Direct solar drying has been widely used as the simple structure,easy manufacturing,and portability.The surface of the material is prone to overheating due to direct exposure to strong light radiation.Mechanical ventilation has been used to improve the drying quality.Shade mesh can be installed to reduce air temperature and excessive light on materials.However,the available solar energy can be reduced at the same time.In addition,the ventilation equipment is typically powered by photovoltaic cells.Most solar radiation energy is converted into heat energy and directly dissipated due to the limitation of the bandgap width of semiconductor materials.Solar energy cannot be fully utilized for drying.Overall,there is a low value in the comprehensive utilization rate of solar energy in the drying systems.It is often required to improve the utilization rate of solar energy for high-quality drying materials.In this study,spectral splitting technology was applied for direct solar drying.The solar spectrum was split into two components at 640 nm.Specifically,the 280-640nm band was reflected into the photovoltaic cell for the direct power generation,while the 640-2 500 nm band was transmitted into the interior of the drying chamber to raise the temperature of the air.A systematic investigation was implemented to explore the effects of direct solar drying,solar shade drying,and spectral splitting solar drying on the drying time,drying efficiency,color difference,nutritional composition,and microstructure of mulberry leaves.Additionally,the electrical performance of the photovoltaic module was also evaluated to determine the comprehensive utilization rate of solar energy.The experimental results show that the drying efficiency of direct solar drying(7.93％)was close to that of spectral splitting solar drying(7.84％),both of which were higher than that of solar shade drying(3.79％);In view of the exposure to intense light and high temperatures,the worst quality of mulberry leaves was found after direct solar drying,with a color difference of 24.39,a large loss of nutrients,and serious shrinkage and deformation of epidermal cells;The color differences of mulberry leaves were 12.01 and 11.33 after solar shade drying and spectral splitting solar drying,respectively.There were high retention rates of nutrients and bioactive compounds,along with minimal shrinkage in microstructure.Therefore,both solar shade drying and spectral splitting solar drying enhanced the mulberry leaf quality.The biological effects of the red light on the mulberry leaves after spectral splitting solar drying also outperformed those after solar shade drying in the quality metrics,such as the color difference and chlorophyll contents;The spectral splitter photovoltaics received less solar energy,with the 11.47％increase of photoelectric conversion efficiency.While the photoelectric conversion efficiency of conventional photovoltaics was only 5.67％,due to the high temperature and light-induced degradation.There was the best quality of mulberry leaves after spectral splitting solar drying,with a solar energy utilization rate of 10.61％.This finding can provide the technical support to improve the quality of solar drying products and the utilization rate of solar energy.
Electrification,intelligence,and multifunctionality can be promoted in agricultural machinery.In this study,a distributed electric tracked chassis was specifically developed for complex unstructured agricultural terrain.A modular chassis also consisted of the power,walking,electrical control,and intelligent perception system.Among them,the power system was driven by a 72 V lithium battery pack.The power was then provided for two 3 kW permanent magnet synchronous servo motors,each of which was integrated with a planetary gearbox to output the high torque suitable for track drive.The walking system was integrated with the rubber tracks,drive wheels,guide wheels,an independent suspension wheel group,and a tensioning device,thus balancing lightweight with high passability.The electrical control system consisted of the vehicle control unit,motor control units,battery system,and CAN communication network.The torque and energy distribution were responsible for the real-time data interaction with the subsystems.The intelligent perception system was integrated with a GPS/IMU navigation device,PTZ camera,and ultrasonic radar using the intelligent driving domain controller.Precise positioning,environmental perception,and path planning were then achieved in complex agricultural working environments.In the electrical and electronic architecture,the"high-voltage drive-low-voltage control"layered power supply and multi-bus communication topology were adopted to adjust the rapid dynamics and high reliability of the power system.The high-voltage system was powered by the 72 V battery,with the energy distribution and protection using the high-voltage distribution box.The low-voltage system consisted of the 12 and 24 V networks,providing power to the controllers,sensors,communication devices,and braking units.The multi-bus collaborative communication topology included multiple CAN buses and an RS485 bus,the real-time data exchange between the vehicle and motor control units,environmental perception and intelligent control data exchange,as well as the program burning and parameter calibration.The coordinated multi-bus system was obtained through efficient and stable data transmission between control units,providing reliable communication support for the intelligent operation.According to the centralized domain controller and standardized V-model,the application layer software was developed for the chassis domain controller.A model-based design was integrated with the multi-level control functions,signal diagnostics,and functional safety mechanisms.The application layer software was verified the automatically generated code,fully meeting the standard requirements of ISO 26262 functional safety,MAAB modeling,MISRA C 2023 code generation,the software compliance and functional safety.Multi-body dynamic rigid-flexible simulations and prototype testing show that the distributed driven electric tracked chassis was also met the requirements of the power,passability,load capacity,climbing,obstacle-crossing and steering performance.In the maximum speed test,the chassis was operated stably at 2.11 m/s;In the load performance test,the chassis ran smoothly with a 1 500 kg load,with the even track grounding and no slippage or yaw;In the 25° slope climbing test,the chassis demonstrated the stable climbing;In the obstacle-crossing test,the chassis successfully passed the obstacles up to 0.25 m high,with the minimal vertical acceleration and no severe shock or subsidence;In the steering performance test,the chassis exhibited the better trajectory consistency during in-place and small-radius turns,with the maximum deviation controlled within±2％,and the minimum turning radius 12％smaller than the design value,indicating the excellent steering flexibility and structural stability.Overall,a systematic technical pathway can be obtained for the electronic,electrical,and controller software architecture of the distributed electric-driven crawler chassis for complex agricultural working environments.The finding can also provide the technical and theoretical support for the high-performance and highly adaptable intelligent agricultural machinery.
Detecting buckwheat hulling is one of the key procedures to improve hulling efficiency and product quality during processing.Conventional detection of hulling performance can rely on manual sampling with visual inspection.However,manual approach cannot meet the efficient,standard and large-scale processing in buckwheat industry,due to the highly subjective,time-consuming and labor-intensive task.Therefore,it is of great practical significance to develop an efficient and reliable online detection for buckwheat hulling.In this study,the performance of an online detection device was evaluated for buckwheat hulling.A 6QB-150 rubbing-type buckwheat hulling machine was selected as the research object.Two modules were composed of:a sampling mechanism and an image acquisition.Among them,the sampling mechanism was used for timely and quantitative sampling of the hulled materials during operation,especially for the stable sample collection.The image acquisition was utilized to capture the high-resolution images of the sampled materials,thereby providing for the reliable visual data for subsequent analysis of hulling performance.The structural parameters of the sampling mechanism were optimized,such as the discharge height.Enhanced discrete element method(EDEM)was conducted to explore the motion behavior and spatial distribution of buckwheat particles during sampling.The simulation results demonstrated that the discharge height posed a major influence on particle dispersion.Once the discharge height was within the range of 550-600 mm,the buckwheat particles exhibited a uniform distribution,indicating the high consistency and accuracy of image acquisition.A series of experiments were conducted to further evaluate the performance and rationality of the online detection device under the different discharge heights.The experimental range was set from 350 to 600 mm with an interval of 50 mm.The distribution states of buckwheat samples were then captured at each height level using an industrial camera.The spatial distribution of the buckwheat grains during sampling was quantitatively evaluated to take the variance-to-mean ratio as an index.The experimental results indicated that discharge height shared the outstanding effect on the spatial distribution of particles and the quality of the captured images.The dispersion of buckwheat grains improved gradually,as the discharge height increased,leading to more uniform spatial distribution.Once the discharge height was controlled within the range of 550-600 mm,the variance-to-mean ratio of the captured buckwheat images ranged from 3.5 to 7.03,indicating low variability and high uniformity.Particle overlap and clustering were reduced to significantly enhance the clarity and reliability of image features for subsequent analysis.Overall,the stable and high-quality image data was achieved for the highly efficient online detection,compared with the conventional manual sampling.The relationship between discharge height and image acquisition quality can provide a theoretical basis and technical support to optimize sampling parameters of online detection.Furthermore,the research can contribute to the processing efficiency,product quality and equipment in modern agriculture.
