The main results of the project will be the following:

1. A complete and functional fresh fruit and vegetable inspection protocol that will contain revolutionary techniques that combine low cost and short completion time which are considered necessary for the identification of bacteria.
2. A low cost extraction and Rapid DNA Isolation and Isothermal PCR Protocol to Increase Analytical Sensitivity for Bacterial Identification. Various extraction methods will be used in order to improve the concentration and purity of the extracted DNA. DNA extraction efficiency will be compared with standard methods (eg spectrophotometry and quantitative Real Time-PCR).
3. The control protocol will include procedures for full traceability of fresh fruits and vegetables based on the continuous recording of events throughout the supply chain using an Internet of Things infrastructure and adopting the intensive use of international standards (UNECE, GS1).
4. Online blockchain technology platform that will support full traceability regarding the safety of fresh fruits and vegetables by focusing on identifying emerging risks throughout the supply chain.

The individual sections of the electronic blockchain platform, that will be developed within the framework of the project, are the following:

1. Quality Module: Tool for monitoring quality control procedures and related measurements/analysis results, according to the control assurance protocol that is to be developed.
2. Farm Module: Detailed information on applications that are to be made at field/greenhouse level and that are associated with risk factors.

The following modules developed on the KalaΘos platform will also be adapted:  

1. IoT Module: Connecting crops and products with information that are to be collected with the help of sensors, by using Internet of Things technologies to transfer the data. The export and download of the information will be done from relevant IoT platforms by using open APIs.
2. External Trace & Internal Trace Module: External and internal tracing tool using GS1 global standards.
3. Consumer Module: Consumers will be provided with information regarding products, from the field to the shelf, by using TraceID or QR codes as well as beacons.

The detailed and accurate information provided about a specific product will focus on food safety issues. Decision Support System using Artificial Intelligence (AI) algorithms to analyze risk models according to the data that will be collected on the platform from the checks that will be carried out and from the actions and measurements at various stages of the production process. DSS will follow the modular architecture of diviz, giving analysts the opportunity to apply alternative decision theory models depending on the data type and the risk evaluation.