Search Results (200)

In view of the problems existing in the application of greenhouse pesticides in China, this paper developed a swing-arm sprayer for greenhouse high-stem crops through field research and a literature review. Static and dynamic simulations of the swing-arm mechanism were carried out to verify the rationality of the structure. The average contact angle between the water and tomato leaves was 49.39°, while the contact angle of the auxiliary solution on the tomato leaves decreased to 40.98°. An indoor atomization test platform was designed to accurately test the particle size and spray performance. The relative span (RS) of droplet distribution showed that the RS values of nozzles 015, 02, and 03 were relatively small, while the RS value of nozzle 04 was about 1.734. With the addition of additives, the RS value of nozzle 02 decreased from 1.305 to 1.021. The field tests showed that the deposition of fog droplets on the front of tomato leaves was in the order of middle > lower > ground > upper (3.622 μL/cm², 3.005 μL/cm², 2.977 μL/cm², and 2.931 μL/cm², respectively). The results indicate that adding additives or increasing the swing-arm angle is beneficial for improving the uniformity of canopy droplet deposition. The front fog droplet coverage of the lower canopy of tomatoes was the lowest, with an average of 26.00%, while the middle and upper canopies had the highest, with an average of 50.58% and 50.72%, respectively. The research found that the spray coverage rate on the front and back sides of tomato leaves was relatively uniform, indicating that the swing-arm greenhouse sprayer designed in this paper could meet the spray quality requirements for tomato pest control. Full article

A self-propelled multi-duct air-delivered sprayer was developed to address the challenges of dense canopies and low pesticide utilization in closed-canopy apple orchards. It featured an intelligently adjustable spray bar and formed a directional air curtain via a centrifugal fan and a duckbill air outlet to improve droplet penetration. Using CFD simulations, the air duct size and the air outlet distance were optimized, and the field orthogonal test was carried out with driving speed, nozzle pressure, and nozzle type as factors. The results showed that the optimal parameters were an air duct size of 230 × 110 mm, an air outlet distance of 350 mm, and a fan speed of 2160 r/min. Compared to liquid pump independent operation, liquid pump–fan cooperative operation significantly increased droplet deposition density (p < 0.05) and reduced the degree of dispersion. All three factors significantly influenced deposition density (p < 0.05), and nozzle type had the greatest influence on deposition density, followed by nozzle pressure, and then driving speed. Optimal performance was obtained at a 0.3 m/s driving speed, a 3 MPa nozzle pressure, and a 6502 nozzle type. Under the optimal combination of operating parameters, field verification tests demonstrated that cooperative operation achieved higher average coverage (60.54% vs. 48.30%) and average deposition density (71.34 vs. 60.54 droplets/cm²), with a more uniform coefficient of variation in droplet coverage on leaves (a range of 13.37–19.07% vs. 9.70–22.67%). These results indicate that the sprayer exhibits strong penetration and provides good uniform coverage, effectively increasing droplet deposition across different canopy heights. Full article

Efficient pesticide delivery in mango orchards is hindered by tall canopies and dense foliage. This study evaluated two ultra-low-volume (ULV) nozzles—TeeJet XR and HYPRO rotary—mounted on an indigenous multirotor drone during flowering and fruit-set stages in ‘Dashehari’ mango. HYPRO achieved 14% higher lower-canopy penetration, while TeeJet provided better upper coverage. Droplet spectra differed by 58 µm. UAV-based ULV spraying reduced carrier water by 97% and CO₂-equivalent emissions by 99% compared to air-blast methods. Results underscore the importance of nozzle selection and support UAV adoption for climate-smart, resource-efficient horticulture in India. Full article

Malaria remains a significant public health challenge in Angola, particularly in Cuando Cubango province. This study aimed to characterize the local Anopheles mosquito population, evaluate the impact of indoor residual spraying (IRS) on key entomological indicators, and assess the community knowledge, attitudes, and practices (KAP) related to malaria and vector control. Mosquito collections were conducted indoors at three sites over five months using CDC light traps and Prokopack aspirators. Ten Anopheles species were identified, with An. funestus s.s. being the predominant vector, accounting for 91.7% of the Funestus group. The overall Plasmodium falciparum circumsporozoite protein (CSP) infection rate was 9.2%, with Makua exhibiting the highest rate (10.2%). Following IRS, the indoor resting density of the Funestus group decreased significantly in Makua and Agostinho Neto. In Makua, An. funestus s.s. CSP infection rates decreased by 55% following IRS implementation; however, this reduction was not statistically significant. Knockdown resistance mutations were detected in An. arabiensis and An. gambiae s.s. The 2020/2021 IRS campaign achieved 95% spray coverage and reached 421,856 individuals. Complementary KAP surveys with 647 households showed that 87% of respondents correctly identified mosquitoes as malaria vectors, 78% recognized key symptoms, and 89% supported continued IRS. Reported adherence to post-IRS precautions exceeded 70% and preference for IRS over ITN was expressed by most households. These findings highlight both biological and social dimensions of malaria control, demonstrating that vector control, community acceptance, and entomological surveillance are essential for effective and sustainable malaria interventions in Cuando Cubango. Full article

