Pilots for food safety

Demonstration of traceability and authenticity in the olive supply chain

This pilot will use Open Food Chain, the blockchain technology developed by The New Fork, to ensure traceability and authenticity along the olive oil value chain. Blockchain technology will work in combination with the micro- and nano-fabricated miniaturized DNA devices that are newly developed by INL for the identification of olive varieties and adulteration with other seeds. This improved traceability system enables corrective actions and, consequently, reduces the risk of adulteration and enhances food safety.

Development of a traceability system and food safety testing for the presence of undeclared food allergens

This pilot will focus on artificial intelligence (AI) applications in the detection of allergens in the cereal supply chain with a focus on wheat. The test will be extended to demonstrate the efficiency of applications for olive oil and mustard. A combination of AI-based traceability tools and nanotechnology-based and user-friendly detection systems for food allergens will be used to reduce the number of samples needed to provide meaningful insights to make the supply chain more secure and protect consumers.

Microbiology of fermented food products, safety demonstration of food cultures

This pilot will develop and validate Next-Generation-Sequencing (NGS) analytical methods for fermented dairy products and plant-based fermented dairy alternatives. The NGS analytical methods will allow the rapid differentiation between inoculated and not inoculated species. Thus, the composition of muti-strain cultures applied to foods for fermentation and bio-preservation, and the minimum viable quantity of designed probiotic species will be monitored during fermentation.

Omics and molecular approaches for microbial and chemical quality of long shelf-life food products

The main goal of this pilot is to ensure the food safety of plant-based beverages and supplements through advanced analytical techniques such as third-generation sequencing technologies and liquid chromatography coupled with mass spectrometry. These techniques will assess the presence of spore-forming pathogenic contaminants and chemical contaminants (i.e., crop protection products and mycotoxins). In addition, the presence of antibiotic-resistance genes and virulence factors can be also evidence. 

Real-time & intelligent data sharing for verification of honey and herbs suppliers

This pilot will use artificial intelligence (AI) and blockchain technologies to enhance transparency and assess the safety risks in organic honey and herb products. An AI-powered online dashboard will help food buyers take fast and cost-efficient decisions by running intelligent risk assessments of suppliers from a distance and will allow suppliers to share data of relevance with their buyers in a secure, easily customizable, and automated manner.