Augmented Reality for Crop Management in Precision Agriculture: From Current Applications to a Development Framework

Crop diseases, pest infestations, environmental stress, and resource-management limitations challenge effective crop management within precision agriculture. Augmented reality (AR) offers opportunities to integrate crop observations with digital agricultural information, yet limited attention has been given to synthesizing limitations affecting AR-assisted systems in disease detection, pest monitoring, and agricultural decision-making. Across these areas, 24 AR-assisted systems were comparatively analyzed alongside the supporting technological, biological, and conventional-method literature. Cross-area synthesis examined the challenges addressed, AR’s role, and technological limitations. The findings informed a development framework comprising five considerations: reliable agricultural information generation, field-capable system architecture, computation, and connectivity, spatial and contextual information presentation, human-interpretable information and decision support, and task-integrated field interaction and operational robustness, complemented by cross-cutting validation. Illustrated through an AR-assisted rice disease-assessment prototype, the framework provides a structured basis for developing and evaluating future AR-assisted crop-management systems. The review highlights that AR’s practical value in crop management depends not only on information visualization but also on task integration, trade-offs between analytical detail and operational feasibility, reliable sensing and processing, field-compatible architectures, and validation of its contribution to agricultural decision-making.