文献类型：期刊文献

英文题名：Transfer of a calibration model for the prediction of lignin in pulpwood among four portable near infrared spectrometers

作者：Zhang, Xiaoxue[1] Chen, Xinyu[2] Xiong, Zhixin[1] Siesler, Heinz W.[2] Liang, Long[3]

第一作者：Zhang, Xiaoxue

通信作者：Xiong, ZX[1];Siesler, HW[2]

机构：[1]Nanjing Forestry Univ, Coll Light Ind & Food Engn, 159 Longpan Rd, Nanjing 210037, Peoples R China;[2]Univ Duisburg Essen, Dept Phys Chem, Schuetzenbahn 70, D-45117 Essen, Germany;[3]Chinese Acad Forestry, Inst Chem Ind Forest Prod, Nanjing, Peoples R China

年份：2022

卷号：30

期号：4

起止页码：208-218

外文期刊名：JOURNAL OF NEAR INFRARED SPECTROSCOPY

收录：;EI(收录号：20223212549771);Scopus(收录号：2-s2.0-85135471790);WOS:【SCI-EXPANDED(收录号:WOS:000835936400001)】；

基金：The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Fundamental Research Funds of Research Institute of Forest New Technology, CAF (NO. CAFYBB2019SY039).

语种：英文

外文关键词：Piecewise direct standardization; direct standardization; slope; bias correction; canonical correlation analysis; near infrared spectroscopic analysis; portable spectrometer; lignin

摘要：In order to reduce the time and cost for near infrared (NIR) model development and maintenance, the transfer of NIR spectra measured on four different portable spectrometers (one master and three target instruments) for predicting the lignin content of pulp wood is investigated in this work. Eighty-two wood samples were prepared by chipping and grinding, and their NIR spectra were recorded with four spectrometers. Calibration models for the determination of lignin in pulp wood have been developed by partial least squares (PLS) regression, while average Mahalanobis distances (AMD) and average differences of spectra (ADS) were used to quantify the spectral differences. Then piecewise direct standardization (PDS) has been applied, and compared to direct standardization (DS), slope/bias correction (SBC) and canonical correlation analysis (CCA). The accuracy of the models has been evaluated by comparing their prediction performance. The results indicated that the prediction performances of the three target instruments are greatly improved by using the three algorithms. The advantage of the PDS algorithm is that fewer samples are required for the transfer sets, which means lower model maintenance cost for practical applications. When it comes to window size setting procedure, it was found that if there are large spectral differences between the master and the target spectrometer, a large window size should be used and if the spectral difference is a significant lateral shift, an asymmetric window with appropriate window size is necessary to ensure a good transfer performance for the PDS algorithm.