This online course is designed to raise awareness and understanding of food authenticity across the entire food value chain. It helps participants explore what food authenticity means in practice, how to interpret food labels and certifications, and how fraudulent practices can occur from farm to fork. Open to a broad audience, the course is self-paced, requires no prior knowledge, and is available at no cost. Participants who complete all modules and quizzes receive a Certificate of Course Completion.

After completing the course, participants achieve:

• A clear understanding of what food authenticity is and why it matters.
• Increased awareness of food fraud, including common types of fraudulent practices and their potential consequences.
• Enhanced ability to act as an informed and responsible food consumer, with improved skills in interpreting labels, certifications, and product claims. 

The main added value of the course lies in its practical, consumer-oriented, and inclusive approach:

• Consumers gain confidence in making informed food choices and recognizing potential authenticity risks.
• The short, modular structure allows flexible learning with minimal time and no financial investment.

Participants can immediately apply what they learn when purchasing food, interpreting labels, assessing product claims, or managing authenticity risks within food businesses. The focus on real-world examples supports the transfer of knowledge into everyday decision-making and professional practices.

Consumers can use the knowledge to make safer, informed, and more confident food choices. Food chain professionals can apply the concepts to improve authenticity awareness, reduce fraud risks, and strengthen trust with customers.

• Access to the “Food Authenticity from Farm to Fork” Course

Europe is one of the world's largest markets for imported dried mushrooms, accounting for approx. 20% of global imports. More than 60% of the European dried mushroom trade comes from developing countries while more than 80% of the value of European imports includes gourmet wild-harvested and medicinal (cultivated) mushrooms. It is forecasted that in the next 5 years, the European market for dried mushrooms is likely to increase, at an annual growth rate of 2%, triggered by the increased global demand for immunity-boosting food and food supplements. This includes dried and powdered mushrooms, such as reishi, cordyceps, chaga and shiitake. In addition, wild-harvested mushrooms are favoured for their unique flavour, taste and culinary value; however, they are highly vulnerable to fraud. High-value gourmet mushroom species such as porcini, morels and truffles are often mislabelled, mixed with lower-quality or cultivated varieties, or falsely claimed to be wild-harvested or from a specific region. Frequently, dried or processed mushrooms are main ingredients in premium convenient food products (e.g., pasta or risotto), which makes identification even more difficult and increases the risk of deception across the supply chain. Besides economic fraud, misidentification can raise food safety concerns, highlighting the need for authenticity, proper labelling, and traceability in the wild mushroom trade. Portable spectroscopy-based solutions can preserve product integrity and ensure a wider variety of authentic, safe convenient food products by enabling rapid and reliable origin authentication of various popular wild-harvested mushrooms and high-value medicinal varieties. This can also reduce potential risks related to food safety and contamination by detecting fraudulent activities that may hide unsafe or unknown species.

Food traceability is the ability to track and trace a food product's journey through all stages of production, processing and distribution. According to the General Food Law, Regulation (EC) No 178/2002, all food business operators must maintain records of where their products come from and where they are sent. Mushroom production is a highly technical process and represents a special case of Controlled Environment Agriculture (CEA), in which agro-industrial byproducts and residues are converted into highly nutritious food. Several species of the genus Pleurotus (Oyster mushrooms) are of particular interest because: (a) their production amounts to ca. 30% of the total, corresponding to the fastest-growing and most profitable section of the mushroom market during the last two decades; (b) they are commonly grown on pasteurized wheat straw, however, they can also be cultivated on a wide variety of agro-industrial waste materials, including straw, sawdust, coffee grounds and wood chips as growing substrates. The most frequent type of fraud in the mushroom supply chain is mislabelling, followed by grey market. The grey market involves mushrooms sold without traceability documentation. For consumer safety and supply chain transparency, it is important that the origin of all these materials can be easily identified. Mushrooms are a great example of a complex supply chain with many intermediaries, from substrate and mushroom production to the retail market. Traceability acts as a preventive tool against fraud, allowing consumers to scan a QR code and follow the mushroom's full journey along the supply chain from the farm to the consumer. Blockchain-enabled traceability, in turn, would enhance mushroom supply chain transparency through tamper-proof event recording allowing fast, accurate, real-time tracking and recording of all transactions across various actors.

Growing concerns over guaranteeing wine authenticity (particularly mislabelling of origin, quality, and grape variety) and improving process efficiency have become essential. Wine producers need assurance that the grapes they buy match the agreed-upon quality and variety to produce wines with consistent characteristics. Moreover, certification entities need additional information and tools to identify and deter unlawful activities and make inspection actions more efficient.

To address these issues, acquiring complete and comprehensive information is critical. The wine pilot deployed solutions to ensure the authenticity and traceability of grapes from vineyard to cellar, maintaining the integrity of the entire supply chain. A weather station monitored environmental conditions, helping to predict potential quality-volume mismatches based on adverse weather. Automated bucket and scissors systems measured the weight of grapes at each georeferenced position, identifying discrepancies in expected volumes. This data, along with the weather information, was crucial for the Early Warning System to assess and predict potential issues, and for efficient consultation of information through the Digital Food Passport. All these technologies were successfully deployed and used during the 2025 harvest, proving their usability and value to farmers and producers.

