Evaluating chlorophyll density in winter oilseed rape (Brassica napus L.) using canopy hyperspectral red-edge parameters

Novel red-edge area indices for evaluating chlorophyll density (ChD) were developed.Optimal red-edge spectral parameters (ORSPs) were characterized and determined.Noise Equivalent (NE) model was used to evaluate the sensitivity of the ORSPs.The novel ORSPs enhances ChD estimation from hyperspectral reflectance data. Accurate assessments of chlorophyll density (ChD) using hyperspectral techniques are important for effective evaluation of plant productivity and precise nitrogen (N) management in winter oilseed rape. To develop a quantitative estimation model for determining ChD in winter oilseed rape, field experiments with different N fertilizer levels were conducted over two successive years by measuring canopy hyperspectral reflectance and ChD at various developmental stages. The relationships between two types of parameters (existing red-edge spectral parameters and newly-developed red-edge area parameters) and ChD were investigated to determine the optimal red-edge spectral parameters (ORSPs) for ChD predictions. The Noise Equivalent (NE) model was adopted to evaluate the sensitivity and accuracy of the ORSPs for detecting changes in ChD across different growth stages. The results indicated that canopy hyperspectral reflectance and its first derivative spectra significantly varied with the levels of N fertilization. A strong correlation also existed between canopy reflectance data and ChD. Using a training dataset, the best results for assessing ChD status were observed when using the newly-developed red-edge area parameter, which indicated a difference between the double-peak areas based on the position of the main peak (DIDRmid). DIDRmid was the ORSP and exhibited a significant exponential relationship with ChD, with a coefficient of determination (R2) of 0.88 and a standard error (SE) of 0.312. Tests conducted on the independent validation dataset showed that DIDRmid can be used to accurately predict ChD in oilseed rape, with a relative root mean square error (RRMSE) of 0.091 and a mean relative error (MRE) of 7.22%. Additionally, this ORSP also had relatively lower NE values and higher sensitivity and accuracy with respect to ChD estimation. Consequently, the ChD of winter oilseed rape can be stably estimated with the hyperspectral red-edge methods established in this study because the newly-developed red-edge area spectral parameter was effective and accurate in evaluating ChD.

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