On 30 May, the final event of the APNR – Academy del Pinot Nero Research project was held at the Prime Alture agricultural company (lead partner), in collaboration with Geosmartcampus Srl. APNR is an industrial Proof of Concept funded under the Cascade Calls – Line A of the NODES – Nord Ovest Digitale e Sostenibile programme, aimed at developing innovative technologies and strategies to enhance the Pinot Noir supply chain in the Oltrepò Pavese region of northern Italy.   The project focused on two complementary areas: experimental fieldwork in the vineyard, with the installation of pilot systems, and market research to analyse consumer preferences and refine product positioning strategies. Among the innovations tested in the vineyard, special attention was given to the use of inter-row mulching, an agronomic technique involving the autumn-winter sowing of temporary cover crops. These are later shredded and channelled beneath the vines using a dual-row mulching machine, creating a uniform organic layer. This practice significantly suppressed weed regrowth throughout the season without the need for further intervention, while repurposing plant residues from within the vineyard ecosystem itself—an example of circular sustainability.   A second pilot involved the use of shade nets, designed to reduce incident solar radiation by 20% to 70%. The results were highly promising: the nets helped prevent sunburn on grape clusters and improved overall agronomic performance. Analytical data recorded slightly higher yields (127 kg per row with nets vs. 124 kg without; 2.12 kg per vine with nets vs. 1.87 kg without), better fruit distribution, and healthier vines with minimal fungal disease. Labour was also optimised, as no de-shooting was required and harvesting was easier thanks to the clear and compact cluster arrangement.   On the industrial research side, the APNR team conducted a two-phase market study. The qualitative phase explored emotional responses, perceptions, and narratives surrounding Pinot Noir, gathering insights from sommeliers, chefs, and wine enthusiasts to guide marketing strategies and uncover new consumption occasions. The subsequent quantitative phase validated these insights across a representative sample of wine consumers, identifying high-potential target groups and effective communication strategies to attract and retain new audiences.   APNR has served as a practical example of how combining field-based innovation with market intelligence can produce tangible benefits for wine producers, enabling a shift toward more sustainable, competitive, and consumer-conscious viticulture.

On May 22, the final event of the SPIDAP project – Development of a Digital Platform Based on Artificial Intelligence for Precision Agriculture – was held at the GAL Terre di Aci headquarters in Acireale (CT). The project was funded through the cascade calls.  SPIDAP is the result of a collaborative effort between Sicilian SMEs Agrigeos and Lualtek, and the CNR-IMEM Institute in Parma. It integrates artificial intelligence, advanced sensor technology, and agronomic analysis to optimize water usage and improve the sustainability of citrus production—an innovative step forward for smart agriculture tailored to local needs. The event was moderated by Mariarita Zappalà (Agrigeos), and opened with institutional remarks by Anna Privitera (Director, GAL Terre di Aci), who emphasized the GAL’s role in promoting agricultural innovation in a region with a strong citrus-growing tradition. Chiara Ferroni, Director of the NODES ecosystem, highlighted the achievements of the program, which has supported over 300 companies, including many in Southern Italy. Salvo Nicolosi (General Manager, Agrigeos) underlined the importance of partnerships between SMEs and research centers in developing knowledge and technologies to advance the agricultural sector. The technical session featured presentations by Marco Acciai (Agrigeos), who showcased field and controlled-environment results using the Plantarray phenotyping system and the Bioristor sensor developed by CNR-IMEM. Michela Janni (CNR-IMEM) explained how the Bioristor enables real-time monitoring of plant physiology, essentially allowing researchers to “listen” to the plants. Luca Occhipinti (CEO, Lualtek) closed the session by demonstrating how Bioristor data and electrical conductivity readings can be integrated into predictive models to optimize irrigation. The event concluded with a shared commitment to continue data collection and refine the predictive model, confirming the value of a collaboration that has already yielded promising results for the digital transformation of the citrus sector.

The DigiFarm project has successfully concluded. This industrial Proof of Concept (POC), funded through the cascade call Line A, was developed to provide innovative tools to dairy sector enterprises, with the goal of improving nutritional and economic efficiency in milk production. At the heart of the project lies a well-known challenge for farmers: feed costs can account for up to 60% of the total cost of milk production. DigiFarm tackled this issue by developing a simple, effective, and easily applicable assessment model, based on a system of aggregated indicators capable of delivering a clear picture of farm performance—even with minimal field data. The strength of the model lies in its accessibility: it does not require full corporate accounting and can be adopted even by small and medium-sized enterprises, which make up the majority of Italy’s livestock production sector. By integrating technical and economic data, DigiFarm overcomes the limitations of partial indicators, which are often affected by external variables such as market fluctuations in feed or milk prices. The model enables precise identification of areas for improvement, enhancing production efficiency and economic sustainability for the farms involved. The results gathered during implementation confirm the model’s effectiveness: good feed conversion efficiency, satisfactory milk quality, and cost coverage even in less favorable market conditions. Beyond operational benefits, DigiFarm has also had a positive impact in terms of training and professional development, strengthening participants’ skills in livestock data analysis, efficiency modeling, and knowledge transfer to the production sector. DigiFarm stands as a concrete example of how digital innovation can support the agro-food sector’s transition toward more resilient, sustainable, and quality-driven production models—fully aligned with the priorities of the new European agriculture.

The session “Soil management practices and land degradation in vineyards”, held on 28–29 April during the European Geosciences Union General Assembly 2025 (EGU) in Vienna, featured active participation from researchers at the University of Pavia. Claudia Meisina chaired the session, guiding an international scientific dialogue on soil degradation and sustainable practices in viticulture.   The contributions presented stemmed from research activities carried out within the VINO flagship project, part of NODES – SPOKE 6 – Primary Agroindustry, and covered a broad range of topics. Massimiliano Bordoni, Valerio Vivaldi, and Claudia Meisina presented work on shallow landslide prediction models, hydrogeological characterisation, and vulnerability analysis on vineyard slopes. Fabio Dell’Acqua introduced an automated mapping approach for inter-row vineyard management using satellite imagery and Bézier curve analysis. Diego Ravazzolo discussed a surface runoff model applied to assess erosion in agricultural landscapes.   Among the on-site posters, Antonio Gambarani, Matteo Giganti, along with Bordoni, Vivaldi, and Meisina, showcased studies on the application of nature-based solutions, the quantification of soil degradation, and future land suitability for perennial crops. The event highlighted the quality and relevance of the outcomes generated by the VINO project, fostering an interdisciplinary exchange between geosciences, digital technologies, and sustainable farming practices. 🔗 Learn more about the session: https://meetingorganizer.copernicus.org/EGU25/session/52887