Monitoring leaf nitrogen accumulation in wheat with hyper-spectral remote sensing

Abstract

Crop nitrogen status is a key indicator for evaluating crop growth, increasing yield and improving grain quality. Non-destructive and rapid assessment of leaf nitrogen is required for improving nitrogen management in wheat production. This study aims at identification of the quantitative relationship between leaf nitrogen accumulation and canopy reflectance spectra in winter wheat ( Triticum aestivum L.), and to derive regression equations to monitor N nutrition status in wheat. 3 field experiments were conducted with different N application rates and wheat cultivars across 3 growing seasons, and time-course measurements were taken on canopy spectral reflectance, leaf N content and leaf dry weights under various treatments. In these studies, leaf nitrogen accumulation in wheat increased with increasing nitrogen rates. Canopy reflectance changed with increasing leaf nitrogen accumulation. Sensitivity bands mainly occurred in near infrared and visible light, and strong correlation existed between red light and leaf nitrogen accumulation. The relationships of 8 vegetation indicators and leaf nitrogen accumulation were analyzed using statistical models. Hyper-spectral variables were significantly correlated with leaf nitrogen accumulation, and the relationships between the leaf nitrogen accumulation and SDr/SDb, FD742 and AVHRR-GVI were all highly significant with determination of coefficients ( R 2) of 0.9163, 0.9097 and 0.9142, respectively, and standard errors (SE) of 1.165, 1.079 and 1.077, respectively. Tests with another independent dataset showed that FD742 and REP IG could be well used to predict leaf nitrogen accumulation in wheat with R 2 of 0.8449 and 0.8394, and root mean square error (RMSE) of 0.984 and 1.014, respectively. This suggests that FD742 and REP IG can be used to estimate leaf nitrogen accumulation, of which FD742 performed better in modeling and testing.