This research aims to systematically investigate the influence of pulsed vacuum drying(PVD)parameters on the drying kinetics,physicochemical attributes,and volatile flavor profiles of red jujube slices.Various PVD parameters were evaluated,including drying temperatures(65,70,and 75 ℃),vacuum holding durations(10,15,and 20 min),and atmospheric holding durations(2,4,and 6 min).Hot air drying(HAD)was utilized as the control group.The experimental results demonstrated that the total drying duration was shortened significantly as the drying temperature escalated,whereas it was moderately extended with the prolongation of both vacuum and atmospheric holding times.The drying kinetics were attributed to the complex interplay between thermal energy transfer and the pressure-driven moisture diffusion in the PVD process.Color preservation was one of the most critical quality indicators for fruit processing.Once the treatment group was subjected to a drying temperature of 70 ℃,a vacuum holding time of 15 min,and an atmospheric holding time of 6 min(designated as PVD-70 ℃-15:6),the color preservation was characterized by the highest luminosity(L* value of 55.50)and the minimum total color difference(ΔE* value of 1.97),indicating the most favorable appearance similar to the fresh samples.The macro-level observations were further supported by microstructural analysis via scanning electron microscopy.While the HAD-treated slices displayed a densely packed and collapsed cellular arrangement,leading to maximum hardness and diminished crispness.By contrast,the PVD-70 ℃-15:6 samples shared a well-developed,uniform honeycomb-like porous structure to facilitate a better balance between low hardness and moderate crispness after the mitigation of structural shrinkage.Furthermore,the landscape of volatile flavor was dominated by the drying parameters.Radar plot analysis and Principal Component Analysis(PCA)indicated that there were significant(P＜0.05)variations in the aromatic profiles under the different treatments.According to the headspace solid-phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS),a total of 77 volatile compounds were identified and then quantified,including 11 acids,14 esters,42 hydrocarbons,2 alcohols,3 aldehydes,1 ketone,and 4 other compounds;Among them,organic acids,with the relative content from 16.66％to 27.92％,were identified as the predominant contributors to the characteristic aroma of the red jujube slices.Notably,the PVD-70 ℃-15:6 treatment demonstrated that the relative content of aldehydes and acids substantially increased by 33.55％and 21.82％,respectively,compared with the HAD control.A relatively stable acidic profile was obtained to promote the synthesis and retention of key aldehyde-based flavor precursors after the fluctuations of cyclic pressure in the PVD process.In the PVD-70 ℃-15:6 treatment,the optimal overall quality was achieved to effectively balance the drying efficiency with the preservation of the structural,aesthetic,and aromatic integrity of the red jujubes.The findings can also provide a robust theoretical and technical framework for pulsed vacuum drying in high-quality dehydrated functional foods.
Particle sorting and transport dynamics of eroded sediment can be expected to clarify the erosion mechanism of spoil tips in soil and water conservation.This study aims to investigate the response of sediment particle sorting and transport to hydrodynamic parameters during erosion.Two spoil materials,namely the Lou soil and aeolian sandy soil,were selected as research objects.Runoff scouring experiments were conducted under two slopes(28°and 32°)and four inflow rates(8,12,16,and 20 L/min).A systematic analysis was also implemented on the particle-size distribution of eroded sediment,the sorting features of sediment particles,and the transport mechanisms under different soil types.In addition,the relationships between sediment particle characteristics and hydrodynamic parameters were examined to identify the key controlling factors of sediment sorting and transport during erosion.The results showed that the eroded sediments from both the Lou soil and aeolian sandy soil spoil tips were dominated by the 0.002～＜0.050 mm size fraction,which accounted for more than 46％of the total.There was great variation in the response patterns of sediment particle composition to slope and inflow rate.In the aeolian sandy soil spoil tips,the particle-size composition of eroded sediment was more sensitive to slope,indicating that the slope played a more significant role in the detachment and transport of sediment particles.In the Lou soil,the transport of coarse particles in the 0.250～2.000 mm size fraction was controlled by the inflow rate.There was a significant correlation between slope and inflow rate.The influence of hydraulic conditions on sediment transport was strongly dependent on the soil type and particle composition.Compared with the Lou soil spoil tips,the eroded sediment from the aeolian sandy soil spoil tips shared a larger mean weight diameter,ranging from 0.061 to 0.085 mm,and a smaller fractal dimension,ranging from 2.494 to 2.561.The coarse particles in aeolian sandy soil were more easily detached and transported during runoff scouring,whereas the sediment sorting was weak.In contrast,the relatively stronger sorting was observed in the smaller mean weight diameter and larger fractal dimension of the eroded sediment from the Lou soil.Fine particles were also enriched in the transported sediment.Therefore,there were differences in soil texture and particle composition between the Lou soil and aeolian sandy soil,leading to sorting responses during erosion.Among the hydrodynamic parameters,stream power was identified as the optimal predictor for the sorting characteristics of eroded sediment from the aeolian sandy soil spoil tips.Specifically,stream power showed the strongest relationship with mean weight diameter and fractal dimension(R2=0.92 and 0.55,respectively).In the Lou soil spoil tips,runoff shear stress was the optimal hydrodynamic parameter for sediment sorting(R2=0.80 and 0.31,respectively).The contribution rates of suspension-saltation exceeded 61％for the aeolian sandy soil spoil tips and 83％for the Lou soil ones.Most eroded sediment was also transported in the form of suspended and saltating particles rather than as bed load.Moreover,the power and logarithmic functions were used to quantitatively describe the contribution rates of suspension-saltation and bed load in the eroded sediment from the Lou soil and aeolian sandy soil spoil tips under stream power.The stream power served as an effective hydraulic indicator to partition the different transport modes during erosion.Dynamic erosion mechanisms of spoil tips can provide a solid theoretical basis to optimize the differentiated soil and water conservation using specific regional soil types.
