Abstract: In the present study, 188 yellow-red loam soil samples were collected in Southern Anhui, and the original spectrum was obtained by non-imaging spectrometer. Firstly, the characteristics of the average spectral reflectance curve at 350-1 657 nm were analyzed after preprocessing. Based on the original spectrum and spectra after 29 preprocesses, a total of 60 models were constructed either by partial least squares regression (PLSR) or radial basis function (RBF)-PLSR, and the constructed models were optimized and evaluated by the models' decision coefficient (R²) and relative percent deviation (RPD). It was shown that the PLSR model constructed on spectra after Savitaky-Golay filtering and log transformation (SG+LG/PLSR model) was most suitable for the prediction of soil available nitrogen content. Its R² and RPD were 0.94 and 3.88 in calibration set and were 0.91 and 3.38 in prediction set, which belonged to A level, and indicated that this model was feasible for soil available nitrogen content prediction.

Key words: hyperspectral analysis, soil available nitrogen, preprocessing, model