Within the framework of the European AgriDataValue project, Tecnova has started the commissioning of Pilot 6 at the facilities of its Experimental Center in Almería (Spain). This pilot is part of the main experimentation phase of the project and aims to validate in real cultivation conditions various digital technologies aimed at improving agronomic management in greenhouse production systems.

For the development of this pilot, Tecnova has established two experimental greenhouses, one dedicated to tomato cultivation and the other to cucumber cultivation, which will allow the implementation and evaluation of use cases 2.1, 2.3 and 2.4 of the AgriDataValue project. Through these trials, it is intended to generate evidence on the applicability of advanced technological solutions in intensive Mediterranean agriculture.

AgriDataValue has as its main objective to develop a European agri-environmental data space, based on a distributed architecture that allows the integration of platforms, sensors and data analysis tools to support decision-making in the agricultural sector. In this context, Tecnova leads the implementation of Pilot 6, contributing to the validation of digital technologies in real production environments.

During the trials at the Tecnova Experimental Centre, various crop monitoring and analysis technologies have been installed. These include IoT sensors for real-time data collection, a SynField climate station for monitoring environmental variables, Teros soil sensors for the analysis of soil moisture, temperature and conductivity, as well as a hyperspectral camera that will allow parameters related to fruit quality to be evaluated in a non-destructive way.

These technologies will make it possible to monitor environmental, soil and irrigation system variables, generating datasets that will be used within the framework of the project to develop and validate advanced analysis tools and models based on artificial intelligence.

The use cases that will be implemented in this pilot are aimed at addressing different challenges related to precision agriculture in greenhouses. Firstly, the Use Case 2.1 focuses on the optimisation of irrigation and fertilisation through the use of sensors and monitoring systems that allow agronomic decisions to be adjusted based on the real conditions of the crop. For its part, Use Case 2.3 addresses the estimation of fruit quality by analysing the soluble solids content (°Brix), using hyperspectral imaging techniques that allow non-destructive evaluations to be carried out directly on the plant. Finally, the Use Case 2.4 is aimed at automating the climate control of the greenhouse, by controlling the opening of windows according to the environmental conditions recorded by the sensors.

Throughout the remaining three years of the project, the data generated in these trials will allow the technologies developed in AgriDataValue to be validated and their potential to improve the efficiency of resource use, optimize agronomic management and facilitate the adoption of digital tools by producers.

With the implementation of this pilot, Tecnova reinforces its role within the project as leader of Work Package 5, dedicated to the validation and adaptation of pilots, and continues to promote the transfer of technological innovation to the agricultural sector. This type of initiative contributes to moving towards a more digital, efficient and sustainable agriculture in Europe.

For more information about the project, you are invited to follow AgriDataValue’s activities on its social networks:

• Twitter/X: https://twitter.com/AgriDataValue
• LinkedIn: https://www.linkedin.com/showcase/agridatavalue/
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Data is all around us. The real question is: do we see it, and do we make use of it? Data has been used in fruit growing for years—often without us even realizing it. Weather data, for example, has long influenced decisions about orchard management. Over time, various decision-support models have been introduced, enabling growers to combat diseases and pests more accurately. The rise of computer technology has further accelerated this development.

Today, more data is being collected than ever before. Blossom data, fruit information (numbers, color, and size), yield data, weather patterns, soil moisture, vigor assessments, and even detailed logs of which tasks were performed where and when. All this information helps growers gain better insight into their production system and continuously improve their operations. With the latest technologies—including artificial intelligence—it is now possible to take things a step further. Smarter models can detect patterns that are not immediately visible to the human eye, enabling growers to make better-informed decisions.

At AgriDataValue, we develop digital support for various cultivation processes. One example is guiding growers toward the ideal fruit load. By using models that provide insight into a tree’s growth potential, growers can make better decisions about which interventions lead to optimal production.

Perhaps the true value of data only becomes clear when it is used so widely and naturally that we barely notice its impact—precisely because it works so well.

On 28 March 2026, NILEAS successfully organised an informative workshop entitled “Fungal Diseases of Olive Trees: Methods of Prevention, Monitoring and Intervention.”

The event began with a presentation by the NILEAS agronomist, Nikos Petoumenos, who referred to the AgriDataValue project, in which NILEAS participates, and the way it is utilised in the fight against fungal diseases. Starting with the phrase “If you can’t measure something, you can’t control it,” he presented the AgriDataValue project, which has been running for four years as of February 2026. He mentioned that technology provider partners have developed tools for the prediction, monitoring and management of three use cases: Colletotrichum gloeosporioides, olive fruit fly, and frost.

