a method for evaluating post-tillage soil structure, including image acquisition, 3D reconstruction, model post-processing, and quantitative metrics.

[Objective]As one of the main planting systems in the Yangtze River Basin of China,the rice-wheat rotation system is playing an important role in ensuring national food security and sustainable agricultural development.A driving type straw inter-row collecting-mulching device was designed to address the problems of straw aerial seeds and clogging of machinery during the operation of no tillage seeders in rice-wheat rotation areas with full straw coverage.The device removes straw from the seed belt and throws it between the rows.[Method]Firstly,through theoretical analysis of the driving type straw-removing spring tooth and reasonable lateral displacement limitation of straw,a mathematical model was established for the spacing between straw paddles and the lateral displacement of straw.The main parameters that affect the cleaning rate and the maximum lateral displacement of straw were determined to be forward speed,rotational speed,and working angle,and the range of values for each parameter was forward speed 4-8 km/h,rotational speed 160-220 r/min,and working angle 25°-35°.Then,with forward speed,rotational speed,and working angle as experimental factors,and straw cleaning rate and maximum lateral displacement of straw as experimental indicators,a three factor three-level quadratic regression orthogonal indoor soil tank experiment was conducted.[Result]The results of the soil bin test showed that the primary and secondary order of influence on the straw removal rate was the rotational speed,the forward speed,and the working angle;Among them,the interaction term between the rotational speed and the working angle had a significant impact on the straw removal rate,while the interaction term between the forward speed and the rotational speed,and the forward speed and the working angle had no significant impact on the straw removal rate.The primary and secondary order of influence on the straw lateral displacement was the rotational speed,the working angle,and the forward speed;Among them,the interaction term between the forward speed and the working angle,as well as between the rotational speed and the working angle,had a significant impact on the straw removal rate,while the interaction term between the forward speed and the rotational speed had no significant impact on the straw lateral displacement.Obtained from the multi-objective optimization model,the optimal parameter combination was forward speed of 4.3 km/h,rotational speed of 220 r/min,and working angle of 26°.At this time,the straw removal rate was 84.7%,and the maximum lateral displacement of straw was 37.5 cm.Finally,field experiments were conducted on the operational performance of the cleaning device using the adjusted optimal parameter combination.The results show that the machine worked stably,with a straw removal rate of 80.6%,an average straw removal width of 25.1 cm,and a width stability coefficient of 82.2%.The operating effect met the requirements of no-tillage sowing agronomy.[Conclusion]The designed driving type straw inter-row collecting-mulching device has a high straw removal rate and stable straw removal width.This study can provide a reference for the study of straw inter-row collecting-mulching tools in rice wheat rotation areas with full straw returning.

[Objective]Precision seeding technology is one of the key ways to achieve reasonable crop group and ensure the increase of crop yield.However,there is a lack of the methods for testing and evaluating the precision of seeding quality as well as the methods of quantitatively evaluating the spatial distribution of post-sowing seeds in soil volume,and the response of crop emergence rate,yield,and its components to different precision sowing technologies.[Method]A precise seeding quality evaluation method based on multi-dimensional indicators was constructed using information technologies such as in-situ laser seed position tester,3D digitization,and Python.The indicators included one-dimensional evaluation indicators(seed straightness),two-dimensional evaluation indicators(seed dispersion),and three-dimensional evaluation indicators(seed homogeneous nutrient utilization rate).Afterwards,a 2-year precision sowing experiment on wheat was conducted using a precision sowing test bench in a residential area.Nine treatments were used,including a row spacing of 20 cm,and a combination of seed spacing×sowing depth of 1.5 cm×2 cm(A1B1),1.5 cm×3 cm(A1B2),1.5 cm×6 cm(A1B3),3 cm×2 cm(A2B1),3 cm×3 cm(A2B2),3 cm×6 cm(A2B3),4.5 cm×2 cm(A3B1),4.5 cm×3 cm(A3B2),and 4.5 cm×6 cm(A3B3).This experiment was conducted to verify the quality evaluation method of this sowing.[Result]The experimental results showed that the seed straightness was better in the A2B3 treatment for 2 years,with coefficients of variation of 28.63%and 32.67%,respectively;The seed dispersion was better in the A2B1 treatment for 2 years,with coefficients of variation of 28.17%and 30.14%,respectively;The seed homogeneous nutrient utilization rate reached its maximum value of 91.33%in A2B1 treatment(2021-2022).There was a significant correlation at the 0.01 level between the seed homogeneous nutrient utilization rate and crop emergence rate,yield per plant,total number of grains per plant,and thousand grain weight.[Conclusion]A precise comprehensive evaluation method for seeding quality based on multi-dimensional indicators such as seed straightness,seed dispersion,and seed homogeneous nutrient utilization rate can accurately analyze the distribution quality of seeds in the field after sowing.In addition,the analysis method of the response relationship between seed-soil homogeneous nutrition rate and crop emergence rate,yield per plant and yield components is also conducive to establishing the relationship between precise seeding technology and crop growth and promoting the integrated development of agricultural machinery and agronomy.

