This study aimed to resolve the problems of full wheat straw returning to the field, which might readily cause stalk obstruction, poor sowing quality, and serious weeds at the seedling stage, affecting the growth of maize. Based on the idea of “simultaneous seeding and spraying, closed weeding”, this paper presented a design method for designing a corn seed-fertilizer-herbicide simultaneous operation machine, which focuses on the design of vertical active straw-removing anti-blocking device mechanism, design of nozzle key parameters, nozzle selection, seeding monomer analysis and spatial layout design of seed-fertilizer-herbicide mechanism. In addition, the interrelated formulas were deduced and machine design and field experiment were conducted. The experiment results showed that the average variation coefficient of spray uniformity of machines was 17.70%. The post-experiment weed amount was 8.9%, which was lower than that before sowing, 8.5% lower than that before artificially closed weeding, and 14.3% lower than that in unenclosed weeding area. Moreover, the weeds were less in the working area of the machine, and the growth of corn was better. Compared with manual closed weeding, the average plant height uniformity and average stem diameter uniformity increased by 4.4% and 5.1%, respectively. Compared with unclosed weeding, the average plant height uniformity and average stem diameter uniformity increased by 18.3% and 10.8%, respectively. Overall, the rationality of the design method proposed in this paper was validated, and these can lay a foundation for the research and development of the same type of machine. Keywords: seed-fertilizer-herbicide, combined application, precision seeding machine, spray device, closed weeding DOI: 10.25165/j.ijabe.20191204.4679 Citation: Huang X, Wang W W, Li Z D, Wang Q Q, Zhu C X, Chen L Q. Design method and experiment of machinery for combined application of seed, fertilizer and herbicide. Int J Agric & Biol Eng, 2019; 12(4): 63–71.

The planter plate is the most important component of the pneumatic hill-drop seed metering system for rapeseed. The structural parameters of the planter plate are the primary determinants of rape planting. The key structural and operational parameters, such as the layout of the suction hole, its diameter, and its shape, were determined through theoretical analysis. Fluent is used to simulate the flow field of various types of suction holes, and the effect of suction hole shape on the change in the flow field of the suction chamber shell is analyzed. Under the same boundary conditions, the results indicate that the maximum velocity of the end face of the horn hole and the average pressure of the section are the highest. Using a high-speed camera, the effects of suction hole diameter and shape on seed filling performance were studied, and the results of Fluent simulation analysis were validated. The optimal seed metering device operating parameters were as follows: planter plate speed of 30–70 r/min and negative pressure of −2.5–−1.5 kPa. The influence of working negative pressure and the rotational speed of the planter plate on seed arrangement performance was studied within the optimal operating parameter range. In order to improve the performance of rational close planting in the seed planter, the multi-objective optimization design of working parameters and the verification test were also conducted. The results showed that with the best combination of working parameters, the empty broadcast rate does not go above 3%, the hole number qualified rate does not go below 96%, and the difference between them and the theoretical optimization result does not go above 5.5%.

On the basis of the discrete element method (DEM), the movement of seed particles during the filling process of a wheat hole-wheel variable seed-metering device was numerically simulated. The impact of various model hole structures, filling postures, and vibration frequencies on the performance of filling was investigated. The results demonstrated that the average speed and filling posture of seeds varied significantly between models. The research demonstrated that the planter’s filling effect was greatly enhanced by raising the average seed population speed in the confined region. Wheat seeds can be filled in the “flat” and “side” postures because the type of hole is conducive to smooth seed filling and the seed in the type of hole is not readily lost owing to vibration. The seed-metering devices adapt well to a vibrational environment, and the vibration factor has no discernible effect on the seed metering rate. The model holes (e.g., inverted fin-shaped holes) with the highest seed filling rate in the simulation test are employed in the bench test to validate the simulation model. The seed rate range was 300–3200 g/min, while the frequency of vibration was 0–10 Hz. Results indicated that the coefficient of variation of the stability of the total seeding rate was less than 1.3%, that the seeding rate of each row was consistent, and that the coefficient of variation was less than 3%, demonstrating that the simulation model was accurate and met the requirements of wheat agronomic seeding.