Synelixis, the coordinating partner, has supplied NILEAS with SynField smart agriculture devices and sensors measuring soil moisture, air and soil temperature, as well as leaf wetness sensors, which are critical for the development of Colletotrichum gloeosporioides. It will also provide fungal spore traps, the data from which will be analysed by a specialised laboratory. Technological partners from across Europe are already providing access to meteorological satellite data, as well as drone-based data. Upon completion of this six-year project, these tools are expected to become an additional asset for olive growers in predicting and managing the above-mentioned threats in olive farming.

All of the above, in combination with the ten AI-based electronic olive fruit fly traps that NILEAS has purchased since last year, the traditional traps installed by the Directorate of Agricultural Economy & Veterinary Medicine of Trifyllia, and the 60 traps placed by NILEAS across the areas where its members operate, provide a comprehensive, real-time monitoring system. However, he emphasised that technology alone is not sufficient; research and proper guidance from agronomists remain essential. Finally, he stressed that past mistakes must not be repeated, as organisational shortcomings, lack of knowledge, inaccurate assessments and poor decision-making have previously led to negative outcomes.

This was followed by presentations from Dimitris Tsitsigiannis, Konstantinos Aliferis, and Sotiris Giannakaris, all from the Agricultural University of Athens. The speakers addressed multiple aspects of the issue and proposed management strategies for Colletotrichum gloeosporioides, which has been established in Messinian olive groves for over a decade, causing significant damage to production and impacting the local economy. Mr Tsitsigiannis also referred to Alternaria, an emerging olive tree disease that is often confused with Colletotrichum gloeosporioides.

The event was attended by more than 140 participants, including representatives of the Regional Unit of Messinia, the Directorate of Agricultural Economy and Veterinary Medicine of Trifyllia and Messinia, and the Kyparissia and Messinia Association of Agronomists, as well as numerous agronomists and olive growers from across Messinia and neighbouring prefectures. Through their questions and observations, participants contributed to a meaningful and in-depth discussion on fungal diseases affecting olive cultivation.

Conclusions from the event:

1. Colletotrichum gloeosporioides is present in Messinian olive groves and, when climatic conditions are favourable, can cause significant damage, particularly in the absence of appropriate interventions and cultivation practices.

2. Structural challenges in Messinian olive cultivation (such as small and fragmented plots, steep terrain, low levels of professionalisation, ageing farmers and abandoned groves) make effective management more difficult, placing additional pressure on professional producers.

3. The occurrence of Colletotrichum gloeosporioides is closely linked to olive fruit fly infestations, highlighting the importance of the National Olive Fruit Fly Control Programme and the need for effective management strategies.

4. The treatment of fungal diseases significantly increases production costs and, in many cases, may become economically prohibitive.

5. The era when olive cultivation was considered an easy activity has definitively passed, requiring a higher level of expertise and professionalism.

6. Addressing these challenges under conditions of climate change requires vigilance, preventive interventions at critical stages, and continuous monitoring of local climatic conditions.

7. Early harvesting, where feasible, remains one of the safest methods to reduce production losses.

8. The new olive-growing season, which has already begun, requires careful planning and heightened attention. The risk of recurrence of issues similar to those observed during the 2025–2026 season is particularly high due to existing infections in the groves and prevailing weather conditions.

CODECS (maximising the CO-benefits of agricultural Digitalisation through conducive digital ECoSystems) is a four year Horizon Europe project that gathers 33 partners all around Europe and which is coordinated by the University of Pisa (https://www.horizoncodecs.eu/. The project aims to improve the motivation and the capacity of European farmers to understand and adopt digitalisation as an enabler of sustainable and transformative change.

Deployment of CODECS results in the framework of the AgriDataValue project represents a strategic alignment designed to bridge the gap between complex technical infrastructure and practical, human-centric adoption in the agri-food sector. While AgriDataValue focuses on the robust technical architecture of big data spaces and smart farming tools, CODECS provides the essential “soft” methodologies—tested engagement tools, digital readiness frameworks, and validated communication pathways—that ensure these technical results are accessible, trusted, and widely adopted by the farming community.

A primary application of CODECS results lies in the customization of training programs through specialized digital readiness frameworks. By segmenting stakeholders—such as individual farmers, cooperatives, or SMEs—based on their specific technical skills and organizational capacities, trainers can tailor capacity-building activities to meet the audience where they are. This targeted approach ensures that complex topics, such as value-chain analytics, are presented in a context that is relevant and manageable for the end-user.

