Author(s)

Yihui Yang, Tao Pan, Jing Zhang^*

Department of Optoelectronic Engineering, Jinan University, Guangzhou, China.

Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stability. A large-scale parameter cyclic and global optimization platform for Norris derivative filter (NDF) of three parameters (the derivative order: d, the number of smoothing points: s and the number of differential gaps: g) was developed with PLS regression. Meantime, the parameters’ adaptive analysis of NDF algorithm was also given, and achieved a significantly better modeling effect than one without spectral pre-processing. After eliminating the interference wavebands of saturated absorption, the modeling performance was further improved. In validation, the root mean square error (SEP), correlation coefficient (R_P) for prediction and the ratio of performance to deviation (RPD) were 1.66 mmol∙L^-1, 0.966 and 4.7, respectively. The results showed that the high-precision analysis of SUN was feasibility based on NIR spectroscopy and Norris-PLS. The global optimization method of NDF is also expected to be applied to other analysis objects.

Near-Infrared Spectral Analysis, Serum Urea Nitrogen, Norris Derivative Filter, Norris-Partial Least Squares, Global Optimization

Yang, Y. , Pan, T. and Zhang, J. (2019) Global Optimization of Norris Derivative Filtering with Application for Near-Infrared Analysis of Serum Urea Nitrogen. American Journal of Analytical Chemistry, 10, 143-152. doi: 10.4236/ajac.2019.105013.