Empty bud Carya cathayensis refer to Carya cathayensis with no seed kernels or stunted development， which will seriously affect the product quality of Carya cathayensis. To achieve rapid and non-destructive identification of empty bud Carya cathayensises， two NIR detection devices were used to collect spectra of shelled Carya cathayensises samples in the wavelength range of 200-1 160 nm. Eight different preprocessing methods wers used for spectral preprocessing， and competitive adaptive reweighted sampling (CARS) was used to select the sensitive wave length variables of empty bud Carya cathayensises. Finally， linear discriminant analysis (LDA)， quadratic discriminant analysis (QDA)， and mahalanobis discriminant analysis (MDA) were applied to establish the classification models of empty bud and normal Carya cathayensises. The results showed that the performance of the classification models of empty bud Carya cathayensis established using detection device 1 were better than that of the detection device 2. The classification models established after multivariate scattering correction (MSC) pretreatment showed the best recognition results. The specificity， sensitivity and correctness of LDA， QDA， and MDA models were all 1， which were better than the classification models established by other preprocessing methods. After CARS variable screening， the number of spectral variables used for modeling was significantly reduced， effectively simplifying the classification model. However， the model performance was still on par with that of the full-band model. This paper provides a feasible method for the rapid nondestructive identification of empty bud Carya cathayensis by near-infrared spectroscopy combined with chemometric methods.