Efforts to revive traditional chestnut growing face a shortage of suitable technological solutions to overcome the physical constraints of mountain terrain and the financial limitations of small family businesses. As a result, chestnut orchard owners tend to rely on labour-intensive, physically demanding and inefficient manual methods. These issues were explored at two events organised by ITABIA on the second day of EIMA International: “Modern Mechanisation and Traditional Chestnut Growing” and “CastaneaGPT: a Chatbot for the Chestnut Community”.
In the past, research focused on plant health and the recovery of traditional varieties, speakers at the first workshop explained. However, restoring the sustainability of chestnut growing requires more than tackling plant health problems such as the chestnut gall wasp and chestnut blight. Labour shortages are another challenge. Several technological solutions are now available, including satellite-based monitoring of tree health, which can improve working efficiency while delivering an economic return.
The event presented the results of mechanisation trials conducted in the experimental chestnut orchard at Sant’Agata d’Esaro, in the province of Cosenza, with the aim of identifying solutions suited to traditional chestnut growing. Coordinated by ITABIA with support from Raffaele Spinelli of CNR IBE, the workshop featured contributions from Dr Biocca of CREA on modern, lightweight machinery for mountain chestnut orchards, including radio-controlled hydraulic tool carriers and electric pruning tools; Dr Di Mauro, who outlined the potential and benefits of occupational exoskeletons; and Dr Seragnoli, a chestnut-growing expert and organiser of Castanea Expo 2026, an annual event held at the Fortezza da Basso in Florence.
This was followed by a session led by CNR researcher Benno Eberhard, entitled “CastaneaGPT: a Chatbot for the Chestnut Community”. Today, the challenge in chestnut growing is not a lack of knowledge, but access to it. CastaneaGPT is an AI-based digital application that enables researchers, forestry professionals, chestnut growers, students and enthusiasts to share knowledge about chestnut trees.
At the heart of the application is a chat interface: users ask questions as they would a consultant and receive answers grounded in actual documents. One of its distinctive features is its ability to adapt to the user. Three response modes adjust the language and level of detail: a professional mode for technical specialists; a decision-support mode for woodland managers and chestnut-growing businesses; and a playful mode for children, school groups and tourists.
To complete the experience, CastaneaGPT offers an interactive map of georeferenced chestnut woodlands, a glossary of forestry and botanical terms, and a quiz to test users’ knowledge of chestnut biology, history and management.