Citation
Abstract
The global concern for ensuring the safety and authenticity of high-quality food necessitates continuous advancements in food assessment technologies. While conventional methods of food assessment are accurate and precise, they are also laborious, destructive, time-consuming, energy-intensive, chemical-demanding, and less eco-friendly. Their reliability diminishes when dealing with large numbers of food samples. This chapter explores recent advances in non-invasive technologies for food quality assessment, including spectroscopy, optical imaging, and e-sensors. Enhanced by artificial intelligence (AI), these technologies have shown remarkable capabilities in rapid and accurate food identification, authentication, physical appraisal, early disease detection, chemical analysis, and biochemical evaluation. As a result, non-invasive technology holds the potential to revolutionize food quality assessment and assure food safety at every stage of the food supply chain.
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Additional Metadata
Item Type: | Book Section |
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Divisions: | Faculty of Engineering International Institute of Aquaculture and Aquatic Science |
DOI Number: | https://doi.org/10.1016/bs.afnr.2024.09.006 |
Publisher: | Academic Press |
Keywords: | Artificial intelligence; Authentication; Food quality; Food safety; Imaging; Non-destructive; Sensors; Spectroscopy |
Depositing User: | Scopus |
Date Deposited: | 23 Jan 2025 01:17 |
Last Modified: | 23 Jan 2025 01:17 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/bs.afnr.2024.09.006 |
URI: | http://psasir.upm.edu.my/id/eprint/114652 |
Statistic Details: | View Download Statistic |
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