Corn is one of the most important crops for national food security.However,weed is a major influencing factor of biological stress on corn growth.They compete with corn seedlings for water,nutrients,and light,serve as hosts for pests and pathogens,thereby causing declines in both crop yield and quality.Conventional weed control strategies rely typically on manual identification or extensive herbicide application,both of which are associated with low efficiency,resource waste,and environmental pollution.Existing detection models for corn seedlings and weeds often suffer from large parameter counts,high computational costs,and low accuracy in complex agricultural environments,leading to the false positives and missed detections.In this study,a lightweight detection framework named YOLO11-SAW was developed using YOLO11n.The high accuracy and inference efficiency were achieved well-suitable for deployment on edge devices.Specifically,three aspects were proposed for the improved YOLO11n:Backbone feature extraction,neck feature fusion,and the loss function for bounding box regression.1)C3STR module was constructed to combine the C3 module with the Swin Transformer at the end of the backbone network.Global contextual dependencies were better captured to distinguish corn seedlings from weeds in scenarios with the overlapping leaves,target occlusion,dense distribution,and complex soil backgrounds.2)Neck structure was augmented with the Alterable Kernel Convolution(AKConv)module.The learnable offsets were introduced to replace conventional convolution.The adaptability to multi-scale and deformed weed targets were enhanced after modification to simultaneously reduce both floating-point operations(FLOPs)and model parameters.3)A bounding box regression was refined to introduce the WIoUv3 loss function.Training instability caused by fixed gradient magnitudes was alleviated to enhance the suppression of low-quality samples.The high-quality samples were consequently promoted the convergence stability and localization accuracy.A series of comparative experiments were conducted to evaluate the effectiveness of the improved model on a self-constructed corn seedling and weed dataset.The YOLO11-SAW was compared with several representative models under unified experiment,including Faster R-CNN,Swin Transformer,RT-DETR-L,and multiple YOLO-series models.It was found that the YOLO11-SAW outperformed existing models in both detection accuracy and computational efficiency.Compared with the baseline YOLO11n model,YOLO11-SAW improved Precision by 1.71 percentage points and Recall by 2.18 percentage points,with mAP0.5 and mAP0.5:0.95 reaching 96.40％and 76.17％,respectively,indicating strong detection and localization.In terms of model complexity,the parameters,floating-point operations and model size of YOLO11-SAW are 1.97 M,8.0 G and 4.3 MB respectively.In addition,an inference speed of 202.77 frames per second(FPS)was fully met the real-time requirements of intelligent agricultural applications.In summary,the YOLO11-SAW model can real-time and accurately detect the corn seedlings and weeds in complex agricultural environments.The findings can provide practical technical support to deploy the mobile robots and variable-rate spraying on edge devices in smart agriculture.
Dry preparation of potato starch is one of the most important procedures in food processing.Existing potato starch extraction can be limited to the low starch yield and a large amount of wastewater.This study aimed to develop the dry preparation of potato starch for high yield in sustainable agriculture.The processing steps were as follows:Potatoes were washed,peeled,cut into cubes,and then pressed to obtain potato press cake and juice.The press cake was subsequently treated by hammer crushing and sieved to separate potato starch from potato residue.It was found that the moisture content of the press cake was crucial for the dry separation of starch.Dry separation of starch was achieved at a moisture content of the press cake below 38.5％.Hammer crushing better maintained the intercellular connections between cell walls,thereby facilitating starch sieving.The performance was significantly superior to that of blade crushing.The starch yield of 17.8％was achieved with a moisture content of 13.6％,a starch content of 88.7％(dry basis),a protein content of 1.94％,and an ash content of 0.60％under optimal conditions.When the pressing pressure was insufficient(20 MPa),drying treatment was used to reduce the moisture content of the press cake.But the starch content and whiteness of the starch product decreased significantly.A comparison was made of the commercial products of potato starch.The starch content(wet basis)was between those of the two commercial products.But the starch content(dry basis)of 88.7％was lower than that of the commercial products(92.0％and 92.4％),while the whiteness was slightly lower as well.The starch after water extraction was further clarified using starch yield,crystalline structure,gelatinization properties,and damage rate.The results indicated that the starch yield was significantly higher than that of the water extraction(12.8％).Crystalline structure analysis showed that the crystal type of potato starch remained unchanged,with the B-type.In terms of gelatinization characteristics,the peak viscosity,trough viscosity,and breakdown of potato starch decreased significantly,whereas the final viscosity and setback increased,indicating suitability for conventional applications.The damaged starch content increased significantly,as the cracks on the surface of starch granules accounted for approximately 70％of the total.These cracks made the starch more susceptible to hydrolysis by α-amylase.The porous starch shared the better adsorption properties under optimal conditions(enzymatic hydrolysis for 12 h),with a water and oil absorption capacity of 156.6％and 101.9％,respectively.The scanning electron microscopy confirmed that there were some cracks on the surface of starch granules.The outstanding pores appeared after 12 h of enzymatic hydrolysis.
The spatial pattern of carbon sinks in estuarine delta regions can greatly contribute to the territorial spatial planning under carbon neutrality goals.This study aims to explore the carbon sink pattern and spatial optimization zoning in the Yellow River Delta of China.Spatiotemporal evolution of regional carbon storage was also examined to explore the spatial strategies for the high carbon sink capacity.Multi-temporal data of land use was interpreted from Landsat images.Land use dynamics were then characterized between 1990 and 2020.Carbon storage was finally estimated using the carbon storage module of the integrated valuation of ecosystem services and Trade-offs model.According to the spatial differentiation of carbon storage,the geographical detector model was applied to evaluate the explanatory power of natural environmental and socio-economic factors.The framework was integrated with mechanism interpretation,spatial response,and planning strategies.In addition,morphological spatial pattern analysis was used to identify ecological patches with high carbon storage.Ecological corridors were simulated using the minimum cumulative resistance model,according to the resistance surface from the key landscape constraints.The spatial regulation strategies were proposed to improve the regional performance of the carbon sink.The results reveal that there was significant spatial variation in the land use and carbon storage in the Yellow River Delta over the past three decades.1)Land use changes were primarily characterized by the conversion of wetlands and marshlands into cultivated land,aquaculture ponds,and construction land.These transitions occurred mainly in areas experiencing intensified human activities in the central and southwestern parts of the delta.Consequently,the spatial pattern of carbon storage gradually developed with relatively high values in the northeastern coastal area and lower values in the southwestern inland region,indicating the contrast between natural wetland ecosystems and developed agricultural and urban landscapes.2)Geographical Detector results indicate that vegetation conditions and soil properties dominated the distribution of carbon storage.Vegetation coverage was represented by the Normalized Difference Vegetation Index,indicating the strong explanatory power for carbon storage patterns.Soil salinity and clay content also shared a considerable influence on the spatial differentiation of carbon storage.Socio-economic factors influencing carbon storage,including population density and gross domestic product,were attributed to the land development intensity and landscape transformation.Environmental conditions and human activities were combined to further enhance the spatial heterogeneity in the delta.3)According to the spatial characteristics of carbon storage and the contribution rate of the driving factors,the study area was classified into four spatial regulation zones,including carbon sink core conservation,carbon sink optimization and regulation,carbon sink fragile restoration,and low-carbon intensive development zones.There was a zoning difference in the ecological importance,restoration potential,and development intensity among different areas.4)Carbon sink areas and ecological corridors were identified after spatial connectivity analysis.Ecological patches were extracted to simulate the corridor after morphological spatial pattern analysis.The potential pathways were identified to connect these patches using the minimum cumulative resistance model.A spatial optimization pattern was characterized by"four zones and multiple corridors"using spatial zoning with the corridor network.A carbon sink structure was formed after zoning regulation and ecological connectivity.This finding can provide an approach to assess the regional carbon storage with territorial spatial planning.The spatial framework can also offer a strong reference to improve the carbon sink capacity in estuarine delta regions.