The Fish Pilot aimed to capture and harmonise whitefish supply‑chain data from catch to processing to strengthen traceability, transparency and fraud prevention. By integrating heterogeneous datasets—catch and landing records, certificates, sensor‑based temperature data, logistics information and Automatic identification Systems (AIS) vessel routes—into Electronic Product Code Information Services (EPCIS) ‑ compliant events, the pilot demonstrated end‑to‑end data interoperability across multiple independent actors.

Key results show successful development of a sensor‑to‑DFPP pipeline, improved upstream visibility, and operational demonstrations of both Business to Business (B2B) and Business to Consumer (B2C) Digital Food Product Passport (DFPP) dashboards. The pilot also delivered an Early Warning System prototype combining AIS data, regulatory zones and behavioural analytics to detect potentially illegal fishing activity. Technical insights included identifying cold‑environment battery limitations and refining traceability units and lot‑governance practices.

Recommendations emphasise the need for consistent lot definitions, interoperable data routines across logistics and processing, and clearer risk‑event thresholds for EWS deployment.

Added value for end users includes improved documentation of origin, targeted control capabilities, better production planning and consumer‑facing transparency.

Some knowledge has already been implemented, particularly EPCIS‑based modelling, sensor integration workflows and EWS mapping components.

The results can be used by supply‑chain actors and authorities to strengthen traceability systems, support regulatory compliance, and develop scalable risk‑monitoring solutions across fisheries.

Consumers expect correct ingredient declarations and truthful claims, while farmers and processors suffer from fraud-driven unfair competition and loss of trust. The meat pilot developed analytical approaches tailored to defined fraud scenarios as part of fraud prevention.

A handheld VIS/NIR spectrometer enabled on-site differentiation of grass-fed and grain-fed meat. Spectra taken 24 h post-mortem remained robust over time, supporting verification of feeding claims as a rapid screening tool.

Injection of a defined collagen hydrolysate into chicken breast was studied using Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry (MALDI-MS) imaging.  The method relies on the spatially resolved detection of different amino acids, allowing visualisation of adulteration within the tissue.

Addition of undeclared beef organs to minced meat was addressed by a Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) method based on marker peptides, enabling simultaneous detection of several organs in processed products.

Species substitution was investigated using Matrix-Assisted Laser Desorption/Ionisation Time-of-Flight (MALDI-TOF) peptide fingerprints and DNA metabarcoding. DNA-based methods allowed reliable quantification, whereas MALDI-TOF showed biological variability.

The methods address different control levels. Rapid approaches such as VIS/NIR and MALDI-TOF are suitable for screening, while LC-MS/MS and DNA-based methods show potential for confirmatory use in official control after further optimisation and future inter-laboratory validation. MALDI imaging currently contributes to methodological understanding rather than routine application.

The honey pilot is focused on Asturias PGI Honey (Spain) and addresses fraud in the value chain by targeting both, adulteration with added sugars (Chinese syrups) and mislabelling of the botanical origin. For this purpose, the pilot deployed sensor devices based on Near-Infrared (NIR) and hyperspectral imaging (HSI) technologies, an Early Warning System (EWS) for risk-based monitoring and a mobile app to support authenticity control and traceability along the whole value chain, from beehives to retail. The main pilot end-users are the food control authorities and consumers (for the mobile APP case).

NIR and HSI based tools were implemented in two validation campaigns using real samples. They demonstrated the ability to detect added sugars and mislabelling of botanical origin with promising balanced accuracies, supporting faster and more objective decision-making. The EWS tool enabled experts to prioritise the most critical cases using combined production and product data (physio-chemical parameters and pollen analysis), while the mobile app demonstrated its potential to inform consumers about origin, production conditions and key traceability attributes of PGI certified honey products.

The results can be used by food authorities for routine on site quality controls by using portable NIR/HSI devices, as well as for proactive fraud prevention by using the EWS, and by consumers through the traceability app for informed purchasing decisions.

During the Cereal and Dairy pilot in the Watson project Smart labelling solutions were developed and piloted in Finland with beer and cheese. The core value of Smart Tags is simple: they create a robust bridge between a physical item (a package, batch, pallet, or case) and its digital identity, enabling access to structured product and process information far beyond what can fit on a conventional label. Each cheese batch, or even each item, can receive a unique and smart identity. Tracking covers milk intake, processing, and storage; consumers can verify claims with a single scan. Similarly in the cereal chain, the origin of raw materials, process steps and product information could be shared with the smart Tag. The use case also demonstrated targeted response capability: e.g. if a product recall is necessary, producers can contact affected customers directly. This enables track and trace, direct consumer communication and improves product and food safety. Consumers appreciated that food items can provide them with the product's whole story—like item history, raw material origin, information about the producer and production as well as traceability information. Thereby smart tags increased consumer trust in the food chain, product quality and safety.

