Background: Stalk lodging (breaking of agricultural plant stalks prior to harvest) results in millions of dollars in lost revenue each year. Despite a growing body of literature on the topic of stalk lodging, the structural efficiency of maize stalks has not been investigated previously. In this study, we investigate the morphology of mature maize stalks to determine if rind tissues, which are the major load bearing component of corn stalks, are efficiently organized to withstand wind induced bending stresses that cause stalk lodging. Results: 945 fully mature, dried commercial hybrid maize stem specimens (48 hybrids, ~ 2 replicates, ~ 10 samples per plot) were subjected to: (1) three-point-bending tests to measure their bending strength and (2) rind penetration tests to measure the cross-sectional morphology at each internode. The data were analyzed through an engineering optimization algorithm to determine the structural efficiency of the specimens. Conclusions: Hybrids with higher average bending strengths were found to allocate rind tissue more efficiently than weaker hybrids. However, even strong hybrids were structurally suboptimal. There remains significant room for improving the structural efficiency of maize stalks. Results also indicated that stalks are morphologically organized to resist wind loading that occurs primarily above the ear. Results are applicable to selective breeding and crop management studies seeking to reduce stalk lodging rates.

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.

The maize (Zea mays) stem is a biological structure that must both balance biotic and structural load bearing duties. These competing requirements are particularly relevant in the design of new bioenergy crops. With the right balance between structural and biological activities, it may be possible to design crops that are high-yielding and have digestible biomass. But increased stem digestibility is typically associated with a lower structural strength and higher propensity for lodging. 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 in vitro data. 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 with are both resilient and digestible. Highlight: This study utilized physical and in silico experiments to confirm that geometric parameters are far more influential in determining stalk strength than mechanical tissue stiffnesses.

Stalk lodging (breaking of agricultural plant stalks prior to harvest) results in millions of dollars in lost revenue each year. Despite a growing body of literature on the topic of stalk lodging, the structural efficiency of maize stalks has not been investigated previously. In this study, we investigate the morphology of mature maize stalks to determine if rind tissues, which are the major load bearing component of corn stalks, are efficiently organized to withstand wind induced bending stresses that cause stalk lodging.945 fully mature, dried commercial hybrid maize stem specimens (48 hybrids, ∼2 replicates, ∼10 samples per plot) were subjected to: (1) three-point-bending tests to measure their bending strength and (2) rind penetration tests to measure the cross-sectional morphology at each internode. The data were analyzed through an engineering optimization algorithm to determine the structural efficiency of the specimens.Hybrids with higher average bending strengths were found to allocate rind tissue more efficiently than weaker hybrids. However, even strong hybrids were structurally suboptimal. There remains significant room for improving the structural efficiency of maize stalks. Results also indicated that stalks are morphologically organized to resist wind loading that occurs primarily above the ear. Results are applicable to selective breeding and crop management studies seeking to reduce stalk lodging rates.Highlight: Maize stem morphology was investigated through an optimization algorithm to determine how efficiently their structural tissues are allocated to withstand wind induced bending stresses that cause stalk lodging.

Breeding for stalk lodging resistance is of paramount importance to maintain and improve maize yield and quality and meet increasing food demand. The integration of environmental, phenotypic, and genotypic information offers the opportunity to develop genomic prediction strategies that can improve the genetic gain for complex traits such as stalk lodging. However, implementation of genomic predictions for stalk lodging resistance has been sparse primarily due to the lack of reliable and reproducible phenotyping strategies. In this study, we measured 10 traits related to stalk lodging resistance obtained from a novel phenotyping platform on approximately 31,000 individual stalks. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of different single and multi-environment genomic prediction models. In total, 555 maize inbred lines from the Wisconsin diversity panel were evaluated in four environments. The multi-environment models more than doubled the prediction accuracy compared to the single-environment model for most traits, particularly when predicting lines in a sparse testing design. Predictive correlations for stalk bending strength and stalk flexural stiffness, a non-destructive method for assessment of stalk lodging resistance, were moderately high and ranged between 0.32 to 0.89 and 0.26 to 0.88, respectively. In contrast, rind thickness was the most difficult trait to predict. Our results show that the use of multi-environmental data could improve genomic prediction accuracy for stalk lodging resistance and its intermediate phenotypes. This study will serve as a first step toward genetic improvement and the development of maize varieties resistant to stalk lodging. Core Ideas The DARLING platform was successfully used to collect lodging resistance-related phenotypes Proportion of variation explained by genotype by environment interaction was not negligible Genomic predictions for lodging resistance phenotypes ranged from moderate to high Accounting for genotype by environment interaction was found to be important for improved predictive performance Plain language summary Stalk lodging - when maize stalks break or fall over before harvest - can seriously reduce crop yields. Breeding maize that resists lodging is important to ensure reliable food production. We tested about 31,000 individual stalks for 10 traits related to lodging resistance using a new phenotyping system. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of single and multi-environment genomic prediction models. By analyzing 555 maize lines, we found that using data from multiple environments improved genomic prediction accuracy by more than twice as much as using data from a single environment. Traits such as bending strength and flexural stiffness were easier to predict, while rind thickness was more difficult. These results show that combining genetic, environmental, and phenotypic data can help breeders more accurately select maize plants with stronger stalks, leading to better, more resilient crops.

Background: Stalk lodging (breaking of agricultural plant stalks prior to harvest) is a multi-billion dollar a year problem. Stalk lodging occurs when bending moments induced by a combination of external loading (e.g. wind) and self-loading (e.g. the plant’s own weight) exceed the bending strength of plant stems. Previous biomechanical plant stem models have investigated both external loading and self-loading of plants, but have evaluated them as separate and independent phenomena. However, these two types of loading are highly interconnected and mutually dependent. The purpose of this paper is twofold: (1) to investigate the combined effect of external loads and plant weight on the displacement and stress state of plant stems / stalks, and (2) to provide a generalized framework for accounting for self-weight during mechanical phenotyping experiments used to predict stalk lodging resistance. Results: A method of properly accounting for the interconnected relationship between self-loading and external loading of plants stems is presented. The interconnected set of equations are used to produce user-friendly applications by presenting (1) simplified self-loading correction factors for a number of common external loading configurations of plants, and (2) a generalized Microsoft Excel framework that calculates the influence of self-loading on crop stems. The effect of self-loading on the structural integrity of wheat is examined in detail. A survey of several other plants is conducted and the influence of self-loading on their structural integrity is also presented. Conclusions: The self-loading of plants plays a potentially critical role on the structural integrity of plant stems. Equations and tools provided herein enable researchers to account for the plant’s weight when investigating the flexural rigidity and bending strength of plant stems.