Fraud Detection in Meat Using Hyperspectral Imaging

Research output: Contribution to journalArticlepeer-review


Fraud detection in meat is a challenging task for researchers, consumers, industries, and regulatory agencies. Traditional approaches for fraud detection are time-consuming, complicated, laborious, and expensive; they require technical skills. Therefore, much effort has been devoted in academia and industry to developing rapid and nondestructive optical techniques for fraud detection in meat. Among them, hyperspectral imaging has gained enormous attention and curiosity throughout the world. Hyperspectral imaging is an emerging analytical technique that combines spectroscopy and imaging in one system to acquire spectra and spatial information from an object simultaneously. Hyperspectral imaging is the only analytical technology that answers commonly asked analytical questions such as what chemical species are in the samples, how much, and most importantly, where they are located. Therefore, the technology will undoubtedly play indispensable roles in research and industry for fraud detection in the coming days.

Original languageEnglish (US)
Article number2
JournalMeat and Muscle Biology
Issue number3
StatePublished - 2021


  • adulteration
  • fraud detection
  • hyperspectral imaging
  • machine learning
  • minced meat

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Food Science


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