This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 861915. Coordinated by George-John Nychas gjn@aua.gr

“Digital Technologies as an enabler for a continuous transformation of food safety system”
DiTECT – H2020- SFS-37-2019 – 861915-2
Learn more
“Digital Technologies as an enabler for a continuous transformation of food safety system”
DiTECT – H2020- SFS-37-2019 – 861915-2
Learn more
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What is DiTECT?

Bringing together research, industrial and food authority partners representing the agro-food industry in the EU and China, DiTECT aspires to establish the foundation for future food safety monitoring platforms, through the development of a standards-based, modular, Big Data-enabled platform, capable of accurately predicting food safety parameters of a given food product based on data collected in real-time via cost-efficient sensors, at crop, grain storage, livestock and finally in the food supply, incorporating blockchain processes.

Midterm Evaluation

Midterm Evaluation   The DiTECT project has reached 18 months...

Bringing together research, industrial and food authority partners...

…representing the agro-food industry in the EU and China, DiTECT aspires to establish the foundation for future food safety monitoring platforms, through the development of a standards-based, modular, Big Data-enabled platform, capable of accurately predicting food safety parameters of a given food product based on data collected in real-time via cost-efficient sensors, at crop, grain storage, livestock and finally in the food supply, incorporating blockchain processes.

DiTECT integrates multidisciplinary research teams...

…from fields such as microbial and spectroscopic fingerprinting technologies; emerging ICT-based food tracing systems; signal analysis and data mining. Microbial profiling will be attained via conventional microbiological analyses in tandem with advanced molecular methods (e.g., NGS-based metagenomics), while spectroscopic profiling will be based on spectral data generated using appropriate rapid, non-invasive methods and sensor devices.

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