Abstract: To obtain the effect and quantitative information of water components in sweet corn by different blanching temperature, Statistical analysis system (SAS) was applied to deal with lowfield nuclear magnetic resonance (LFNMR) data of blanched sweet corn. Statistic analysis on batch raw data of LFNMR was performed by SAS system, including exponential fitting, principal component analysis (PCA) and partial least squares regression (PLSR). The corresponding SAS codes were provided. The fitting result of multiexponential model indicates that the percentages of two components with relaxation times (405-750 ms) and (50-70 ms) change distinctly. Three blanching temperature ranges: 20-40, 50-70 and 80-100 °C are roughly discriminated by PCA. PLSR does well in prediction of bound water in blanched sweet corn (determined coefficient is 0.974, root mean square error of crossvalidation is 0.32%). From the whole data processing, SAS programming performs efficiently on data management and analysis and gives valuable reference for LNNMR application.