Furthermore, CODECS offers vital insights into data governance and interoperability frameworks. Practical dissemination is further enhanced through the adoption of CODECS’ validated “Farminar” (farm-based webinar) methodologies. These methodologies prioritize high-quality practical content and dynamic facilitation over traditional, theory-heavy lectures. By implementing the five prioritized CODECS principles—practicality, expert facilitation, user-centered design, targeted recruitment, and interactivity—AgriDataValue can ensure its dissemination events are not only informative but also inclusive. This “social-by-design” approach is crucial for reaching those with lower digital literacy, ensuring that technological barriers do not prevent the most vulnerable or traditional stakeholders from benefiting from the project’s innovations.

Ultimately, the synergy between these two projects transforms technical data into actionable knowledge. By embedding CODECS’ practical insights and ranked good practices into its dissemination protocols, AgriDataValue ensures a consistent quality of outreach across various European countries and pilot activities. This collaborative approach fosters a culture of participation and clarity, strengthening the long-term adoption potential of digital tools and moving the European agri-food ecosystem toward a more sustainable, data-driven future.

Union “Farmers’ Parliament” as partner of Codecs Latvian Living Lab worked to understand the practical realities, motivations, and concerns of Latvian farmers regarding digital transformation. Acting as a bridge between technological developers and end-users, the organization ensured that farmers’ voices were systematically integrated into the testing and validation of CODECS tools. Through participatory workshops, surveys, and on-farm demonstrations, the Living Lab explored barriers to digital uptake—ranging from limited digital skills and connectivity issues to concerns about data ownership and unclear return on investment.

On 25–26 February 2026, the Joint Research Centre (JRC) organised the 2nd FIRE Workshop in Ispra, Italy, bringing together representatives from the European Commission, Member States and partner organisations to discuss the implementation of regulatory elements in agricultural monitoring. The workshop provided an important forum for exchanging experience on the Area Monitoring System (AMS), land parcel identification system (LPIS), and new technologies supporting the implementation of the Common Agricultural Policy (CAP). Tomas Orlickas, the Deputy Director of the National Paying Agency, Lithuania (NPA), familiarised the audience with the innovative AMS solutions and cutting-edge approaches by sharing the insights from NPA‘s participation in the international projects.

The workshop opened with remarks from JRC and DG AGRI representatives, setting the context for two days of discussion on both current challenges and future opportunities. A key message of the event was that effective agricultural monitoring increasingly depends not only on technical capacity, but also on cooperation between institutions, countries and research networks.

The discussions focused on AMS implementation challenges and possible solutions, reviewing survey results and highlighting current difficulties in monitoring. Presentations covered practical approaches such as the Dutch experience, outlier detection in Sentinel time series, and crop detection models designed to improve AMS performance. Further presentations explored the use of LPIS and GSA data, AI-supported updates of aerial imagery, and continuous updates of the Land Parcel Identification System with geotagged information. The day ended with a forward-looking session on the next CAP period and innovative monitoring tools.

Tomas Orlickas, Deputy Director of the National Paying Agency (Lithuania), presented “What’s Next after AMS? Strategy of Lithuania post-2027”, focusing on future developments in agricultural monitoring systems. He highlighted the growing role of international projects within this domain, showcasing Horizon Europe (HE), Horizon 2020 projects and other EU initiatives, as as well as national and EU-funded platforms that support data-driven agriculture. His presentation demonstrated how these collaborative projects contribute to advancing monitoring capabilities, including climate and environmental assessment, biodiversity tracking, and carbon accounting systems, thereby reinforcing the importance of international cooperation in shaping the next generation of agricultural monitoring tools. In the presentation the Horizon Europe project AgriDataValue was defined as an example of a “platform of platforms”, demonstrating how multiple data sources and digital tools can be integrated into a unified ecosystem. By combining satellite data, sensor information and farm-level inputs, the project supports smarter decision-making in agriculture, enhances environmental monitoring and promotes more efficient and sustainable farming practices. The project benefits farmers by providing integrated data tools that improve decision-making, optimise resource use, and enhance productivity while reducing environmental impact.

During the workshop the discussions also covered support to candidate countries and LPIS creation, followed by rapid-fire presentations on tools related to crop phenology, farming practices, vegetation dynamics, parcel viewing, image occurrence estimates and farm fragmentation analysis. Drone technology was another important topic, with presentations on the Czech use case and JRC field tests showing how drones can complement satellite-based monitoring with more detailed and flexible observations.

