文献类型：期刊文献

英文题名：Pulpwood holocellulose model transfer based on screening with consistent and stable signals algorithm

作者：Wang, Honghong[1] Li, Penghui[1] Xiong, Zhixin[1] Liang, Long[2]

第一作者：Wang, Honghong

通信作者：Xiong, ZX[1]

机构：[1]Nanjing Forestry Univ, Coll Light Ind & Food Engn, Nanjing 210037, Peoples R China;[2]Inst Chem Ind Forest Prod, Chinese Acad Forestry, Nanjing 210042, Peoples R China

年份：2024

外文期刊名：ANALYTICAL SCIENCES

收录：;EI(收录号：20241515863341);Scopus(收录号：2-s2.0-85189443985);WOS:【SCI-EXPANDED(收录号:WOS:001197088600002)】；

基金：The authors would like to express their gratitude to the Institute of Forest Products and Chemical Industry of the Chinese Academy of Forestry for the samples provided, Associate Professor ZhiXin Xiong for providing the experimental apparatus and experimental expenses, and Penghui Li for translating and revising the article and collecting the sample spectra.

语种：英文

外文关键词：Near-infrared spectroscopy; Holocellulose; SWCSS; Pre-processing; Model transfer

摘要：In this study, in order to realize the sharing of the near-infrared analysis model of holocellulose between three spectral instruments of the same type, 84 pulp samples and their content of holocellulose were taken as the research objects. The effects of 10 pre-processing methods, such as 1st derivative (D1st), 2nd derivative (D2nd), multiplicative scatter correction (MSC), standard normal variable transformation (SNV), autoscaling, normalization, mean centering and pairwise combination, on the transfer effect of the stable wavelength selected by screening wavelengths with consistent and stable signals (SWCSS) were discussed. The results showed that the model established by the wavelength selected by the SWCSS algorithm after the autoscaling pre-processing method had the best analysis effect on the two target samples. Root mean square error of prediction (RMSEP) decreased from 2.4769 and 2.3119 before the model transfer to 1.2563 and 1.2384, respectively. Compared with the full-spectrum model, the value of AIC decreased from 3209.83 to 942.82. Therefore, the autoscaling pre-processing method combined with SWCSS algorithm can significantly improve the accuracy and efficiency of model transfer and provide help for the application of SWCSS algorithm in the rapid determination of pulp properties by near-infrared spectroscopy (NIRS).