Nitrogen fertilization produces divergent effects on canopy structure between indica and japonica rice reflected in leaf to panicle ratio based on deep learning

High throughput plant phenomics enables precise quantification of structural information for the complex crop canopy. Leaf to panicle ratio (LPR) in terms of light interception is a physiological trait we formerly developed to clarify the light distribution pattern within the canopy of japonica rice. Here, using the methodology of deep learning neural network (Transformer Feature Pyramid Network), we proposed a general method for LPR calculation for both japonica and indica rice, and tested it in the study on variation of canopy structure across nitrogen (N) fertilization modes. Field experiments over three years (2020-2022) with three nitrogen levels and two basal to topdressing ratios were conducted for two cultivars of each japonica and indica rice. Results showed contrasting dynamic variation of LPR between the two species, ascending for indica rice but descending for japonica rice along with the grain-filling progression. Indica rice had larger temporal variation in LPR than the japonica. N topdressing significantly increased the LPR of indica rice cultivars at same N level, whereas that of japonica was dependent on N level and genotype. Morphological measurement revealed that the differential response of LPR to N was associated with the height difference between the flag leaf and panicle, panicle cur-vature, leaf area index and panicle area index. Correlation analysis revealed that the relation between LPR and grain yield was significantly positive for indica rice but negative for japonica rice. Our findings suggest that LPR can effectively reflect the characteristics of canopy structure as affected by cultivars and fertilization modes, thus being a valuable physiological indicator for crop science.