The extra virgin olive oil (EVOO) pilot implemented innovative, certifiable technologies to support all stakeholders in achieving effective traceability across the value chain.

Blockchain, an Early Warning System (EWS), a Digital Food Product Passport (DFPP), and DNA-based fingerprint analysis were made interoperable to collect and monitor qualitative and quantitative production data at four key points in the chain—from the field to the bottled product.

Sustainable and portable DNA extraction and genetic authentication technologies, when integrated with tamper-proof digital systems, ensure the absence of adulteration before the product reaches the consumer.

Through the DFPP and EWS, stakeholders and control authorities can perform cross-checks for safety assurance and fraud risk assessment.

The system also allows consumers, via a QR code on the bottle, to verify the authenticity of the label information, ensuring full transparency regarding the EVOO's origin and production history—from raw material to shelf—in compliance with food safety and data protection regulations.

The holistic approach adopted in selecting and integrating these traceability tools represents a major technological advancement. It enables new applications for real-time monitoring and traceability, supporting both upstream and downstream controls and enabling anomaly detection without disrupting the production process.

The system should now be further implemented and validated within comprehensive, transferable technological development programmes to ensure its scalability and integration within the agri-food sector.

Buying groceries is a common everyday activity, as is picking food products from the pantry at home. Reading and making sense of all the information present on the labels is less easy. For visually impaired consumers, these are considerable challenges that make their lives difficult and raise safety issues. The wine label analysis tool provides a mechanism to help these users find the intended product, particularly in their homes. While this phase of development targets wine bottles, future versions can be extended to other products. The tool includes automatic detection of product and label, guides the user, and conveys label information with semantic meaning, enabling the user to confirm the product and its characteristics. Moreover, it targets unconstrained home environments, which increases flexibility, and all operation is done in real-time on common smartphones making it highly accessible.

Evaluation by consumer focus groups showed that it is easy to use. Lessons learned show that augmenting existing datasets is crucial to improve future results and extend to other food products.

Every day we consume food products, an act that seems straightforward and requires little thought. However, this act can present considerable challenges for consumers, especially those with visual impairments. For wine, distinguishing between different types may be difficult, if not impossible.

The tools consist of an application running on a smartphone for real-time, fast, and flexible coarse analysis of wine types based on colour. It uses common cameras and can operate in everyday scenarios. With a special focus on supporting visually impaired consumers and their inclusion in society, this application automatically detects wine containers, provides sound cues, and then speaks the type of wine back to the user.

Evaluation by consumer focus groups showed that the application is easy to use, and its potential increases significantly if integrated with other supporting functionalities. Lessons learned show that augmenting existing datasets is crucial to improve future results and potentially extend to other food products.

Currently, the number of consumers seeking products derived from sustainable and responsible animal production that contribute as little as possible to climate change is constantly increasing. Production systems based on grass consumption by animals meet these criteria. The traceability of products derived from these systems is essential to prevent fraud, increase consumer confidence and generalise their use.

Using near-infrared (NIR) and/or visible (VIS) spectroscopy directly on carcasses in slaughterhouses can distinguish grass-fed animals from others. Spectral models were developed using spectra taken from muscle or fat tissue. The models' robustness was evaluated regarding spectrum collection timing, production systems in other countries and using the models outside the slaughterhouses for which they were developed.

Due to their greater accuracy, it is recommended to use animal feed classification models developed based on VIS spectra taken from subcutaneous fat (SF) and the Longissimus thoracis muscle. Models developed under French conditions adequately classified the feeding of animals from German production systems.

Most models developed under slaughterhouse conditions to differentiate animal feed cannot be used in supermarket or butcher shop conditions. Only the model developed using VIS spectra from SF is adequate. A mobile or computer application has been created for the public to use the models.

VIS spectroscopy on muscle or fat tissue from carcasses has proven to be an easy and cheap technology to apply on a large scale for classifying animals in terms of feed traceability. 

The NIR-based sensors pilot in Asturias (Spain) addresses honey fraud in PGI “Honey from Asturias” by deploying low-cost, handheld NIR devices for real-time, non-destructive detection of adulteration with sugar syrups and mislabelling of botanical origin (Coast, Mountain, Forest).

A low cost, handheld NIR based tool integrated with Machine Learning algorithms allows for on-site analysis, requiring only quick sample pretreatment (preheating to 30°C). End-users validated this tool during two campaigns across the honey value chain from production to retail.

In the final validation round 30 real samples were analysed. The metrics provided by the algorithms in terms of balance accuracy were 89% for adulteration and 59% for botanical origin identification (Forest: 88%, Coast: 67%, Mountain: 50%). This highlights the need for expanded datasets and proper sample handling to minimise false positives from samples with crystallisation or dirt. It can be concluded that the NIR-based tool offers easy implementation, real-time results, and high potential for operational quality control.

Clearly, the main added value for quality control agents is the possibility of faster, on-site fraud detection using low-cost NIR devices, which supports control authorities in real-time and provides data-based decisions.

