Best Practices

Best Practices

Enhancing traceability and transparency across EU food systems

The Watson project has collected and assessed best practices and replicable activities in various food systems, focusing on solutions, use cases, tools, and methodologies that demonstrate traceability, transparency and authenticity.

These practices are designed to generate synergies with Watson and deliver mutual benefits for producers, technology providers and consumers. They include both general initiatives improving food system integrity and specific examples directly linked to Watson’s use cases.

Selected best practices by category

Watson has identified 10 best practices across multiple thematic areas. These practices leverage innovative technologies such as AI, DNA-based methods, blockchain, and decision support systems to enhance food safety, quality and sustainability.

The best practices were drawn from projects and initiatives including ALLIANCE, TITAN, FAIRCHAIN, Ploutos, CO-FRESH, and the private company Intertek.

The selected best practices have been carefully assessed for their potential to positively impact food systems. Their value lies in several key aspects:

  • Effectiveness: Improve traceability, authenticity, safety and sustainability across food supply chains.
  • Efficiency: Provide cost- and time-efficient solutions for all stakeholders, from producers to consumers.
  • Ethics: Promote transparency, fairness and build consumer trust.
  • Innovation: Introduce cutting-edge technologies and methodologies with transformative potential.
  • Scalability: Solutions can be adapted and expanded across different products, regions and supply chains.
General Initiatives

G01: Use of NIR and HSI Technologies to Detect Alteration in PGI Faba Beans

This best practice involves the use of portable Near Infrared (NIR) and Hyperspectral Imaging (HSI) technologies, developed within the ALLIANCE Project in Asturias (Spain), to detect adulteration in PGI Asturian Faba beans. Targeting producers, packaging managers and certification bodies, the approach leverages AI- and ML-driven chemometric models to provide fast, non-destructive, on-site authentication. This approach enhances traceability and ensures product authenticity, boosting consumer confidence.

  • Effectiveness: Analyses 100% of lots with data-driven results
  • Efficiency: Low-cost, non-destructive, rapid on-site method; easy to use
  • Ethics: Inclusive of all supply chain stakeholders; no ethical concerns
  • Innovation: Real-time, on-site testing not available in other methods
  • Scalability: Applicable to other PGI products; usable by all stakeholders to verify authenticity

G03: Digital Tools for Consumers – Transparency on Sustainability

This best practice, developed within the CO-FRESH project in Almería (Spain), involves UNICA Group, a second-tier cooperative, supporting healthy diets and sustainability through an online product box of fresh fruit and vegetables. Targeting farmers, processors, transporters, input suppliers and consumers, the initiative aims to reduce food waste from mainstream supply chains while providing easy-to-use digital tools, such as QR codes on the boxes, to share detailed information about products and producers. Primarily involving family farmers selling through cooperatives, this approach generates consumer transparency reports covering traceability and certifications and enhances the UNICA website with expanded product information.

  • Effectiveness: Direct access to product and producer information, improving traceability, authenticity and sustainability
  • Efficiency: Immediate traceability, though success depends on platform creation, stakeholder training and cost considerations
  • Ethics: Includes all stakeholders in the supply chain with no ethical concerns
  • Innovation: Richer product information, consumer customisation, sustainable packaging and food-waste reduction
  • Scalability: Expanding to large or cross-border supply chains is challenging due to regulatory, operational and coordination complexities

G16: Omics and Molecular Approaches to Enhance the Safety and Quality of Fermented Foods and Supplements

This best practice, developed within the TITAN project in Italy, focuses on enhancing the safety and quality of fermented foods and supplements through a high-resolution metabarcoding protocol using Highly Polymorphic and Modular Extragenic (HPME) markers. Traditional 16S rRNA and ITS methods do not provide sufficient resolution, so the pilot targets key genera such as Lactobacillus, Bifidobacterium, and Bacillus to achieve precise species- and subspecies-level identification. The HPME-based metabarcoding approach, combined with optimised workflows for DNA extraction, sequencing, and bioinformatics, delivers a robust and reliable method for verifying microbial composition in probiotic supplements, fermented foods and products containing added microbial cultures.

