food authenticity methods (3)

10936849884?profile=RESIZE_400x  IAEA have just published a book on AI accelerating nuclear applications, science and technology.  Chapter 5 deals with AI applications to food and agriculture, and in particular to food authenticity methods, food fraud detection and traceability. The advantages and limitations for AI, and ML (machine learning) applications are discussed in sample preparation and calibration involved with authenticity methodology, the advantages of data sharing, but with the proviso that data-driven decision-making is only as good as the data used. 

Read the abstract here and the full pdf version of the book and Chapter 5 in the above link


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A Practical Guide to Food Analysis


Analytical testing at every step along the global supply chain is essential to ensure food safety, authenticity, quality and regulatory compliance and is an important component in a factory’s FSQMS (Food Safety and Quality Management System). This paper provides guidance for factory regulatory and technical managers on the basic principles behind the analytical strategies and procedures commonly used to test products in the food and drink industry. It is written by Sterling Crewe, who is Chair of the Food Authenticity Network's Board. The paper discusses the importance of choosing the right method and laboratory, and taking into account the method uncertainties and any regulatory considerations in the interpretation of the results.

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Analytical Toolbox for Food Fraud


This article summarises the authenticity analytical approaches (based on building blocks of food) to identify the most suitable procedures to prevent food fraud. The methods described are not exhaustive, but cover the majority of approaches that are currently
undertaken. In particular, DNA methodology, proteomics, chromatographic methods and stable isotope ratio analysis are discussed.

Read the full article here

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