AI-Driven Design and Environmental Risk Assessment of Nanoformulated Mycoherbicides for Sustainable Weed Management

This review explores recent advancements in AI-assisted nanoformulated mycoherbicides as sustainable alternatives to synthetic herbicides for precision weed management. The integration of nanotechnology enhances the delivery, stability, and efficacy of fungal metabolites, while artificial intelligence enables optimization of formulation parameters and predictive modelling of environmental behavior. Key physicochemical properties, mechanisms of action, and AI-driven design strategies are discussed in detail. The environmental fate and biosafety of nanoformulated mycoherbicides are critically evaluated, including their interactions with soil, water systems, plants, and non-target organisms. Compared to conventional herbicides, these systems exhibit improved target specificity, reduced environmental persistence, and enhanced biodegradability. However, challenges related to scalability, regulatory frameworks, and long-term ecological impacts remain. The review highlights commercialization pathways and emphasizes the role of AI in risk mitigation and formulation optimization. Strategic recommendations are proposed to accelerate adoption, including standardization of biosafety protocols, investment in AI-driven research, and strengthening industry–academia collaborations. Overall, AI-assisted nanoformulated mycoherbicides represent a promising approach for sustainable and precision-based weed management.