@article{a0c42a47207847e690697c9e5610c7bb,
title = "Chemometrics in instrumental analysis of complex systems—in honor and memory of Yi-Zeng Liang",
abstract = "A true pioneer in the fields of chemometrics and analytical chemistry was lost with the passing of Yi-Zeng Liang in October 2016. This is an enormous loss to both the local and global community of chemometrics. Yi-Zeng Liang is recognized as one of the major players in China in the field of chemometrics. As a professor of chemometrics and analytical chemistry in Hunan University and Central South University, he made significant advances within instrumental analysis of complex systems. Liang inspired many students and visiting scholars. As Liang's former students, we have attempted to summarize Liang's contributions to the field over the past 30 years. This review covers different chemometric areas, signal preprocessing, multivariate curve resolution, and multivariate calibration and discusses the application of these methods in traditional Chinese medicine, metabolomics, proteomics, and quantitative structure-activity relationship research.",
keywords = "chemometrics, complex systems, instrumental analysis, Yi-Zeng Liang",
author = "Zhimin Zhang and Hongdong Li and Yonghuan Yun and Pan Ma and Lunzhao Yi and Dabing Ren and Liangxiao Zhang and Jun Yan and Naiping Dong and Baichuan Deng and Hongmei Lu",
note = "Funding Information: During 1990 to 1992, Liang received a postdoctoral fellowship from Royal Norwegian Council for scientific and industrial research (NTNF). He collaborated with his coworkers, Prof. Kvalheim and Prof. Manne, and proposed a widespread and powerful notion, ie, white, gray, and black multicomponent systems. They divided mixture samples into white, gray, and black categories according to their complexity, ie, how much information of their chemical components is known in priori17 and developed a series of multivariate curve resolution (MCR) methods to resolve the qualitative and quantitative problem of complex multicomponent systems. Heuristic evolving latent projection (HELP),18proposed in 1992, was one of the most well‐known noniterative resolution methods for two‐way data analysis. The full‐resolution procedure for the HELP method is described in the following steps and illustrated in Figure 2: 1. Confirm and correct the drifting baseline. Funding Information: National Natural Science Foundation of China, Grant/Award Numbers: 21675174, 21873116 and 21705162 Funding Information: The authors gratefully thank the National Natural Science Foundation of China for their support of the projects (grant nos. 21675174, 21873116, and 21705162). Publisher Copyright: {\textcopyright} 2018 John Wiley & Sons, Ltd.",
year = "2018",
month = nov,
doi = "10.1002/cem.3095",
language = "English",
volume = "32",
journal = "Journal of Chemometrics",
issn = "0886-9383",
publisher = "John Wiley and Sons Ltd",
number = "11",
}