Open Access

ARTICLE

Retrieval of Winter Wheat Canopy Carotenoid Content with Ground- and Airborne-Based Hyperspectral Data

Ting Cui, Xianfeng Zhou^*, Yufeng Huang, Yanting Guo, Yunrui Lin, Leyi Song, Jingcheng Zhang

College of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, 310018, China

* Corresponding Author: Xianfeng Zhou. Email:

Phyton-International Journal of Experimental Botany 2023, 92(9), 2633-2648. https://doi.org/10.32604/phyton.2023.029259

Received 09 March 2023; Accepted 15 May 2023; Issue published 28 July 2023

Abstract

Accurate assessment of canopy carotenoid content (CC_x+cC) in crops is central to monitor physiological conditions in plants and vegetation stress, and consequently supporting agronomic decisions. However, due to the overlap of absorption peaks of carotenoid (C_x+c) and chlorophyll (C_a), accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging. The objective of present study was to assess CC_x+cC in winter wheat (Triticum aestivum L.) with ground- and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum. In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments. At the canopy level, a remarkable linear relationship (R² = 0.95, p < 0.001) existed between C_x+c and C_a, and correlation between CC_x+cC and wavelengths within 400 to 1000 nm range indicated that CC_x+cC could be estimated using reflectance ranging from visible to near-infrared wavebands. Results of C_x+c assessment based on chlorophyll and carotenoid indices showed that red edge chlorophyll index (CI red edge) performed with the highest accuracy (R² = 0.77, RMSE = 22.27 μg/cm² , MAE = 4.97 μg/cm² ). Applying partial least square regression (PLSR) in CC_x+cC retrieval emphasized the significance of reflectance within 700 to 750 nm range in CC_x+cC assessment. Based on CI red edge index, use of airborne hyperspectral imagery achieved satisfactory results in mapping the spatial distribution of CC_x+cC. This study demonstrates that it is feasible to accurately assess CC_x+cC in winter wheat with red edge chlorophyll index provided that C_x+c correlated well with C_a+b at the canopy scale. it is therefore a promising method for CC_x+cC retrieval at regional scale from aerial hyperspectral imagery.

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Keywords

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