Specialty Crop Disease Identification & Action Planning
Diagnose specialty crop diseases and generate evidence-based treatment plans instantly
What You Can Do
Document field symptoms and receive AI-assisted disease diagnosis with confidence levels based on pathogen patterns, environmental conditions, and crop-specific vulnerabilities. Generate integrated pest management (IPM) treatment plans that include fungicide/biological options, application timing, and prevention strategies—all within hours instead of waiting for lab results or extension appointments. Compare treatment costs against crop value to prioritize management efforts across multiple field issues.
Features
Cross-references leaf lesions, canopy patterns, root damage, and environmental conditions against specialty crop disease profiles
Suggests fungicide, biological, and cultural control options ranked by efficacy, cost, and certification compatibility
Creates step-by-step application schedules, spray intervals, and tank-mix compatibility checks for your specific crop and operation scale
Outlines monitoring schedules, resistant variety options, and sanitation protocols to break disease cycles
Filters recommendations based on organic, conventional, or transitional certification requirements
Compares treatment expense against crop market value and yield loss projections to guide ROI decisions
Tracks symptom progression and environmental triggers to inform future season planning and spray timing adjustments
Example Output
Disease Diagnosis Example:
- Suspected pathogen: Botrytis cinerea (gray mold) — 85% confidence
- Key indicators: Brown-gray fuzzy mycelium on ripening berries, high humidity + cool nights (58–72°F), poor canopy airflow
- Secondary risk: Phomopsis leaf spot (40% confidence)
Generated Treatment Plan:
- Immediate (24–48 hrs): Apply sulfur dust or biological fungicide (e.g., Bacillus subtilis) on all affected blocks; thin canopy for airflow
- Week 1–2: Scout daily; increase spray interval to 7-day cycles if conditions favor disease
- Prevention: Install micro-sprinklers to reduce leaf wetness duration; remove infected fruit debris post-harvest
- Cost estimate: $250/acre for 3 applications vs. estimated $1,800/acre yield loss if untreated
Monitoring Checklist: ✓ Humidity levels at dawn (target <85% by 10am) ✓ New lesion appearance (indicates active infection) ✓ Fungicide efficacy (sample 20 berries/block post-application)
What's Included
- SKILL.md instruction file with diagnostic framework and disease reference database:
- Field Observation Template: Structured form for documenting symptoms, environmental conditions, and crop stage
- IPM Treatment Planner: Fungicide/biological option matrix with application schedules and tank-mix compatibility
- Prevention Protocol Checklist: Sanitation, monitoring, and variety selection workflows for disease cycle management
- Cost-Benefit Decision Tool: Worksheet for comparing treatment costs against crop value and yield loss projections
Who It's For
- Specialty crop farm managers (berries, stone fruits, tree nuts, vegetables, hops, wine grapes) managing disease outbreaks during growing season
- Organic and transitional operation owners needing certification-compliant treatment options under time pressure
- Multi-block farm operators triaging disease issues across fields to prioritize scouting and management resources
- Integrated pest management (IPM) consultants preparing preliminary diagnoses before lab confirmation or extension consultation
- Agricultural extension educators supporting remote or off-hours farmer decision-making for disease management
Best For
- Rapid preliminary disease diagnosis from field observations (symptoms + photos) when lab results unavailable
- Generating treatment protocols within 24–48 hours before disease spread compromises yield
- Comparing fungicide, biological, and cultural control options aligned with crop value and certification status
- Building disease monitoring schedules and prevention strategies to reduce future season incidence
- Documenting symptom progression and environmental conditions for disease cycle pattern recognition and spray timing optimization
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