摘要： We applied near-infrared (NIR) spectroscopy with chemometrics for the rapid and reagent-free analysis of serum urea nitrogen (SUN). The modeling is based on the average effect of multiple sample partitions to achieve parameter selection with stability. A multiparameter optimization platform with Norris derivative filter–partial least squares (Norris-PLS) was developed to select the most suitable mode (d = 2, s = 33, g = 15). Using equidistant combination PLS (EC-PLS) with four parameters (initial wavelength I, number of wavelengths N, number of wavelength gaps G and latent variables LV), we performed wavelength screening after eliminating high-absorption wavebands. The optimal EC-PLS parameters were I = 1228 nm, N = 26, G = 16 and LV = 12. The root-mean-square error (SEP), correlation coefficient (RP) for prediction and ratio of performance-to-deviation (RPD) for validation were 1.03 mmol L?1, 0.992 and 7.6, respectively. We proposed the wavelength step-by-step phase-out PLS (WSP-PLS) to remove redundant wavelengths in the top 100 EC-PLS models with improved prediction performance. The combination of 19 wavelengths was identified as the optimal model for SUN. The SEP, RP and RPD in validation were 1.01 mmol L?1, 0.992 and 7.7, respectively. The prediction effect and wavelength complexity were better than those of EC-PLS. Our results showed that NIR spectroscopy combined with the EC-PLS and WSP-PLS methods enabled the high-precision analysis of SUN. WSP-PLS is a secondary optimization method that can further optimize any wavelength model obtained through other continuous or discrete strategies to establish a simple and better model.