Assessment of leaf carotenoids content with a new carotenoid index: Development and validation on experimental and model data

Abstract

Leaf carotenoids content (LCar) is an important indicator of plant physiological status. Accurate estimation of LCar provides valuable insight into early detection of stress in vegetation. With spectroscopy techniques, a semi-empirical approach based on spectral indices was extensively used for carotenoids content estimation. However, established spectral indices for carotenoids that generally rely on limited measured data, might lack predictive accuracy for carotenoids estimation in various species and at different growth stages. In this study, we propose a new carotenoid index (CARI) for LCar assessment based on a large synthetic dataset simulated from the leaf radiative transfer model PROSPECT-5, and evaluate its capability with both simulated data from PROSPECT-5 and 4SAIL and extensive experimental datasets: the ANGERS dataset and experimental data acquired in field experiments in China in 2004. Results show that CARI was the index most linearly correlated with carotenoids content at the leaf level using a synthetic dataset (R2=0.943, RMSE=1.196μg/cm2), compared with published spectral indices. Cross-validation results with CARI using ANGERS data achieved quite an accurate estimation (R2=0.545, RMSE=3.413μg/cm2), though the RBRI performed as the best index (R2=0.727, RMSE=2.640μg/cm2). CARI also showed good accuracy (R2=0.639, RMSE=1.520μg/cm2) for LCar assessment with leaf level field survey data, though PRI performed better (R2=0.710, RMSE=1.369μg/cm2). Whereas RBRI, PRI and other assessed spectral indices showed a good performance for a given dataset, overall their estimation accuracy was not consistent across all datasets used in this study. Conversely CARI was more robust showing good results in all datasets. Further assessment of LCar with simulated and measured canopy reflectance data indicated that CARI might not be very sensitive to LCar changes at low leaf area index (LAI) value, and in these conditions soil moisture influenced the LCar retrieval accuracy.