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At present, potato seeders in China generally have poor uniformity of seed rows and high coefficients of variation in plant spacing during seed rows, causing difficulties for subsequent mechanized plant protection and harvesting. Based on the effect of seed discharge to analyze the sowing process, a potato seed discharger with a double-layer seed picking spoon structure was designed. By analyzing the seed discharging mechanism and its operation process, the shape and size structural parameters of the seed picking spoon were determined. Finite element simulation of the seed pickup process and seed carrying process of the seed discharging mechanism was carried out by EDEM software to determine the double-layer seed scoop scheme and the range of factors for subsequent tests. A two-factor test was conducted with seeding line speed and seed drop height as test factors, and plant spacing coefficient of variation and seed potato lateral offset dispersion as test indexes. The test results showed that the double-layer seeding spoon chain seeder reduced the coefficient of variation in plant spacing by 5.8%, and the dispersion in lateral offset by 5.5 mm, compared with the single seeding spoon seeder, when the seeding speed was 0.184 m/s and the height of falling seed was 9 cm. [ABSTRACT FROM AUTHOR]

The discrete element computer simulation method is an effective tool that enables the study of the interaction mechanism between the pulping components and the paddy soil during the paddy field pulping process. The findings are valuable in optimizing the parameters of the paddy beating device to improve its working quality and efficiency. However, the lack of accurate soil models for paddy soil has limited the application and development of the discrete element method in paddy pulping research. This study selected the Hertz-Mindlin with Johnson-Kendall-Roberts discrete element model for the pre-pulping paddy loam soil and used the slump error as the test index to select nine parameters, including soil Poisson's ratio and surface energy, as test factors to calibrate the model parameters. The Plackett-Burman test identified soil shear modulus, surface energy, and soil-iron plate static friction coefficient as significant factors affecting the test index. The steepest ascent test results determined the test range of the above parameters. The Box-Behnken test obtained the regression model between the significant factors and the test index, and the regression model was optimized using the slump error as the target. The optimal combination of parameters was surface energy of 3.257 J/m2, soil shear modulus of 0.709 MPa, and static friction coefficient between soil and iron plate of 0.701. The slump simulation test using this combination of parameters yielded an average slump error of 2.04%. The collective results indicate the accuracy of the calibrated discrete element simulation parameters for paddy loam soil. These parameters can be used for discrete element simulation analysis of the paddy pulping process after paddy field soaking. [ABSTRACT FROM AUTHOR]

At present, the measurement of tillage depth is mainly based on manual measurement, but the manual raking method results in low measurement accuracy and high labor intensity. Due to the complexity of soil, theoretical research on tillage depth is relatively scarce. In order to provide a new research direction and research idea for soil stratification, topsoil was taken as the research object of this paper. The correlation between penetration resistance and penetration depth of a probe in a cultivated soil was studied, and a mathematical model was established. There is a certain similarity between the process of spherical cavity expansion and the process of probe penetration, so we introduced the theory of spherical cavity expansion into the modeling of penetration resistance of the cultivated soil. In this paper, the spherical cavity expansion theory of unsaturated soil was used as the basis for solving the penetration resistance. And the unified strength criterion was employed as a yield condition of the soil to set a stress solution and a displacement solutionin into of the probe penetrating into the elasto-plastic zone of the cultivated soil to determine the model of expansion force. We have carried out indoor tests to revise the expansion force model. Firstly, according to the range of soil density and water content in the field, the soil densities were classified into 1.1×103kg/m3, 1.2×103kg/m3 and 1.3×103kg/m3, and the water contents were divided into 10%, 15% and 20%. In addition, the orthogonal tests were performed at different levels. The soil was put into the barrel, and the probe was inserted into the soil in the barrel at the speed of 8mm/s to determine the test values of the change of the probe penetration resistance with depth. Finally, the expansion force model was fitted with the results of the indoor test, and coefficient B was introduced to express the influence degree of density and water content on the resistance. Coefficient B was substituted into the expansion force model to obtain the penetration resistance model of the cultivated soil. Through the goodness of fit analysis of the penetration resistance model, the results show that the overall average goodness of fit of the penetration resistance modelat was up to 0.871 at different water contents and densities, which was a good fit and could present novel insights into the study relating to soil stratification theory. [ABSTRACT FROM AUTHOR]

Objective: To improve the accuracy of parameters used in discrete element simulation test of Chinese cabbage seeds harvesting process. Methods: Firstly, the key physical parameters of Chinese cabbage seeds were measured. According to the results, the discrete element simulation model was established and the value range of simulation test parameters was determined. Then, the actual repose angle of Chinese cabbage seeds was obtained by physical accumulation test using bottomless conical cylinder lifting method. Plackett-Burman test, steepest climb test, Box-Behnken test and parameter optimization test were carried out in sequence with the actual angle of repose as the response value. Finally, the obtained parameters are verified. Results: 1. The Plackett-Burman test showed that the seed-seed rolling friction coefficient, the seed-steel rolling friction coefficient, the seed-seed static friction coefficient, and the seed-steel static friction coefficient had significant effects on the repose angle of Chinese cabbage seeds (P<0.05). 2. The optimization test showed that the seed-seed rolling friction coefficient was 0.08, the seed-steel rolling friction coefficient was 0.109, the seed-seed static friction coefficient was 0.496, and the seed-steel static friction coefficient was 0.415. 3. The validation test showed that the repose angle of Chinese cabbage seeds under such parameter was 23.62°, and the error with the repose angle of the physical test was 0.73%. Conclusion: The study show that the discrete element simulation parameters of Chinese cabbage seeds model and calibration are reliable, which can provide reference for the discrete element simulation of Chinese cabbage seeds. [ABSTRACT FROM AUTHOR]

Objective: To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm. Methods: Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations. GA can obtain better initial network weights and thresholds and find the optimal individual through selection, crossover, and mutation operations; that is, the optimal initial weight of the Back Propagation (BP) neural network. Field experiments verify the seeding performance of the precision corn planter and the accuracy of the seeding monitoring system. Results: 1. The deviation between the average value of the six precision positioning seeding experiments of corn under the random disturbance signal and the ideal value of the distance is less than or equal to 0.5 cm; the deviation between the average value of the six precision positioning seeding experiments of corn under the sine wave disturbance signal (1 Hz) is less than or equal to 0.4 cm; the qualified rate of grain distance reaches 100%. 2. The precision control index, replay index, and missed index of the designed corn precision seeding intelligent control system have all reached the national standard. During the operation of the seeder, an alarm of the seeder leaking occurred, and the buzzer sounded and the screen displayed 100 times each; therefore, the reliability of the alarm system is 100%. Conclusion: The intelligent corn seeder designed based on precision positioning seeding technology can reduce the seeding rate of the seeder and ensure the stability of the seed spacing effectively. Based on the machine vision and GABP algorithm, the seeding effect detection system can provide a reference for the further realization of precision seeding operations. [ABSTRACT FROM AUTHOR]