Computational models of maize cellular microstructure for stalk lodging resistance
Parametric computational models that link cellular microstructure to tissue flexural rigidity and strength in maize stems. Supports improved phenotyping for stalk lodging resistance, a major yield-limiting trait in maize and other crops.
Overview
Stalk lodging, the bending or breaking of crop stems, reduces agronomic yields in maize and other vital crops. Because the stalk lodging phenotype is complex and spans multiple scales, selective breeding efforts to reduce it are difficult. This research applies computational tools of cellular microstructure to connect sub-tissue features with tissue-level and plant-level mechanical behavior. The goal is to generate understanding that leads directly to improved stalk lodging resistance phenotyping methods and breeding techniques.
Technical specifications
Research approach:
- Parametric computational models of cell shape, size, and orientation paired with traditional materials science experiments
- Micro-CT scanning of maize internode and meristem sections using a SkyScan 1272 at a resolution of 4.3 micrometers per voxel for cellular microstructure
- Three-dimensional continuum models of cellular microstructure developed and analyzed using Abaqus/CAE
- Three-point bending tests on B73 x Mo17 Zea maize hybrids to measure flexural rigidity
- Gaussian process models used to quantify the parameter space and model uncertainty
Multi-scale modeling framework:
- Plant-level models linking flexural stiffness with stalk lodging
- Organ-level models linking tissue-level properties with plant-level flexural stiffness
- Tissue-level models linking cellular microstructure phenotypes with tissue stiffness and strength
Technology readiness level
Preliminary laboratory research has demonstrated that cellular microstructure plays a significant role in tissue stiffness and strength. The investigator has previously developed plant-level and organ-level models linking structural phenotypes to stalk lodging resistance. The proposed work represents the next step in a top-to-bottom framework connecting intermediate- and high-level phenotypes. Future validation will use B73 x Mo17 maize hybrids with three-point bending tests combined with micro-CT imaging and parametric Abaqus/CAE simulations to investigate the effect of cellular microstructural phenotypes on tissue mechanical properties.
About Fairleigh Dickinson University
Fairleigh Dickinson University is a private, comprehensive university based in northern New Jersey, with two campuses near New York City and additional locations in Vancouver and Wroxton. Its position in the New York–New Jersey metro places faculty and students near major corporate hubs, and FDU Health integrates programs and partnerships that enable clinical training and practice-based collaboration. Structured work‑integrated learning, including co‑op options and internships, creates predictable talent pipelines, while new simulation facilities support hands‑on engagement. Research activity is supported by competitive federal and state funding, including programs from NIH, NSF, and HHS. A central Office of Grants & Sponsored Projects assists with agreements, compliance, and industry contracting.
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