Laser induced breakdown spectroscopy as an emerging technique for olive oil, milk and honey authentication and traceability: A review
Eleni Nanou, Nefeli Pliatsika, Dimitrios Stefas, Dimitrios Polygenis, Stelios Couris
Abstract
Economic-driven food fraud has raised global concerns, prompting regulatory agencies and consumers to demand greater food transparency. Ensuring food authenticity and preventing fraud requires efficient analytical techniques that operate reliably and fast, both online and/or in situ. The present study reviews the progress made during the last years and the current state-of-the-art of Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning, for the authentication and traceability of foodstuffs. Emphasis is given to the geographical and/or animal and/or botanical origin identification/classification, the detection of adulteration, and the quality control of three essential foodstuffs, namely, olive oil, milk, and honey. The findings of the reviewed studies demonstrate the great potential of LIBS, combined with machine learning, for the efficient quality control of foodstuffs, providing a rapid, non-destructive approach for food authentication .