A parameterised model of maize stem cross-sectional morphology. (June 2022) - Ottesen, Michael A.; Larson, Ryan A.; Stubbs, Christopher J.; Cook, Douglas D.
Abstract : 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. Highlights: The maize stalk geometry was decomposed to create a parameterised model. The parameterised model allows control over geometric shape and fidelity. The maize stalk was shown to be well-approximated by an ellipse. This method can be used to control the shape of the maize stalk in future models.