In this study, a rapid nondestructive testing model for the textural quality of freshwater fish using near-infrared spectroscopy is developed to study the relationship between storage periods and the textural quality of freshwater fish. Spectral data for the Parabramis pekinensis fish samples were collected using the Antaris Ⅱ Fourier transform near-infrared spectrometer, and the hardness, springiness, and chewiness values of the samples were measured using the TMS PRO type structure instrument. The S-G smoothing method was used to pretreat the raw spectra, and competitive adaptive reweighting sampling, stable competitive adaptive reweighted sampling, and successive projections algorithms were integrated to extract the characteristic wavelength for the first time. Based on the above three textural indexes,the least partial square regression (PLSR) model was established. Based on the primary characteristic wavelengths extraction, the SPA algorithm was used to extract the secondary characteristic wavelengths. Then, the optimal model of hardness, springiness and chewiness of freshwater fish was established according to the extracted secondary characteristic wavelengths. The correlation coefficients R_c and R_p of the correction and prediction sets are 0.968, 0.947, and 0.927, and 0.964, 0.939, and 0.926, respectively. The root mean square error of the correction and prediction sets are 0.753, 0.827, and 0.986, and 0.846, 0.897, and 0.964, respectively. The results show that this method is suitable for rapid and nondestructive testing of the textural quality of freshwater fish in storage and has high accuracy.