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Abstract Maize stalk lodging is the structural failure of the stalk prior to harvest and is a major problem for maize (corn) producers and plant breeders. To address this problem, it is critical to understand precisely how geometric and material parameters of the maize stalk influence stalk strength. Computational models could be a powerful tool in such investigations, but current methods of creating computational models are costly, time-consuming and, most importantly, do not provide parameterized control of the maize stalk parameters. The purpose of this study was to develop and validate a parameterized 3D model of the maize stalk. The parameterized model provides independent control over all aspects of the maize stalk geometry and material properties. The model accurately captures the shape of actual maize stalks and is predictive of maize stalk stiffness and strength. The model was validated using stochastic sampling of material properties to account for uncertainty in the values and influence of mechanical tissue properties. Results indicated that buckling is influenced by material properties to a greater extent that flexural stiffness. Finally, we demonstrate that this model can be used to create an unlimited number of synthetic stalks from within the parameter space. This model will enable the future implementation of parameter sweep studies, sensitivity analysis and optimization studies, and can be used to create computational models of maize stalks with any desired combination of geometric and material properties. 

Stalk lodging, or failure of the stalk structure, is a serious problem in the production of maize (corn). Addressing this problem requires an understanding of the parameters that influence lodging resistance. Computational modelling is a powerful tool for this purpose, but current modelling methods have limited throughput and do not provide the ability to modify individual geometric features. A parameterised model of the maize stalk has the potential to overcome these limitations. The purposes of this study were to (a) develop a parameterised model of the maize stalk cross-section that could accurately simulate the physical response of multiple loading cases, and (b) use this model to rigorously investigate the relationships between cross-sectional morphology and predictive model accuracy. Principal component analysis was utilised to reveal underlying geometric patterns which were used as parameters in a cross-sectional model. A series of approximated cross-sections was created that represented various levels of geometric fidelity. The true and approximated cross-sections were modelled in axial tension/compression, bending, transverse compression, and torsion. For each loading case, the predictive accuracy of each approximated model was calculated. A sensitivity study was also performed to quantify the influence of individual parameters. The simplest model, an elliptical cross-section consisting of just three parameters: major diameter, minor diameter, and rind thickness, accurately predicted the structural stiffness of all four loading cases. The modelling approach used in this study model can be used to parameterise the maize cross-section to any desired level of geometric fidelity, and could be applied to other plant species.