Although there are existing interplant weed control devices for soybeans, they mostly rely on image recognition and intelligent navigation platforms. Simultaneously, automated weed control devices are not yet fully mature, resulting in issues such as high seedling injury rates and low weeding rates. This paper proposed a reciprocating interplant weed control device for soybeans based on the idea of intermittent reciprocating opening and closing of weeding execution components. The device consists of a laser ranging sensor, servo motor, Programmable Logic Controller (PLC), and weeding mechanism. Firstly, this paper explained the overall structure and working principle of the weed control device, and discussed the theoretical analysis and structural design of the critical component, elastic comb teeth. This paper also analyzed the working principle of the elastic comb teeth movement trajectory and seedling avoidance action according to soybean agronomic planting requirements. Then, field experiments were conducted, and the experiment was designed by the quadratic regression general rotation combination experimental method. The number of combs, the speed of the field management robot, and the stabbing depth were taken as the test factors to investigate their effects on the test indexes of weeding rate and seedling injury rate. The experiment utilized a response surface analysis method and designed a three-factor, three-level quadratic regression general rotation combination experimental method. The results demonstrate that the number of comb teeth has the most significant impact on the weeding rate, while the forward speed has the most significant impact on the seedling injury rate. The optimal combination of 29.06 mm stabbing depth, five comb teeth, and a forward speed of 0.31 m/s achieves an optimal operational weeding rate of 98.2% and a seedling injury rate of 1.69%. Under the optimal parameter combination conditions, the machine’s performance can meet the requirements of intra-row weeding operations in soybean fields, and the research results can provide a reference for the design and optimization of mechanical weed control devices for soybean fields.

Under soybean–corn intercropping in China, quizalofop-p-ethyl is recommended as a herbicide for stem and leaf treatment after soybean seedling. Nonetheless, herbicide drift during spraying may lead to environmental contamination and damage to the corn plants. In order to clearly show the threshold of the drift deposition amount of quizalofop-p-ethyl that causes herbicide damage to corn, we used a bioassay spray tower to spray quizalofop-p-ethyl herbicide on corn in the laboratory and a boom sprayer to spray quizalofop-p-ethyl herbicide, which drifts to corn in the field, to study and evaluate the damage quizalofop-p-ethyl herbicide causes to corn under different spray volumes and drift deposition rates. The results showed that under a drift deposition rate of 1% of three spray volumes, the corn showed no symptoms of herbicide damage and their plant height was not inhibited 14 days after spray; under a spray volume of 150 L/ha and a drift deposition rate of 5%, the corn showed symptoms of mild herbicide damage but their plant height was not inhibited 14 days after spray, while the corn showed symptoms of moderate herbicide damage and their plant height was slightly and moderately inhibited, respectively, under the spray volumes of 300 L/ha and 450 L/ha; under drift deposition rates of 10% and 30% of three spray volumes, half or more of the corn in each treatment withered and their plant height was severely inhibited or completely inhibited. Under the same spray volume, the symptoms of herbicide damage and the inhibition rate of plant height increased with the increase in the drift deposition rate; under the same drift deposition amount, the symptoms of herbicide damage and the inhibition rate of plant height increased with a decrease in the spray volume. The effect of the drift deposition rate on the symptoms of herbicide damage and plant height was extremely significant, but the spray volume was not significant. The drift deposition rates for 10% inhibition and no inhibition of corn plant height were 5.70% (R₁₀) and 5.05% (R₀) under spray volume of 150 L/ha, 4.56% (R₁₀) and 1.23% (R₀) under 300 L/ha, and 3.31% (R₁₀) and 1.86% (R₀) under 450 L/ha, respectively. When the herbicide was sprayed in the field using a soybean–corn-dedicated plant protection machine under the spray volume of 450 L/ha, the drift deposition rate ranged from 1.22% to 1.69%, and the corn did not produce symptoms of herbicide damage and plant height was not inhibited 14 days after the spray. In actual weeding operations, it is better to ensure that the drift deposition rate of quizalofop-p-ethyl is below R₀ by setting reasonable operational parameters, using anti-drift nozzles or additives, and so on, and, at most, not more than R₁₀. This study clarified the drift hazard of quizalofop-p-ethyl herbicide on corn and the safety value of the herbicide drift deposition amount, which provided data support for the standardized use of quizalofop-p-ethyl herbicide under soybean–corn intercropping and guidance for the safe production of field corn.

When endeavoring to study the complex growth conditions of soybean plants under natural conditions, a problem arises due to the similar appearances of both soybean plants and weeds. To address this issue, a soybean plant recognition model based on a laser ranging sensor is proposed. To demonstrate the applicability of the soybean plant recognition model, experiments are conducted using ultrasonic sensors and laser ranging sensors to analyze the diameter, height, and spacing conditions in the model. A test environment is built, and during the pre-test, the laser range sensor detects objects with diameters of 3 mm and 5 mm with two and three measurement points, respectively, at a speed of 0.2 m/s. At a speed of 0.3 m/s, there is one measurement point for objects with 3 mm diameter and two measurement points for objects with 5 mm diameter. At 0.4 m/s, there are also one and two measurement points for objects with diameters of 3 mm and 5 mm, respectively. These results demonstrate that the laser range sensor can more accurately recognize the diameter conditions of soybean plants and weeds and can distinguish between the diameters of soybean plants and weeds. Subsequently, the recognition rate of the model is evaluated by observing whether the weeding mechanism can synchronize seedling avoidance after the soybean plant passes through the sensor. The recognition rates of the optimized model at speeds of 0.2 m/s, 0.3 m/s, and 0.4 m/s are 100%, 98.75%, and 93.75%, respectively. Upon comprehensive analysis, the soybean plant recognition model is determined to achieve a recognition rate of 98.75% at a speed of 0.3 m/s, which is considered a moderate speed, and demonstrates more stable recognition of plant diameters. The test further verifies the reliability and effectiveness of the method for distinguishing between soybean plants and weeds. The research results can serve as a reference for recognizing soybean plants based on the use of laser ranging sensors.