Xuemin Zhang

Aiming at addressing the issues of poor uniformity of liquid deposition, low coverage on the abaxial side of leaves, and significant pesticide drift loss during traditional spraying operations in the current facility greenhouse environment, a crawler-type electrostatic spraying plant protection machine suitable for the ridge cultivation mode of tomatoes was designed. Based on the computational fluid dynamics method, the electrostatic spraying process was simulated and analyzed using Fluent software. The effects of nozzle spacing on the uniformity of spatial electric field distribution and of charging voltage on the deposition thickness of the liquid film on the target surface were investigated. The optimal nozzle spacing was determined to be 300 mm and the optimal charging voltage to be 6 kV. Through field experiments, using droplet deposition density, adhesion rate, and deposition amount as evaluation indicators, the effects of spraying distance, electrostatic voltage, and working pressure on the droplet deposition characteristics on both the adaxial and abaxial sides of plant leaves were studied. The results showed that when the spraying distance was 50 cm, the electrostatic voltage was 6 kV, and the spraying pressure was 0.8 MPa, the droplet adhesion rate reached 86% on the adaxial side and 42% on the abaxial side of tomato leaves. The findings of this study provide a theoretical basis for precise and efficient electrostatic spraying plant protection operations in facility tomato cultivation.

To achieve the objectives of a variable spreading width and uniform fertilizer distribution in different operating environments, such as orchards and greenhouses, this study proposes a multi-channel fertilizer spreading method and designs a multi-channel fertilizer spreading system. The system mainly consists of a fertilizer delivery device and multi-channel spreading fertilizer disc. Based on the fertilizer delivery requirements, the fertilizer delivery device was designed using kinematic theories and the EDEM software. To address the optimization problem of the fin angle (λ), EDEM simulation is combined with machine learning methods, the multi-channel fertilizer spreading system was simulated using EDEM, and a spreading model was established based on the CNN-LSTM–Attention algorithm using simulation data. The model was employed to optimize the fin angle (λ), with spreading uniformity and width as the evaluation metrics. The optimization yielded a fin angle of λ = 34.15°, a coefficient of variation (Cv) of transverse distribution uniformity of 9.29%, and a spreading width of 3.0 m. The optimization results were validated through a combination of EDEM simulation and field tests. The EDEM simulations indicated a Cv of transverse distribution uniformity of 7.66% and an effective spreading width of 2.95 m. Field test results show a spreading width of 2.97 m and an average Cv of transverse distribution uniformity of 10.21%. The model optimization results align well with both the EDEM simulation and field test outcomes, providing new insights into researching fertilizer spreading methods.

Wolfberry originates from China and is mainly distributed across temperate and subtropical regions. Currently, wolfberry is predominantly harvested manually, which presents significant challenges, such as high labor intensity, low picking efficiency, and high cost. With the advancement of agricultural automation, mechanized wolfberry harvesting has become an inevitable trend and a research hotspot. In recent years, scholars have made numerous innovative attempts to develop wolfberry harvesting machinery, but a systematic review of these technologies and devices is still scarce. Therefore, this review comprehensively examines the cultivation characteristics and harvesting challenges of wolfberries. It categorizes and elaborates on the research status and progress of various mechanized harvesting devices based on their working principles and structural designs. It also discusses the challenges confronting the development of mechanized wolfberry harvesting technology. Finally, it reviews several promising research directions, including vibration-pneumatic hybrid harvesting systems, non-contact harvesting methods utilizing pulsed vortex-ring airflow, and differentiated precision harvesting approaches integrating visual recognition technology. This review aims to provide a crucial reference for the future development of mechanized wolfberry harvesting technology and equipment.

Supplementary pollination is essential for achieving optimal yields (> 70 t ha-1) and quality in greenhouse tomato production. Colony collapse disorder affects natural pollinators, creating an urgent need for supplementary mechanical pollination alternatives, driving significant research and application development. This review systematically analyzes the current research and applications of three mechanical pollination approaches: vibrator-based, ultrasonic, and airflow methods. Vibration systems typically achieve 60-85% pollen release efficiency and fruit set rates comparable to bumblebee pollination. Ultrasonic devices enhance pollen shedding by approximately 10-25% over conventional vibrators. Airflow-based methods provide 30-50% wider pollen coverage and 2-4 times higher operational efficiency, but with lower pollen deposition precision. Cost comparisons indicate that device prices range from $80-300 for vibrators, $300-$1200 for ultrasonic tools, and $150-$1500 for airflow devices. Despite rapid progress, research gaps remain in pollen release mechanisms, pollen transport modelling, and intelligent control algorithms. Future studies should prioritize mechanistic modelling of tomato pollination, the development of energy efficient and cost-effective pollination devices, and the integration of intelligent robotic systems for fully automated mechanical pollination.