The application of artificial intelligence in food fraud and adulteration analysis: a review

Key Points

• The research aims to evaluate how artificial intelligence can improve methods of detecting food fraud and adulteration across the food supply chain.
• Review of current analytical techniques and their limitations
• Analysis of artificial intelligence and machine learning applications
• Discussion of challenges in implementing AI technologies in the food industry
• Identification of future directions for intelligent fraud detection systems
• AI and machine learning offer faster and more efficient food fraud detection compared to traditional methods.
• Integration of these technologies can lead to predictive capabilities for preventing fraud.
• Challenges such as data quality and implementation costs remain significant.

Abstract