Advances in non-destructive assessment of rice canopy dynamics using plant canopy analyzer measurements

Canopy structure, particularly the leaf area index (LAI), is a major determinant of crop productivity because it influences light interception, photosynthetic efficiency, and overall resource use. Nondestructive measurement tools, such as plant canopy analyzers (PCA), have enabled repeated field-based assessments of canopy traits without the need for destructive sampling. This review synthesizes recent advances in the PCA-based evaluation of rice canopy dynamics and examines their integration with complementary sensing and modeling approaches. PCA-derived parameters have been effectively used to characterize genotypic variation in leaf expansion and to parameterize growth models, thereby supporting yield prediction and physiological interpretation. Recent advances in nondestructive profiling have enabled more accurate estimation of vertical LAI distribution, linking canopy architecture to light-use efficiency and overall productivity. Although PCA measurements require careful calibration and are constrained by labor intensity, they remain valuable ground-based references for scalable canopy monitoring. Integrating PCA with UAV-based and satellite remote sensing, supported by multispectral and hyperspectral data, offers substantial potential for large-area phenotyping and varietal discrimination. Evidence from multi-environment and multi-genotype trials demonstrates the feasibility of this integrated approach for quantitatively evaluating canopy development and crop performance. Collectively, these developments underscore the importance of integrating ground-based and remote sensing approaches to advance canopy physiology, precision agriculture, and crop breeding applications.