The AgriDataValue project proudly took part in the 31st Agrotica Expo, the International Fair for Agricultural Machinery, Equipment & Supplies, held in Thessaloniki from 12–15 March 2026.

Over the course of four days, the exhibition attracted a large number of visitors, transforming Thessaloniki into a dynamic hub for knowledge exchange, innovation, and collaboration within the agricultural sector.

AgriDataValue was represented by SYNELIXIS, welcoming attendees at Hall 2, Stand 15. Throughout the event, visitors had the opportunity to discover ADV’s forward-looking approach to smart agriculture. Particular interest was shown in how the project integrates advanced sensing technologies, AI-powered decision support systems, and agroecological practices to help farmers adapt to evolving climate challenges.

As emphasized during the exhibition, AgriDataValue goes beyond conventional farming methods by promoting data-driven, precise, and sustainable agricultural practices, ultimately enhancing both efficiency and effectiveness.

The strong engagement with stakeholders throughout the event highlighted the critical role of collaboration, knowledge exchange, and the adoption of innovation in tackling today’s agricultural challenges.

Participating in events like Agrotica offers valuable opportunities to increase the visibility of ADV’s work, strengthen ties with the farming community, and support the transition toward more resilient and sustainable agricultural systems.

AgriDataValue proudly participated in the Verde.Tec Exhibition, one of Greece’s leading events dedicated to environmental technologies and sustainable development. The exhibition took place from February 27–28 and March 1, 2026, at the Mediterranean Exhibition Center (MEC) in Paiania, Attica.

Verde.Tec brings together pioneering companies, research institutions, public authorities, and innovation-driven initiatives that showcase cutting-edge solutions in the fields of environmental protection, circular economy, smart cities, and sustainable infrastructure. The event serves as a key meeting point for stakeholders shaping the green and digital transition in Greece.

During the exhibition, AgriDataValue presented its vision and ongoing work toward its goals. Visitors had the opportunity to learn more about the project’s approach to the development of scalable digital solutions that support sustainable farming and informed decision-making.

Participation in Verde.Tec 2026 provided an excellent platform for networking, knowledge exchange, and strengthening collaboration with industry leaders and technology providers active in environmental and smart-city ecosystems. Through its presence at the exhibition, AgriDataValue further reinforced its commitment to contributing to Europe’s green transition by promoting innovation at the intersection of agriculture, data, and sustainability.

On Friday, 27 February, AgriDataValue successfully organized the 1st Liaison Webinar of Sister Projects, bringing together seven European projects in a highly productive and engaging online meeting. The webinar marked an important step toward strengthening collaboration and fostering synergies among projects working on agricultural data, digital innovation, and interoperability across Europe.

The session kicked off with a dynamic lightning overview round, where each participating project delivered a concise presentation outlining its core objectives, recent progress, and key achievements, setting the stage for a focused and engaging exchange. Alongside AgriDataValue, the sister projects AGRARIAN, CEADS, CODECS, ScaleAgData, 4Growth, and OpenAgri contributed to the exchange, highlighting the complementary nature of their approaches and their shared ambition to advance data-driven agriculture.

AgriDataValue was represented by its Project Coordinator, Theodore Zahariadis, Professor and Head of the Department of Agricultural Development, Agri-Food & Natural Resources at the National and Kapodistrian University of Athens and CTO at Synelixis. The webinar also featured distinguished speakers from across Europe, including Miguel Cachão (Winegrowers’ Association of the Setúbal Peninsula, Portugal), Capwell Forbang Echo (ILVO, Belgium), Gianluca Brunori (University of Pisa, Italy), Tuna Coppens (ILVO – Research Institute for Agriculture, Fisheries and Food, Belgium), Dáire Boyle (Evenflow Consulting LTD, Belgium), and Felipe Arruda Pontes (Maastricht University)

Following the project presentations, participants engaged in a constructive discussion focusing on interoperability approaches, standards and vocabularies, APIs, governance models, and FAIR data practices. The dialogue highlighted common technical and organizational challenges, while also identifying opportunities for alignment and joint development efforts.

The webinar concluded with an agreement on next steps and follow-up collaboration opportunities, reinforcing the importance of structured cooperation among sister projects. Through initiatives like this, AgriDataValue continues to promote knowledge exchange and contribute to building a more connected, interoperable, and sustainable European agri-food data ecosystem.

