Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat

Leaf total chlorophyll content (LTCC) is an important indicator for assessment of crop health and prediction of crop yield. The objective of this study was to develop a precise agricultural practice that could estimate wheat LTCC. In this study, we compared two methods of LTCC estimation: one method used the products of spectral parameters and biomass dry weight (BDW), and the other method used stepwise regression methods (SRM). We selected the highest determination coefficient (R2) simulation model to improve prediction accuracy. The results showed that for the mND705 × BDW index, the R2 was 0.9639 and the root mean square error (RMSE) was 0.202 g/m2. For the 3.575Red edge model-1.118PSSRb index, the R2 was 0.868 and RMSE was 0.384 g/m2. The mND705 × BDW index accounted for 96.39% of LTCC, while the 3.575Red edge model-1.118PSSRb accounted for 86.8% of LTCC. Further, the RMSE of mND705 × BDW was lower than that of 3.575Red edge model-1.118PSSRb for predicting LTCC. The results indicated that the spectral parameters × BDW methods, in which spectral parameters defection was improved, was superior to SRM.