Design and experiment of a soybean shaftless spiral seed discharge and seed delivery device.

When the driven stubble-breaking and anti-blocking no-till planter operates in the Southwest China, the stubble-breaking blades will impact with the ground as they cut through the soil and straw stubble, causing the planter to vibrate. This results in poor performances of the seed discharge by seed discharger and the seed guide by the seed guide tube. Based on the principle of spiral conveying, a soybean shaftless spiral seed discharge and seed delivery device was designed. The optimum seed filling size and speed range of the spiral blade were obtained by analyzing the size, force, and motion of soybean seeds of "ZhongHuang 37". The quadratic regression orthogonal rotation test and response surface method were used to analyze the operating parameters of the shaftless spiral seed discharge and seed delivery device by joint EDEM (Discrete Element Method)-RecurDyn simulation. The optimum parameters were obtained: the spacing of spiral was 11.4 mm, spiral outer radius was 5.5 mm, spiral inner radius was 2.9 mm and rotation speed was 10.4 r·s-1. Based on simulation and optimization results, the device was trialed and its field performance was tested. The results showed that at a surface slope of 16.1°, an average surface flatness of 8.9 cm, an average planter vibration frequency of 75.2 Hz, and an average amplitude of 7.2 mm, the average seeding qualification index, multiple index, missing seeding index, and damage index of the shaftless spiral seed discharge and seed delivery device were 92.6%, 5.03%, 2.4% and 0.92%, respectively, which were in line with the local agronomic requirements. The designed soybean shaftless spiral seed discharge and seed delivery device meets the requirements of the quality of no-till seeding and can provide a reference for the design and improvement of seed discharger and seed guide tube under poor ground leveling and long-distance seed delivery conditions.

Design and experimental study on pruning machine of Yunnan edible rose.

Edible rose is one of the main cash crops in Yunnan, China. Due to the high degree of lignification of rose stalks which is difficult to cut, and roses can only be pruned by hand after picking. Most of Yunnan Province is hilly landscape. Therefore, it is necessary to design an efficient small rose pruner for hills. Based on the experimental results of the physical and mechanical properties of rose stems, a simulation experiment of three different cutting methods was conducted to determine the optimal scheme. The results showed that single disc cutter is the best cutting method. An improved disc cutter with variable sliding angle is designed. In order to study the effects of the different structure parameters on the performance of the pruning machine and get the optimal combination of parameters, the orthogonal test was conducted. Forward speed, rotational speed of cutter, number of blades, cutting angle and knife-edge angle as factors, and the quality of pruning was selected as the evaluation index. The experiment results indicated that the working performance of machine was the highest when the number of blades was 6, rotational speed of cutter was 2000 rpm, cutting angle was 20°, knife-edge angle was 10°, forward speed was 0.5 m s-1. The average quality of pruning index, miss cutting index and tearing index were 90.6%, 5.68% and 3.72%, respectively. The designed machine can meet the agronomic requirements of Yunnan edible rose pruning operation. The research provides a reference for the design and extending of the pruning machine for edible rose.

YOLOX-based blue laser weeding robot in corn field.

A YOLOX convolutional neural network-based weeding robot was designed for weed removal in corn seedling fields, while verifying the feasibility of a blue light laser as a non-contact weeding tool. The robot includes a tracked mobile platform module, a weed identification module, and a robotic arm laser emitter module. Five-degree-of-freedom robotic arm designed according to the actual weeding operation requirements to achieve precise alignment of the laser. When the robot is in operation, it uses the texture and shape of the plants to differentiate between weeds and corn seedlings. The robot then uses monocular ranging to calculate the coordinates of the weeds using the triangle similarity principle, and it controls the end actuator of the robotic arm to emit the laser to kill the weeds. At a driving speed of 0.2 m·s-1 on flat ground, the weed robot's average detection rate for corn seedlings and weeds was 92.45% and 88.94%, respectively. The average weed dry weight prevention efficacy was 85%, and the average seedling injury rate was 4.68%. The results show that the robot can accurately detect weeds in corn fields, and the robotic arm can precisely align the weed position and the blue light laser is effective in removing weeds.