  • Effectiveness: Accurate, high-resolution identification of microbial species for reliable quality and safety control
  • Efficiency: Streamlined workflows and automation enable fast, resource-efficient analysis
  • Ethics: Ensures product safety, transparency and responsible data use
  • Innovation: Introduces advanced HPME metabarcoding and scalable protocols for precise microbial analysis
  • Scalability: Workflows and tools can expand across microbial genera and industrial applications

O02: DNA Fingerprinting to Detect and Prevent Fraud in PDO/PGI Extra Virgin Oil 

This best practice, developed within the ALLIANCE project in Italy, uses DNA-based authentication to detect and prevent food fraud in olive oil (OO) and extra virgin olive oil (EVOO). Targeting tech providers, producers, importers/exporters, wholesalers and companies producing private-label olive oils, the technology generates a unique genetic ID for each product, verifying the olive variety composition and ensuring authenticity from field to store. DNA profiling makes adulteration nearly impossible while supporting agro-biodiversity and adding value to local olive cultivars. Aligned with the EU Green Deal’s Farm to Fork strategy, this approach enhances transparency, traceability and consumer confidence.

  • Effectiveness: High-throughput DNA analysis and farm-to-shelf monitoring to ensure food safety, authenticity and sustainability
  • Efficiency: Integrates easily with AI/ML systems and distributed ledgers, reducing time and costs
  • Ethics: Complies with standards and governance systems with no identified ethical concerns
  • Innovation: Transformative genetic analysis with seamless integration into existing workflows
  • Scalability: Broad adoption potential across geographies, stakeholders and food system value chains

O03: DNA-based Rapid Detection Method to Ensure Olive Oil Authenticity 

This best practice, developed within the TITAN project across the Mediterranean region, focuses on ensuring olive oil authenticity and protecting autochthonous olive varieties from adulteration. Targeting technology providers, producers, and international organisations such as the International Olive Council, it combines DNA-based identification of olive varieties with stakeholder engagement across countries including Cyprus, Turkey, Portugal and Spain. Key achievements include the development of portable DNA detection systems, identification of single nucleotide polymorphisms (SNPs) and integration with blockchain for secure traceability, preventing adulteration and ensuring product quality.

  • Effectiveness: Reliable, on-site DNA-based traceability and fraud prevention, improving transparency, safety and sustainability
  • Efficiency: Portable, rapid and AI/ML-integrated analysis, though it requires significant operational investment
  • Ethics: Delivers objective and unbiased results, with compliance and governance ensuring ethical operation
  • Innovation: Transformative DNA-based approach that complements existing quality control systems
  • Scalability: Strong potential for adoption across regions, stakeholders and other food value chains

CD01: Trustworthy Information Sharing from Local Dairy Production Using Blockchain

This best practice, developed within the FAIRCHAIN project in Greece, leverages blockchain technology as a distributed ledger to ensure trustworthy information registration and verification by consumers. Targeting farmers and cooperatives, industry and retail actors, policymakers and technology providers, the approach applies end-to-end monitoring and recording of information throughout the production of Feta cheese as part of the project, enhancing transparency, traceability and consumer confidence.

  • Effectiveness: Transparency, traceability and consumer trust in Feta cheese production through secure, end-to-end blockchain records
  • Efficiency: Data collection and access across production stages, reducing administrative burden and supporting faster, informed decisions
  • Ethics: Ensures truthful product information, protects PDO integrity and promotes fairness across the supply chain
  • Innovation: Integrates blockchain with traditional Feta production, translating complex data into consumer-friendly insights via a mobile app
  • Scalability: Can be adapted to other PDO products, additional suppliers and international markets, supporting cross-border traceability and replication across value chains

CD02: Blockchain to Build Trust, Transparency and Accountability in PDO Feta Cheese

This best practice, developed within the ALLIANCE project in Greece, uses blockchain technology to create a secure, tamper-proof data layer that enhances trust, transparency and accountability in the Feta cheese supply chain. Targeting producers, supply and storage operators, manufacturers, distributors and supermarkets, the case study at OLYMPOS, a leading Greek dairy producer, focuses on improving PDO Feta production. Using Hyperledger Fabric, the solution secures the supply chain and enables reliable data verification, while the DAHBSIM bio-economic model provides insights into farmers’ decision-making to support more informed production choices.