Honey fraud remains a persistent issue in the EU, misleading consumers, eroding trust, and creating unfair competition for honest beekeepers. Existing real-time verification solutions are often limited, leaving both consumers and producers vulnerable to fraud. To address this gap, the Honey Pilot App was developed as a mobile solution that verifies product authenticity, strengthens traceability, and provides transparent, enriched information directly to consumers.

With a simple barcode or QR code scan, users can instantly confirm a honey product’s authenticity, review its origin and ingredients, and explore healthier or more sustainable alternatives available in their country. The app brings together data from advanced food authentication tools developed during the project and trusted public databases, presenting a comprehensive product overview clearly and user-friendly. It also offers insights into nutritional value, environmental impact, and the level of food processing.

Users can personalise their experience by defining dietary preferences and allergies, organising scanned products into custom lists, and monitoring their food choices over time through intuitive visual statistics. A built-in chatbot assistant further enriches the experience by providing tailored recipe suggestions based on preferred ingredients.

Designed to fit seamlessly into everyday shopping routines, the Honey Pilot App empowers consumers with reliable information while supporting responsible producers and promoting transparency across the honey supply chain. The mobile APP is currently available to project partners and testers, interested stakeholders can quickly obtain more information by contacting WCS.

Smart packaging contains a range of technologies that enhance package functionality and communicate with the users. Sensors are one technology used to monitor packaging conditions and communicate changes in the product or environment to different stakeholders.

These sensors can be printed functional layers or indicators that provide qualitative or semi-quantitative monitoring through visual colour change. In the Watson project, VTT developed a printed oxygen indicator based on an oxidation-reduction reaction that results in a visual colour change in the presence of oxygen. The indicator can show if an oxygen-free package has been opened, alerting potential package tampering due to counterfeiting attempts. Furthermore, oxygen indicators can also indicate if there is a risk of spoilage for oxygen-sensitive food products.

Finetuning the indicator chemistries and developing other technologies, such as protective layers is required to control the indicator's reaction speed and sensitivity, enabling semi-quantitative monitoring. Furthermore, integrating multiple sensing capabilities into a single tag can broaden application cases for general food quality and safety monitoring. Finally, if the indicator is placed inside the food package, the direct and/or indirect food contact compatibility of the developed indicator chemistries must be ensured.

Smart labelling refers to technologies that provide an item-level identity to products. Such technologies include 2D barcodes or RFID (Radio Frequency Identification) tags. The technology is called a smart tag when it is treated as a persistent identifier tied to digital records that can be updated, queried and validated across the supply chain. In practice, this means linking the barcode or the tag to databases, blockchains and traceability platforms that store origin data, processing events, quality certificates, cold-chain history and recall-related metadata. Intelligence within smart tags can increase by integrating monitoring functionalities using functional inks as well as printed indicators and sensors that react to changes in product, package, or environmental conditions with a visual colour change detectable by a mobile application when the smart tag is scanned. Physically Unclonable Functions (PUFs) that use package or label fiber structures, for example, as unique identifiers, offer additional functionality to increase the security features of smart tags.

In the Watson project, smart tags are presented not as a standalone label upgrade, but as an access key to a broader platform that couples product identity, shared histories, interoperability standards, and anti-fraud intelligence. The project has shown that tracking of individual items is already possible in most products, so placing unique identifiers on each item should be implemented quite rapidly. This enables track and trace, direct consumer communication, next level food safety and many other applications.

Research conducted during the Watson project indicates that consumers find it valuable when food items provide more than just nutrition values, such as item history, producer and production information, and traceability details. Therefore, smart tags increase consumer trust in the food chain and product quality.

Extra Virgin Olive Oil (EVOO) is a premium commodity facing significant economic threats from fraud, specifically through lower-quality admixtures and mislabelling of origin or variety. The main outcome of this activity is the introduction of FieldNA, a patent-filed hand-held device designed to deliver rapid, on- site DNA authentication when coupled with portable molecular analysers to detect the presence of fraud in EVOO samples in real-time anywhere in the supply chain.

Practical Recommendations For olive oil producers, millers, bottlers, retailers FieldNA transforms complex genetics and testing practices into a practical business asset:

• Cost Efficiency: Reduces the reliance on expensive external laboratories and eliminates delays. This allows for more frequent, low-cost routine checks without interrupting the supply chain.
• Supply Chain Security: It serves as a real-time “gatekeeper”. Stakeholders can test incoming EVOO batches before they reach their supply chain, ensuring the absence of fraud, thereby accelerating decisions and avoiding costly recalls.
• Market Competitiveness: By guaranteeing EVOO authenticity, producers protect their brand reputation, justify premium price, and offer tangible proof of product quality and integrity to customers and retailers.

FieldNA changes how olive oil testing is performed, creating positive social, environmental, and economic value.

