Demonstrates the effectiveness of AI-driven biocontrol in horticulture, suggesting improved pest management strategies.
<ns3:p>Modern horticulture faces the dual imperatives of increasing global food production while mitigating the severe environmental and health impacts of conventional chemical pesticides. Biological control agents (BCAs), which utilize beneficial microorganisms, macroorganisms, semiochemical and botanicals to suppress pathogens, represent a cornerstone of sustainable agriculture but have been historically constrained by inconsistent field performance, high specificity, and slow action. Concurrently, Artificial Intelligence (AI) is emerging as a transformative force in agriculture, offering a powerful suite of tools for data analysis, prediction, and automation. The synergy of BCAs and AI creates advanced strategies where AI directly addresses the inherent limitations of biological control. It can foster the deployment of AI-driven predictive models for proactive pest outbreak forecasting, enabling timely and effective BCA application. Furthermore, it details the role of precision robotics and drones, guided by computer vision, in the targeted delivery of these agents. These components are synthesized into the concept of Integrated Pest Management (IPM) 5.0, where intelligent decision support systems orchestrate a holistic, data-driven approach to plant health. However, the realization of this vision is contingent on overcoming significant economic, regulatory, and adoption hurdles. High initial costs, complex and divergent regulatory countries in the EU and US, and socio-technical barriers to farmer adoption present formidable challenges. A focus on developing robust, low-cost technologies, enhancing BCA formulation and stability, creating interoperable data frameworks, and addressing the socio-economic factors is necessary to translate technological potential into widespread, sustainable practice.</ns3:p>
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Andrea Lovazzano (2026) studied this question.
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