Phytosanitary treatments, to achieve maximum effectiveness, must be applied at specific phenological stages of the trees.
The following table provides a brief summary of the relationship between the phenological moments when treatments should be applied in stone and pome fruit trees, along with the degree‑days (°D) required for Anarsia lineatella and Grapholita molesta, calculated from the following biofix points:

• Anarsia lineatella: first male captured consistently in traps.
• Grapholita molesta: first consistent peak in traps.

For Anarsia, the first treatment is determined mainly by the crop’s phenology, since the overwintering larvae attack tender shoots at the beginning of the cycle, and this moment is not well described by degree‑days. However, later generations do show a good thermal correlation: the first generation usually coincides with approximately 150–180 °D, the second with 350–450 °D, and the third with 650–750 °D, which allows for more precise scheduling of interventions throughout the season.

For the oriental fruit moth (Grapholita molesta), development depends much more on thermal models than on phenology, making degree‑days an essential tool for correctly timing treatments. Key thresholds begin at 90–120 °D, when damage to young shoots typically starts, and exceed 350 °D when the risk of significant fruit damage increases. These thermal milestones make it possible to anticipate generational development and adjust interventions more effectively.

The availability of models capable of predicting when specific phenological stages will be reached, and how the pests will develop, is therefore essential for carrying out effective phytosanitary treatments, contributing to a reduction in the use of such products and, consequently, to the sustainability of agricultural operations.

Traditional models for phenology prediction (GDD, Winkler, Richardson, etc.) and disease‑risk models are based on calibrating formulas that link temperature to the development of plants and pests. While calibration can be done relatively easily for a field with a local weather station, it becomes much more complex when, as in AgriDataValue Pilot 12: Non‑Citrus Fruit Trees, the goal is to model an entire region (Aragón, in northeastern Spain). In such cases, manual calibration is practically impossible. This is where the capabilities of Big Data and Artificial Intelligence (AI)—particularly Machine Learning (ML)—become crucial: these technologies can perform an enormous number of calculations in a time frame unthinkable for humans, and they can learn from their errors.

Furthermore, these techniques allow for the use of many more data sources: ML‑based models can incorporate additional variables. This enables the models to find relationships that, whether due to limited computational capacity or lack of knowledge, are not considered in current models based primarily on temperature—although temperature is known to be the most influential variable, it is not the only one.

For the development of the ML models, data from  49 public meteorological stations located near the selected fruit orchards are being used. Field observations—phenology and pest presence—are obtained from Red FARA, an application of the Plant Health and Certification Center of the Government of Aragón, responsible for issuing regional phytosanitary advisories, which for woody crops cover 160.000 ha. Additionally, although their relevance is limited, images from Copernicus Sentinel‑2 are included. This restricts the time period considered: data from 2016 to 2025 have been used to train the initial models.

These models represent, to some extent, a general model for Aragón that can be specialized for specific zones or orchards within the region. This will allow the consortium to test the Federated Learning capabilities of the AgriDataValue data space.

The results of the models are made available as services to be used by the CSCV, more than 2000 users, and by anyone interested in applying them in Aragón. In addition, the dataset on which they are based will be published as an outcome of the AgriDataValue project.

As part of the project, Synelixis installed leaf wetness sensors on existing SynField stations in NILEAS olive groves, targeting locations with a known history of olive anthracnose (gloeosporium). To date, a total of two SynField and six SynOdos devices have been installed across NILEA groves, equipped with sensors that collect real-time climatological and soil data. The recently installed leaf wetness sensors help identify and diagnose conditions that are favorable for the development of olive anthracnose (gloeosporium)

Disease development is favoured by the combination of prolonged leaf/fruit wetness, high relative humidity, and mild temperatures – conditions that are common in spring and autumn. Risk increases particularly during periods of rainfall, fog, or overnight dew, and becomes critical from autumn through harvest, especially when targeted spring plant protection has not been implemented, and when the ripening fruit is more susceptible due to olive fruit fly damage, leading to major yield losses ranging from 30% in mild epidemics to 70% in severe cases. This is why continuous monitoring of wetness duration at canopy level is essential for reliable forecasting.

Using sensor data (leaf wetness, meteorological and microclimatic variables etc), and integrating these into AI-based predictive models being developed within the AgriDataValue project, Synelixis’ digital tools translate measurements into risk indicators and send notifications/alerts when conditions converge towards an increased likelihood of infection. The aim is early warning, enabling growers and agronomists to make evidence-based plant protection decisions at the right time.