Soil salinization has seriously threatened the national food security in saline-alkali land.Salt stress can severely inhibit rice seed germination to induce the osmotic imbalance and ionic toxicity,indicating a major constraint for rice cultivation.Melatonin(MT),an indole derivative,can be expected to enhance the salt tolerance in various crops using reactive oxygen species(ROS)scavenging and ion homeostasis regulation.However,it is lacking in specific regulations on internal water metabolism under salt stress during the seed germination stage.Since the germination is driven by water uptake and redistribution,it is often required for real-time,non-destructive monitoring of internal water status and phase transitions.Low-field nuclear magnetic resonance(LF-NMR)and magnetic resonance imaging(MRI)techniques can be expected to non-invasively detect hydrogen proton signals,thereby precisely characterizing water content,migration,and phase distribution within biological tissues.This study aims to investigate the regulatory effects of exogenous MT on germination and internal water dynamics in rice seeds under salt stress.The research object was taken as the japonica conventional rice cultivar'Tijin'.A preliminary screening of NaCl concentration gradient was established at 150 mmol/L as the standard salt stress condition(N150 treatment),which reduced the germination potential to 32％of the water control.The experiments included a water control group(CK1),a salt stress control group(CK2,N150),and five MT treatment groups(50,100,200,400,and 800 μmol/L MT+N150).Germination physiological indices were monitored using LF-NMR(utilizing CPMG sequence)with MRI(using MSE sequence).Internal water dynamics and phase changes were tracked after the 72-hour germination period.The results revealed that there was a concentration-dependent biphasic regulation of rice seed germination by MT under salt stress.The 200μmol/L MT concentration was identified as the optimal,significantly enhancing germination rate(94.33％),germination potential(78.67％),fresh weight accumulation,and the growth of radicles,plumules,and secondary roots.This treatment effectively alleviated salt-induced osmotic stress and ionic toxicity,indicating stable cell membrane permeability.MRI pseudo-color mapping illustrated the dynamic internal water distribution.The germination was delineated into three stages using physiological metabolism:imbibition(0-24 h),initiation(24-48 h),and germination(48-72 h).LF-NMR T2 relaxation analysis characterized four water fractions:strongly bound water(T20,0.1-1 ms),bound water(T21,1-10 ms),semi-bound water(T22,10-100 ms),and free water(T23,100-1000 ms).Furthermore,the medium MT concentrations(200 and 400 μmol/L)effectively maintained water phase stability,indicating relaxation akin to the CK1 group.In contrast,the high MT concentration(800 μmol/L)failed to confer beneficial effects,with its water phase features.The T22 peak area was consistently reduced to converge towards those of the salt-stressed CK2 group.In conclusion,an optimal concentration of exogenous MT(200μmol/L)can effectively avoid the inhibition of salt stress on rice seed germination.There were patterns of internal water with MT-mediated alleviation of salt stress during rice seed germination.The LF-NMR and MRI techniques can be expected for the robust,non-destructive,and precise detection of the internal water dynamics and phase transitions.The finding can offer valuable theoretical and technical reference for rice seed salt tolerance.
Agricultural organic waste resource utilization was a key pathway for improving the efficiency of resource recycling,controlling agricultural pollution,and promoting the green transformation of agricultural development.This study explored the research hotspots,key scientific questions,and technological innovation trends associated with different types of agricultural wastes.Using bibliometric methods,the study found that aerobic composting and anaerobic digestion were the mainstream technologies for the treatment and utilization of organic wastes,whereas research on waste agricultural films focused primarily on recycling and the development of new biodegradable products.Although research on technologies such as aerobic composting and maturation,straw return to fields,pyrolysis and gasification,and the removal of emerging pollutants was on par with international standards,a gap remained in equipment standardization.Technologies such as anaerobic fermentation,lagoon,process monitoring and intelligent management,as well as the recovery and treatment of waste agricultural films,were still at a developmental stage,and a significant gap existed in technologies for the high-value utilization of waste.Overall,challenges remained,including unclear transformation mechanisms,poor applicability of technical equipment,low efficiency in resource recycling,and undefined risks associated with safe land application.Based on a comprehensive analysis,it was projected that scientific and technological innovation in agricultural waste resource utilization would exhibit the following trends:integrated mechanism research,cleaner and more efficient technology and equipment,diversified development of high-value products,precision and intelligence in recycling processes,and integrated demonstration and application.For instance,in the diversified and high-value utilization of crop straw,advanced technologies such as Flash Joule heating and off-field electrocatalysis could be employed to prioritize the development of high-value products,including flash graphene,straw-derived sugars,bio-jet fuel,green methanol,and bioplastics.For targeted and precise management of livestock and poultry manure,integrating techniques such as specialized habitat domestication,isotope labelling,and material modification could accelerate the research,development,application,and performance monitoring of novel additives:such as specialized functional microbial agents and nano-composting agents:to achieve rapid composting.In-depth investigation into material transformation pathways,supported by technologies like carbon chain extension,could facilitate the development of high-value intermediates such as short-and medium-chain fatty acids and humic acid.In terms of technical equipment,emphasis was placed on"AI+"technologies,utilizing convolutional neural networks and machine learning to establish high-precision,high-sensitivity intelligent control and recognition systems,thereby improving the accuracy of compost maturity image recognition,the sensitivity of sensor monitoring,and the stability of equipment.Regarding biodegradable agricultural film and intelligent recycling,efforts were intensified to address challenges related to the thickness and mechanical strength of biodegradable films,to develop plastic identification technologies integrating optics and artificial intelligence,and to produce integrated equipment for straw shredding and agricultural film recycling,thereby further enhancing the recycling efficiency and sorting accuracy of waste agricultural film.Therefore,based on analysing and summarizing recent advances in research,and following the principles of industrial and scientific development,this paper identifies potential innovations and breakthroughs in cutting-edge scientific theories,emerging technologies,and mature equipment that may affect the future development of this field.It provides theoretical support for achieving the efficient treatment and utilization of agricultural waste,fulfilling the"dual carbon"goals,and promoting the development of green agriculture in China.
