Hyperspectral estimation of canopy chlorophyll of winter wheat by using the optimized vegetation indices

The vegetation indices (VIs) derived from the different band combinations can be used for monitoring crop quality traits. We conducted field experiments over two years time to investigate critical growth stages across four varieties and by using different nitrogen (N) application rates. In order to explore and evaluate the performance of different VIs on estimation of the canopy chlorophyll content (CCC) of winter wheat, the published and modified indices were optimized by using the random band combination through original spectrum (OS) and first-order differential (FD) treatment. The results showed that the first derivative processing improved the correlation between the red edge band and winter wheat CCC. The three-band VI can break the restriction of the number of bands on the extraction of target information, relieved the saturation problem of the dual-band VI, and improved the monitoring accuracy of winter wheat CCC. The index 2 x R1-R2-R3 was found to be the best VI for assessing the CCC of winter wheat based on the original and first-order differential spectrum (calibration R2 > 0.733), R-2 and RMSE of validation set were 0.688, 0.755 and 1.515, 1.336, respectively. In addition, the index expression formula R1/(R2 x R3) was recommended as a favorable choice for monitoring the agronomic traits of crop. Moreover, the VI is suggested to use at the red edge position band to monitor crop growth indicators. In conclusion, the use of VI can better monitor winter wheat CCC which could provide a theoretical basis for precision agriculture.

Automated summary

This study optimized vegetation indices for estimating the canopy chlorophyll content (CCC) of winter wheat using different spectral processing methods. The results showed that the first derivative processing improved the correlation between the indices and crop quality traits, and the three-band index improved the monitoring accuracy of CCC.