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Modeling and validation of coupled air–water–mud structure interactions on rice seedlings under mechanical weeding disturbance

Computers and Electronics in Agriculture. · 1 Feb 2026

Abstract

Flow disturbances induced by mechanical weeding significantly affect the mechanical behavior of rice seedlings, posing a critical challenge to the mechanization of paddy field operations. To elucidate the mechanisms by which weeding blades affect the mechanical properties of rice seedlings, we developed a coupled CFD model integrating air–water–mud three-phase flow with the flexible structure of rice seedlings. The model accounts for both hydrodynamic forces and the biomechanical properties of seedlings, enabling accurate prediction of deflection, displacement, and stress responses under blade-induced disturbance. Validation experiments, including seedling deflection under steady flow and field measurements of flow fields around operating blades, demonstrated that the model’s predictions deviate from measured data by less than 10 %, confirming its accuracy and robustness. The results indicate that, during operation, maximum seedling stress reached 8.37 MPa, and maximum intra-row displacement was 53.34 mm (≈ 20 % of seedling height) at 10 days after transplanting, decreasing by 29.9 % by 30 days as stiffness increased. Stress concentration occurred primarily at the seedling base and near the water–air interface, indicating critical regions for structural failure. These findings provide new mechanistic insight into the coupled dynamics of seedlings, fluid, and weeding blades, establishing a quantitative foundation for optimizing blade spacing, rotational speed, and working depth to minimize seedling damage during mechanical weeding.

Plant phenotyping relevance

イネ苗の変位・たわみ・応力という植物状態を推定する連成CFDモデルを開発し、実測値で検証しており、植物表現型の取得・推定手法が研究の中心である。

abstractwe developed a coupled CFD model integrating air–water–mud three-phase flow with the flexible structure of rice seedlings
abstractValidation experiments, including seedling deflection under steady flow and field measurements of flow fields around operating blades, demonstrated that the model’s predictions deviate from measured data by less than 10 %
abstractenabling accurate prediction of deflection, displacement, and stress responses under blade-induced disturbance

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