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- W2802852942 abstract "Abstract In semi-arid conditions, nitrogen (N) is the main limiting factor of crop yield after water, and its accurate quantification remains essential. Recent studies have demonstrated that solar-induced chlorophyll fluorescence (SIF) quantified from hyperspectral imagery is a reliable indicator of photosynthetic activity in the context of precision agriculture and for early stress detection purposes. The role of fluorescence might be critical to our understanding of N levels due to its link with photosynthesis and the maximum rate of carboxylation (Vcmax) under stress. The research presented here aimed to assess the contribution played by airborne-retrieved solar-induced chlorophyll fluorescence (SIF) to the retrieval of N under irrigated and rainfed Mediterranean conditions. The study was carried out at three field sites used for wheat phenotyping purposes in Southern Spain during the 2015 and 2016 growing seasons. Airborne campaigns acquired imagery with two hyperspectral cameras covering the 400–850 nm (20 cm resolution) and 950–1750 nm (50 cm resolution) spectral regions. The performance of multiple regression models built for N quantification with and without including the airborne-retrieved SIF was compared with the performance of models built with plant traits estimated by model inversion, and also with standard approaches based on single spectral indices. Results showed that the accuracy of the models for N retrieval increased when chlorophyll fluorescence was included (r2LOOCV ≥ 0.92; p" @default.
- W2802852942 created "2018-05-17" @default.
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- W2802852942 date "2018-08-01" @default.
- W2802852942 modified "2023-10-13" @default.
- W2802852942 title "Improved nitrogen retrievals with airborne-derived fluorescence and plant traits quantified from VNIR-SWIR hyperspectral imagery in the context of precision agriculture" @default.
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- W2802852942 doi "https://doi.org/10.1016/j.jag.2018.04.013" @default.
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