Lettuce is one of the most favorite leafy vegetable in precision cultivation.It is often required to monitor the lettuce growth for real-time robotic harvesting.Nevertheless,leafy vegetables are characterized by leaves,diverse morphologies,and thin,flexible,and deformable textures.There is a more complex structure,compared with the morphologically regular objects,such as spherical fruits,umbrella-shaped mushrooms,and conical carrots.As such,plant growth and leaf expansion can lead to mutual occlusion among lettuce plants.Furthermore,the high planting density has commonly adopted in plants,leading to the inter-leaf occlusion.Additionally,height differences between individual plants can also cause upper leaves to shade lower ones.These occlusions then result in missing data in the point cloud images,seriously affecting the accurate acquisition of key phenotypic parameters.Conventional point cloud processing has mostly developed for regularly shaped crops,making it difficult to effectively reconstruct complex structures.Therefore,it is challenging to accurately detect the complete three-dimensional phenotypic parameters of lettuce from severely incomplete point cloud data.In this study,the AdaPoinTr-ER model and progressive completion were proposed for the overall completion pipeline of incomplete lettuce images in point cloud.Since the occlusion among lettuce plants occurred at edge positions,AdaPoinTr-ER model was integrated edge attention into the AdaPoinTr framework to enhance feature extraction of geometric contour.In view of the lettuce leaves with the more complex multilayer structures,AdaPoinTr-ER model was integrated residual module into AdaPoinTr to reduce feature degradation during point cloud generation for the prediction accuracy of generated point clouds.Three sequential stages were proposed to realize the progressive completion for incomplete lettuce:(1)Mask3D was employed to segment top-view lettuce clusters with mutual occlusion,thus capturing the top-view images of incomplete lettuce plants.(2)The top-down completion model trained by AdaPoinTr-ER model was used to complete the image,and the resulting images were then input into the three-dimensional completion model for training.(3)The phenotypic parameters of the completed intact lettuce were acquired after three-dimensional completion.The experimental results demonstrated that AdaPoinTr-ER model achieved the best performance in Chamfer Distance,Earth Mover's Distance,and F1-score,compared with FoldingNet,GRNet,PCN,PoinTr,and AdaPoinTr.The ablation experiments demonstrated that the AdaPoinTr-ER model achieved a Chamfer Distance of 2.88× 1 0-4 cm,an Earth Mover's Distance of 0.19 cm,and an F1-score of 72.68％.Compared with the original AdaPoinTr model,the Chamfer Distance and Earth Mover's Distance decreased by 43.3％and 42.4％,respectively,while the F1-score improved by 9.52 percentage points.In the lettuce phenotypic analysis,the progressive completion yielded coefficients of determination(R2)of 0.933,0.917,and 0.903 for the projected area,crown width,and plant height,respectively,with the root mean square errors(RMSE)of8.569 cm2,0.434 cm,and 0.591 cm,respectively.Compared with the phenotypic analysis from incomplete lettuce,the R2 values increased by 45.6％,61.4％,and 30.7％,respectively.Furthermore,the R2 values improved by 24.9％,29.5％,and 11.1％,respectively,whereas,the RMSE was reduced by 64.8％,56.6％,and 37.4％,respectively,compared with direct completion using only 3D reconstruction without top-view completion.Consequently,AdaPoinTr-ER model exhibited superior performance to restore both the local geometric details and the overall shape structure of lettuce point clouds.Completing occluded lettuce point clouds is a challenging task.The occluded lettuce point clouds were accurately and effectively reconstructed to significantly improve the accuracy of phenotypic parameter extraction for leafy vegetables in densely planted environments.Thereby,the finding can provide the robust support for the intelligent and precise completion of leafy vegetable species.The completion pipeline can also be integrated with real-time robotic harvesting for fully automatic operations in plants.
Severe acoustic emissions and structural vibrations have been caused by insufficient suction oil supply in external gear pumps at elevated rotational speeds.In high-speed hydraulic applications,fluid inertia and inlet flow restrictions often lead to severe fluid starvation,massive cavitation,pressure pulsations,and consequently,intense hydrodynamic noise.Taking a centrifugal pump in series as a pre-pressurization stage,the inlet conditions of the gear pump have improved significantly to prevent unexpected acoustic behaviors.It is often required to clarify the precise flow-acoustic coupling mechanisms and the optimal matching criteria between the two pump stages.This study aims to systematically investigate the influences of a series-boost centrifugal pump on the noise characteristics of a primary gear pump.The testbed was initially designed and then constructed to measure the high-speed gear pump noise.Preliminary experimental investigations revealed that there was a highly non-linear relationship between the vibration and noise levels of the gear pump and the varying supply flow rates delivered by the auxiliary centrifugal pump.An acoustic-flow field coupling model was also established for the tandem centrifugal-gear pump.The numerical framework was developed to combine Computational Fluid Dynamics(CFD)with Lighthill's acoustic analogy.A decoupling simulation analysis was performed on the four primary noise generation mechanisms:turbulence-induced noise,trapped oil(fluid confinement)noise,kinematic flow pulsation noise,and cavitation-induced noise.The experimental and numerical results indicate that the volumetric efficiency of the gear pump shared a two-stage evolutionary trend—initially increasing sharply and subsequently plateauing—as the supply flow rate increased from the centrifugal pump.Conversely,the overall vibration and noise levels demonstrated the parabolic trend,initially increasing before ultimately experiencing a significant reduction.The flow matching critical point was identified precisely after the dynamic process,when the supply flow rate of the centrifugal pump was equivalent to 1.2 times the theoretical displacement flow rate of the gear pump(defined as the flow ratio QC/QG=1.2).Prior to the critical flow ratio,the volumetric efficiency ascended proportionally with the increase in supply flow.The maximum enhancement of 8.68％was achieved under high-speed conditions,compared with the baseline performance of a standalone gear pump.Interestingly,an upward trend was observed in the fundamental frequency sound pressure level at the pump's inlet and outlet during the initial stage.The acoustic emission was attributed to the initial reduction in the gas volume fraction within the fluid.As the aeration and cavitation bubbles dissolved,due to the pre-boost pressure,the effective bulk modulus of the hydraulic oil rose sharply,leading to a restoration of the fluid's inherent stiffness.Consequently,the transmission efficiency of the fluid was significantly enhanced as an acoustic propagation medium.Simultaneously,the acoustic damping and energy absorption were diminished under the two-phase bubble mixture,leading to the more intense sound waves.Once the supply flow rate surpassed the critical matching ratio(QC/QG＞1.2),the gear pump reached the complete fluid saturation state,and the volumetric efficiency remained constant.The overall sound pressure level also declined.The noise reduction was driven by the synergistic attenuation of cavitation intensity,flow pulsation rates,and trapped oil behavior.The source drastically reduced the acoustic output because the turbulent kinetic energy and the fluid stiffness no longer increased to exacerbate acoustic transmission.Quantitative acoustic source allocation revealed that the cavitation was the overwhelmingly dominant factor contributing to the overall noise reduction,accounting for 60.91％of the total decrease in the sound pressure level.In contrast,the contribution from the trapped oil pressure was fundamentally minimized to be negligible within the overall noise spectrum.In conclusion,there were complex nonlinear dynamics between pre-boost flow rates and acoustic emissions in tandem hydraulic architectures.The findings can provide a robust theoretical foundation and practical guidelines for engineering high-speed gear pumps.Simultaneously,exceptional volumetric efficiency and low-noise performance can be expected for industrial and aerospace fluid power applications.
Agricultural carbon emission efficiency is of great significance to accelerate the green and low-carbon transformation,thus promoting high-quality agriculture under the dual-carbon strategy in Liaoning Province,China.In this study,the Super-Efficiency Slack-Based Measure(Super-SBM)model was adopted to accurately measure the agricultural carbon emission efficiency.A systematic analysis was also made for the dynamic spatiotemporal evolution from 2012 to 2022.The key driving factors and their internal action were further explored to combine the Geodetector model and the Geographically and Temporally Weighted Regression(GTWR)model.The results show that:1)The total agricultural carbon emissions of Liaoning Province presented a trend of first decreasing and then increasing during the period of 2012-2022,while the overall agricultural carbon emission efficiency maintained a steady upward trend with an outstanding stage.The agricultural carbon emission efficiency shared significant spatial agglomeration and regional heterogeneity.Among them,Chaoyang,Dalian,and Yingkou were characterized by high efficiency with stable and excellent performance.Fuxin,Tieling,and Huludao cities were trapped in low-efficiency lagging areas with a slow improvement speed.Shenyang,Panjin,and Benxi cities shared a fluctuating upward state with exciting potential for high efficiency.2)The dominant driving factors of agricultural carbon emission efficiency shared staged evolution,gradually transforming from the single dominance of resource use in the initial stage to the dual dominance of employment structure and industrial structure in the middle and late stages;Meanwhile,the explanatory power of key influencing factors continued to increase,such as regional economic scale,technical application level,urbanization rate,and mechanization level,indicating the multi-factor driving trend for agricultural carbon emission efficiency.3)All the influencing factors also presented significant spatial differentiation in the study area.The agricultural carbon emission efficiency was restricted by multiple key factors,including the inter-regional economy,advanced technical promotion,technological investment,allocation structure,and green support.Thus,the high-quality low-carbon transformation can be realized to optimize technical adaptability,coordinated allocation of key production factors,and industrial structure in green agriculture.In conclusion,the spatiotemporal evolution and driving mechanism of agricultural carbon emission efficiency can provide a practical path for the differentiated and precise low-carbon transformation.The finding can also offer a useful reference for green and low-carbon agriculture in the major grain-producing areas of Northeast China.
