A series of 598 pure polyester,pure cotton and polyester-cotton blended samples were selected by FT-MIR,and their relative contents were determined by the national standard method(GB/T 2910.11-2009).The samples original spectra were acquired by near-infrared(NIR)spectrometry，which were distributed into the calibration set(252 samples) and the validation set(346 samples).The best modeling spectra were obtained according to the size and trend range of regression coefficient distribution.Using preprocessing such as S-G smoothing，Differential 1st derivative and mean centering to analyze the samples NIRS，and the NIR quantitative analysis model for polyester-cotton blended fabrics was established by partial least squares(PLS) method.The influence of sample’s color on the NIRS was analyzed，and the effects of slash spectrum samples，singular samples and fabric stitch structure of samples on the prediction accuracy of the model were investigated. The result of experiment indicated that the NIR quantitative analysis model for polyester-cotton blended fabrics was established by PLS method，which included 1 spectral interval and 9 principal factors.The correlation coefficient of calibration and the standard errors of calibration were obtained to be 0.998 and 0.908,respectively.To verify the accuracy，validity and practicability of the model，346 bound samples were predicted. The variance analysis indicated that there was no significant difference between NIR method and national standard method，and the accurate recognition rate reaches up to 97%.The model will provide a foundation database for sorting the waste polyester-cotton blended fabrics quickly and non-destructively.