1. Introduction
  - Rationale for utilizing artificial intelligence in crop disease diagnosis and management
  - Objectives of the research
2. Review of Literature
  - Applications of AI in plant disease detection and classification
  - Challenges and opportunities for AI-based disease management
3. Methodology
  - Selection of AI algorithms and models for disease diagnosis
  - Data collection and annotation for training AI systems
  - Validation and performance evaluation of AI-based disease detection tools
4. AI Model Development
  - Training and optimization of AI models for crop disease diagnosis
  - Integration of AI tools with disease management decision support systems
5. Case Studies
  - Application of AI-based disease diagnosis and management in specific crops or regions