This study attempts to optimize the arc-shaped coned disk affecting the uniformity of the earlier designed fertilizer apparatus (FA), in particular, for application in the rice–oil rotation region in the middle and lower reaches of the Yangtze River, China. Based on theoretical analysis, a circular coned disk with the curvature gradual decline (GD) from top to bottom was designed, and the equation of the circular cone was determined. The EDEM discrete element software was used, using the coefficient of variation of the fertilization amount consistency in every row, the coefficient of variation of the fertilization amount stability, and the coefficient of variation of the fertilization amount consistency in the same row as evaluation indices. Simulations and comparative tests of FA performance were performed for three cases of the busbar top-to-bottom curvature variation: (i) gradual increase (GI), (ii) gradual decline (GD), and (iii) zero (0) variation. The experimental results show that at the FA rotation speed of 100~120 r/min and tilt of 1°~5°, the optimized FA had the optimal performance. High tilts and low rotation speeds provided the worst performance, with the variation coefficient of inter-row fertilization amount consistency of the FA below 10.23%. The variation coefficient of fertilizing amount stability was lower than 6.74%. The variation coefficient of intra-row fertilizing amount consistency was lower than 3.52%, while all performance indicators met the quality requirements of fertilizer discharge. Bench tests of the FA revealed that the variation coefficient of inter-row fertilizing amount consistency of the FA was below 10.23%, the variation coefficient of fertilizing amount stability was below 6.74%, and the variation coefficient of intra-row fertilizing amount consistency was below 3.52%. Field tests of the FA revealed that the variation coefficient of inter-row fertilizing amount consistency was below 7.68%, the variation coefficient of fertilizing amount stability was below 4.95%, and the variation coefficient of intra-row fertilizing amount stability was below 3.57%. All parameters were better than the industry standard, demonstrating that the FA had good fertilizing performance and met the quality requirements of field fertilization operations.

Existing rice inter-plant weed control devices have difficulty achieving inter-plant weed control in one pass. Due to the complex environment of paddy fields, these devices have a low weed removal rate and high seedling damage rate, making it difficult to ensure high-quality operation. This study innovatively designed a water jet-based rice inter-plant weed control device. Based on the mechanism of water jet erosion of soil, it can erode and excavate the soil layer on which weeds depend, achieving inter-plant weed control in paddy fields. The optimal range of structural parameters of the water jet angle and nozzle opening diameter was analyzed. The results showed that the optimal structural parameters of the device were a jet angle of 31° and a nozzle opening diameter of 4 mm, which can achieve the best operational performance. Based on virtual simulation experiments, single-factor and multi-factor orthogonal rotation combination experiments were carried out with weed removal rate as the test index and different operating speeds and nozzle outlet pressures as the test factors to optimize the water jet-based inter-plant weed control device. The experimental results showed that when the working parameters of the water jet-based inter-plant weed control device were a forward speed of 0.30 m∙s⁻¹ and a nozzle outlet pressure of 1.50 MPa, the weed removal rate was the highest at 92.78%. Field validation experiments showed that the weed removal rate was 90.16% and the seedling damage rate was 1.80% under this operation condition, and the quality of the operation met the requirements of inter-plant weed control technology. This study provides a technical reference for promoting the development of inter-plant weed control technology in paddy fields.

Automatic picking of ginkgo fruits is beneficial for prolonging their freshness and ensuring quality during storage. Accurate identification of ginkgo fruits is a critical prerequisite for enabling stable and reliable operation of the end-effector during the harvesting process. However, due to the similarities in color and size between ginkgo fruits and leaves, traditional recognition methods are prone to being affected by variations in lighting, occlusion, and background interference. To solve these challenges, this paper presents an accurate identification method for ginkgo fruits based on GinkgoSense-Net. Specifically, EMA and SAF are integrated into the YOLOv11n framework, and the bounding box regression function is replaced with EIoU. At the same time, methods such as Grad-CAM visualization, ablation experiments, and comparative experiments are used to validate the efficacy of GinkgoSense-Net. The experimental results demonstrate that GinkgoSense-Net has a precision of 95.0%, a recall of 92.1%, and an mAP of 93.6% in the detection of ginkgo fruits, and its real-time performance reaches 74.9. These findings indicate that the proposed model achieves an effective balance among detection accuracy, computational efficiency, and model complexity. The research findings facilitate the advancement of smart agriculture and promote the practical application of vision technology in the field of intelligent harvesting.