The accurate measurement of orchard canopy volume serves as a crucial foundation for wind regulation and dosage adjustments in precision orchard management. However, existing methods for measuring canopy volume fail to satisfy the high precision and real-time requirements necessary for accurate variable-rate applications in fruit orchards. To address these challenges, this study develops a canopy volume measurement model for orchard spraying using LiDAR point cloud data. In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. This method improves the validity judgment for contour line segments, effectively reducing contour length errors on each 3D point cloud projection plane. Additionally, improvements to the mesh integral volume method incorporate the effects of canopy gaps in height difference calculations, significantly enhancing the accuracy of canopy volume estimation. For feature selection, a random forest-based recursive feature elimination method with cross-validation was employed to filter 10 features. Ultimately, five key features were retained for model training: the number of point clouds, the 2D point cloud contour along the X- and Z-projection directions, the 2D width in the Y-projection direction, and the 2D length in the Z-projection direction. During model construction, the study optimized the hyperparameters of partial least squares regression (PLSR), backpropagation (BP) neural networks, and gradient boosting decision trees (GBDT) to build canopy volume measurement models tailored to the dataset. Experimental results indicate that the PLSR model outperformed other approaches, achieving optimal performance with three principal components. The resulting canopy volume measurement model achieved an R² of 0.9742, an RMSE of 0.1879, and an MAE of 0.1161. These results demonstrate that the PLSR model exhibits strong generalization ability, minimal prediction bias, and low average prediction error, offering a valuable reference for precision control of canopy spraying in orchards.

The characteristics of soil ditching and backfilling are crucial for orchard ditching operations. However, experimentally investigating the dynamic ditching and backfilling process is currently not feasible. To address this issue, the 3DGZ-50A self-propelled orchard ditching machine (SPODM) was designed using a modular concept, incorporating three types of ditching cutter discs (01#, 02#, and 03#). These discs were designed, trial-manufactured, and tested in orchard ditching experiments. A corresponding simulation model was also constructed using EDEM 2022 software. This study evaluated the ditching and backfilling process, analyzing the performance of the three cutter discs through experimental and simulation methods. Results indicated that the 01# and 02# cutter discs created V-shaped furrows, whereas the 03# cutter disc formed an arc-shaped furrow. The relative errors in the final furrow depth (D_f) and width (W_f) between experimental and simulated results were 30.70% and 8.61%, respectively, while those in the maximum furrow depth (D_m) and width (W_m) were 9.44% and 3.00%. These minor relative errors confirmed the accuracy of the simulation model. Regarding maximum power consumption, the 01# cutter disc used 86.3% of the power consumed by the 02# cutter disc and 85.1% of that used by the 03# cutter disc. During the ditching process, the blades penetrated the soil to create the maximum furrow cross-section, which then gradually decreased due to backfilling. Both simulation and test results demonstrated that the 01# cutter disc performed best, achieving a maximum furrow cross-sectional area (46.70%), minimum final surface furrow cross-sectional area (6.04%), and lower power consumption (31.03 kW). This study provides equipment for ditching operations in low-height close-planting orchards in northern China.

As the core actuation component of intelligent precision spraying systems, the variable-rate nozzle is essential for achieving on-demand agricultural spraying; improving the use efficiency of water, fertilizers and pesticides; and reducing environmental pollution. This paper systematically reviews the development of agricultural variable-rate nozzles, from early mechanical profiling structures to modern intelligent control technologies based on Pulse Width Modulation (PWM). First, the existing variable-rate nozzles are classified into three major categories: electromagnetic-integrated type, centrifugal type, and variable-diameter type. A comparative analysis is conducted from three dimensions of working principle, performance characteristics and application scenarios, to delineate the respective advantages and limitations of each nozzle category. Second, the paper examines key technological advances in three areas: high-frequency solenoid valves, PWM control, and pressure and flow stabilization. It identifies the nonlinear response of solenoid valves, flow distortion under low duty cycles, and water hammer pressure fluctuation induced by high-speed switching as the three core technical bottlenecks at the current stage. Subsequently, the latest achievements and typical methodologies of variable-rate nozzles in structural design, simulation and experimental analysis are systematically reviewed, and their application performance in scenarios including field crops, orchards, protected agriculture and beyond are summarized. Finally, the remaining open issues in this field are put forward. It is suggested that future research should focus on key breakthroughs in the development of corrosion and wear-resistant high-frequency solenoid valves, the formation mechanism and suppression methods of pressure fluctuation, as well as adaptive algorithms based on machine learning or Model Predictive Control (MPC), to promote the leapfrog development of agricultural variable-rate nozzle technology from single variable control to multi-factor coupling optimization. All references cited in this paper are from articles published after the year 2000. Among them, the literature published in the last decade accounts for 86.6%, and literature published in the last five years accounts for 58.9%.