The seeding performance of a pneumatic seed-metering equipment for rapeseed has a significant bearing on the sowing effect. When the negative pressure falls abruptly, the pneumatic system experiences a significant loss of negative pressure. This will prevent rapeseed from being entirely absorbed by the seed plate, resulting in inconsistent seeding quantities along each row. In this study, CFD simulations were used to analyze the airflow field affecting the airflow transmission of an airflow distribution device. The essential structural characteristics of a conical cylinder conical-arranged kind of airflow distribution device were found, and the causes of negative pressure loss were analyzed from the standpoint of fluid kinematics. The optimal structural type of airflow distribution device was determined using fluid simulation. In addition, an orthogonal examination of the ideal type’s essential structural characteristics was conducted to minimize negative pressure loss during airflow transmission. Then, the influence of the negative pressure loss rate of the airflow distribution device on the variation coefficient of seeding quantity in each row of the seed-metering device was investigated using a bench test involving three factors: seed plate rotational speed, working negative pressure, and structure type. It was discovered that three parameters have highly substantial impacts on the negative pressure loss rate and the variation coefficient of seeding quantity in each row, and that the negative pressure loss rate correlates positively with the variation coefficient of the seeding quantity in each row. When negative pressure fell to 500 Pa, the negative pressure loss rate of the optimal structure type and the variation coefficient of seeding amount in each row of the seed-metering device fell by 6.25% and 3.45%, respectively. Field experiments reveal that the negative pressure loss rate of an airflow distribution device was below 20% and that the variation coefficient of seeding amount in each row of seed-metering devices was below 3.5%. The results can be used to analyze the construction of the pneumatic system and enhance the performance of the seed-metering equipment.

In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wheat centralized seed feeding device was taken as the research object, and the experimental factors were cone angle of type hole, working speed and seed filling gap. The working process of wheat centralized seed feeding device was simulated by discrete element method (DEM). The average seed number of type hole, the variation coefficient of the average seed number of type hole, and the maximum tangential force between seed and seed feeding mechanism were selected as the evaluation indexes. Through the variance analysis of the evaluation indexes by the experimental factors, the optimization objective function was constructed. Using PSO algorithm, the multi-objective optimization was carried out for the wheat centralized seed feeding device. The optimization results show that the best structural combination parameters of the wheat centralized seed feeding device are the hole cone angle of 31.6° and the seed filling gap of 4.6 mm. The validity of the method was verified by simulation and field test. The results show that the PSO algorithm multi-objective optimization method proposed in this paper can provide a reference for the structural improvement and optimal design of the centralized seed feeding device. Keywords: centralized seed feeding device, multi-objective, optimization, PSO algorithm DOI: 10.25165/j.ijabe.20201306.5665 Citation: Wang Q Q, Li Z D, Wang W W, Zhang C L, Chen L Q, Wan L. Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm. Int J Agric & Biol Eng, 2020; 13(6): 76–84.

Soil block distribution is one of the important indexes to evaluate the tillage performance of agricultural machinery. The traditional manual screening methods have the problems of low efficiency and damaging the original surface of the soil. This study proposes a statistical method of farmland soil block distribution based on deep learning. This method combines the adaptive learning rate and squeeze-and-excitation networks channel attention mechanism based on the original Mask-RCNN and uses the improved model to identify, segment and distribute statistics of the farmland soil blocks. Firstly, the influence of different learning rates and an improved Mask-RCNN algorithm model on training results were analyzed. Secondly, the effectiveness of the model in soil block identification and size measurement was analyzed. Finally, the identified soil blocks were classified accordingly, and the scale problem of soil block distribution after removing edge soil blocks was analyzed. The results show that with the decrease of learning rate, the loss value of model training decreases and the prediction accuracy of model is improved. The average precision value of the improved model increased by 25.29 %, and the recall value increased by 8.92%. The correlation coefficient of the maximum diameter measured by manual measurement and the maximum diameter measured by model algorithm was 0.99, which verifies the feasibility of the algorithm model. The prediction error of the model is the smallest when the camera height is 40 cm. Large-scale detection of soil block size in an experimental field in Hefei, Anhui, with an average confidence of over 97%. At the same time, the soil block is effectively classified according to the set classification standard. This study can provide an effective method for the accurate classification of soil block size and can provide a quantitative basis for the control of farmland cultivation intensity.