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The xanthophyll cycle regulates the energy flow to photosynthetic reaction centres of plant leaves. Changes in the de-epoxidation state (DEPS) of xanthophyll cycle pigments can be observed as changes in the leaf absorption of light with wavelengths between 500 to 570 nm. These spectral changes can be a good remote sensing indicator of the photosynthetic efficiency, and are traditionally quantified with a twoband physiologically based optical index, the Photochemical Reflectance Index (PRI). In this paper, we present an extension of the plant leaf radiative transfer model Fluspect (Fluspect-CX) that reproduces the spectral changes in a wide band of green reflectance: a radiative transfer analogy to the PRI. The idea of Fluspect-CX is to use in vivo specific absorption coefficients for two extreme states of carotenoids, representing the two extremes of the xanthophyll de-epoxidation, and to describe the intermediate states as a linear mixture of these two states. The 'photochemical reflectance parameter' (Cx) quantifies the relative proportion of the two states. Fluspect-CX simulates leaf chlorophyll fluorescence (ChlF) excitation-emission matrices, as well as reflectance (R) and transmittance (T) spectra as a function of leaf structure, pigment contents and Cx. We describe the calibration of the model and test its performance using various experimental datasets. Furthermore, we retrieved Cx from optical measurements of various datasets. The retrieved Cx correlates well with xanthophyll DEPS (R2=0.57), as well with non-photochemical quenching (NPQ) of fluorescence (R2=0.78). The correlation with NPQ enabled us to incorporate Fluspect-CX in the model SCOPE to scale the processes to the canopy level. Introducing the dynamic green reflectance into a radiative transfer model provides new means to study chlorophyll fluorescence and PRI dynamics on leaf and canopy scales, which is crucial for the remote sensing.

The growing availability of global measurements of sun-induced chlorophyll fluorescence (SIF) can help in improving crop monitoring, especially the monitoring of photosynthetic activity. However, variations in top-of-canopy (TOC) SIF cannot be directly interpreted as physiological changes because of the confounding effects of vegetation biochemistry (i.e. pigments, dry matter and water) and structure. In this study, we propose an approach of using radiative transfer models (RTMs) and TOC reflectance to estimate