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Stalk lodging in the monocot Zea mays is an important agricultural issue that requires the development of a genome-to-phenome framework, mechanistically linking intermediate and high-level phenotypes. As part of that effort, tools are needed to enable better mechanistic understanding of the microstructure in herbaceous plants. A method was therefore developed to create finite element models using CT scan data for Zea mays. This method represents a pipeline for processing the image stacks and developing the finite element models. 2-dimensional finite element models, 3-dimensional watertight models, and 3-dimensional voxel-based finite element models were developed. The finite element models contain both the cell and cell wall structures that can be tested in silico for phenotypes such as structural stiffness and predicted tissue strength. This approach was shown to be successful, and a number of example analyses were presented to demonstrate its usefulness and versatility. This pipeline is important for two reasons: (1) it helps inform which microstructure phenotypes should be investigated to breed for more lodging-resistant stalks, and (2) represents an essential step in the development of a mechanistic hierarchical framework for the genome-to-phenome modeling of herbaceous plant stalk lodging. 

Abstract Stalk lodging destroys between 5 and 25% of grain crops annually. Developing crop varieties with improved lodging resistance will reduce the yield gap. Field-phenotyping equipment is critical to develop lodging resistant crop varieties, but current equipment is hindered by measurement error. Relatively little research has been done to identify and rectify sources of measurement error in biomechanical phenotyping platforms. This study specifically investigated sources of error in bending stiffness and bending strength measurements of maize stalks acquired using an in-field phenotyping platform known as the DARLING. Three specific sources of error in bending stiffness and bending strength measurements were evaluated: horizontal device placement, vertical device placement and incorrect recordings of load cell height. Incorrect load cell heights introduced errors as large as 130% in bending stiffness and 50% in bending strength. Results indicated that errors on the order of 15–25% in bending stiffness and 1–10% in bending strength are common in field-based measurements. Improving the design of phenotyping devices and associated operating procedures can mitigate this error. Reducing measurement error in field-phenotyping equipment is crucial for advancing the development of improved, lodging-resistant crop varieties. Findings have important implications for reducing the yield gap. 

This study sought to better understand how time of day (ToD) or turgor pressure might affect the flexural stiffness of sweet sorghum stalks and potentially regulate stalk lodging resistance. Stalk flexural stiffness measured across a 48 h period in 2019 showed a significant diurnal association with leaf water potential and stalk flexural stiffness. While the correlation between stalk flexural stiffness and this proxy for internal turgor status was statistically significant, it only accounted for roughly 2% of the overall variance in stiffness. Given that turgor status is a dynamic rather than fixed physiological variable like the cellular structure, these data suggest that internal turgor plays a small yet significant role in influencing the flexural stiffness of fully mature stalks prior to a stalk lodging event. The association was assessed at earlier developmental stages across three distinct cultivars and found not to be significant. Panicle weight and stalk basal weight, but not stalk Brix or water content, were found to be better predictors of stalk flexural stiffness than either ToD or turgor status. Observation across three cultivars and four distinct developmental stages ranging from the vegetative to the hard-dough stages suggests that stalk flexural stiffness changes significantly as a function of time. However, neither ToD nor turgor status appear to meaningfully contribute to observed variations in stalk flexural stiffness in either individual stalks or across larger populations. As turgor status was not found to meaningfully influence stalk strength or flexural stiffness at any developmental time point examined in any of the three sweet sorghum cultivars under study, turgor pressure likely offers only inconsequential contributions to the biomechanics underlying sweet sorghum stalk lodging resistance. 

Stalk lodging (structural failure crops prior to harvest) significantly reduces annual yields of vital grain crops. The lack of standardized, high throughput phenotyping methods capable of quantifying biomechanical plant traits prevents comprehensive understanding of the genetic architecture of stalk lodging resistance. A phenotyping pipeline developed to enable higher throughput biomechanical measurements of plant traits related to stalk lodging is presented. The methods were developed using principles from the fields of engineering mechanics and metrology and they enable retention of plant-specific data instead of averaging data across plots as is typical in most phenotyping studies. This pipeline was specifically designed to be implemented in large experimental studies and has been used to phenotype over 40,000 maize stalks. The pipeline includes both lab- and field-based phenotyping methodologies and enables the collection of metadata. Best practices learned by implementing this pipeline over the past three years are presented. The specific instruments (including model numbers and manufacturers) that work well for these methods are presented, however comparable instruments may be used in conjunction with these methods as seen fit. • Efficient methods to measure biomechanical traits and record metadata related to stalk lodging. • Can be used in studies with large sample sizes (i.e., > 1,000). 

Non-hydrostatic high pressure X-ray diffraction is used to study the hardness of superhard ReB₂nanocrystals. All nanocrystals show less plastic deformation under load than bulk ReB₂, with the smallest nanocrystals showing the most enhancement. 

Proton radiography is a promising development in proton therapy, and researchers are currently exploring optimal detector materials to construct proton radiography detector arrays. High-density glass scintillators may improve integrating-mode proton radiography detectors by increasing spatial resolution and decreasing detector thickness. We evaluated several new scintillators, activated with europium or terbium, with proton response measurements and Monte Carlo simulations, characterizing relative luminosity, ionization quenching, and proton radiograph spatial resolution. We applied a correction based on Birks’s analytical model for ionization quenching. The data demonstrate increased relative luminosity with increased activation element concentration, and higher relative luminosity for samples activated with europium. An increased glass density enables more compact detector geometries and higher spatial resolution. These findings suggest that a tungsten and gadolinium oxide-based glass activated with 4% europium is an ideal scintillator for testing in a full-size proton radiography detector. 

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. 

Abstract 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. 

Nuclear reactions play a crucial role in determining the nucleosynthesis that occurs in astrophysical events. The rates of many reactions that significantly impact certain nucleosynthesis processes can not be currently measured via direct means. These reactions must be constrained in another manner, such as determining the level energies and other structure properties of the compound nuclei. In order to measure level energies of nuclei relevant to nuclear astrophysics, the Enge split-pole spectrograph has been installed and commissioned at the University of Notre Dame’s Nuclear Science Laboratory. The first scientific measurement has also been performed. Structure properties of⁵⁸Cu were measured via the reaction⁵⁸Ni(³He,t)⁵⁸Cu to provide the first experimental constraint of the⁵⁷Ni(p,γ)⁵⁸Cu reaction rate, which impacts the production of of⁴⁴Ti,⁵⁷Fe, and⁵⁹Ni in core-collapse supernovae. Preliminary analysis of this measurement confirms the level energies of states in⁵⁸Cu that could lead to significant resonances in the⁵⁷Ni(p,γ)⁵⁸Cu reaction rate, while suggesting the presence of additional states that have not been previously observed but could also lead to significant resonances.