New vegetation index for estimating nitrogen concentration using fresh leaf spectral reflectance

Field experiment was conducted to study the feasibility of estimating the nitrogen status of rice using fresh leaf spectral reflectance. Based on the mechanism of nitrogen transfer among different rice leaves, red edge slope and red edge position of the most upper and the 3rd expanded leaves were investigated specially. And using the two red edge parameters (red edge slope and red edge position), a new vegetation index (red edge curve shoulder angle vegetation index, abbreviation RSAVI) was calculated to detect rice nitrogen nutrition status. The correlation between nitrogen concentration and RSAVI at different rice growth stages was studied in order to prove availability of the new index determining nitrogen nutrition. The conclusion shows that RSAVI is correlated significantly with the nitrogen at leaf level and regression analysis indicates that polynomial models are creditable for determining nitrogen concentration using RSAVI at 0.01 level. The correlation coefficients(R) and determination coefficient (R2) between RSAVI and nitrogen nutrition are all large and highly significant, with the range of R from 0.867 to 0.938 and R2 from 0.7512 to 0.8796. The results support the hypothesis that RSAVI is an effective tool for estimating nitrogen concentration in this experimentation.