data sharing (2)

11005123687?profile=RESIZE_710xDo you have an authenticity database or datasets?

The Food Authenticity Network (FAN) is undertaking a project on ‘Open Data’ funded by its Government Partners, which seeks to collate of list of organisations that have food authenticity datasets i.e. assessed foods or beverages against a reference database of authentic samples. This could be any analytical, physical or sensory testing technique, or combination of techniques, that matches against patterns of multivariate data.

We are interested to know about both proprietary in-house reference databases and uses of shared data sets. We would like to include both laboratories offering a current testing service and research groups and others who hold data from previous projects.

Photo by Markus Spiske on Unsplash

If you have, or use, reference datasets for an “authentic” food or beverage and are willing for this to be signposted on the FAN website then please contact:

Thank you

Food Authenticity Network Executive Team

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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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