In order to measure wheat yield and wheat spike phenotypes, the grain number of wheat spikes is counted manually at present, but acquiring the grain number of wheat spikes is laborious and time-consuming. Counting the grain number of wheat spikes with an image processing method is promising, yet the application of this method is flawed due to its low accuracy. In this work, images of wheat spikes were collected and processed with technical procedures, including image cropping, image graying, histogram equalization, image binarization, eroding operation, removing small objects, filling image holes, revolving vertical spikes, cutting off stems, and removing stems. Wheat stems in binary images were eliminated by the sum pixels method, and the morphological characteristic parameters of the image areas of wheat spikes and lengths of wheat spike axes were calculated. Mathematical models relating the image areas of wheat spikes and lengths of the wheat spike axes to the grain number were established, and the mathematical models were verified. The results showed that the characteristic parameters of the image areas of wheat spikes and the lengths of the wheat spike axes for the spike images were linear relative to the grain number, and the maximum determination coefficients R2 were 0.9336 and 0.9012, respectively. The maximum determination coefficients R2 for the practical and predicted grain numbers were 0.9552 and 0.9369, respectively, and the minimum average absolute error was 2.3, while the average relative error for the mathematical models was 5.65%. The mathematical models relating the image areas of wheat spikes and the lengths of the wheat spike axes to the grain number were practical and accurate, and the mathematical model comparing the image area of wheat spikes and the grain number was superior to that comparing the length of the wheat spike axis and the grain number. The grain number of wheat spikes could be acquired accurately and quickly by the image processing method extracting the characteristic parameters of wheat spikes.

The monitoring and the rapid quantification of pesticides and their residues are becoming increasingly important in the field of food safety. Herein, the polycaprolactone/polypyrrole/beta-cyclodextrin (PCL/PPy/beta-CD) flexible sensor was developed for the electrochemical determination of new neonicotinoid insecticide Dinotefuran (DNF). The morphology, structure, and hydrophilicity of PCL/PPy/beta-CD sensor probes were characterized by SEM, FTIR spectroscopy and static contact angle test. Under optimum conditions, the fabricated PCL/PPy/beta-CD sensor exhibited excellent electrochemical sensing performance for DNF with a low detection limit of 0.05 mu M in the linear concentration range from 0.2 mu M to 50 mu M and high sensitivity 14.07 mu Amu M-1cm(-2), which attributed to the two-stage porous structure, good electron transfer rate and the adsorption effect. The PCL/PPy/beta-CD sensor also showed reproducibility (RSD = 4.76%), stability, and high selectivity towards DNF. In addition, a real samples investigation in rice with recoveries of 96.67 % similar to 103.65 % implied the good application potential of PCL/PPy/beta-CD in DNF monitoring.

Field in situ infiltration experiments at different depths can be used to express the state of soil stratification, and the physical differentiation of soil layers, in order to quantify the changes in the water of the soil profile. This study aims to obtain the infiltration capacity and water retention of paddy soils. The field in situ soil infiltration experiments were also carried out at different depths to identify the soil stratification in the representative plot under long-term mechanized tillage of smallholder farmers in the rice-wheat rotation region of eastern China. Seven infiltration pits of different depths were excavated in the experimental plots. After that, the infiltration experiments were conducted at the bottom of the pits. Soil water content was then measured in the layers for 48 hours of infiltration. A systematic investigation was made to explore the soil infiltration capacity at the bottom of the pits and the soil water content of each layer. The results showed that an accurate description was achieved in the water infiltration and water holding capacity of the soil at different pits after the infiltration experiments at different depths. The location and thickness of the plow pan were also clearly identified during this time. The plow pan was started at a depth of about 15 cm, indicating the outstanding difference between the cultivated layer and the plow pan. The average soil penetration resistances of the cultivated layer and the plow pan were 1 005.79 kPa, and 1 910.73 kPa, respectively.The soil profile showed that the soil in the cultivated layer shared a loose morphology and dense root distribution, whereas, the soil in the plow pan presented a high bulk density, low porosity, and poor permeability, while the soil in the subsoil layer was in more iron-manganese spots and poor structure. Furthermore, the soil infiltration parameters decreased with the increasing pit depth. The average infiltration rate and cumulative infiltration in the 0-15 cm pit depth range were 17.04 and 18.06 times higher,respectively, than those in the ＞20-30 cm pit depth range. The three infiltration models were fitted using Horton, Kostiakov and Philip. Specifically, the Kostiakov model had the highest R~2（0.98-0.99） and the smallest RMSE（0.01-0.77 mm/min）, indicating the consistency of the fitted parameters. Infiltration parameters were extremely significant correlated with the soil bulk density,water content, total porosity, and field capacity（P＜0.01）, but not with the soil penetration resistance（P＞0.05）. Field in situ infiltration experiment at different depths was an important tool to identify the soil stratification and quantify the water function differentiation in the soil profiles, according to the soil profile, cone penetration and sampling. Long-term mechanized tillage under the smallholder production model in the rice-wheat rotation region of eastern China can be expected to result in the apparent stratification and vertical differentiation of soil water functions in paddy soils. In turn, there are also some significant differences in the infiltration capacity between the cultivated layer and soil layers below the cultivated layer. This study can provide a reference for mechanical cultivation and irrigation in rice-wheat rotation regions.

