In order to improve the quality of oil peony transplanting, based on the characteristics of peony seedlings and the transplanting effect, the transplanting process was analyzed. A peony seedling transplanting machine was designed, which was mainly composed of a chain-clamp type planting mechanism (clamp, transmission chain, sprocket), slideway, profiling wheels, trencher, the power transmission system and rack. Through the movement analysis of the planting mechanism and its operation process, its structural parameters were optimized. The effective length of the clamp was determined as L1=235 mm, the adjustment range was 235-285 mm, and the height of the planting trajectory was H=340 mm. Based on the physical characteristics and mechanical characteristics of the peony seedlings, the parameters of the slideway and the putter were determined. The effective length of the slideway was determined as L2=420 cm, the width T2=105 mm, the distance between the slideways S=45 mm. The initial angle difference of the putter was θ=13°, and the putter rotation angle β=37°, putter height ratio ε=2. Based on the above parameters and design requirements, the radius of the planting sprocket R1=42 mm, R2=80 mm. “Feng Dan” peony seedlings were used as transplantation test objects. The results showed that: when the planting frequency was 60-75 plants/min, the upright rate was 89.2%-92.8%, the leakage rate was 0-0.28%, the injury rate of seedlings was 0, and the qualified rate of planting depth was 91.7%-95.3%, the variation coefficient of plant spacing was 0.25%-0.54%. This machine can effectively improve the quality and efficiency of transplanting, meeting the requirements of mechanical design and production needs. Keywords: peony transplanting, planting mechanism, oil peony, peony seedlings, parameter design, test analysis DOI: 10.25165/j.ijabe.20201304.5695 Citation: Ji J T, Cheng Q, Jin X, Zhang Z H, Xie X L, Li M Y. Design and test of 2ZLX-2 transplanting machine for oil peony. Int J Agric & Biol Eng, 2020; 13(4): 61–69.

This study aimed to evaluate the effects of aspirin eugenol ester (AEE) on growth performance, oxidative liver damage, inflammation, and liver metabolomics in broilers under high-stocking-density (HSD) stress. A total of 360 broilers were divided into four groups: normal density (ND, 14/m²), high density (HD, 22/m²), ND-AEE (ND + 0.01% AEE), and HD-AEE (HD + 0.01% AEE). HSD decreased total antioxidant capacity, increased malondialdehyde (MDA) levels, and elevated the expression of cyclooxygenase-2 (COX-2) and microsomal prostaglandin E synthase-1 (mPGES-1) mRNA, which contributed to the reduced performance of broilers. Specifically, HSD caused abnormalities in linoleic acid metabolism, leading to elevated levels of Prostaglandin E2 (PGE2) and Leukotriene B4 (LTB4) synthesis, which aggravated inflammation, increased liver lipid levels, and impaired ATP production. AEE counteracted the decline in broiler production performance induced by HSD by enhancing total antioxidant capacity, reducing MDA levels, protecting the liver from oxidative damage, and maintaining mitochondrial oxidative phosphorylation. AEE positively regulated the linoleic acid metabolism by promoting the synthesis of γ-linolenic acid and phosphatidylcholine, which reduced the synthesis of COX-2 and mPGES-1. AEE alleviated the metabolic imbalance caused by HSD stress and enhanced the efficiency of mitochondrial fatty acid oxidation, which reduced excess lipid accumulation in the liver and promoted ATP production. In summary, this study provides strong support for the dietary addition of AEE to alleviate liver oxidative damage, inflammation, and energy metabolism disorders caused by HSD stress.

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network, GY, based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and the SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While mAP@0.5 increased by 0.514% to 95.364, the model simultaneously reduced the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system localization accuracy and robustness. It shows a remarkable 92.59% improvement in RMSE for Absolute Trajectory Error (ATE), along with a 93.11% improvement in RMSE for the translational drift of Relative Pose Error (RPE) and a 92.89% improvement in RMSE for the rotational drift of RPE. Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.

This study designed a cam-linked planetary gear system automatic seedling picking mechanism to address unstable operation and issues of high damage to the substrate caused by the picking mechanism of the dryland vegetable seedling transplanter. Through an analysis of the kinematic principle of the structure and the establishment of the kinematic model, computer-aided analysis software was developed using Visual Basic 6.0. Consequently, a set of structural parameter values satisfying the target trajectory was derived employing the human–computer interaction method, and the 3D model was designed. The model was imported into Adams for kinematic simulation, and the seedling picking mechanism’s trajectory during the operation was obtained through simulation. Modal analysis of the model was performed using Ansys, and the first six-order modal vibration patterns and modal frequencies of the seedling picking mechanism were obtained under the simulated working environment. The results confirmed that no resonance occurred during the operation. Comparisons of the seedling picking needle trajectory with the idle test revealed that the theoretical, simulated, and test trajectories were approximately identical. This proved the reliability of the theoretical design of the seedling picking mechanism, the machining of the parts, and the test bench construction. The success rates of seedling picking were 97.66, 96.09, 93.75, and 90.63% at 90, 100, 110, and 120 plants/min, respectively, with rates of substrate damage of 4.43%, 6.73%, 9.57%, and 14.37%, respectively. Thus, the experimental results confirmed that the operating parameters of the cam-linked planetary gear system seedling picking mechanism satisfied the design requirements.

Method for the fruit tree recognition and navigation in complex environment of an agricultural robot