Application of Wavelength Selection Combined with DS Algorithm for Model Transfer between NIR Instruments

Abstract

This study aims to realize the sharing of near-infrared analysis models of lignin and holocellulose content in pulp wood on two different batches of spectrometers and proposes a combined algorithm of SPA-DS, MCUVE-DS and SiPLS-DS. The Successive Projection Algorithm (SPA), the Monte-Carlo of Uninformative Variable Elimination (MCUVE) and the Synergy Interval Partial Least Squares (SiPLS) algorithms are respectively used to reduce the adverse effects of redundant information in the transmission process of the full spectrum DS algorithm model. These three algorithms can improve model transfer accuracy and efficiency and reduce the manpower and material consumption required for modeling. These results show that the modeling effects of the characteristic wavelengths screened by the SPA, MCUVE and SiPLS algorithms are all greatly improved compared with the full-spectrum modeling, in which the SPA-PLS result in the best prediction with RPDs above 6.5 for both components. The three wavelength selection methods combined with the DS algorithm are used to transfer the models of the two instruments. Among them, the MCUVE combined with the DS algorithm has the best transfer effect. After the model transfer, the RMSEP of lignin is 0.701, and the RMSEP of holocellulose is 0.839, which was improved significantly than the full-spectrum model transfer of 0.759 and 0.918.