Abstract: By studying the original, SNV and first derivative near infrared spectra (NIRS)of 125 domestic flue-cured tobacco samples from different areas in 2003, the principal components in these samples were analyzed.The grown areas of tobacco samples were discriminated by Mahalanobis distance under principal components' space.It was proposed to determine the maximum number of principal component on the basis of instrument noise and error level.The effects of principal component number, specimen space and spectral region on the accuracy in discrimination of tobacco grown area were studied.The embodiments of NIR characteristic regions and characteristic informations of grown area on different principal components were analyzed.The results indicated that the highest recognition accuracy was offered by the models which were established while analyzing principal components in modeling specimen spaces and the first derivative near infrared spectra in full wavelength range were used.