Failover

Preventive Food Fraud – Counterfeit Modeling

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To assure quality and prevent false labeling, developing a method of “fingerprinting” product samples to indicate their original source is useful. Advanced data analytics can be used to discriminate between real products and fake replicates, such as verifying that a product comes from a certain region or has a certain claimed composition.

For example, it can be used to make a distinction between Cava and Champagne wines based upon data about the trace element composition of the wines. Champagne is a much stricter controlled variety of wine than Cava, with very specific demands to qualify as a Champagne, so this type of data analytics can be useful to determine counterfeits.

It involves creating a definition based on how closely specific parameters fall from the acceptable model domain, and determining what the critical limits are in order for a wine to fall within the acceptable range.

Benefits for the company

Assures quality and distingushes from fake replicas in the market.

Feasability

High

Type of expertise/ AI domain

Principal Component Analysis

Internal data required

Input used, Quality of raw materials

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