Abstract
BackgroundThe visible and near infrared region has been widely used to estimate the leaf nitrogen (N) content based on the correlation of N with chlorophyll and deep absorption valleys of chlorophyll in this region. However, most absorption features related to N are located in the shortwave infrared (SWIR) region and the physical mechanism of leaf N estimation from fresh leaf reflectance spectra remains unclear. The use of SWIR region may help us reveal the underlying mechanism of casual relationships and better understand the spectral responses to N variation from fresh leaf reflectance spectra. This study combined continuous wavelet analysis (CWA) and water removal technique to improve the estimation of N content and leaf mass per area (LMA) by reducing the effect of water absorption and enhancing absorption signals in the SWIR region. The performance of the wavelet-based method was evaluated for estimating leaf N content and LMA of rice and wheat crops from fresh leaf reflectance spectra collected over a 2-year field experiment and compared with normalization difference (ND)-based spectral indices.ResultsThe LMA and area-based N content (Narea) exhibited better correlations with the determined wavelet features derived from the water-removed (WR) spectra (LMA: R2 = 0.71, Narea: R2 = 0.77) than those from the measured reflectance (MR) spectra (LMA: R2 = 0.62, Narea: R2 = 0.64). The wavelet features performed remarkably better than the optimized ND indices for the estimations of LMA and Narea with MR spectra or WR spectra. Based on the best estimations of LMA and Narea with wavelet features from WR spectra, the mass-based N content (Nmass) could be retrieved with a high accuracy (R2 = 0.82, RMSE = 0.32%) in the indirect way. This accuracy was higher than that for Nmass obtained in the direct use of a single wavelet feature (R2 = 0.68, RMSE = 0.42%).ConclusionsThe enhancement of absorption features in the SWIR region through the CWA applied to water-removed (WR) spectra was able to improve the spectroscopic estimation of leaf N content and LMA as compared to that obtained with the reflectance spectra of fresh leaves. The success in estimating LMA and N with this method would advance the spectroscopic estimations of grain quality parameters for staple crops and individual dry matter constituents for various vegetation types.
Highlights
The visible and near infrared region has been widely used to estimate the leaf nitrogen (N) content based on the correlation of N with chlorophyll and deep absorption valleys of chlorophyll in this region
The leaf reflectance spectra under three N treatments exhibited marginal differences in the shortwave infrared (SWIR) region (Fig. 3e). This phenomenon was expected for fresh leaves, which demonstrated the need of water removal technique to remove the water absorption and continuous wavelet analysis (CWA) to enhance the absorption features of nitrogen and dry matter
Difference in sensitive spectral features derived from measured reflectance (MR) and WR spectra When comparing the spectral features sensitive to leaf mass per area (LMA), area-based leaf nitrogen content (Narea) and mass-based leaf nitrogen content (Nmass), we found that the difference in wavelet feature was less significant between MR and WR spectra than that in normalization difference (ND) index
Summary
The visible and near infrared region has been widely used to estimate the leaf nitrogen (N) content based on the correlation of N with chlorophyll and deep absorption valleys of chlorophyll in this region. Most absorption features related to N are located in the shortwave infrared (SWIR) region and the physical mechanism of leaf N estimation from fresh leaf reflectance spectra remains unclear. Based on a number of N-sensitive wavelengths in the SWIR region, leaf N can be estimated accurately from the reflectance spectra of dried and ground leaves [11, 12]. These absorption features are masked by water absorption and not clearly visible in the SWIR reflectance spectra of fresh leaves, thereby leading to weaker signals of N in the entire spectra [13,14,15]. How accurately the N content could be estimated from reflectance spectra of fresh leaves in the SWIR region alone is poorly understood
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