The Risk-Based Food-Fraud Decision Support Module uses a state-of-the-art methodology to quantitatively assess food fraud risk in complex food systems, through a software application named the Food Fraud Risk Engine. The Engine uses various techniques to gather information about a particular supply chain, such as screening food fraud databases, analysing socioeconomic drivers, collecting climatic and agricultural data, and using expert elicitation methods. Additionally, real-time Internet of Things (IoT) data are collected from various sensors. All this information is synthesised and processed comprehensively to evaluate food fraud vulnerability factors. Specifically, the Engine is fed periodically with real-time data to update the fraud risk indicators of each node (e.g., harvesting, transportation, storage) composing the stages of a supply chain. Thereafter, the underlying probabilistic model integrates the risks stemming from the individual nodes to evaluate the food chain's overall risk. When the overall risk factor exceeds a pre-defined threshold value, the Decision Support System sends an alarm alerting pertinent authorities to potential food fraud activities. The main added value of this Engine for the end user is the ability to proactively detect and quantify food fraud risks in real time across the entire supply chain, enabling timely and evidence-based interventions. The outputs can inform policy decisions, compliance strategies, and operational controls through evidence-based, real-time risk insights.

The Watson project involved the design and development of an Early Warning System (EWS) for food safety authorities, based on the processing of various data sources, while revealing connections they may have with food fraud-related incidents.

The EWS deals with food fraud in four separate supply chains: honey, wine, olive oil and fish. In the fish chain, Automatic Identification System (AIS) tracking data combined with weather information is fused to detect potentially illegal fishing activities in the Norwegian sea. For honey, detecting mislabelling of botanical origin is the main focal point, while mislabelling of botanical variety was also pursued. In olive oil and wine supply chains, statistical modelling of key production related variables helps detect irregular figures in reported yields. Finally, Internet of Things (IoT) sensor data from the wine chain facilitates the detection of possible tampering of grapes during transportation.

Predictive outcomes are visualised in a simple and intuitive web dashboard, featuring a map where alerts for potential fraud incidents are highlighted, along with statistical trends over time. Authorities and control laboratories can be warned when risk levels spike for specific fraud types - enabling proactive inspections and targeted interventions. By helping authorities detect and address suspicious patterns before they escalate, EWS contributes directly to:

• Safeguarding consumers from deceptive and potentially harmful products.
• Protecting honest producers and exporters from unfair competition.
• Strengthening the integrity, transparency and resilience of Europe’s food supply chains.

Interested stakeholders can gain access to the system by contacting UBITECH, to see the technology in action and evaluate its usefulness.

By implementing a digital food product passport utilising blockchain technology, food traceability can be revolutionised, ensuring every step from farm to table is meticulously documented transparently and securely. This innovation yields a plethora of key benefits:

1. Enhanced Trust: Consumers gain unprecedented insight into their food's journey, fostering trust and confidence in the products they purchase.
2. Combatting Food Fraud: The immutable nature of blockchain records deters tampering and counterfeit products, guaranteeing authenticity and integrity.
3. Operational Efficiency: Farmers and suppliers streamline their operations through better tracking mechanisms, reducing losses and optimising supply chain management.

Practical recommendations for the implementation of a food passport:

• Leverage Market Transparency: Utilise the transparency afforded by blockchain to differentiate your products in the market. By emphasising the ethical and traceable nature of your offerings, you can cater to the growing consumer demand for responsible sourcing. 
• Empower Quality Control: Verified products can command higher prices, increasing profit margins.
• Capitalising on Premium Pricing: Verified products can command a premium in the market. Capitalise on this by positioning your offerings as premium, ethically sourced products, thereby maximising profit margins. For farmers and end-users, this means meeting consumer demands for sustainability and transparency, leading to better product quality, trust, and potentially higher revenues. Blockchain not only streamlines operations but also opens new markets, offering a competitive edge in a conscientious market.
   

In the cereal and dairy pilot, tools enabling authenticity verification were created for milk products. An item-level track and trace solution is being implemented which can track and trace items and their raw materials at product level. The pilot's purpose was to implement a data collection chain targeting weak points in the dairy supply chain, where each individual product has its own authentication process. Raw material information was collected, including elements such as the origins, manufacturers, ingredients and shelf life of each product. This information was included in a single QR code that can be used to obtain product information at different stages of the supply chain. The information's accuracy can be determined at different levels (consumer, authority, etc.). The pilot also implemented a simple blockchain-based product lifecycle management to support authenticity verification. The developed solutions were also piloted in the cereal chain in a brewery at the same time. This solution helps provide information on the origin and quality of dairy products so consumers can verify this information firsthand. The pilots benefit different actors of the food chain including manufacturers and authorities.

The WATSON project aimed to combat the counterfeiting of Norwegian white fish by developing a blockchain-based platform that ensures product authenticity and quality. The platform secured data sharing through blockchain technology, collected real-time data from Internet of Things (IoT) sensors, and provided reliable access to this data via non-copyable labels, such as QR codes and near field communication (NFC) tags. These measures ensure that all information is exchanged securely across the supply chain, maintaining privacy and security.
The main practical recommendation for fishermen and end-users is to implement this blockchain solution to guarantee the origin and quality of their fish products. By adopting this technology, stakeholders can prevent species substitution and adulteration, ensure ethical trade practices, and meet the environmental standards necessary for global export.
The solution offers substantial benefits to practitioners. The platform expected to slash the number of illegally sold fish by over 70%. Additionally, maintaining the cooling chain will boost fish quality by more than 60%, and the traceability feature is projected to increase consumer willingness to pay more for authenticated fish by over 30%. An increase in turnover of 15% outside the EU and 7% within the EU is also expected.
Practitioners can leverage the secure labels and IoT sensor data to track and verify the fish's journey from the sea to the consumer. This comprehensive approach not only improves product quality and safety but also fosters stronger trust among stakeholders. The result will enhance the efficiency and profitability of the seafood supply chain, meeting the needs of all involved parties.

