| A model monitoring the quantitative content of chlorophyll was established using correlation and linear and nonlinear analyses to determine the relationships between chlorophyll content of maize at the heading stage and a variety of high spectral parameters. The results showed that the raw spectral reflectance had a maximal negative correlation coefficient at 713 nm(r=0.86) with the chlorophyll content. The first derivative spectral reflectance had a maximal positive correlation coefficient at 760 nm (r=0.84). The parameters included λr, λb, λy, λg, Rg, SDr, SDr/SDb, SDr/SDy, (Rg-Ro)/(Rg+Ro) and (SDr-SDb)/(SDr+SDb), all of which reached significant correlations with the chlorophyll content. Models were built based on 12 kinds of spectral parameters that showed significant correlations. The R2 is of the models were greater than 0.72, constructed by the raw spectral reflectance, green reflection peak, the spectral reflectance of the first derivative, vegetation index and normalized difference vegetation index based on the red edge and blue edge area ratio. The first two exponential models established were better than the linear model, whereas the latter three linear models were better than the exponential models. Through precision evaluations of the estimation models, the model yChlorophyll content=6912x760nm+44.878 constructed in the first derivative spectral reflectance at 760 nm. This model seemed to be the best prediction for the chlorophyll content of maize at the heading stage due to its maximal correlation coefficient and minimal RMSE, and its relatively simple expression. The correlation coefficient R2 of the model was increased at least 11.4% more than other models. |