Abstract: The purpose of this study was to develop a rapid non-destructive detection on of polysaccharides in the dry red wine by the attenuating total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) with chemometric technologies. 100 dry red wines were also collected from the Xinjiang production area of western China. Alcohol precipitation was utilized to extract the wine polysaccharides from these test materials. After that, the polysaccharide powder was obtained after vacuum freeze-drying. Then, the polysaccharides were decomposed into the monosaccharides with the trifluoroacetic acid. The monosaccharides were quantitatively characterized by high high-performance liquid chromatography (HPLC-PDA). As such, the different types of polysaccharides were identified from the wine samples. The monosaccharide concentration was calculated to compare their respective characteristic structures in the molar ratio, including total soluble polysaccharides (TSP), mannosan protein (MP), arabinose-galactose-rich polysaccharides (PRAG), rhamnogalacturonic acid glycan type II (RG-II), homogalacturonized glycan (HG), and dextran (GL). The mid-infrared spectra of wine was were also collected by ATR-FTIR. The spectral preprocessing was carried out by standard normal transform (SNV) and multivariate scattering correction (MSC). The competitive adaptive reweighting algorithm (CARS) was followed for band screening. Finally, the partial least squares regression (PLSR) and backpropagation neural network (BPNN) were combined to simulate, predict and evaluate the indicators. The spectral characteristic information in the 1900~900 cm-1 band was screened to determine the content of several polysaccharide substances that were measured by HPLC-PDA. The results indicate that the content of various polysaccharide varied greatly among the test liquor samples, with the TSP content of (859.41±293.65) mg/L, MP (208.08±78.42) mg/L, PRAG (418.30±140.00) mg/L, RG-II (113.17±55.11) mg/L, GL (95.46±62.10) mg/L, and HG (24.41±55.86) mg/L. The content of several polysaccharides in the test wine samples was also verified using the linear and nonlinear correction. The ATR-FTIR model shared the a better prediction on the content of several polysaccharides in wine. The PLSR model showed the better performance than the BPNN. The coefficient of determination (R_c²) values of the PLSR model between the characteristic bands and the content of polysaccharides (TSP, MP, PRAG, RG-II, and GL) were 0.98, 0.96, 0.92, 0.99, 0.98, respectively. The coefficient of determination (R_p²) values were 0.85, 0.92, 0.83, 0.83, 0.84, respectively. The relative analysis errors (RPDc) in the training set were 6.50, 5.31, 3.62, 9.10, and 7.86, respectively. The relative analysis errors (RPDP) of the prediction set were 2.68, 3.99, 2.44, 2.52, and 2.37, respectively. Therefore, the ATR-FTIR can be expected to detect the polysaccharides in dry red wine. The content of polysaccharides can be accurately predicted in the TSP, MP, PRAG, RG-II, and GL, according to the spectral characteristic band of 1900 ~900 cm-1. The finding can provide the application potential for the rapid and nondestructive detection of polysaccharides in dry red wine.