University of Oulu

Kharbach M, Alaoui Mansouri M, Taabouz M, Yu H. Current Application of Advancing Spectroscopy Techniques in Food Analysis: Data Handling with Chemometric Approaches. Foods. 2023; 12(14):2753.

Current application of advancing spectroscopy techniques in food analysis : data handling with chemometric approaches

Saved in:
Author: Kharbach, Mourad1,2; Alaoui Mansouri, Mohammed3,4; Taabouz, Mohammed5;
Organizations: 1Department of Food and Nutrition, University of Helsinki, 00014 Helsinki, Finland
2Department of Computer Sciences, University of Helsinki, 00560 Helsinki, Finland
3Nano and Molecular Systems Research Unit, University of Oulu, 90014 Oulu, Finland
4Research Unit of Mathematical Sciences, University of Oulu, 90014 Oulu, Finland
5Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Rabat BP 6203, Morocco
6Shenzhen Hospital, Southern Medical University, Shenzhen 518005, China
7Chemometrics group, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.7 MB)
Persistent link:
Language: English
Published: Multidisciplinary Digital Publishing Institute, 2023
Publish Date: 2023-09-18


In today’s era of increased food consumption, consumers have become more demanding in terms of safety and the quality of products they consume. As a result, food authorities are closely monitoring the food industry to ensure that products meet the required standards of quality. The analysis of food properties encompasses various aspects, including chemical and physical descriptions, sensory assessments, authenticity, traceability, processing, crop production, storage conditions, and microbial and contaminant levels. Traditionally, the analysis of food properties has relied on conventional analytical techniques. However, these methods often involve destructive processes, which are laborious, time-consuming, expensive, and environmentally harmful. In contrast, advanced spectroscopic techniques offer a promising alternative. Spectroscopic methods such as hyperspectral and multispectral imaging, NMR, Raman, IR, UV, visible, fluorescence, and X-ray-based methods provide rapid, non-destructive, cost-effective, and environmentally friendly means of food analysis. Nevertheless, interpreting spectroscopy data, whether in the form of signals (fingerprints) or images, can be complex without the assistance of statistical and innovative chemometric approaches. These approaches involve various steps such as pre-processing, exploratory analysis, variable selection, regression, classification, and data integration. They are essential for extracting relevant information and effectively handling the complexity of spectroscopic data. This review aims to address, discuss, and examine recent studies on advanced spectroscopic techniques and chemometric tools in the context of food product applications and analysis trends. Furthermore, it focuses on the practical aspects of spectral data handling, model construction, data interpretation, and the general utilization of statistical and chemometric methods for both qualitative and quantitative analysis. By exploring the advancements in spectroscopic techniques and their integration with chemometric tools, this review provides valuable insights into the potential applications and future directions of these analytical approaches in the food industry. It emphasizes the importance of efficient data handling, model development, and practical implementation of statistical and chemometric methods in the field of food analysis.

see all

Series: Foods
ISSN: 2304-8158
ISSN-E: 2304-8158
ISSN-L: 2304-8158
Volume: 12
Issue: 14
Article number: 2753
DOI: 10.3390/foods12142753
Type of Publication: A2 Review article in a scientific journal
Field of Science: 1182 Biochemistry, cell and molecular biology
Funding: Open access funding provided by University of Helsinki.
Copyright information: © 2023 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 (