Fertilizer structure has been confined to the fertilization mode for summer corn in the Huang-Huai-Hai region of China,such as one-time basal application("one-shot")or base-topdressing splits.There has been a serious mismatch between nutrient supply and crop demand in recent years.This study aims to propose the V-shaped layered fertilization and its mechanical supporting device.The spatial distribution of the layered fertilization was integrated with the controlled release of the specialized fertilizers.A systematic investigation was conducted using pot experiments,device design,discrete element simulation,and field validation.In the pot experiments,seven treatments(CK,T2,T3,T4,T5,T6,and T7)were carried out to investigate the effects of different fertilizer types(conventional and controlled-release urea)and application modes(single-side,bilateral,and bottom)on the maize agronomic features,soil nitrogen dynamics ammonium-N and nitrate-N,and crop yield.A V-shaped layered fertilization planter was designed with the optimal fertilization strategy(T7)that was identified from the pot experiments.Its core component,the double-disc opener,was theoretically analyzed to determine the structural parameters(the disc diameter and disc angle)and operational parameters(the forward speed).A simulation model of the opener-soil-fertilizer interaction was established using the discrete element method(EDEM).A quadratic orthogonal rotational combination was employed with the disc diameter,disc angle,and forward speed as the experimental factors,while the operational resistance and fertilization qualification rate as the performance indicators.Regression models were developed and then optimized to determine the optimal parameters.Field trials were carried out to verify the operational performance of the prototype with the optimal parameters.Fertilization positioning accuracy was achieved to clarify the impact on the root development and final yield.The pot experiment results showed that compared with other treatments,the T7 treatment(controlled-release urea combined with conventional phosphorus and potassium fertilizers applied in bilateral and bottom layers at a ratio of 30％,30％and 40％)increased the stem diameter,leaf area and chlorophyll content of maize.More importantly,this treatment could maintain a relatively high level of soil ammonium nitrogen and nitrate nitrogen in the late growth stage of maize,effectively prevent the occurrence of nitrogen deficiency,and realize the matching of nutrient release with crop demand.Ultimately,the maize yield in the T7 treatment reached 31.7050 g,which was significantly higher than that in all other treatments(P＜0.05).Simulation results were derived into the optimal combination of the parameters:The disc diameter of 360.75 mm,disc angle of 10.97°,and forward speed of 4.26 km/h.The predicted operational resistance was 239.71 N,and the fertilization qualification rate was 95.69％under the optimal combination of the parameters.Field tests confirmed that the highly accurate positions of the fertilization were measured with an average vertical distance of 39.6 mm for the side fertilizer to the seed,a horizontal distance of 99.4 mm between side fertilizer bands,and a vertical distance of 110.7 mm for the base fertilizer to the seed.All parameters were within a 10 mm error margin from the design targets,indicating the high performance of the device.The trials demonstrated that the V-shaped fertilization(VF)treatment significantly promoted the root growth,thus resulting in longer,denser root systems with more aerial roots,compared with the conventional fertilization(CF).Ultimately,the VF treatment achieved a 100-grain weight of 37.42 g and a yield of 11 100 kg/hm2,which were significantly greater than the CF treatment's 31.85 g and 9 520 kg/hm2(P＜0.05),indicating a yield increase of 16.6％.The VF treatment with the controlled-release and conventional fertilizers was effectively achieved in the precise spatial and temporal nutrient supply,thereby enhancing the nitrogen utilization efficiency,maize root and shoot development,as well as the yield.The supporting device was optimized through discrete element simulation.Features rational design and stable performance fully meet the agronomic requirements for precise fertilization.This finding can provide a theoretical foundation and effective technical solution for simplified,efficient,and high-yielding maize cultivation.
Previous research on ecological restoration in mining areas has predominantly focused on restoration techniques,whereas in-depth investigations into the composition of raw materials for restoration and the assessment of multi-scale spatiotemporal restoration outcomes remain limited.Phyllite has been widely available,directly accessible,and free from heavy metal contamination.It is often required for the investigation into the sourcing of restoration materials and the ecological environment over multiple temporal and spatial scales in mining areas.Among them,the ecological restoration of mining areas can involve backfilling mine pits with artificial soil in the Qinling region.It is crucial to select the optimal soil-building materials.Conventional materials like coal gangue-a byproduct of mineral extraction-contain heavy metals to hinder ecological restoration.In this study,soil cultivation,potted plant,and wilting experiments were conducted to compare optimal conditions for the weathered phyllite artificial soil.Soil quality indices(soil bulk density,pH values,maximum water-holding capacity,and electrical conductivity)were calculated for each combination of weathered phyllite artificial soil.Optimal parameters were identified using variance analysis.Key variables were also determined to enhance the reliability of the optimal parameters.Furthermore,two-dimensional interpolation of biomass and germination rates was also carried out to validate the optimization.The results revealed that microbial inoculants significantly improved the physicochemical properties of weathered phyllite artificial soil.The optimal combination of treatment was 60g of straw composting agent(JG)for 60-day cultivation.The bulk density of artificial soil stabilized at an ideal range near 1.20g/cm3,with the moderate pH and electrical conductivity close to that of natural soil.Notably,the maximum water-holding capacity reached 50.87％,with a 37.93％increase over natural soil,indicating the superior water retention and drought resistance.Pot experiments further validated that this treatment group achieved the highest germination rate(92％)of Bermuda grass seed and high biomass levels.Field verification revealed that crop germination rates and growth conditions significantly outperformed in the plots with this artificial soil,compared with the control group.There was a consistent trend over all measured parameters.Specifically,the bulk density shared a progressive decrease over the cultivation period,eventually plateauing at the optimal 1.20 g/cm3 within the ideal range for root growth and water infiltration.The pH values stabilized between 6.5 and 7.2,which was a neutral to slightly acidic environment conducive to nutrient availability and microbial activity.Low electrical conductivity remained on the minimal salinity stress for plant development in restored sites.The maximum water-holding capacity of 50.87％was enhanced by 37.93％over the local natural soil.The key factor was reduced irrigation demands for seedling survival during dry periods.The pot experiments validated that the 92％germination rate was accompanied by seedling growth.Two-dimensional interpolation of biomass and germination showed that the 60g JG 60-day cultivation point also represented the peak performance.The finding can provide the preliminary theoretical support for the practical needs in ecological conservation,restoration,and sustainable ecosystems.The optimal artificial soil formula can also offer practical,effective,and locally sourced solutions to significantly accelerate the ecosystem recovery in the mining areas.
