The lack of accurate simulation model parameters in the optimization design process of variable fertilizer application devices has resulted in large errors between simulation and theoretical calculation results, which has restricted the development of variable fertilizer application devices to a certain extent. Additionally, there are few scholars studying urea granules, so many parameters of urea granular fertilizer cannot be directly obtained from the literature. The aim of this study is to calibrate a set of simulation parameters by combining physical and simulation tests. In this study, intrinsic parameters were systematically determined, including the particle size, particle density, elastic modulus, Poisson’s ratio and their static friction coefficients, rolling friction coefficients and restitution coefficients of urea particles. By performing the urea particle stacking test, the static friction coefficient between urea particles was calibrated to 0.27, and the rolling friction coefficient between particles was 0.11. To check the reliability of the calibration parameters, the simulation and physical tests of the repose angle and bulk density of urea particles were compared, and the results show that the relative error of repose angles and bulk density of urea particles was 0.78% and 1.19%, respectively. Through the simulation of the mechanical variable fertilizer discharger and the comparison test of the benchtop fertilizer discharging performance, the maximum relative error between the simulation and physical test fertilizer discharge is 3.69% when the working length of the outer sheave is 25 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 3.39% when the working length is 35 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 6.86% when the working length is 45 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 4.95% when the working length is 55 mm. The maximum relative error between the simulated and physical test fertilizer discharge was 6.86% at 45 mm opening and 4.95% at 55 mm opening, and the results show that the urea particle calibration parameters are reliable. The results of this study can provide a theoretical reference for the optimization design and simulation study of variable fertilizer application devices.

The rapid and accurate detection of soil nutrient content through spectral technology is one of the requisite technologies for precision fertilization, which, however, is an unsolved issue. In order to achieve this purpose, a more robust and accurate model is established in this study. The regression algorithm is integrated with effective wavelength selection to construct the prediction model for total nitrogen, available phosphorus, and available potassium (N, P, and K), which removes the need for complex pretreatment and algorithm constraints. According to the research results, with regard to the prediction of soil nitrogen, phosphorus, and potassium contents, the joint interval support vector regression (Si-SVR) model performed best in modeling, with the root mean square error of prediction (RMSEP) limited to 0.0231%, 1.0554%, and 3.4225%, respectively. In addition, the relative percentage deviation (RPD) values were restricted to 2.68, 2.12, and 2.37, respectively. As indicated by the prediction results obtained for the above three nutrient contents, the RPD values of the Si-SVR model prediction accuracy evaluation indicators exceeded 2.0, which evidences a high level of prediction accuracy. This method makes it possible for spectral data to be applied in practical production, and these results provide a valuable reference for the effective detection of major soil nutrients.

Based on a combination of physical and simulation experiments, a set of basic physical characteristic parameters and contact parameters suitable for granular fungal fertilizers were calibrated, which up to now have received little attention. The physical morphological characteristic parameters (overall dimension, 1000 grain weight, density, and moisture content), mechanical characteristic parameters (Poisson’s ratio, elastic modulus, and shear modulus), and contact parameters (static friction coefficient, rolling friction coefficient and recovery coefficient) of particles were measured through physical experiments. The parameters were screened for significance using the Plackett–Burman test. The results showed that the impact recovery coefficient, static friction coefficient, and rolling friction coefficient for the granular fungal fertilizer particles had a significant effect on the repose angle. The best range for the three parameters was determined using the steepest climbing test. The second-order regression model was optimized using the Box–Behnken design test. The relative error between the simulated repose angle (21.74°) and the physical test repose angle (21.84°) was small (0.50%). These optimal parameters obtained by calibration can provide a basis for the simulation analysis and parameter optimization of variable-rate fertilization systems.