Nicholas Birse

AI promises to solve cost, labor, and regulatory challenges, but a shortage of deployment expertise means it can create more problems than it solves.

Deborah McKenzie, Chris Elliott, Michele Suman, and Nicholas Birse summarize their thoughts on food adulteration and fraud and provide a personal “call‑to‑action" to share with analytical scientists working to protect the integrity of food in the supply chain.

Are chemometrics and artificial intelligence (AI) currently delivering real value in relation to pattern recognition, anomaly detection, and spectral libraries in food fraud and food adulteration applications? The panel explore potential risks when chemical understanding is not strong enough.

Nontargeted high-resolution mass spectrometry (HRMS) workflows are getting a lot of attention. The panel explore where these worklows are genuinely advancing authenticity testing, and if these workflows are meeting expectations.

Food matrices are notoriously complex. The panel explore how to overcome the biggest challenges to develop validated, reproducible methods that hold up across regions, seasons, and suppliers.

The limitations of current analytical techniques in food adulteration and food fraud are explored and complementary techniques that can enhance results are discussed.

Food is one of the most challenging matrices to analyze in terms of complexity. The panelists explore the role that chromatography plays in food authenticity and food fraud applications to successfully analyze such complex matrices.

The panelists explore how food authenticity is defined in today’s global supply chain, and how that definition has evolved as fraud has become more sophisticated and difficult to detect.

The panelists introduce themselves and describe their expertise in separation science and experience in food authenticity and food fraud research.