Abstract: Aims Accurate monitoring of gross primary production (GPP) in terrestrial ecosystems is crucial for global carbon cycle and climate change studies. The near-linear relationship between solar-induced chlorophyll fluorescence (SIF) and GPP offers a new avenue for estimating vegetation carbon uptake from local to global scales. However, the contributions of radiative, structural, and physiological information of SIF to GPP estimation at different temporal scales remain unclear. Methods This study utilizes canopy spectroscopy and eddy covariance flux data from a field site in Shangqiu, Henan, focusing on wheat and maize as representative C3 and C4 crops, respectively. By comparing methods based on the near-infrared reflectance of terrestrial vegetation (NIRv) and the fluorescence correction vegetation index (FCVI) to decompose SIF components, we refined the leave-one-out method to quantify their contributions to GPP estimation and analyzed the impact of crop type and temporal resolution on the SIF-GPP relationship. Important findings The study reveals that the SIF-GPP relationship is influenced by differences in crop type and significantly strengthens as temporal resolution decreases. At shorter temporal scales, such as half-hour and one-day, the radiative component predominantly drives the SIF-GPP relationship. However, as the time scale extends to a week or longer, the influences of structural and physiological components become increasingly significant. The methods based on NIRv and FCVI showed high consistency in decomposing the radiative, structural, and physiological components of SIF. Through a deeper understanding and precise quantification of the SIF-GPP relationship, this research enhances the application of remote sensing technologies and models in global vegetation monitoring and carbon cycle studies.

Key words: solar-induced chlorophyll fluorescence (SIF), gross primary production (GPP), temporal resolution, crop, physiological information, canopy structure