Reflectance indices with precision and accuracy in predicting cotton leaf nitrogen concentration

By L. Tarpley, K. Raja Reddy, G. F. Sassenrath-Cole. 2000

207 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/33fcf925f5796eb4cef343c1db4d939b05f440df

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Citations in the corpus

LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands (2011, background): “…chlorophyll contents, seasonal patterns, and canopy biomass (Baret et al., 1992; Blackburn & Steele, 1999; Buschmann & Nagel, 1993; Cho & Skidmore, 2006; Clevers et al., 2001; Dawson & Curran, 1998; Delegido et al., 2008; Jorgensen, 2002; Moran et al., 2004; Pu et al., 2003; Tarpley et al., 2000).”
Random forest regression and spectral band selection for estimating sugarcane leaf nitrogen concentration using EO-1 Hyperion hyperspectral data (2013, background): “Methods that take advantage of remote sensing, particularly the use of hyperspectral data, can provide non-destructive, cost-effective, and near-real-time monitoring routines for the estimation of sugarcane N concentration (Tarpley, Reddy, and Sassenrath-Cole 2000).”
Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply (2003, background): “Our results indicated that a simple reflectance ratio (R712/R1040 or R575/R526) improved precision of estimating corn leaf N concentration (Figure 8), although the wavebands did not exactly match the findings of either Blackmer et al. (1996) or Tarpley et al. (2000).”
Prediction of grain protein content in winter wheat (Triticum aestivum L.) using plant pigment ratio (PPR) (2004, unknown): “, 1996; Sunderman, 1997), and possibly lack of the very near-infrared region contribution to normalization and base-lining (Tarpley et al., 2000).”
SWIR-based spectral indices for assessing nitrogen content in potato fields (2010, background): “Note that although the red edge is an indirect measure of N content, it was found to be highly correlated to it (Tarpley et al. 2000).”
Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum (2005, background): “…that leaf reflectance ratios were superior to single reflectance values in predicting leaf Chl or N status in different crops in spite of inconsistence in the wavebands used in calculating reflectance ratios (Tarpley et al., 2000; Carter and Spiering, 2002; Read et al., 2002; Zhao et al., 2003).”
Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation (2007, background): “2000 ); (iii) characteristics of first and second derivatives of reflectance spectra, including the wavelength position of the red edge (e.”
Analysis of vegetation indices derived from hyperspectral reflection measurements for estimating crop canopy parameters of oilseed rape (Brassica napus L.) (2008, background): “Published by Elsevier Ltd (Tarpley et al., 2000; Hansen and Schjoerring, 2003; Johnson et al., 2003; Lukina et al., 2001; Raun et al., 2002).”
Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression (2014, background): “Remote estimation of the canopy N content of winter wheat, rice, cotton and grass have been comprehensively discussed by many studies (Tarpley et al., 2000; Gislum et al., 2004; Nguyen and Lee, 2006; Fava et al., 2009; Stroppiana et al., 2009; Wang et al., 2012).”
Selection of Optimum Reflectance Ratios for Estimating Leaf Nitrogen and Chlorophyll Concentrations of Field-Grown Cotton (2005, background): “Tarpley et al. (2000) reported that using specific true-leaf stage.”