This study presents a methodology for a high-throughput digitization and quantification process of plant cell walls characterization, including the automated development of two-dimensional finite element models. Custom algorithms based on machine learning can also analyze the cellular microstructure for phenotypes such as cell size, cell wall curvature, and cell wall orientation. To demonstrate the utility of these models, a series of compound microscope images of both herbaceous and woody representatives were observed and processed. In addition, parametric analyses were performed on the resulting finite element models. Sensitivity analyses of the structural stiffness of the resulting tissue based on the cell wall elastic modulus and the cell wall thickness; demonstrated that the cell wall thickness has a three-fold larger impact of tissue stiffness than cell wall elastic modulus.
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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.more » « less
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The maize (Zea mays) stem is a biological structure that must balance both biotic and structural load bearing duties. These competing requirements are particularly relevant in the design of new bioenergy crops. Although increased stem digestibility is typically associated with a lower structural strength and higher propensity for lodging, with the right balance between structural and biological activities it may be possible to design crops that are high-yielding and have digestible biomass. This study investigates the hypothesis that geometric factors are much more influential in determining structural strength than tissue properties. To study these influences, both physical and in silico experiments were used. First, maize stems were tested in three-point bending. Specimen-specific finite element models were created based on x-ray computed tomography scans. Models were validated by comparison with experimental data. Sensitivity analyses were used to assess the influence of structural parameters such as geometric and material properties. As hypothesized, geometry was found to have a much stronger influence on structural stability than material properties. This information reinforces the notion that deficiencies in tissue strength could be offset by manipulation of stalk morphology, thus allowing the creation of stalks which are both resilient and digestible.more » « less
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Abstract Background Stalk lodging (breaking of agricultural plant stalks prior to harvest) is a multi-billion dollar a year problem. Stalk lodging occurs when high winds induce bending moments in the stalk which exceed the bending strength of the plant. Previous biomechanical models of plant stalks have investigated the effect of cross-sectional morphology on stalk lodging resistance (e.g., diameter and rind thickness). However, it is unclear if the location of stalk failure along the length of stem is determined by morphological or compositional factors. It is also unclear if the crops are structurally optimized, i.e., if the plants allocate structural biomass to create uniform and minimal bending stresses in the plant tissues. The purpose of this paper is twofold: (1) to investigate the relationship between bending stress and failure location of maize stalks, and (2) to investigate the potential of phenotyping for internode-level bending stresses to assess lodging resistance.
Results 868 maize specimens representing 16 maize hybrids were successfully tested in bending to failure. Internode morphology was measured, and bending stresses were calculated. It was found that bending stress is highly and positively associated with failure location. A user-friendly computational tool is presented to help plant breeders in phenotyping for internode-level bending stress. Phenotyping for internode-level bending stresses could potentially be used to breed for more biomechanically optimal stalks that are resistant to stalk lodging.
Conclusions Internode-level bending stress plays a potentially critical role in the structural integrity of plant stems. Equations and tools provided herein enable researchers to account for this phenotype, which has the potential to increase the bending strength of plants without increasing overall structural biomass.
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Abstract Background Stalk lodging (mechanical failure of plant stems during windstorms) leads to global yield losses in cereal crops estimated to range from 5% to 25% annually. The cross-sectional morphology of plant stalks is a key determinant of stalk lodging resistance. However, previously developed techniques for quantifying cross-sectional morphology of plant stalks are relatively low-throughput, expensive and often require specialized equipment and expertise. There is need for a simple and cost-effective technique to quantify plant traits related to stalk lodging resistance in a high-throughput manner.
Results A new phenotyping methodology was developed and applied to a range of plant samples including, maize (
Zea mays ), sorghum (Sorghum bicolor ), wheat (Triticum aestivum ), poison hemlock (Conium maculatum ), and Arabidopsis (Arabis thaliana). The major diameter, minor diameter, rind thickness and number of vascular bundles were quantified for each of these plant types. Linear correlation analyses demonstrated strong agreement between the newly developed method and more time-consuming manual techniques (R2 > 0.9). In addition, the new method was used to generate several specimen-specific finite element models of plant stalks. All the models compiled without issue and were successfully imported into finite element software for analysis. All the models demonstrated reasonable and stable solutions when subjected to realistic applied loads.Conclusions A rapid, low-cost, and user-friendly phenotyping methodology was developed to quantify two-dimensional plant cross-sections. The methodology offers reduced sample preparation time and cost as compared to previously developed techniques. The new methodology employs a stereoscope and a semi-automated image processing algorithm. The algorithm can be used to produce specimen-specific, dimensionally accurate computational models (including finite element models) of plant stalks.
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