Photosynthetic and Canopy Trait Characterization in Soybean (Glycine max L.) Using Chlorophyll Fluorescence and UAV Imaging

Photosynthesis (PS) is the cornerstone of crop productivity, directly influencing yield potential. Photosynthesis remains an underexploited target in soybean breeding, partly because field-based photosynthetic traits are difficult to measure at scale. Also, it is unclear which reproductive stage(s) provide the most informative physiological signals for yield. Few studies have evaluated soybean PS in elite germplasm under field conditions, and the integration of chlorophyll fluorescence (CF) with UAV imaging for PS traits remains largely unexplored. This study evaluated genotypic variation in photosynthetic and canopy traits among elite soybean germplasm across environments and developmental stages using CF and UAV imaging. Linear mixed-model analysis revealed significant genotypic and G×E effects for yield, canopy and several photosynthetic parameters. Broad-sense heritability (H2) estimates indicated dynamic genetic control, ranging from 0.12 to 0.77 at the early stage (S1) and 0.20–0.81 at the mid-reproductive stage (S2). Phi2, SPAD and FvP/FmP exhibited the highest heritability, suggesting their potential as stable selection targets. Correlation analyses showed that while FvP/FmP and SPAD were modestly associated with yield at S1, stronger positive relationships with Phi2, PAR and FvP/FmP emerged during S2, underscoring the importance of sustained photosynthetic efficiency during pod formation. Principal component analysis identified photosynthetic efficiency and leaf structural traits as key axes of physiological variation. UAV-derived indices such as NDRE, MTCI, SARE, MExG and CIRE were significantly correlated with CF-based traits and yield, highlighting their utility as high-throughput proxies for canopy performance. These findings demonstrate the potential of integrating CF and UAV phenotyping to enhance physiological selection and yield improvement in soybean breeding.