Affiliation:
1. Department of Food and Nutrition, University of Helsinki, 00014 Helsinki, Finland
2. Department of Computer Sciences, University of Helsinki, 00560 Helsinki, Finland
3. Nano and Molecular Systems Research Unit, University of Oulu, 90014 Oulu, Finland
4. Research Unit of Mathematical Sciences, University of Oulu, 90014 Oulu, Finland
5. Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Rabat BP 6203, Morocco
6. Shenzhen Hospital, Southern Medical University, Shenzhen 518005, China
7. Chemometrics group, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark
Abstract
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.
Subject
Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science
Reference260 articles.
1. Food Adulteration;Lakshmi;Int. J. Sci. Invent. Today,2012
2. The Lancet (2009). Melamine and Food Safety in China. Lancet, 373, 353.
3. Ramesh, R., Jha, S., Lawrence, F., and Dodd, V. (2005). From Mumbai to Your Supermarket: On the Murky Trail of Britain’s Biggest Food Scandal. Guardian, 23.
4. Potential of Hyperspectral Imaging and Multivariate Analysis for Rapid and Non-Invasive Detection of Gelatin Adulteration in Prawn;Wu;J. Food Eng.,2013
5. A Review of Vibrational Spectroscopic Techniques for the Detection of Food Authenticity and Adulteration;Lohumi;Trends Food Sci. Technol.,2015