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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 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. 

High-magnitude storm events such as Hurricane Sandy are powerful agents of geomorphic change in coastal marshes, potentially altering their surface elevation trajectories. But how do a storm’s impacts vary across a large region spanning a variety of wetland settings and storm exposures and intensities.We determined the short-term impacts of Hurricane Sandy at 223 surface elevation table–marker horizon stations in estuarine marshes located across the northeast region of the United States by comparing poststorm surface elevation change with pre-storm elevation trends.We hypothesized that the storm’s effect on marsh elevation trends would be influenced by position relative to landfall (right or left) and distance from landfall. The structural equation model presented predicts that marshes located to the left of landfall were more likely to experience an elevation gain greater than expected, and this positive deviation from pre-storm elevation trends tended to have a greater magnitude than those experiencing negative deviations (elevation loss), potentially due to greater sediment deposition. The magnitude of negative deviations from elevation change in marshes to the right of landfall was greater than for positive deviations, with a greater effect in marshes within 200 km of landfall, potentially from the extent and magnitude of storm surge. Overall, results provide an integrated picture of how storm characteristics combined with the local wetland setting are important to a storm’s impact on surface elevation, and that the surface elevation response can vary widely among sites across a region impacted by the same storm.