Multi-way analysis coupled with near-infrared spectroscopy in food industry : models and applications
|Author:||Yu, Huiwen1; Guo, Lili2,3; Kharbach, Mourad4;|
1Chemometric and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark
2Department of Plant and Environmental Science, Faculty of Science, University of Copenhagen, Højbakkegaard Alle 13, DK-2630 Taastrup, Denmark
3College of Water Resources and Architectural Engineering, Northwest A&F University, Weihui Road 23, Yangling 712100, China
4Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland
5School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China
|Online Access:||PDF Full Text (PDF, 0.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021051830379
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2021-05-18
Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way models which were used for analyzing NIRS data, as well as the advances, advantages and limitations of different multi-way models. The applications of multi-way analysis in NIRS for the food industry in terms of food process control, quality evaluation and fraud, identification and classification, prediction and quantification, and image analysis are also reviewed. It is evident from this report that multi-way analysis is presently an attractive tool for modeling complex NIRS data in the food industry while its full potential is far from reached. The combination of multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding about food systems and food processes. To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of multi-way analysis in NIRS for the food industry.
|Type of Publication:||
A2 Review article in a scientific journal
|Field of Science:||
215 Chemical engineering
This research was funded by the PARADISe Project of Danish Dairy Research Foundation and the Program of China Scholarship Council (201807080012).
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).