Power electronics convert and control electrical power in applications ranging from electric motors to telecommunications and computing. Ongoing efforts to miniaturize these systems and boost power density demand advanced thermal management solutions to maintain optimal cooling and temperature control. Spray cooling offers an effective means of removing high heat fluxes and keeping power electronics within safe operating temperatures. This study presents an experimental investigation of flash spray cooling in a closed-loop system using R410A refrigerant. In particular, two nozzles with different spraying angles are used to study the effects of the distance between the spray nozzle and a heated flat surface, as well as the mass flow rate of the coolant. Results indicate that three key flow-pattern factors—surface coverage, impingement intensity, and liquid film dynamics—govern the heat transfer mechanisms and determine cooling efficiency. Flash spray cooling using refrigerants like R410A demonstrates strong potential as a high-performance thermal management strategy for next-generation power electronics. Full article

Maize, as a critical crop for China’s food security, is constantly challenged by weed infestations and environmental risks associated with herbicide overuse. Improving herbicide utilization efficiency through equipment optimization and intelligent control during spraying has become an essential strategy for weed management in Chinese maize fields. However, most current sprayers fail to achieve coordinated control of spray volume and nozzle parameters, and their performance is typically evaluated using single indices, such as the coefficient of variation (CV) for spray uniformity and deposition density. In this study, a split-split-plot experiment was conducted in 2022–2023 to assess the feasibility of herbicide reduction using intelligent variable-rate boom sprayers in summer maize fields on the North China Plain (NCP). The key variables included spray volume (225 vs. 180 L/ha), nozzle type (AI11003VS/LECHLER11003 in 2022; TTI11004/LECHLER11004 in 2023), and herbicide dose (recommended, −15%, and −30% reduction). Results showed that the coefficients of variation for droplet coverage and density remained below 12% for all treatments (n = 4), indicating stable spray performance. A higher spray volume (225 L/ha) significantly improved deposition uniformity (p < 0.01). In 2022, herbicide input could be reduced by 15–30% while maintaining efficacy above 90% when applied at the 3–4 leaf stage of dominant weeds. However, in 2023, efficacy dropped to 72.67% when the herbicide was applied at a 30% reduced dose with 180 L/ha and when dominant weeds had reached the 5–6 leaf stage or higher, indicating an agronomic risk. Reduced herbicide input decreased maize injury by 47–53%. Only the 30% reduced-dose treatment significantly increased maize yield by 3.05% in 2022 and 2.62% in 2023 compared to the control (both p < 0.05). Spray volume significantly influenced droplet deposition and weed control efficacy; thus, caution is warranted regarding herbicide reduction for later weed growth stages. This study demonstrates that real-time variable-rate boom sprayers, optimized for spray volume and nozzle type, can reduce herbicide use without compromising weed control efficacy or maize yield, providing both theoretical support and practical guidance for sustainable herbicide management in summer maize fields on the NCP. Full article

Spin-spray-assisted layer-by-layer (LbL) assembly is an innovative method for producing nanostructured thin films due to its rapid assembly and extensive coverage of substrates. In this study, a nanofiltration (NF) membrane consisting of multilayers of polyethyleneimine (PEI) and poly(sodium-4-styrene sulfonate) (PSS) was fabricated on a polysulfone (PSF) support. The resulting membrane was further coated with a metal–organic framework (MOF303). The resulting (PEI/PSS)₅-MOF303 showed a rejection rate of 18.94 ± 1.58% and a permeability of 0.91 ± 0.13 L/(h·bar·m²)while also showing enhanced antifouling properties. This work explores the possibility of spin-spray-assisted LbL assembly as a promising method for fabricating membranes. Full article

