To demonstrate the feasibility and improve the implementation of laser weeding, a static movable lift-adjustable closed fiber laser weeding device and system have been developed, followed by experiments and performance evaluations. Physical experiments were conducted on the energy required for laser cutting of weed stems, targeting four common larger weeds (Chenopodium album, Amaranthus spinosus, Setaria viridis, and Eleusine indica) in farmland and orchards. At the same irradiation distances, the energy required to cut the same type of large weed generally increases with increasing distances and stem diameters but decreases with increasing irradiation time. The variance of stems’ power density after irradiation was larger and the values were more dispersed for Chenopodium album and Setaria viridis weeds, and the values were relatively scattered, while the power density values of Amaranthus spinosus and Eleusine indica weeds were more concentrated. When the irradiation time was 10 s, the 3.892 W/mm² laser was sufficient to eliminate weeds and plants with the irradiation distances of 2 m. The 2.47 W/mm² laser was more effective, as it killed weeds within a distance of 1 m in less than 1 s. This work demonstrates the feasibility of the laser weeding device and system that can completely cut off the stems of large weeds, and this technology has the potential to promote sustainable agriculture.

In response to the global labor shortage in the pear industry, the use of robots for harvesting has become an inevitable trend. Developing pear harvesting robots for orchard operations is of significant importance. This paper systematically reviews the progress of three key technologies in pear harvesting robotics: Firstly, in the field of recognition technology, traditional methods are limited by sensitivity to lighting conditions and occlusion errors. In contrast, deep learning models, such as the optimized YOLO series and two-stage architectures, significantly enhance robustness in complex scenes and improve handling of overlapping fruits. Secondly, positioning technology has advanced from 2D pixel coordinate acquisition to 3D spatial reconstruction, with the integration of posture estimation (binocular vision + IMU) addressing occlusion issues. Finally, the end effector is categorized based on harvesting mechanisms: gripping–twisting, shearing, and adsorption (vacuum negative pressure). However, challenges such as fruit skin damage and positioning bottlenecks remain. The current technologies still face three major challenges: low harvesting efficiency, high fruit damage rates, and high equipment costs. In the future, breakthroughs are expected through the integration of agricultural machinery and agronomy (standardized planting), multi-arm collaborative operation, lightweight algorithms, and 5G cloud computing.

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.

To solve the problems of low seeding precision and the poor operational adaptability of traditional no-till seeders under dense planting mode, and meet the agronomic requirements for high maize yield, this study carried out optimization and experimental research on the no-till precision fertilizer-seed co-sowing system for maize with wide-narrow row dense planting, relying on the experimental base of the Science and Technology Courtyard for Super High-Yield Cropping Systems in Qihe, China Agricultural University. Through modular integration and the optimization of key components, precise row spacing adjustment and improved sowing depth consistency in complex plots were achieved. A tractor-implement integrated a kinematic model and a dynamic model of the seed metering tube, which were constructed to quantify the correlation between operational parameters and motion states, providing theoretical support for structural parameter optimization. Field tests showed that all operational quality indicators of the system met the local high-yield requirements for no-till dense planting; the comprehensive performance was optimal at a density of 75,000 plants·ha⁻¹, with the best seeding uniformity (coefficient of variation: 5.65%), seedling emergence and seedling uniformity, which is well adapted to the agronomic characteristics of the wheat–maize rotation areas in the Huang-Huai-Hai Plain. Subsequent optimization by reducing the operating speed and increasing the spring stiffness can further improve the operational quality, realize the deep integration of agronomy and agricultural machinery, provide agricultural machinery support for high-yield and high-quality maize cultivation, and is of great significance for improving agricultural production efficiency and resource utilization.

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.

This study systematically identified the pathogenic fungi affecting Areca catechu in Hainan. Using diseased tissues from five regions, isolates were obtained using molecular methods, and their pathogenicity was confirmed using Koch’s postulates. We obtained 44 distinct fungal isolates from 9 genera. Fusarium (27.27%) and Colletotrichum (38.12%) were the dominant genera across all tissues. Twenty isolates were confirmed as pathogens. Key findings include the first report of Alternaria angustiovoidea and A. pogostemonis as areca leaf spot pathogens in China and the first confirmation of pathogenicity for three Fusarium species complexes (FSSC, FFSC, FIESC). Five Fusarium species are newly reported as pathogens in China. Cladosporium tenuissimum and Plectosphaerella cucumerina were confirmed for the first time to cause leaf spot. Fusarium, Colletotrichum, and Alternaria were core pathogens, all exhibiting high polygalacturonase and cellulase activity. The FFSC and Colletotrichum gloeosporioides species complex (CGSC) showed broad-spectrum pathogenicity on tropical fruits. Fungicide sensitivity assays ranked efficacy as prochloraz > difenoconazole > tebuconazole > ethylicin > pyraclostrobin, with genus-specific responses observed. This research fills a systematic knowledge gap on areca fungal diseases in China, providing a crucial basis for precise control strategies and integrated management.