Monitoring leaf nitrogen status with hyperspectral reflectance in wheat

By Wei Feng, Xia Yao, Yan Zhu, Yun-lu Tian, W. Cao. 2008

194 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fbd30c0905ae3904788159f43802d6b28c9aa67f

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In Ecology

In Plant Science

Citations in the corpus

Review of optical-based remote sensing for plant trait mapping (2013, background): “…% L / C FieldSpec (F) LR with red edge 0.75 n.a. 17.8 5a / - (Feng et al., 2008) N crops g m-2 L / C FieldSpec (F) LR with FD@742nm 0.87 n.a. 17.4 6a / - (Feng et al., 2008) N mixed % L / C GER 3700 (F) LR – VI (NDVI-based) 0.72 n.a. n.a. - / 2 (Ferwerda et al., 2005) N mixed % L / L GER 3700 (L)…”
Quantification of Nitrogen Status in Rice by Least Squares Support Vector Machines and Reflectance Spectroscopy (2009, background): “Feng et al. (2008) established a quantitative model for real-time monitoring of leaf N status with key hyperspectral bands and estimation indices in wheat.”
SWIR-based spectral indices for assessing nitrogen content in potato fields (2010, background): “Email: karnieli@bgu.ac.il International Journal of Remote Sensing Vol. 31, No. 19, 10 September 2010, 5127–5143 fundamental for optimizing yields (Bonfil et al. 2004, Reyniers et al. 2006, Jain et al. 2007, Feng et al. 2008, Zhu et al. 2008).”
Quantitative modelling for leaf nitrogen content of winter wheat using UAV-based hyperspectral data (2017, background): “Currently, some scholars have studied the crop nitrogen concentration estimating and monitoring model using hyperspectral data (Chen et al. 2010; He, Liu, and Li 2014; Feng et al. 2008; Erdle, Mistele, and Schmidhalter 2011; Zhang and Zhang 2008; Li et al. 2014b; Wang and Wei 2013).”
Assessment of plant nitrogen stress in wheat (Triticum aestivum L.) through hyperspectral indices (2012, unknown): “The observations of Feng et al. (2008) confirmed this finding.”
Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors (2009, background): “Due to recent availability, fine resolution spatial and spectral (hyperspectral) remotely sensed data are being used to retrieve LAI and other biochemical contents such as chlorophyll in leaves of forests [18-20].”
Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages (2010, methodology): “At Feekes growth stages 4–7, indices that use the red edge and NIR bands perform better than the visible bands, which agrees with the results of Feng et al. (2008) for wheat and with those of Fava et al. (2009) for pasture.”
Integrating remotely sensed leaf area index and leaf nitrogen accumulation with RiceGrow model based on particle swarm optimization algorithm for rice grain yield assessment (2014, methodology): “In addition, data for both of these parameters could be retrieved by RS successfully.(34,35) Sowing date, seeding rate, and nitrogen rate, which are generally difficult to obtain accurately at the regional scale, were chosen as the assimilating parameters of the RiceGrow model.”