文献类型：期刊文献

英文题名：Application of SWCSS-DS algorithm in the transfer of near infrared analysis model for holocellulose in pulpwood

作者：Wang, Honghong[1] Wang, Ying[1] Huang, Haoran[1] Xiong, Zhixin[1] Hu, Yunchao[1] Liu, Zhijian[1] Liang, Long[2]

第一作者：Wang, Honghong

机构：[1] College of Light Industry and Food Engineering, Nanjing Forestry University, Nanjing, 210037, China; [2] Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing, 210042, China

年份：2024

卷号：43

期号：6

起止页码：864-870

外文期刊名：Chinese Journal of Analysis Laboratory

收录：EI(收录号：20242816662122)

语种：英文

外文关键词：Infrared devices - Mean square error - Near infrared spectroscopy - Spectrometers - Standardization

摘要：In this paper， the holocellulose content model in pulpwood was transferred and analyzed to solve the problem that the multivariate calibration models between different near-infrared spectrometers could not be shared. The wavelength with stable and consistent spectral signals （SWCSS） between the instruments algorithm was used to select the wavelength with better stability， and the direct standardization （DS） method was used to further correct the systematic errors that still exist after being corrected by the SWCSS method. The combined algorithm can improve the universality of the master model， reduce the dimension of the spectral matrix， and make the model transfer more stable and simpler. The results of this work were compared with the transfer results corrected by SWCSS， DS and piecewise direct standardization （PDS） algorithm. The results showed that the root mean squared error for prediction （RMSEP） of the SWCSS-DS combined algorithm for two slave samples decreased from 2.48 and 2.31 to 1.05 and 1.07， respectively， compared with the pre-transfer analysis ability of the model， which was better than the results of the single SWCSS， DS and PDS algorithms. ? 2024, Youke Publishing Co.,Ltd. All rights reserved.