Affiliations 

  • 1 Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
  • 2 Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia; SMART Farming Technology Research Centre, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia; Institute of Aquaculture and Aquatic Sciences (I-AQUAS), Universiti Putra Malaysia, Port Dickson, Negeri Sembilan, Malaysia. Electronic address: norhashila@upm.edu.my
Adv Food Nutr Res, 2025;114:301-352.
PMID: 40155087 DOI: 10.1016/bs.afnr.2024.09.006

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.