Water and fertilizer inputs can dominate the soil quality and crop yield during cultivation in Southwest China.It is essential to explore efficient,collaborative modes in sustainable agriculture.This study aims to systematically evaluated the diverse effects of different irrigation-fertilization modes on the soil water storage,available nutrient content,photosynthesis,edible rose yield,and irrigation water use efficiency(IWUE).A fully factorial design was established,consisting of three irrigation regimes—full irrigation(FI,100％ETc),light deficit irrigation(DIL,80％ETc),and moderate deficit irrigation(DIM,60％ETc)—and four levels of organic fertilizer substitution for chemical fertilizer—R0(0％),R1(15％),R2(30％),and R3(45％).The treatment FI combined with R0 served as the control(CK).Correlation analysis and structural equation modeling were applied to explore yield-increasing mechanisms triggered by deficit irrigation with organic fertilizer partial substitution.Experimental results demonstrated that deficit irrigation strategies(DIL and DIM treatments)significantly increased the storage of available soil nutrient reserves by a margin ranging from 6.07％to 15.99％,compared with the full irrigation.Furthermore,the deficit irrigation enhanced the IWUE by 22.76％to 45.00％.The water deficit also caused a measurable decrease in essential physiological indicators.Net photosynthetic rate(Pn),transpiration rate(Tr),stomatal conductance(Gs),and intercellular CO2 concentration(Ci)were reduced between 10.89％and 40.28％.The DIL treatment achieved an average increase in overall rose yield of 2.23％,with an increase in the total economic benefits of 31.25％during 2023,compared directly to the FI baseline treatment.Conversely,the DIM treatment was reduced the total crop yield and economic benefits over the consecutive two-year period,with the average 7.72％and 24.89％,respectively.Furthermore,the critical parameters—including Pn,Tr,Gs,Ci,harvested crop yield,IWUE,and overall economic benefits—exhibited initially a steady increase,followed by the decrease,as the proportion of organic fertilizer increased progressively.Absolute optimal peak values reached at the R2 treatment level.Compared with the baseline R0 treatment,the R2 treatment shared a remarkable increase in the available reserves of soil nutrient,with the crop yield by 9.64％to 121.56％and 23.72％to 38.52％,respectively,after harvest.Additionally,the IWUE was also enhanced by 32.28％after treatment.The DIMR0 treatment also showed the lowest overall yield,compared with the CK.In contrast,the optimal DILR2 treatment significantly increased the storage capacity of soil available nutrients,final crop yield,the IWUE,and the highest overall economic benefits.In addition,the structural equation model confirmed that the optimal combination of irrigation and fertilization indirectly regulated the final yield of cultivated edible roses,significantly affecting soil moisture dynamics,nutrient content,and photosynthetic parameters.This finding can provide a highly reliable reference to optimize the irrigation-fertilization systems for edible roses.
Most large pumping stations have suffered from substantial water and energy resource wastage with high operational costs,due mainly to the absence of scientific operation strategies.This study aims to reduce the cost of secure and reliable operations in large pumping stations.A case study was employed at the Dayuzhang Pumping Station within the Yellow River-to-Qingdao Water Diversion Project.An optimal model was formulated to minimize the total cost of daily electricity.A systematic investigation was implemented to reduce the energy consumption of primary pump units,auxiliary equipment,and substation facilities under a time-of-use(TOU)electricity pricing mechanism.Safety and reliability were realized to constrain the unit start-stop operations within short-duration cycles.While the critical hydraulic and engineering constraints were simultaneously incorporated,including flow rate,adjustable blade angles,and the permissible number of operating units.A mathematical model was constructed to determine the optimal unit commitment and blade angles for each period.An enhanced Hybrid Black-winged Kite Algorithm(HBKA)was proposed to simulate the annealing mechanism using Black Kite Algorithm(BKA).The feasible global optima were then obtained after optimization.According to parameter sensitivity tests,the population sizes and maximum iterations were configured as 300 and 200,respectively.Benchmark tests against a classic optimization model confirmed that the superior efficacy of HBKA was achieved with a 23.2％reduction in relative standard deviation and a 28％decrease in computational time,compared with the Hybrid Particle Swarm Optimization(HPSO)algorithm.A strong suitability was found for this class of nonlinear and constrained pump station.A case study from the target pumping station revealed that the blade angles were adjusted to optimally allocate the pumping volume under an operating head of 5.0 m in the different TOU price periods.The continuous units were used under total pumping volume constraints.There was an inverse correlation between the optimal blade angle and the prevailing electricity price after optimization:A smaller blade angle reduced the hourly averaged pumping volume,as the TOU price escalated.The blade angle reached its operational lower bound to stabilize at the minimum;Consequently,the hourly averaged electricity cost increased linearly with the tariff,directly taking the electricity price as the dominant factor in the operational cost function.Comparative analysis revealed that one of the alternative unit commitment was taken as the lowest theoretical electricity cost,which was required for approximately 10 start-stop cycles daily,leading to significant mechanical stress and long-term reliability.In contrast,the daily electricity costs were reduced by 2.50％to 5.15％,and 7.58％to 21.14％,compared with the constant flow constraints and the on-site actual operation,respectively.Crucially,the 13.01％cost was significantly reduced during on-peak hours,while the start-stop cycles were reduced to prioritize the operational safety and equipment longevity.Sensitivity analysis further revealed that there was the±10％ variation in the operating head,leading to an electricity cost from-8.11％to+14.33％.Yet the optimization model maintained feasibility over this range,indicating its practical robustness against parameter fluctuations.This finding can provide a theoretical and practical contribution to the optimal design,unit selection,and advanced operation of large-scale pumping stations.The HBKA optimization can offer a viable pathway towards a sustainable water-energy nexus in critical water infrastructure.Future work can tackle operational uncertainties in head,electricity price,and equipment efficiency.Robust optimization was integrated to enhance disturbance-resistant dispatch.Hydraulic model experiments were then validated to predict the real-time command adjustment and system integration.
