Abstract: This paper focused on identifying the geographic origin of chestnut by using visible and near-infrared（VIS/NIR） spectroscopy. The VIS/NIR spectra were obtained at the spectral range of 600-1 100 nm for chestnut samples. Partial least square discriminant analysis models were developed, and different spectral pre-processing methods were used and compared to evaluate the effect on mathematical models. Besides, different spectral ranges were also compared to determine the influence on the accuracy of the PLSDA model. The results showed that different spectral pre-processing methods could influence the PLSDA models. PLSDA model for the spectra based on 1^st derivative test could provide optimal performance with the determination coefficients for calibration and validation sets of 0.884 and 0.863, RMSEC and RMSEP of 0.170 and 0.191, respectively. The spectral range also affected mathematical models. The performance for the PLSDA models over the spectral range of 750-1 000 nm overall was better, especially for the spectra based on Savitzky-Golay smoothing pre-processing method, which could provide noticeable improvement for model performance. The models for the original spectra and the spectra based on Savitzky-Golay smoothing pre-processing method in calibration and validation sets had optimal sensitivity and specificity, which suggested that the recognition rate for calibration and validation sets could reach 100%. Thus, visible and near-infrared spectroscopy can recognize the geographic origin of chestnut.