Stage-specific LAI-based estimation of maize biophysical parameters: Allocation characteristics and biomass assessment

Maize canopy biophysical parameters support crop monitoring and the assessment of biomass for industrial and energy uses. However, representing the seasonal variation, growth stage dependent changes, and parameterization of crop biophysical parameters, particularly canopy development, senescence, and component allocation. To address these issues, this study collected maize biophysical parameter data from 490 plots in Northeast China during 2021–2024, we developed a Stage-specific Relationship Model of maize biophysical parameters (SRM). and the model was evaluated using independent regional field observations and satellite LAI inputs. The results showed that maize biophysical parameters generally increased with leaf area index (LAI) during the vegetative stage, following linear or logarithmic relationships, whereas height, stem radius, and above ground biomass of stem and leaf showed weaker relationships with LAI and tended to stabilize during the reproductive stage. The segmentation point between the vegetative and reproductive stages was determined using a strategy that minimized the fitting errors of biophysical parameters and was consistently identified as DOY 212. In local calibration, the mean normalized mean absolute error (NMAE) was 0.12 in the vegetative stage and 0.14 in the reproductive stage. For the entire growing season, the mean NMAE was 0.09, 0.24, and 0.12 for local calibration, independent regional validation, and Sentinel-2 LAI-driven validation, respectively. In addition, the separation of non-photosynthetic leaf components improved the estimation accuracy of leaf fresh above ground biomass, above ground biomass, and vegetation water content by 8.7%, 22.9%, and 4.3%, respectively. Regional application in Kaoshan during 2021–2023 yielded reproductive stage stem dry biomass estimates of 5.96–6.89 t/ha. The estimated stem contribution to combined stem and leaf dry biomass remained at approximately 70.0% during DOY 220–228 and DOY 243–245, and increased to 70.9% at DOY 255. SRM provides an interpretable approach for estimating maize canopy biophysical parameters and supports field-scale crop monitoring and component-specific biomass assessment.