Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices.

Leaf pigment content is an important indicator of plant status and can serve to assess the vigor and photosynthetic activity of plants. The application of spectral information gathered from laboratory, field and remote sensing-based spectrometers to non-destructively assess total chlorophyll (Chl) content of higher plants has been demonstrated in earlier studies. However, the precise estimation of carotenoid (Car) content with non-destructive spectral measurements has so far not reached accuracies comparable to the results obtained for Chl content. Here, we examined the potential of a recently developed angular vegetation index (AVI) to estimate total foliar Car content of three tree species. Based on an iterative search of all possible band combinations, we identified a best candidate AVIcar. The identified index showed quite close but essentially not linear relation with Car contents of the examined species with increasing sensitivity to high Car content and a lack of sensitivity to low Car content for which earlier proposed vegetation indices (VI) performed better. To make use of the advantages of both VI types, we developed a simple merging procedure, which combined the AVIcar with two earlier proposed carotenoid indices. The merged indices had close linear relationship with total Car content and outperformed all other examined indices. The merged indices were able to accurately estimate total Car content with a percental root mean square error (%RMSE) of 8.12% and a coefficient of determination of 0.88. Our findings were confirmed by simulations using the radiative transfer model PROSPECT-5. For simulated data, the merged indices again showed a quasi linear relationship with Car content. This strengthens the assumption that the proposed merged indices have a general ability to accurately estimate foliar Car content. Further examination of the proposed merged indices to estimate foliar Car content of other plant species is desirable to prove the general applicability of the index for non-destructive estimation of Car from leaf reflectance data.