Mounting posture is one of the most intuitive,reliable,and visual indicators of estrus in dairy cows.Its accurate estimation can be widely recognized to determine whether a cow is in heat.However,a challenging task remains to recognize the posture in the group-housed dairy environments,due to complex practical conditions,diverse individual appearances,and frequent occlusions among cows.The visual features of individual cows can often blend with complex backgrounds,such as bedding,fences,and other animals.Moreover,conventional vision algorithms cannot accurately differentiate individuals or posture transitions,due to the high similarity or ambiguities between coat patterns and body structures.In addition,substantial scale variations among key anatomical regions—such as the head,limbs,and torso—have made it difficult to accurately detect and locate the keypoints,especially with the varying camera distance and viewing angle.Thereby,conventional pose estimation cannot fully meet the actual requirement of robustness,accuracy,and generalization,due to the frequent misidentification or loss of critical keypoints.In this study,a lightweight framework,termed Frequency-Spatial and Multi-scale Self-calibrated Pose Estimation(FSMCPose),was proposed to estimate cow mounting posture.Specifically,the group-housed dairy scenarios were also designed for high detection accuracy and computational efficiency.A lightweight backbone network(CowMountNet)was incorporated to efficiently extract the visual features with low computational complexity and memory footprint.Spatial-frequency enhancement block(SFEB)served as the first critical component in the overall architecture.Multi-scale decomposition of wavelet transforms was used to capture fine-grained features at different spatial frequencies.The smoothing properties of Gaussian distributions were combined to suppress the background noise for the feature continuity.Collaborative enhancement between spatial-and frequency-domain representations effectively improved background separation to preserve the lightweight nature of the model.Following SFEB,the receptive-field adaptive block(RAB)was employed to extract the multi-scale contextual feature.Multiple parallel branches were introduced after pointwise convolutions,each of which was configured with a dilation rate to capture contextual information under varying receptive fields.Such a structure was used to strengthen the sensitivity to small-scale keypoints-such as subtle joints or limb regions-to maintain the integrity of large-scale anatomical features of the cow's body.Finally,the Spatial-Channel Self-calibration Head(SCSCHead)was integrated with the spatial and channel attention mechanisms to enhance both spatial awareness and semantic discrimination of high-level features.In addition,a self-calibration branch was introduced to compensate for the potential structural deviations caused by occlusions,overlapping individuals,or motion blur,further improving the stability and precision of keypoint predictions.Experimental evaluations demonstrated that the FSMCPose was achieved in the improvements of 1.2,3.0,0.9,and 1.8 percentage points in the AP,AP75,AR,and AR75,respectively,which was improved by 89.0％,92.5％,89.9％,and 973.1％,respectively,compared with the baseline combination of MobileNet as the backbone and RTMPose as the detection head.Furthermore,the framework reduced the number of parameters by 80.1％to only 2.698 M,compared with the baseline mode,where the floating-point operations were limited to 0.354 G,indicating an excellent balance between performance and efficiency.The FSMCPose can provide the robust and accurate localization of keypoints under complex background interference,individual overlap,and scale variation,indicating an efficient upstream module for subsequent behavior recognition and estrus detection.Consequently,the finding can also provide a reliable reference for the cow monitoring in scalable precision dairy farming.
Concentrated solar power(CSP)has emerged as an effective low-carbon pathway for large-scale renewable electricity generation in global energy.Among them,solar tower power generation(STPG)is characterized by the high optical concentration ratios,large thermal energy storage capacity,and delivering dispatchable power at scale.Particularly,supercritical carbon dioxide(SCO2)recompression Brayton cycle-based STPG(SCRBC-STPG)can be expected for the favorable thermophysical properties of SCO2,compact turbomachinery,and the potential for high thermal efficiency among various power-block configurations.However,existing SCRBC-STPG configurations have suffered from a high levelized cost of electricity(LCOE)and low generation efficiency,thus hindering large-scale commercialization and practical deployment.In this study,an integrated configuration was proposed to couple a steam Rankine cycle(SRC)with an SCRBC-STPG,termed as SCRBC+SRC-STPG.The SRC was designed to recover residual thermal energy from both the SCO2 Brayton cycle and the molten-salt thermal energy storage subsystem.Additional low-grade heat was extracted to enhance the effective thermal storage capacity.The SRC then lowered the required operating temperature of the low-temperature molten-salt tank.A series of simulations was conducted on a baseline SCRBC-STPG and the SCRBC+SRC-STPG model using the EBSILON Professional platform.Key subsystems—including the heliostat field,receiver heat transfer,molten-salt storage,and power conversion units:Were validated for the model reliability.Following model validation,a parametric analysis was then performed to evaluate the thermodynamic and economic performance of two configurations over a wide range of operating conditions.The results demonstrate that the SCRBC+SRC-STPG system consistently achieved higher net power generation efficiency than the standalone SCRBC-STPG ones.Specifically,the efficiency was improved by 4.97％at a turbine inlet temperature of 550 ℃and a high-pressure turbine inlet pressure of 30 MPa,compared with the baseline.From an economic perspective,once the power output of the steam Rankine cycle(PSRC)was limited to 16 MW,the optimal performance of the SCRBC+SRC-STPG system achieved an LCOE of 0.814 CNY/kWh,which was 0.091 CNY/kW·h lower than that of the conventional ones.Multi-objective optimization was conducted to enhance efficiency with low COE.The optimal operation was then determined to balance the system performance and economy.The optimal variables included the cycle flow split ratio,high-pressure turbine inlet pressure,and turbine inlet temperature.The Pareto frontier can represent the trade-offs between thermodynamic efficiency and economic competitiveness under the impacts of key parameters.In conclusion,an SRC with an SCO2 recompression Brayton cycle and molten-salt thermal storage can significantly enhance the technical and economic performance of solar tower CSP plants.The SCRBC+SRC-STPG concept can represent a viable pathway to improve conversion efficiency with low LCOE.The findings can offer valuable insights to optimize the high-performance,cost-effective STPG system.
Cultivated land use has been one of the major challenges to national food security and ecological stability in sustainable agriculture,especially in rapid urbanization and industrialization in recent decades.Current cultivated land is often required to balance between the supply and demand of multiple functions,rather than a single production.This study aims to clarify the impact of urbanization on the supply-demand matching multiple for cultivated land functions(CLFs).Land resource allocation was also optimized for sustainable utilization and coordinated development of modern agriculture.The study area was taken from the Yangtze River Delta(YRD),one of the most economically developed and urbanized regions in China.There were drastic variations in the land use,especially in Shanghai,Jiangsu,Zhejiang,and Anhui,due to rapid urban expansion,indicating the supply and demand of various CLFs.The supply and demand levels of five CLFs(grain production,water conservation,carbon sequestration,habitat quality,and landscape culture)were quantitatively measured from 2000 to 2023 using remote sensing data,statistical yearbooks,and field surveys.The spatial-temporal patterns of supply-demand matching were finally obtained to evaluate the different types of urbanization,such as population,economic,spatial,and social urbanization.The results showed that:1)Grain supply shared a"higher in the north,lower in the south"pattern in the south in the study period,which was closely related to superior natural conditions in northern Jiangsu and Anhui.While the water supply presented the opposite trend,due to more abundant precipitation.Carbon sequestration showed significant overall growth,which was attributed to ecological and agricultural policies.High-value areas of habitat quality supply were in the YRD's southwest.Landscape culture high-value areas were in eastern coastal Jiangsu.All CLFs increased with the expansion of city size in Shanghai,southern Jiangsu,and eastern Zhejiang.2)City size significantly dominated CLF supply-demand matching.Small cities generally shared the surplus supply of various CLFs,while megacities and supercities presented a shortage of supply for various CLFs,as the urban expansion occupied cultivated land for the demand of populations/industries.Shanghai and southern Jiangsu significantly enhanced the urbanization pressure on sustainable cultivated land.3)Different types of urbanization varied in the heterogeneous impacts.Social urbanization also dominated the supply and demand matching for grain production.There was a tradeoff between the urban population and the rural labor transfer.Economic urbanization shared the greater impact on carbon sequestration and landscape culture than the rest.Spatial and economic urbanization strongly dominated the supply and demand matching for the habitat quality.Importantly,the interactions between urbanization types also dominated the supply-demand matching for the multiple CLFs more than the rest of the single urbanization.This finding can provide the decision-making basis to promote high-quality urbanization and sustainable cultivated land in the YRD region.
