A novel combined spectral index for estimating the ratio of carotenoid to chlorophyll content to monitor crop physiological and phenological status |
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| Institution: | 1. Irtsea, UMR TETIS, Maison de la Télédétection, 500 Rue Jean François Breton, 34000 Montpellier, France;2. Faculty of Civil and Environmental Engineering, Israel Institute of Technology, Technion City, Haifa, Israel;3. School of Natural Resources, University of Nebraska, Lincoln, USA;4. College of Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK S7N 5A9, Canada;5. Institut de physique du globe de Paris - Sorbonne Paris Cité, Université Paris Diderot, UMR CNRS 7154, Case 7071, 35 rue Hélène Brion, 75013 Paris, France;1. Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan;2. River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan;3. Faculty of Life and Environment Sciences, University of Tsukuba, 1-1-1 Tennohdai, Tsukuba, Ibaraki 305-8572, Japan |
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| Abstract: | Accurate estimation of the ratio of carotenoid (Car) to chlorophyll (Chl) content is crucial to provide valuable insight into diagnoses of plant physiological and phenological status in crop fields. Studies for assessing the ratio of Car to Chl content have been extensively conducted with semi-empirical approaches using spectral indices. However, spectral indices established in previous studies generally relied on site- or species-specific measured data and these indices typically lacked sufficient estimation accuracy for the ratio of Car to Chl content to be used across various species and under different physiological conditions. In this study, we propose a novel combined carotenoid/chlorophyll ratio index (CCRI) in the form of the carotenoid index (CARI) divided by the red-edge chlorophyll index (CIred-edge): The value of the index is illustrated using synthetic data simulated from the leaf radiative transfer model PROSPECT-5 and with extensive measured datasets at both the leaf and canopy level from the ANGERS dataset and winter wheat and maize field experiments. Results show that CCRI was the index with the highest correlation with the ratio of Car to Chl content in PROSPECT-5 simulations (R2 = 0.99, RRMSE = 8.65%) compared to other spectral indices. Calibration and validation results using the ANGERS and winter wheat leaf level data showed that CCRI achieved accurate estimation of the ratio of Car to Chl content (R2 = 0.52, RRMSE = 14.10%). CCRI also showed a good performance (R2 = 0.54, RRMSE = 17.08%) for estimation of the ratio of Car to Chl content in both calibration and validation with the winter wheat and maize canopy spectra measured in field experiments. Further investigation of the effect of the correlation between leaf Chl and Car content on the performance of CCRI indicated that variation of the correlation affected the retrieval accuracy of CCRI, and CCRI might not be very sensitive to changes of the ratio of Car to Chl content with low values (<0.10). |
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| Keywords: | Ratio of Car to Chl content Hyperspectral Spectral index Leaf optical modeling Crop monitoring |
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