In response to the need for precise blossom identification and optimization of key operational parameters in intelligent cherry spraying pollination, the SMD-YOLO (You Only Look Once with spatial and channel reconstruction convolution, multi-scale channel attention, and dual convolution modules) cherry blossom detection model is proposed, along with a pollination experiment platform for parameter optimization. The SMD-YOLO model, built upon YOLOv11, enhances feature extraction through the ScConvC3k2 (spatial and channel reconstruction convolution C3k2) module, incorporates the MSCA (multi-scale channel attention) attention mechanism, and employs the DualConv module for a lightweight design, ensuring both detection accuracy and operational efficiency. Tested on a self-constructed cherry blossom dataset, the model delivered a precision of 87.6%, a recall rate of 86.1%, and an mAP (mean average precision) reaching 93.1% with a compact size of 4765 KB, 2.28 × 10⁶ parameters, a computational cost of 5.8 G, and a detection speed of 75.76 FPS, demonstrating strong practicality and potential for embedded real-time detection in edge devices, such as cherry pollination robots. To further enhance pollination effectiveness, a dedicated pollination experiment bench was designed, and a second-order orthogonal rotational combination experiment method was employed to systematically optimize three key parameters: spraying distance, spraying time, and liquid flow rate. Experimental results indicate that the optimal pollination effect occurs when the spraying distance is 3.4 cm, spraying time is 1.9 s, and liquid flow rate is 339 mL/min, with a deposition amount of 0.18 g and a coverage rate of 97.25%. This study provides a high-precision image detection algorithm and operational parameter optimization basis for intelligent and precise cherry blossom pollination. Full article

In wind-assisted orchard spraying operations, the dynamic response of leaves—manifested through changes in their posture—critically influences droplet deposition on both sides of the leaf surface and the penetration depth into the canopy. These factors are pivotal in determining spray coverage and the spatial distribution of pesticide efficacy. However, current research lacks comprehensive quantification and correlation analysis of the temporal response characteristics of leaves under wind disturbances. To address this gap, a systematic analytical framework was proposed, integrating real-time leaf segmentation and tracking, geometric feature quantification, and statistical correlation modeling. High-frame-rate videos of fluttering leaves were acquired under controlled wind conditions, and background segmentation was performed using principal component analysis (PCA) followed by clustering in the reduced feature space. A fine-tuned Segment Anything Model 2 (SAM2-FT) was employed to extract dynamic leaf masks and enable frame-by-frame tracking. Based on the extracted masks, time series of leaf area and inclination angle were constructed. Subsequently, regression analysis, cross-correlation functions, and Granger causality tests were applied to investigate cooperative responses and potential driving relationships among leaves. Results showed that the SAM2-FT model significantly outperformed the YOLO series in segmentation accuracy, achieving a precision of 98.7% and recall of 97.48%. Leaf area exhibited strong linear coupling and directional causality, while angular responses showed weaker correlations but demonstrated localized synchronization. This study offers a methodological foundation for quantifying temporal dynamics in wind–leaf systems and provides theoretical insights for the adaptive control and optimization of intelligent spraying strategies. Full article

To compensate for the instability of renewable energy sources during China’s energy transition, large thermal power plants must provide critical operational flexibility, primarily through deep peaking. To investigate the combustion performance and wear and tear of a 600 MW pulverized coal boiler under deep peaking, the gas–solid flow characteristics and distributions of flue gas temperature, wall heat flux, and wall wear rate in a 600 MW tangentially fired pulverized coal boiler under variable loads (353 MW, 431 MW, 519 MW, and 600 MW) are investigated in this study employing computational fluid dynamics numerical simulation method. Results demonstrate that increasing the boiler load significantly amplifies gas velocity, wall heat flux, and wall wear rate. The maximum gas velocity in the furnace rises from 20.9 m·s⁻¹ (353 MW) to 37.6 m·s⁻¹ (600 MW), with tangential airflow forming a low-velocity central zone and high-velocity peripheral regions. Meanwhile, the tangential circle diameter expands by ~15% as the load increases. The flue gas temperature distribution exhibits a “low-high-low” profile along the furnace height. As the load increases from 353 MW to 600 MW, the primary combustion zone’s peak temperature rises from 1750 K to 1980 K, accompanied by a ~30% expansion in the coverage area of the high-temperature zone. Wall heat flux correlates strongly with temperature distribution, peaking at 2.29 × 10⁵ W·m⁻² (353 MW) and 2.75 × 10⁵ W·m⁻² (600 MW) in the primary combustion zone. Wear analysis highlights severe erosion in the economizer due to elevated flue gas velocities, with wall wear rates escalating from 3.29 × 10⁻⁷ kg·m⁻²·s⁻¹ (353 MW) to 1.23 × 10⁻⁵ kg·m⁻²·s⁻¹ (600 MW), representing a 40-fold increase under full-load conditions. Mitigation strategies, including ash removal optimization, anti-wear covers, and thermal spray coatings, are proposed to enhance operational safety. This work provides critical insights into flow field optimization and wear management for large-scale coal-fired boilers under flexible load operation. Full article