In compliance with current regulations and accredited analyses, this pilot aimed to apply genetic approaches for the traceability of the olive oil supply chain, from farm to fork, passing through all stakeholders.
The final objective was to fight against olive oil fraud and defend the consumer by filling the information gap on the label from the beginning, for the analysis and choice of an oil, based on its intrinsic value of quality and identity for specific consumption. The olive oil supply chain was genetically traced step by step, from the raw materials in the field, to the milling and storage tanks, as well as during the related movements (carriers) up to the bottling, labelling and product for sale (ex post).
The traceability system involved the development of field/mill portability technologies for high-throughput DNA extraction and molecular characterisation for low-cost genetic profile analysis. Work was carried out on an innovative database, capable of executing complex queries in a robust Artificial Intelligence/Machine Learning post-processing pipeline. This allowed for an accurate and automated classification of the genetic profiles of cultivars and olive oils for each batch of a label based on its varieties, creating a “DNA fingerprint”. The most useful data (e.g. geo-localised orchards, date of pressing, bottling, etc.) was collected and stored in the blockchain platform and is accessible to interested parties up to the consumer who have access to the secure olive oil chain via the QR code on the product label. Finally, a digital passport of produced and bottled batches was created to provide credible and reliable information for a food product tracked in one place.

The meat supply chain is characterised by many stakeholders and a wide variety of products. It also exhibits several vulnerabilities to various kinds of manipulations. Past food scandals have highlighted the complexity of fighting food fraud in a supply chain that is highly dynamic and moves across many borders. The aim of the pilot is to provide an analysis of various levels of vulnerability in the meat chain and to identify gaps in the food fraud vulnerability assessment.
A key vulnerability in the prevention of food fraud is related to the development of analytical methods. This pilot provided an overview of existing methods covering all possible manipulations at every stage of the supply chain. It developed and tested a methodological framework to detect and prevent meat mislabelling.
Furthermore, analytical tools such as mass spectrometry, NIR, DNA biochip, DNA barcoding and DNA metabarcoding were developed and adapted to detect fraudulent practices. The pilot tests included the substitution of beef with beef organs, the substitution of beef with other animal species, the mislabelling of grain-fed as grass-fed beef, and the addition of hydrolysate to poultry. Methods for highly sensitive, targeted High Performance Liquid Chromatography (HPLC) - Applications of Tandem Mass Spectrometry (MSMS) and non-targeted mass spectrometric fingerprinting by MALDI Time of Flight Mass Spectrometry (ToF MS) were developed using defined test materials. The advantages and disadvantages of the different approaches were evaluated as well as the suitability for different stakeholders and products along the meat chain. Most of the high-end methods are aimed at the food safety authorities as the main end-user for an expansion of their analytical portfolio, which will strengthen their ability to combat food fraud in the meat sector.

The need for effective traceability in the wine industry has greatly increased in recent years due to the growing consumer awareness of the safety and quality of products they buy, as well as the responsibility of practices involved. The lack of traceability to the origin of a product can cause significant disruptions in the production and distribution of goods but also poses serious fraud risks, and adverse economic consequences. In contrast, the promotion of traceability will contribute to consumer trust. According to the European Commission's science and knowledge service, wine fraud costs the regular EU wine sector an estimated 1.3 billion euro per year, around 3% of the total sales value. To overcome these aspects, public authorities perform controls and checks, which can, however, achieve limited success as they cannot detect the roots of the problem. Moreover, the isotopic analysis performed by authorities must be done in laboratory with expensive equipment and the information is confidential. In Watson, the wine pilot case focuses on a blockchain-based platform that enables stakeholders to access trustworthy information related to grapes and wine along the supply chain. The technologies used cover secure data sharing, real-time geo-referenced data collection from Internet of Things (IoT) sensors, and image analysis techniques. The implementation of IoT technologies for monitoring environmental conditions in the vines and grapes transportation; integration of the information in the digital ledger and with the digital passport; wine colour analysis for information sampling and fast screening; and label processing for assisting visual impaired consumers. The last two focusing on assistance and higher integration of consumers.

Honey ranks 3rd in the world for most-faked food just behind milk and olive oil. Moreover, recent studies conducted by the Joint Research Institute (JRC), concluded that practically half of the honey that is commercialised is suspected to have been adulterated and therefore non-compliant with the EU Honey Directive. According to previous studies, the main unfair practices in the honey sector include:

• adulteration of honey with additional sugars and low-quality honey added to high-priced honey.
• mislabelling respect to the geographical and botanical origin of the honey.

