Prediction of Leaf Nitrogen Content of Rice in Cold Region Based on Spectral Reflectance

In order to realize the real-time prediction of nitrogen content in the rice leaf population by using the rice leaf spectral index, the spectral reflectance of the top three fully expanded leaves (upper 1, upper 2 and upper 3 leaves were recorded as La. 1 and L respectively) at the main growth stages of rice in cold region (T, mid-spike differentiation stage. T, jointing stage. Ta booting stage. T. full heading stage and T. wax ripening stage) under different nitrogen and variety differences in different years were collected. The change rule and the relationship between spectral index and leaf nitrogen content were explored. P-k, Root Mean Square Error (RMSE). Symmetric Mean Absolute Percentage Error (SMAPE). Root Mean Square Error of Calibration (RMSEC), Root Mean Square Error of Interactive Verification (RMSECV) and Residual Prediction Deviation (RPD) were used to verify the accuracy of the model. The results showed that with the increase of nitrogen fertilizer input, the leaf reflectance decreased in the visible region, while the leaf reflectance increased in the near-infrared platform, With the advance of the growth period, in the visible light region, the reflectance of L., leaves of different varieties decreased first and then increased, and the reflectance of 14 and 1 leaves increased all the time. The sensitive hands of leaf nitrogen percentage were 500-550 and 650-700 nm. The correlation analysis of the spectral index and leaf nitrogen percentage content showed that the correlation coefficient of the spectral index of the following leaves was high in the carly stage of growth, but it was the opposite in the later stage of growth. The L. leaf index FD- NDNI in the T, period, Le leaf index GM2 in the Te period, Le leaf index Licz in the T, period. L., leaf index MRESRI in the T, period, and L, leaf index Ctrl in the T, period were selected as the best indexes. to predict leaf nitrogen content in different periods. The regression equations R for predicting leaf nitrogen content were 0.54 0.60 0.66 0.62 and 0.51, respectively, which reached extremely significant levels, The P-k values of the validation indexes were 0.00, 0.04, 0.06, 0.01 and 0.04, respectively. RMSE were 0.39, 0.58. 0.22.0.54, 2.56, SMAPE were 1.11. 1.41. 1.03. 1.64.3.89. RMSEC were 0.17.0.15. 0.13, 0.13, 0.13. RMSECV were 0. 18. 0.14. 0. 12. 0. 12. 0. 14. the RPD were 2. 46. 2. 19. 3. 15. 1.74 and 3. 01. respectively. Among them, the prediction effect of the 14 leaf index Lic? at the T, stage was the best. In summary, with the help of the selected spectral indicators, the nitrogen nutrition status of rice at different growth stages can be predicted quickly, non-destructively, and in real-time, and the sustainable development of high-yield and high-quality cold rice can be promoted.