Spectroscopic data of samples recorded by spectroscopic instruments are confused by a series of noises, and interferences, therefore the proper data preprocessing is the basis of the following spectroscopic calibration, model establishment and transference, which is very important for the achievement of accurate analytical results. This paper reports our research work, combined with NIR spectroscopic analyses of the protein contents of wheat, that is the preprocessing of NIR spectral data recorded for 66 different wheat samples by a NIR grating spectrophotometer and a NIR Fourier transform spectrometer, respectively. The preprocessing algorithm is wavelet transform with the Gaussian first and second order derivatives. Compared with the result of preprocessing by normal first order difference algorithm, the wavelet transform algorithm by Gaussian derivatives was proved to be very effective and applicable, the spectra were smoothed perfectly, noises were eliminated obviously, and the spectral sections, which include all useful information for spectral analyses, were displayed clearly. So, it is very beneficial to the following spectral calibration, model establishment and transference.
