Spectroscopic techniques for edible oil evaluation - Technology overview and recent applications from lab to industry
Ensuring the quality and safety of edible oils is essential for the food industry and public health. Traditional analysis methods are often slow, costly, and destructive. Spectroscopic techniques, including established methods like Raman, infrared, ultraviolet–visible, and nuclear magnetic resonance...
Saved in:
Published in | Food control Vol. 176; p. 111352 |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.10.2025
|
Subjects | |
Online Access | Get full text |
ISSN | 0956-7135 |
DOI | 10.1016/j.foodcont.2025.111352 |
Cover
Summary: | Ensuring the quality and safety of edible oils is essential for the food industry and public health. Traditional analysis methods are often slow, costly, and destructive. Spectroscopic techniques, including established methods like Raman, infrared, ultraviolet–visible, and nuclear magnetic resonance (NMR), alongside emerging approaches such as hyperspectral imaging, terahertz, and laser-induced breakdown spectroscopy, offer rapid, non-destructive, and detailed molecular insights, improving edible oil analysis. This review explores the transformative impact of these methods, highlighting their applications in compositional analysis, adulteration detection, oxidative stability assessment, and process monitoring. Recent advancements, including portable devices, chemometrics, machine learning, and sensor fusion, have expanded their practicality and precision. Despite these advantages, challenges such as standardization, validation protocols, and spectral database development remain. The review emphasizes the significant impact of these techniques on food safety and transparency. It suggests future research integrating spectroscopy with nanotechnology, microfluidics, and IoT to enhance capabilities in the edible oil sector. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0956-7135 |
DOI: | 10.1016/j.foodcont.2025.111352 |