An in situ approach for validation of canopy chlorophyll fluorescence radiative transfer models using the full emission spectrum

Abstract

The intensity and spectral properties of solar-induced chlorophyll fluorescence (SIF) carry valuable information on plant photosynthesis and productivity, but are also influenced by leaf and canopy structure. Physically based models provide a quantitative means to investigate how SIF intensity and spectra propagate and scale from the photosystem to the leaf and to the canopy levels. However, the validation of canopy SIF models is limited by the lack of methods that combine direct, independent, and complementary measurements of the full fluorescence spectrum at the leaf and canopy levels. Here, we propose a novel validation approach that combines in situ measurements of leaf and canopy fluorescence spectra. The approach is demonstrated with measurements in a rice crop at two contrasting stages of canopy development. We measured leaf reflectance, transmittance, and fluorescence spectra in situ, and subsequently inverted leaf structural and biochemical parameters and determined the leaf fluorescence quantum efficiency (FQE) using the Fluspect-Cx model. Two FQE inversion methods (Inversion-IIA and Inversion-IIB) were tested for the forward simulation of leaf fluorescence spectra. Leaf fluorescence spectra were then scaled up to the canopy level using 1D, 2D, and 3D radiative transfer schemes (SCOPE, mSCOPE, and DART), and compared with the direct canopy fluorescence spectral observations measured under red, green, blue, and white illumination. The validation results demonstrate that accounting for 3D canopy structure, as in the DART model, is critical to successfully scale the fluorescence spectrum from the leaf to the canopy level, whereas 1D SCOPE or even 2D mSCOPE were unable to fully reproduce the canopy fluorescence spectra. The results also demonstrate that the Inversion-IIB method matches relatively well the measurements with mean relative absolute errors (MRAE) of 20 %, 37 %, and 43 % versus Inversion-IIA with mean relative absolute errors (MRAE) of 62 %, 100 %, and 108 % for DART, mSCOPE, and SCOPE, respectively. We suggest that our validation approach is transferable to other plant species and canopy geometries, providing a means to standardize and evaluate the performance of canopy SIF models and improve our understanding of canopy SIF observations.