The main aim of this pilot was to develop and validate low-cost and portable digital devices, based on Near Infrared Spectroscopy (NIR) and hyperspectral imaging (HIS), for the fast detection of fraudulent practices in the PGI Asturian honey. This novel tool was integrated into the control and inspection tasks performed by the main control bodies of the PGI. Currently, only minimal controls are carried out, due the time-consuming, high cost of scientific equipment and destructive nature of the required laboratory analysis. This new device revolutionised the field thanks to its high sampling and throughput, as well as the fast visualisation of the analysis results. It is also noteworthy to highlight that this authenticity proof device was complemented by other cutting-edge technologies that support food traceability, such as Blockchain, Digital Food Passport and the Early Warning System. The main target groups for this innovative practice include EU honey operators, honey control bodies, EU consumers and other related organisations such as food clusters, researchers, institutes and technology centres.

The Watson project focuses on implementing a platform for data storage and use by various stakeholders in the food supply chain leveraging blockchain technology. Critical information regarding the authenticity of food products is stored on the blockchain. This information cannot be tampered with, thereby ensuring traceability and preventing food fraud. Different supply chains have similar steps and stakeholders, but the information can vary in each one. Information collection can occur using Internet of Things (IoT) devices and smart sensors, through interfaces with the involved parties' information systems, or by recording control measurements such as DNA tests. Each participant (farmer/primary producer, processor, packager, distributor, wholesaler, retailer, etc.) enters the critical information for which they are responsible and can access others' critical information to ensure transaction transparency. Smart contracts help automate transactions, while a digital passport provides the necessary blockchain information in a simple and user-friendly manner for every platform user. Using appropriate technological solutions to keep usage costs low or having the main stakeholder/dominant player in the supply chain bear the cost, can make the platform more acceptable in practice to the involved parties. In addition to those involved in the food supply chain, regulatory authorities can also utilise the blockchain platform to control the authenticity of food products.

The project team conducted a needs analysis, focusing on fraud prevention systems across six pivotal supply chains: olive oil, wine, honey, meat, dairy, cereal, and fish. Through meticulous interviews conducted from farm to retail, insights directly from industry stakeholders were identified, shedding light on critical challenges and opportunities. The main conclusions from this analysis include: 

• Food fraud issues are pervasive, underlining the need for tailored systems to effectively manage these risks. 
• Traceability emerges as a paramount requirement for most supply chain participants, emphasising the demand for heightened transparency and accountability. 
• Despite this imperative, many stakeholders lack technological maturity and have limited awareness of emerging systems, indicating a notable gap in knowledge and adoption readiness.
• Integrating advanced technological solutions presents a significant avenue for improvement, although concerns about cost implications and adoption complexities persist.
• Regulatory consistency is a non-negotiable prerequisite for any prospective system, ensuring conformity and trust within the marketplace. 
• The efficacy of suggested solutions and cultivating effective communication channels between business and IT sectors are linchpins for successful implementation.

A systematic literature review was carried out to investigate the current state-of-the-art of use of blockchain technology (BCT) in agro-food supply chains to increase traceability and transparency, screening and reviewing about 550 academic articles. The detailed analysis of these papers provided insight into the appropriate uses, and suitable implementations, of BCT in supply chains. Results included the following:

• Lack of mature applications: BCT is becoming mature as a technology. However, its practical application has so far only been tested for physical asset supply chains traceability.
• Difficulty of BCT past the prototyping stage: Many supply chain transparency initiatives utilising blockchain may reach a prototype phase but are subsequently not heard from again. This indicates that the technology is interesting from a development and research point of view but is not yet delivering on its promises from a business perspective.
• BCT may not be necessary: Some such projects have achieved laudable milestones by digitalising parts of the supply chain, providing sensor data and data from other systems to blockchains, thus making the data available and the supply chain more transparent. However, closer examination often reveals that the BCT itself was not necessary, indeed, a shared or open data platform could have served the same purpose, but the novelty of BCT spurred the digitalisation groundwork.
• Need for more research: The proper use of BCT in SCM requires additional research to map BCT's capabilities to supply chain management needs.

Food fraud is becoming a big challenge to the supply chain due to multiple types of adulteration, mislabelling, counterfeiting, dilution, etc., which cause damage to public health and economic loss. Food fraud vulnerability can be understood as a weakness that food fraudsters can exploit to gain illegal profits. The aim of food fraud vulnerability assessment is to investigate and analyse the vulnerabilities and root drivers of integrity issues within the 6 most important food supply chains in the EU. In total, 131 stakeholders from cereal, dairy, fish, honey, meat, olive oil, and wine value chains were interviewed in the food fraud vulnerability assessment. The three critical elements—opportunities, motivations, and control measures—were evaluated in the assessments. The results included

• The honey, olive oil, and wine supply chains had the most highly vulnerable markers, such as the complexity of adulterating raw materials and the availability of technology to adulterate final products. 
• In many cases, a lack of updated testing equipment at processors or farms and fierce market competition, such as price wars, make food fraud more likely to occur. 

