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Parameters calibration and experimentation of a discrete element model for tomato stems

5 May 2026 · 10.21203/rs.3.rs-9042683/v1

Abstract

Abstract The effective optimization of tomato pruning robots was hindered by the lack of accurate simulation models for the shearing process of tomato stems and precise calibration and optimization methods for bonding parameters to predict shearing force. This paper proposed a simulation model along with a bonding parameter calibration method. Taking shearing force as the evaluation metric, a two-level factorial experiment was conducted to screen for significant parameters. A steepest ascent experiment was employed to determine the optimal range of these significant parameters. Then a Box-Behnken design was implemented, and the optimal combination of bonding parameters was derived based on the established regression model. Finally, comparative experiments were conducted to validate the simulation's shearing performance under this optimal parameter set. The results show that the optimal combination for the tomato stem model bonding parameters was a normal stiffness x 3 = 2.05×10⁸ N·m⁻³, tangential stiffness x₈=1.62×10⁸ N·m⁻³, and a bonding radius x₂₁=3.26×10⁻⁴ m. The optimized model reduced the shearing force simulation error by 75.8 and 43.7 percentage points compared to the traditional and pre-optimization models. These results demonstrate that the calibrated parameters of the simulation model are accurate and reliable. It can provide valuable parameters for optimizing the design of a tomato pruning robot.

Plant phenotyping relevance

トマト茎のせん断力を推定する離散要素シミュレーションモデルと結合パラメータ校正法を開発し、実験で性能検証しており、植物器官の測定・推定手法が中心である。

abstractThis paper proposed a simulation model along with a bonding parameter calibration method.
abstractFinally, comparative experiments were conducted to validate the simulation's shearing performance under this optimal parameter set.

Code and data availability

The paper reports tomato stem shear tests and DEM calibration but provides no public dataset, code, model, or image repository. Data availability states data can be obtained from the corresponding author, so any qualifying asset requires a request.

No evidence-backed public reproduction asset is currently recorded.

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