To determine the optimal fertilizer discharging performance, a spiral fertilizer applicator was designed according to orchard agricultural requirements. The influence of different parameter combinations of the spiral speed, blade diameter, and pitch on the coefficient of variation (CV) of the fertilizer discharge uniformity was predicted using a neural-network-based model by using the Box–Behnken design (BBD) test. According to the extracted results, the neural network model has a good prediction ability, with the determination coefficient of the model and the mean relative error reaching 0.99 and 2.29%, respectively. The impact of the fertilizer discharge parameter combinations on the discharging performances was examined from both macroscopic and microscopic perspectives. During the fertilizer discharge process, the openness formed between the spiral blades and fertilizer outlet presented periodic changes with the continuous rotation of the spiral blade, thus resulting in the uneven discharge of the fertilizer particles. In addition, there are interacting force chains among fertilizer particles, which are not broken in time during the fertilizer discharge procedure, thus resulting in uneven fertilizer discharge. With comprehensive consideration of the fertilizer discharge efficiency, the fertilizer discharge effect, and CV of the fertilizer discharge uniformity, the spiral parameter combination of the fertilizer discharge after neural network optimization are as follows: rotating speed of 47.6 rpm, blade diameter of 90 mm, pitch of 60 mm, and CV of fertilizer discharge uniformity of 19.05%. Under this optimal spiral parameter combination, the fertilizer discharge effect and discharge efficiency were considered to be relatively good. Our work provides references for the design optimization of the spiral fertilizer applicator and fertilizer discharge parameter combination.

To investigate the causes of flow fluctuations in a worm-type distributor during the fertilization process, this study employed the discrete element method to simulate the fertilization process. The analysis focused on the influences of force chain evolution on particle flow fluctuations and the effects of the rotational speed. The results indicate that the flow fluctuations in the worm-type distributor are not solely attributed to its helical structure but are closely associated with the evolution of force chains within the particle systems. Furthermore, a one-to-one correspondence between the flow fluctuations and force-chain evolution exists. The rotational speed was found to exert significant influences on the axial and circumferential distributions of the force chains. As the rotational speed increases, the coefficient of variation (CV) of the axial distribution of the force chains gradually decreases. Meanwhile, the uniformity index (UI) of the circumferential distribution of the force chains initially increases and then decreases. In the context of a worm-type distributor, the axial distribution of force chains emerges as the dominant influencing factor for flow fluctuations. For the specific worm-type distributor model chosen in this study, the minimum flow fluctuations were observed at a rotational speed of 80 rpm. These research findings offer valuable insights into understanding the flow fluctuations of worm-type distributors and provide references for further exploration in this field.

With the industrialization and standardization of Chinese cuisine, accurate discrete element simulation parameters are essential for analyzing the flow and conveying behavior of dishes. This study focused on standardized Kung Pao Chicken and employed the Hertz–Mindlin (JKR) model to develop a discrete element model suitable for cohesive, multi-component Chinese cuisine. The triaxial dimensions of diced chicken, peanuts, and scallions were measured to construct the model. Physical experiments were conducted to obtain basic parameters. The main parameters of the constitutive model were determined using a stepwise regression fitting method. For inter-material contact parameters that are difficult to measure directly, key model parameters were calibrated by fitting simulated repose angle results to experimental measurements. The calibrated parameters enabled high simulation accuracy, with repose angle errors below 0.05%, confirming the model’s reliability. This study provides a theoretical foundation for the simulation and design of automated conveying systems tailored to Chinese cuisine.