Abstract: The content of moisture, tannic acid and gallic acid was an important index to evaluate the quality of Chinese gallnut. Generally, it was determined according to the forestry industry standard of the People's Republic of China, which was cumbersome and its timeliness was not guaranteed. In order to study the feasibility of rapid detection of these indicators, 130 Chinese gallnut samples were collected, and chemical values were determined by chemical method. NIR spectroscopy was used to scan Chinese gallnut samples, which was fitted with chemical values measured by traditional methods. The partial least squares(PLS) was used to build a mathematical model, and the correlation coefficient and error of the model were compared to evaluate the prediction performance of the model. The optimal pretreatment methods for moisture, tannic acid and gallic acid in gallnut were FD+MSC, FD and FD+ML, respectively. The characteristic bands of moisture were 9 403.7-7 498.2, 6 012.0-5 774.1, 4 601.5-4 246.7 cm^-1, the characteristic bands of tannic acid were 9 403.7-7 498.2, 6 102.0-4 597.7 cm^-1, and the characteristic bands of gallic acid were 6 102.0-5 446.3, 4 601.5-4 246.7 cm^-1, respectively. The number of principal factors were 9, 10 and 5, respectively. The correlation coefficients of corrected sets(R_c²) for moisture, tannic acid and gallic acid were 0.968, 0.915 and 0.926, the root mean square error of cross validation(RMSECV) were 0.72%, 2.55% and 1.47%, and the relative percent deviation(RPD) were 5.57%, 3.42% and 3.69%, respectively. The correlation coefficients of validation sets(R_p²) were 0.951, 0.891 and 0.891, and root mean square error of prediction(RMSEP) were 0.563%, 1.28% and 0.414%, respectively. The results showed that it was feasible and effective to detect the content of moisture, tannic acid and gallic acid in Chinese gallnut by NIR combined with chemometrics.