Geometric Evaluation and Optimization of Maize Leaf Morphology and Canopy Architecture

Maize leaf and canopy are the primary media to interact with environmental factors, including light interception, water evaporation, wind fluctuation, etc. Leaf morphology and canopy architecture affect the interaction process and activity significantly. Maize canopy architecture, a critical determinant of light capture and photosynthetic efficiency, is influenced by complex interactions between leaf morphology and arrangement. This study aimed to explore the relationships between key leaf morphological traits (midrib shape, blade contour, undulations) and canopy architecture in maize, and to identify optimal leaf morphologies for light interception. We employed correlation analysis and stepwise Bayesian optimization to quantify the relationships between leaf traits and to identify optimal leaf morphologies for maximizing leaf area and minimizing self-shading. Our results revealed that midrib shape and leaf width distribution positively influence leaf area, while undulation has a bidirectional effect depending on its orientation. Optimization results showed that optimal canopies feature upright top leaves, intermediately erect middle leaves, and relatively flat bottom leaves. This study provides a quantitative framework for understanding and predicting optimal canopy structure in maize, which can inform breeding strategies aimed at improving light utilization and yield potential.