[Monitoring leaf nitrogen concentration and nitrogen accumulation of double cropping rice based on crop growth monitoring and diagnosis apparatus]. / 基于作物生长监测诊断仪的双季稻叶片氮含量和氮积累量监测.

ABSTRACT

To verify the accuracy and adaptability of crop growth monitoring and diagnosis apparatus (CGMD) in monitoring nitrogen nutrition index of double cropping rice, we established a monitoring model of leaf nitrogen concentration (LNC) and leaf nitrogen accumulation (LNA) for double cropping rice based on CGMD. Eight early and late rice cultivars were selected and four nitrogen application rates were set up. The differential vegetation index (DVI), normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) were collected using CGMD. Meanwhile, ASD FH2 high spectrometer was used to collect canopy spectral reflectance and calculated DVI, NDVI, and RVI. To verify the accuracy of CGMD, we compared the canopy vegetation indices change characteristics collected by CGMD and ASD FH2. The CGMD-based monitoring models of LNC and LNA were established, which was tested with independent field data. The results showed that LNC, LNA, DVI, NDVI and RVI of early and late rice increased with increasing nitrogen application rate, and increased first and then decreased with the advance of growth progress. The determination coefficient (R2) of fitting for DVI, NDVI and RVI from CGMD and ASD FH2 were 0.9350, 0.9436 and 0.9433, respectively. This result indicated that the measurement accuracy of CGMD was high, and that the CGMD could be used to replace ASD FH2 to measure canopy vegetation indices of early and late rice. Compared with the three canopy vegetation indices based on CGMD, the correlation between NDVICGMD and LNC and that between RVICGMD and LNA was the highest. The exponential model based on NDVICGMD could be used to accurate estimate LNC with the R2 in the range of 0.8581-0.9318, and the root mean square error (RMSE), relation root mean square error (RRMSE) and correlation coefficient (r) of model validation in the range of 0.1%-0.2%, 4.0%-8.5%, and 0.9041-0.9854, respectively. The power function model based on RVICGMD could be used to estimate LNA with the R2 in the range of 0.8684-0.9577, and the RMSE, RRMSE and r of model validation in the range of 0.37-0.89 g·m-2, 6.7%-20.4% and 0.9191-0.9851, respectively. Compared with the chemical testing method, using the CGMD could conveniently and accurately measure LNC and LNA of early and late rice, which had a potential to be widely applied for high yield and high efficiency cultivation and precise management of nitrogen fertilizer in double cropping rice production.