Subsoiling (SS) is an important technology in conservation tillage, but soil-disturbance characteristics in the SS are rarely described. Research on soil-disturbance characteristics during SS is conducive to the design and optimization of subsoilers, which provides a basis for reducing draft force and energy consumption. This study conducted SS experiments at five different tillage depths in the field with a specific field in situ test-rig facility, and in situ videotaping was made from five positions during SS. The microrelief test, draft force test, disturbance cross-section test and disturbance process analysis were conducted after SS. The results showed that draft force increased with tillage depth as a quadratic function. Soil displacement parameters and soil crack parameters extracted from the video of SS were significantly correlated with tillage depth, which could be used for a quantitative description of the paddy soil-disturbance characteristics. Cross-sectional area showed a trend of “increasing then decreasing” with increasing tillage depth, reaching a maximum at a tillage depth of 20 cm. When the tillage depth was greater than 20 cm, the bottom of the disturbing boundary formed a “mole cavity”. Fallback rate was used to describe the change in disturbed height or width during and after SS, which exceeded 100% at maximum. The surface roughness of microrelief and the size of the average clods reached the maximum at tillage depth of 20 cm. Considering the shallow cultivation layer of paddy soil in rice–wheat rotation, the recommended tillage depth of 20 cm could achieve maximum soil disturbance and minimum energy consumed.

为探究波纹管结构参数与输送均匀性的关系,获得最优参数组合以提高气力排肥均匀性.本文基于CFD-DEM耦合仿真技术构建了以排肥均匀性变异系数为响应值的二次响应面模型,在单因素试验的基础上采用BDD法研究了波纹管幅宽、波纹间距和波长之间交互作用对排肥均匀性的影响,并获得了波纹管的最佳参数组合,最后进行台架试验对仿真模型与优化结果进行验证.仿真试验结果表明,排肥均匀性变异系数随波长、幅宽、波纹间距的增加先减小后增加,波纹管结构参数对排肥均匀性的影响显著性顺序为幅宽>波长>波纹间距.波纹管最优结构参数为波长18.103 mm,波纹间距12.158 mm,幅宽8.863 mm,此时排肥均匀性变异系数为7.5％.单因素台架试验中尿素颗粒仿真预测值与台架实际值变化趋势一致,数值基本重合,最优参数组合波纹管排肥均匀性变异系数与仿真试验预测值相对误差的均值为5.84％,说明仿真模型精确可靠.复合肥颗粒变化趋势与尿素颗粒基本一致,说明仿真模型具有普适性.本研究可为波纹管的使用与优化提供参考.

【Objective】In order to quantify the influence of seed-to-seed distance on wheat root development in soil layers under single seed precision sowing,an integrated technique combining root architecture digitizer and MATLAB simulation was developed to quantify wheat root length density （RLD） and relative root length density （NRLD）,as well as related models in each soil layer in the field.【Method】Ningmai 13 was used as experiment marital and the seed was sown with single seed precision sowing method in no-till paddy soil.The experiment was carried out in 2020 and 2021,respectively.Five treatments （JT1.5,JT3,JT4.5,JT6.7,and JT9）with row spacing of 1.5,3.0,4.5,6.7 and 9.0 cm were introduced for field stand control.RLD was analyzed with combined technologies,i.e.root architecture digitizer and 3D root system architecture reconstruction with Pro-E,supplemented with MATLAB simulation,which facilitated fine segmentation and analysis of the rhizosphere dynamics under soil space voxel resolution of 3 mm~3,and this further results quantified RLD distribution dynamics and the development of NRLD models along soil layers.【Result】The post-paddy wheat RLD decreased gradually along the soil layers under different treatments.As much as 95%of the root system was confined within the top soil layer in 0-9 cm,below which,root length decreased rapidly.The wheat root expansion area of a single plant first increased along the soil layers and then decreased.Root expansion started from the seed site as its central point,and revealed an obvious directional and constraining effects induced by the soil environment.With the increase of seed-to-seed distance,wheat RLD experienced first an increasing and then a decreasing trend,and the maximum value of which was found at JT4.5.The expansion area of wheat RLD increased with the increased seed-to-seed distance,and the maximum value of which was 22 972 mm~2.Either the too high or the too low density stand was found adversely impacts the efficiency of root configuration.Only the most suitable sowing density led to the best 3D distribution of wheat root system,which has been considered as the primary mechanism for efficient utilization of soil spatial resources.The NRLD distribution within 0-20 cm soil layers satisfied both cubic polynomial and exponential models well （R~2＞0.99,RMSE＜0.1）,but when considered the field state root system architecture,it was found that the exponential model was more realistic and fit the field wheat RLD the best along the soil layers.【Conclusion】An integrated technique combining root architecture digitizer and MATLAB simulation was developed to quantify wheat RLD and NRLD in the field,which satisfactorily illustrated the influence of seed-to-seed distance on RLD and NRLD along the soil layers.The results showed that the proposed method could be applicable for studies of wheat precision cultivation,precise water and fertilizer management,root configuration regulation and so on in the future.