Monitoring Leaf Nitrogen Status in Rice with Canopy Spectral Reflectance

By L. Xue, W. Cao, W. Luo, T. Dai, Yan Zhu. Agronomy Journal, 2004

279 citations recorded by the source corpus.

Nondestructive monitoring and diagnosis of plant N status is necessary for precision N management. The present study was conducted to determine if canopy reflectance could be used to evaluate leaf N status in rice (Oryza saliva L.). Ground-based canopy spectral reflectance and N concentration and accumulation in leaves were measured over the entire rice growing season under various treatments of N fertilization, irrigation, and plant population. Analyses were made on the relationships of seasonal canopy spectral reflectance, ratio indices, and normalized difference indices to leaf N concentration and N accumulation in rice under different N treatments. The results showed that at each sampling date, leaf N concentration was negatively related to the reflectance at the green band (560 nm) while positively related to ratio index, with the best correlation at jointing. However, the relationships between leaf N accumulation and reflectance at green band and ratio index were consistent across the whole growth period. The ratio of near infrared (NIR) to green (R 810 /R 560 ) was especially linearly related to total leaf N accumulation, independent of N level and growth stage. Tests of the linear regression model with different field experiment data sets involving different plant densities, N fertilization, and irrigation treatments exhibited good agreement between the predicted and observed values, with an estimation accuracy of 96.69%, root mean square error of 0.7072, and relative error of -0.0052. These results indicate that the ratio index of NIR to green (R 810 /R 560 ) should be useful for nondestructive monitoring of N status in rice plants.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/4014cefcb258363874f4a954f94695d610141d80

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Citations in the corpus

Topdressing nitrogen recommendation for early rice with an active sensor in south China (2014, methodology): “…have been employed successfully to assess crop N status in terms of plant/leaf N concentration, estimating plant N uptake (Hansen and Schjoerring 2003; Xue et al. 2004; Nguyen and Lee 2006) and guiding N fertilization (Raun et al. 2002; Wood et al. 2003; Welsh et al. 2003; Raun et al. 2005).”
Predicting Grain Yield and Protein Content in Winter Wheat at Different N Supply Levels Using Canopy Reflectance Spectra (2007, methodology): “At each date of spectra measurement, 5–8 plants were harvested at random from each plot.”
Estimating Rice Grain Yield Potential Using Normalized Difference Vegetation Index (2011, unknown): “Several studies have documented the potential use of remote sensing technology to monitor and evaluate rice N status (Xue et al., 2004; Lee et al., 2008).”
Quantification of Nitrogen Status in Rice by Least Squares Support Vector Machines and Reflectance Spectroscopy (2009, background): “In some early papers, Xue et al. (2004) found that R810/ R560 was especially linearly related to total leaf N accumulation, and the predicted and observed values was with an estimation accuracy of 96.69%, root mean square error of 0.7072, and relative error of 0.0052.”
Analysis of vegetation indices derived from hyperspectral reflection measurements for estimating crop canopy parameters of oilseed rape (Brassica napus L.) (2008, methodology): “Nondestructive, sensory measurements may be useful measures to assess those parameters in realtime and for large areas (Xue et al., 2004; Boegh et al., 2002).”
Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels (2013, background): “However, at canopy level the estimation of Chl and N content is much more problematic and only a few papers have demonstrated a way to estimate them (Gitelson et al., 2005; Gitelson, 2011b; Lee et al., 2008; Sripada et al., 2008; Takahashi et al., 2000; Tian et al., 2011; Xue et al., 2004; Zhu et al”