Model for calculating corn nitrogen nutrition index using hyper-spectral data

A method to fastly, accurately and dynamicly diagnose nitrogen nutrition status in large acreage is essential for corn growth vigor evaluation, production prediction and agriculture management. Two study sites respectively located in Changping district of Beijing and Changchun city were investigated and multiple spectral parameters were derived from the hyper-spectral data of the corn canopy of the two study areas. Further, based on stepwise regression analysis, quantitative relation between the corn nitrogen nutrition index (NNI) and hyper-spectral parameters was established, and the hyper-spectral parameters which had distinct correlation with the corn NNI as well as the predictive equations were presented. The results showed that three hyper-spectral parameters, i.e. NIR/G, NIR/NIR and REIP, were highly correlated with the corn NNI. Path coefficients of NIR/G and NIR/NIR to the corn NNI were calculated to be -0.14942 and -0.35218 respectively, which indicated an indirect effect of the two hyper-spectral parameters on the corn NNI. The path coefficient of REIP to the corn NNI was 1.41549, which revealed that REIP was highly sensitive to the corn NNI. The correlation index of the multi-variant regression model for the distinct hyper-spectral parameters and the corn NNI was 0.95507, fitting error between predicted and measured valuse was less than 0.1, Root mean square error was 0.06016, F value was 167.727 and P value was 0.0045.