In conclusion, consumers' health, economic interests, and stakeholders' reasonable profits are all worth protecting. Adequate regulatory guidance and affordable traceability systems are recommended to mitigate food fraud in EU supply chains.

Concerns about food safety and traceability have increased significantly due to greater awareness about climate change and news about food fraud. In addition to the societal aspects, there is also the economic axis, with food fraud amounting to billions of euros per year in the EU alone. For example, according to the European Commission's science and knowledge service, wine fraud costs the regular EU wine sector an estimated 1.3 billion euros per year, around 3% of the total sales value. Public authorities seek to overcome these issues by performing controls and checks, resorting to food analysis in a laboratory context. While these methods are precise and robust, they are expensive, destructive, and based on sampling. 
Watson has researched the applicability of a set of food scanning tools to complement current procedures, through flexibility, democratisation, and augmented coverage of the value chains. These tools are diverse in scope, including: 

1. Target food product (meat, olive oil, honey, wine).
2. Technology (from RGB images to mass spectrometry).
3. Cost and flexibility (from mobile apps to infra-red sensors).
4. Precision (coarse analysis for assisting visually impaired consumers to DNA analysis).
5. Portability (from mobile devices to lab equipment). 

The potential of these tools is augmented by their integration into the Watson platform, acting as data sources for triggering actions from food safety authorities and promoting traceability by covering different stages of the value chains. These tools promote further developments in the cross-food product applicability.
 

Food chains are typically complex, involving multiple stakeholders and processes from raw material collection to transformation into the final product. Such processes typically involve multiple parties and consist of different steps. The execution and completion of each step are supported by parameter measurements retrieved using standalone measuring devices or Internet of Things (IoT) platforms. On top of such processes, a rich portfolio of applications can be designed using process-related data, either to provide information to stakeholders and /or consumers (e.g. in the context of traceability offerings) or to perform validations (for food fraud confrontation). Exchanging data among processes, services and applications is challenging due to the different semantics and formats employed or expected by data sources and consumers respectively. 
In the Watson project, the team worked on interoperability solutions for modelling parameters and their respective values involved in food chains. The solution leverages and extends ETSI Smart Applications Reference for agriculture and food domains (saref4agri) and the H2020 DEMETER Agriculture Information Model (AIM) according to the needs of Watson chains. Interoperability facilitates binding data sources and data sinks for more advanced and rich services, retrieving and transforming ad hoc data into standard-based information.

The digital transformation of vertical sectors, including agriculture and supply chain management, has significantly relied on the proliferation of Internet of Things (IoT) devices and the increasing availability of data-driven services. The complexity of those systems, however, poses significant challenges in ensuring reliable and resilient tracing and tracking capabilities for the transported commodities. Leveraging IoT technologies through a data-driven framework capable of handling unexpected events with accurate and timely information is an essential design principle. The Watson team proposes the implementation of two basic key components:

1. WATCHER component that:
   a.    Establishes the Message Queuing Telemetry Transport (MQTT) Connectivity. It is responsible for establishing and maintaining a connection with the MQTT server.
   b.    Enables subscription to the topics. It is responsible for subscribing to specific MQTT topics where IoT sensing devices publish their data.
   c.    It performs data collection: It is responsible for identifying and extracting the actual information from the MQTT payload.
2. Electronic Product Code Information Services (EPCIS) component that:
   a.    Conducts the data processing: It is responsible for aligning with the EPCIS standard by aggregating the data over time intervals.
   b.    Performs data control and checking. It ensures that collected measurements are within the specified ranges and performs checks to validate the data.
   c.    Stores the data.

Practitioners can use this to optimise routing and scheduling of the food commodities transportation through data-driven decision making, resulting in cost savings for the operations, improved business continuity, increased competitiveness, better compliance management, and adaptability to changing market conditions.
 

The project team conducted expert interviews in the 6 WATSON project pilot supply chains to assess their vulnerability and the opportunity to introduce digital traceability tools. Due to contextual differences in the supply chains tackling food fraud requires a diverse set of approaches that include regulation and social and technological innovations. The main conclusions from these interviews have been summarised below:  

• In the honey supply chain, reliance on traditional production methods and knowledge gaps make social innovation crucial.
• The wine supply chain has already implemented efficient anti-fraud technologies. High entry costs and the need for compliance can lead to the exclusion of smaller producers.
• In the dairy supply chain actors are closely connected. Pricing strategies have been used to tackle food fraud. Digital solutions can help tackle remaining vulnerabilities.
• In the fish supply chain, technology is essential due to its complexity and global nature. This helps address both fraud and unintentional alterations.
• In the meat supply chain, new technologies need development to detect a wide range of potential alterations. The reliance on technology plays an important role due to health implications. 
• In the olive oil supply chain social innovation and technology must be combined. Technology can assist in monitoring and ensuring quality. Social innovations can enhance supply chain integrity.

Before investing in a technology or other measures to combat food fraud, supply chain actors should analyse its adequacy with their needs and context.