Simulation and Experimental Study on the Optimization of Operating Parameters for Coating Pellets of Agropyron Seeds

In addressing the challenges of low pelletization qualification rates, poor uniformity between seeds and powder, and difficulties in optimizing equipment parameters for agropyron seed coating, this paper integrates numerical simulation with experimental verification to optimize the working parameters of pelletization coating. The study investigates the impact of vibration frequency, vibration direction, vibration amplitude, rotational speed, and inclination angle on seed-powder mixing uniformity and single-seed pellet qualification rates through both physical experiments and simulation tests. The study found that the coefficient of variation obtained through discrete element simulation can serve as a reliable surrogate indicator for evaluating pelletization coating quality, with its variation trend highly consistent with the single-seed pellet qualification rate observed in physical experiments. A secondary regression orthogonal design experiment used these indicators to establish a second-order regression equation, thereby performing single-objective optimization of the regression model. The results showed that the relative errors between simulation and physical test parameters were 1.24% for vibration frequency, 1.08% for coating pan rotational speed, and 0.17% for coating pan inclination angle. This demonstrates the high reliability of the coefficient of variation as a surrogate indicator for pellet qualification. With the optimized parameters, the qualification rate of single-seed pellets for agropyron seeds reached 95.3%, and the relative error between model predictions and physical tests was 1.7%. These findings validate the use of the second-order regression equation for predicting and analyzing single-seed pellet qualification rates and provide valuable insights for designing small-grain forage seed pelletization coating machines and optimizing coating parameters.

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Publication Details

Journal
Agriculture
Published
2025-09-26
DOI
https://doi.org/10.3390/agriculture15192017
Citations
1
Primary Topic
Seed Germination and Physiology
Type
article
Field-Weighted Citation Impact
1.75

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article

Simulation and Experimental Study on the Optimization of Operating Parameters for Coating Pellets of Agropyron Seeds

Aijun Tan, Yishuai Liu, Xuejie Ma, Haiyang Liu et al.
1 citations
Agriculture
Seed Germination and Physiology
1.75
article

Simulation and Experimental Study on the Optimization of Operating Parameters for Coating Pellets of Agropyron Seeds

Aijun Tan, Yishuai Liu, Xuejie Ma, Haiyang Liu, Liying Chen, Zhanfeng Hou
article en
1 citations

Abstract

In addressing the challenges of low pelletization qualification rates, poor uniformity between seeds and powder, and difficulties in optimizing equipment parameters for agropyron seed coating, this paper integrates numerical simulation with experimental verification to optimize the working parameters of pelletization coating. The study investigates the impact of vibration frequency, vibration direction, vibration amplitude, rotational speed, and inclination angle on seed-powder mixing uniformity and single-seed pellet qualification rates through both physical experiments and simulation tests. The study found that the coefficient of variation obtained through discrete element simulation can serve as a reliable surrogate indicator for evaluating pelletization coating quality, with its variation trend highly consistent with the single-seed pellet qualification rate observed in physical experiments. A secondary regression orthogonal design experiment used these indicators to establish a second-order regression equation, thereby performing single-objective optimization of the regression model. The results showed that the relative errors between simulation and physical test parameters were 1.24% for vibration frequency, 1.08% for coating pan rotational speed, and 0.17% for coating pan inclination angle. This demonstrates the high reliability of the coefficient of variation as a surrogate indicator for pellet qualification. With the optimized parameters, the qualification rate of single-seed pellets for agropyron seeds reached 95.3%, and the relative error between model predictions and physical tests was 1.7%. These findings validate the use of the second-order regression equation for predicting and analyzing single-seed pellet qualification rates and provide valuable insights for designing small-grain forage seed pelletization coating machines and optimizing coating parameters.

AgricultureVol. 15(19)
Inner Mongolia Agricultural University (CN)
Inner Mongolia Agricultural University, Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region
Openalex Percentile: Top 12%
Seed Germination and Physiology
1.75
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