The integration of information technology into agriculture is fundamental to modern agricultural development. However, traditional agricultural information models, which rely on analytical AI for prediction and monitoring, face significant limitations in handling unstructured data, generating actionable knowledge, and supporting complex decision-making in dynamic farm environments. This study's core innovation lies in constructing a “Generative AI-Driven Agricultural Informatization Framework” (GAAIF), which quantifies the synergistic mechanisms between generative models and specific agricultural scenarios. By introducing a multi-modal data fusion engine and a task-specific fine-tuning p... More >