  • Effectiveness: Transparent, tamper-proof data layer across the Feta cheese supply chain
  • Efficiency: Automates verification, streamlines information flow and enables rapid scenario simulations, reducing administrative overhead and errors
  • Ethics: Ensures data integrity, fair farmer compensation, consumer protection and responsible governance aligned with PDO standards
  • Innovation: Integrates blockchain, AI, and behavioural science with bio-economic modelling to advance digital transformation and evidence-based policymaking in dairy production
  • Scalability: Broad applicability to other dairy and agri-food value chains, with modular, adaptable systems that support expansion across stakeholders, regions and markets

CD04: Better Food-Chain Contracts for Durum Wheat Production Through the Use of a Decision Support System 

This best practice, developed within the Ploutos project in Italy as part of the Sustainable Innovation Pilot 2, focuses on ensuring high-quality durum wheat production through sustainable crop management. Targeting technology providers and farmers, it promotes the adoption of the Decision Support System (DSS) granoduro.net, enabling farmers to implement optimal agricultural practices and maximise crop performance while optimising the use of technical inputs. Additionally, a parametric insurance mechanism, designed using DSS model outputs, safeguards farmer revenues in case of reduced grain yield or quality caused by uncontrollable weather events, supporting both productivity and economic resilience.

  • Effectiveness: Supports farmers in applying optimal, sustainable practices, improving yield, quality, and revenue security through DSS guidance and parametric insurance
  • Efficiency: Cost-effective input use, fast data-based verification, and streamlined farm and insurance management
  • Ethics: Fairness, inclusivity, climate-risk protection and responsible environmental practices across the durum wheat value chain
  • Innovation: Combines advanced analytics, IoT, blockchain, and DSS knowledge transfer to modernise farm management and strengthen contractual stability
  • Scalability: Potential expansion to other regions and cereal crops, supported by collaborative value chains, digital infrastructure and adaptable insurance models

H03: Better Analysis and Tracking of Honey Through Blockchain – HoneyTrace 

This best practice, developed by Intertrek in Germany, implements HoneyTrace, a hive-to-jar traceability solution for honey. Targeting beekeepers, exporters, importers, packers and retailers, it combines blockchain technology with Intertek’s extensive industry expertise to analyse, track and verify honey throughout the supply chain, enhancing transparency, authenticity and consumer trust.

  • Effectiveness: End-to-end hive-to-jar visibility, verifying honey authenticity and reducing adulteration risks in real time
  • Efficiency: Data access, supplier monitoring and risk assessment through a centralised, AI-enabled platform
  • Ethics: Promotes transparency, fairness and consumer protection while ensuring secure, responsible management of supplier data
  • Innovation: Integrates AI, predictive risk modelling and visual analytics to deliver proactive, real-time supply chain insights
  • Scalability: Cloud-based platform can expand to additional suppliers, product categories and other high-risk commodity chains, though broader adoption depends on data standardisation, availability and improved predictive accuracy

H04: Real-Time & Intelligent Data Sharing for Verification of Honey and Herbs Suppliers

This best practice, developed within the TITAN project in Greece, enhances transparency and food safety in the honey and herbal product sectors through real-time data sharing and AI-powered risk assessments. Targeting food industry actors and providers, it integrates diverse data sources for comprehensive supplier monitoring, applies predictive risk models to anticipate potential issues and offers a user-friendly platform that enables companies to make informed, proactive decisions across their supply chains.

  • Effectiveness: Diverse data sources and AI-driven analytics to provide real-time supplier risk insights, improving visibility and decision-making for honey and herbal products
  • Efficiency: Supplier monitoring and data management, enabling faster, more informed risk assessments despite current limitations in data completeness and model accuracy
  • Ethics: Fairness, transparency, and consumer protection through standardised, secure and responsible AI-based evaluations
  • Innovation: First-of-its-kind AI platform with predictive risk modelling, visualisation tools and real-time monitoring for proactive food safety management
  • Scalability: Cloud-based, modular platform supports expansion to additional suppliers, categories, regions and high-risk commodity chains, with adaptability dependent on data standardisation and collection improvements