Tung oil, as dry oil, can quickly dry and polymerize into tough and glossy waterproof coatings, with a very high application value. Tung oil was used as a core material to prepare Tung oil microcapsules coated with chitosan–Arabic gum, and the preparation process of the microcapsules was optimized. The effect of adding a UV coating on the performance of the microcapsules was explored. Under the conditions of a core–wall mass ratio of 0.5:1.0, pH value of 3.5, mass ratio of chitosan to Arabic gum of 1.0:4.0, and spray drying temperature of 130 °C, Tung oil microcapsules coated with chitosan–Arabic gum had a higher yield and coverage rate, which were 32.85% and 33.20%, respectively. With the increase of the spray drying temperature during preparation, the roughness of the coating first increased and then decreased, the visible light transmittance decreased first and then increased, and the glossiness showed an overall downward trend. The self-repairing rate decreased gradually. When the microcapsules #11 were added to the UV topcoat at 5%, the coating can obtain excellent comprehensive properties; the roughness was 0.79 μm, elongation at break was 5.04%, visible light transmittance was 77.96%, gloss loss rate was 10.95%, and self-repairing rate was 20.47%. Full article

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

This paper presents, within an arable farming context, a predictive logic for the on- and off-switching of a set of nozzles. The predictive logic is tailored to a specific path planning pattern. The nozzles are assumed to be attached to a boom aligned along a working width and carried by a piece of machinery with the purpose of applying spray along the working width. The machinery is assumed to be travelling along the specific path planning pattern. The concatenation of multiple path patterns and the corresponding concatenation of the proposed switching logics enable nominal lossless spray application for area coverage tasks. The proposed predictive switching logic is compared to the common and state-of-the-art reactive switching logic for Boustrophedon-based path planning for area coverage. The trade-off between a reduction in pathlength and increase in the number of required on- and off-switchings for the proposed method is discussed. Full article

Problem: Agriculture in India faces pressing challenges related to water scarcity, excessive pesticide use, and inefficient energy consumption, impacting both economic sustainability and environmental health. Methodology: This study integrates Life Cycle Assessment (LCA), Data Envelopment Analysis (DEA), Intelligent Management Models (IMMs), and Multi-Criteria Decision Analysis (MCDA) to assess the economic and environmental benefits of UAV-based spraying in Indian agriculture. Data were collected from UAV service providers and field trials in Punjab, Haryana, and Rajasthan. Results: UAV spraying achieved a 70% reduction in water use, 40% reduction in pesticide consumption, and a 50% reduction in CO₂ emissions compared to conventional spraying. DEA results showed higher efficiency scores for UAVs, while IMM optimization achieved 95% pesticide coverage and reduced drift by 80%. Implications: MCDA ranked government subsidies as the most effective policy intervention. These findings support UAV spraying as a viable, scalable solution for climate-smart agriculture in India, offering both productivity and sustainability gains. Full article

The use of unmanned aerial vehicle (UAV) pesticide spraying technology in precision agriculture is becoming increasingly important. However, traditional spraying methods struggle to address the precision application need caused by the canopy differences of fruit trees in orchards. This study proposes a UAV orchard variable-rate spraying method based on canopy volume. A DJI M300 drone equipped with LiDAR was used to capture high-precision 3D point cloud data of tree canopies. An improved progressive TIN densification (IPTD) filtering algorithm and a region-growing algorithm were applied to segment the point cloud of fruit trees, construct a canopy volume-based classification model, and generate a differentiated prescription map for spraying. A distributed multi-point spraying strategy was employed to optimize droplet deposition performance. Field experiments were conducted in a citrus (Citrus reticulata Blanco) orchard (73 trees) and a litchi (Litchi chinensis Sonn.) orchard (82 trees). Data analysis showed that variable-rate treatment in the litchi area achieved a maximum canopy coverage of 14.47% for large canopies, reducing ground deposition by 90.4% compared to the continuous spraying treatment; variable-rate treatment in the citrus area reached a maximum coverage of 9.68%, with ground deposition reduced by approximately 64.1% compared to the continuous spraying treatment. By matching spray volume to canopy demand, variable-rate spraying significantly improved droplet deposition targeting, validating the feasibility of the proposed method in reducing pesticide waste and environmental pollution and providing a scalable technical path for precision plant protection in orchards. Full article