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1. A data-driven sensitivity analysis of maize stalk models reveals the dominant factors influencing stalk strength

   https://doi.org/10.1093/insilicoplants/diaf001  

   Carter, Joseph; Hall, Ryan; Cook, Douglas D (January 2025, in silico Plants)

   Zhu, Xin-Guang (Ed.)

   Abstract Morphological factors significantly impact maize stalk strength, but no study has fully characterized the impact of maize stalk shape on stalk strength. This study uses a data-driven and machine-learning modeling approach to characterize these relationships through a comprehensive sensitivity analysis of model inputs. Using 3D parameterized maize stalk models gave a higher level of control than previous studies by adding more parameters, but with the increase of the dimensionality. The large dimensionality of the models was greatly reduced via principal component analysis (PCA). Analysis revealed that model flexural stiffness, failure strength, and biomass were primarily determined by the first principal component. Material sensitivity analysis was also conducted on the models, and its results were consistent with past studies. The results of this study improve researchers’ understanding of the parameters that influence 3D parameterized maize stalk models. Statistical analysis indicates a strong relationship between the first principal component and section modulus, which further validates the 3D parameterized maize stalk model. Results also show that maize stalk morphology is primarily controlled by only one factor: the first principal component. This may limit researchers’ ability to increase stalk strength without increasing mass. 

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2. Measurement of maize stalk shear moduli

   https://doi.org/10.1186/s13007-024-01264-6  

   Carter, Joseph; Hoffman, Joshua; Fjeldsted, Braxton; Ogilvie, Grant; Cook, Douglas D (December 2024, Plant Methods)

   Maize is the most grown feed crop in the United States. Due to wind storms and other factors, 5% of maize falls over annually. The longitudinal shear modulus of maize stalk tissues is currently unreported and may have a signifi- cant influence on stalk failure. To better understand the causes of this phenomenon, maize stalk material properties need to be measured so that they can be used as material constants in computational models that provide detailed analysis of maize stalk failure. This study reports longitudinal shear modulus of maize stalk tissue through repeated tor- sion testing of dry and fully mature maize stalks. Measurements were focused on the two tissues found in maize stalks: the hard outer rind and the soft inner pith. Uncertainty analysis and comparison of multiple methodologies indicated that all measurements are subject to low error and bias. The results of this study will allow researchers to better under- stand maize stalk failure modes through computational modeling. This will allow researchers to prevent annual maize loss through later studies. This study also provides a methodology that could be used or adapted in the measurement of tissues from other plants such as sorghum, sugarcane, etc 

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3. Maize stalk stiffness and strength are primarily determined by morphological factors

   https://doi.org/10.1038/s41598-021-04114-w  

   Stubbs, Christopher J; Larson, R; Cook, Douglas D (January 2022, Scientific reports)

   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. 

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4. Unveiling the phenotypic landscape of stalk lodging resistance in diverse maize hybrids

   https://doi.org/10.1016/j.fcr.2023.109168  

   Kunduru, Bharath; Kumar, Rohit; Brar, Manwinder S; Stubbs, Christopher J; Tabaracci, Kaitlin; Bokros, Norbert T; Bridges, William C; Cook, Douglas D; DeBolt, Seth; McMahan, Christopher S; et al (December 2023, Field Crops Research)

   Context: Stalk lodging causes up to 43 % of yield losses in maize (Zea mays L.) worldwide, significantly worsening food and feed shortages. Stalk lodging resistance is a complex trait specified by several structural, material, and geometric phenotypes. However, the identity, relative contribution, and genetic tractability of these intermediate phenotypes remain unknown. Objective: The study is designed to identify and evaluate plant-, organ-, and tissue-level intermediate phenotypes associated with stalk lodging resistance following standardized phenotyping protocols and to understand the variation and genetic tractability of these intermediate phenotypes. Methods: We examined 16 diverse maize hybrids in two environments to identify and evaluate intermediate phenotypes associated with stalk flexural stiffness, a reliable indicator of stalk lodging resistance, at physiological maturity. Engineering-informed and machine learning models were employed to understand relationships among intermediate phenotypes and stalk flexural stiffness. Results: Stalk flexural stiffness showed significant genetic variation and high heritability (0.64) in the evaluated hybrids. Significant genetic variation and comparable heritability for the cross-sectional moment of inertia and Young’s modulus indicated that geometric and material properties are under tight genetic control and play a combinatorial role in determining stalk lodging resistance. Among the twelve internode-level traits measured on the bottom and the ear internode, most traits exhibited significant genetic variation among hybrids, moderate to high heritability, and considerable effect of genotype × environment interaction. The marginal statistical model based on structural engineering beam theory revealed that 74–80 % of the phenotypic variation for flexural stiffness was explained by accounting for the major diameter, minor diameter, and rind thickness of the stalks. The machine learning model explained a relatively modest proportion (58–62 %) of the variation for flexural stiffness. 

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5. A Parameterised Model of Maize Stem Cross-sectional Morphology

   Ottesen, Michael A; Larson, Ryan A.; Stubbs, Christopher J; Cook, Douglas D (April 2022, Biosystems engineering)

   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. 

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