This projects aims at gaining consumer trust through improving the transparency of the supply chain using rapid-reactive and proactive risk management using a combination of technologies such as block chain, predictive analytics and multi-analytical tests
The need to radically improve ingredient supply management from highly complex supply chains due to accidental contamination, fraud and food terrorism has never been greater. Food fraud alone costs an estimated $US49b per year to the global food industry. The purpose of this project it to identify, manage mitigate and predict risks of chemical contamination and fraud in the food supply chain. The project will concentrate on 2 supply chains as a model: red meat;herbs and spices.
AZTI will develop rapid methods for the detection of key fraud and contaminant parameters based on two different technologies. On one hand RPA (Recombinase Polymerase Amplification) technology will allow the rapid on-site meat authentication and on the other hand enzyme-based biosensor technology will be applied to the screening of key chemical contaminants (i.e. PCBs and dioxins). The new kits will be compared with standard reference methodologies and validated in terms of sensitivity, reproducibility, accuracy and robustness.
AZTI, Queen’s University Belfast, Sodexo, ABP Food Group, Waitrose, Analytics Engines
EIT Food IVZW