文献类型：期刊文献

英文题名：Calibration transfer of near-infrared spectra for extraction of informative components from spectra with canonical correlation analysis

作者：Zheng, Kaiyi[1,2];Zhang, Xuan[1,2];Iqbal, Jibran[3];Fan, Wei[4];Wu, Ting[1,2];Du, Yiping[1,2];Liang, Yizeng[4]

机构：[1]E China Univ Sci & Technol, Shanghai Key Lab Funct Mat Chem, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Res Ctr Anal & Testing, Shanghai 200237, Peoples R China;[3]COMSATS Inst Informat Technol, Interdisciplinary Res Ctr Biomed Mat, Lahore, Pakistan;[4]Cent South Univ, Coll Chem & Chem Engn, Res Ctr Modernizat Chinese Med, Changsha 410083, Hunan, Peoples R China

年份：2014

卷号：28

期号：10

起止页码：773

外文期刊名：JOURNAL OF CHEMOMETRICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000344323400006)】；

基金：This work was supported by the National Natural Science Foundation of China (20975039 and 21205041).

语种：英文

外文关键词：calibration transfer; CCA; PLS; PDS; NIR

摘要：A new calibration transfer method that applies canonical correlation analysis (CCA) to transfer the informative components extracted from a spectral dataset is proposed to reduce the interference of noise, background and non-predicted properties. This method employs the partial least squares method to extract the informative components related to the predicted properties from the raw spectra and then corrects the informative components based on CCA. The performance of this algorithm was tested using three pairs of spectra batches: two pairs of corn spectra and one pair of tri-component solvent spectra. The results showed that this method can significantly reduce prediction errors compared with CCA and piecewise direct standardization. Copyright (c) 2014 John Wiley & Sons, Ltd.