Advanced biocontrol strategies boosted by artificial intelligence in some horticultural living labs and socio-economic issues

The urgent transition toward sustainable agricultural systems, driven by European policies (Green Deal, Farm to Fork), necessitates a drastic reduction in reliance on plant protection products. This thesis explores the integration of advanced biocontrol strategies and Artificial Intelligence (AI) technologies into Integrated Pest Management (IPM) for horticulture, while simultaneously evaluating the associated complex socio-economic challenges. The research employs an experimental, participatory approach based on "living labs," involving pilot farms in the province of Alessandria that cultivate crops such as onions, shallots, and processing tomatoes. Agroecological protocols combining biocontrol agents (e.g., Orius laevigatus, Macrolophus pygmeus) and "banker plants" (such as Lobularia maritima and Tagetes spp.) with advanced digital infrastructure were tested in the field. The synergistic use of IoT networks, Decision Support Systems (DSS), and AI-driven smart traps for pest detection enabled real-time, predictive monitoring of pest dynamics. Results demonstrate that data analysis combined with proactive biocontrol ensures effective crop protection and competitive yields, while significantly reducing the chemical footprint and toxicological risks for operators. However, the socio-economic analysis highlights significant systemic barriers to the adoption of these technologies: the digital divide, high initial investment costs, cybersecurity vulnerabilities, and complexities regarding data governance. The study confirms that the transition to Agriculture 5.0 requires not only technological innovation but also a profound overhaul of agricultural advisory services (AKIS networks) and inclusive active policies—elements essential to ensuring equity, resilience, and profitability for future generations of farmers.