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Agri Intelligence

智能农业分析助手 - 作物病害识别、种植优化、产量预测及农业市场情报。支持...

person作者: ai-gaoqianhubclawhub

Agri Intelligence - Smart Agriculture AI Skill

Core Capabilities

| Capability | Description | |---|---| | Crop Disease ID | Identify crop diseases from images or symptom descriptions with treatment recommendations | | Planting Calendar | Generate optimized planting schedules based on region, climate zone, and crop type | | Yield Prediction | Predict harvest yields using historical data, weather patterns, and soil conditions | | Market Intelligence | Track agricultural commodity prices across major markets, supply-demand analysis | | Soil Analysis | Interpret soil test results and recommend fertilization strategies | | Pest Management | Integrated pest management plans tailored to specific crops and regions |

Trigger Scenarios

  • "What disease is affecting my tomato plants?"
  • "When should I plant wheat in Henan province?"
  • "Predict my corn yield based on 50 acres with loam soil"
  • "Current soybean prices in major Chinese markets"
  • "Analyze this soil report and suggest fertilizers"

Execution Flow

Phase 1: Context Gathering

  • Collect crop type, region, field size, soil data, and historical records
  • Request images if disease/ pest identification is needed

Phase 2: Domain Analysis

  • Cross-reference symptoms with agricultural pathology database
  • Factor in regional climate data and seasonal patterns
  • Apply crop-specific growth models for yield estimation

Phase 3: Recommendation Output

  • Disease: diagnosis confidence score, treatment options (organic/chemical), prevention tips
  • Planting: week-by-week calendar with action items
  • Market: price trends table with buy/sell timing suggestions
  • Yield: predicted range with confidence interval and key influencing factors

Output Template

## Agri Intelligence Report
**Crop**: [crop type]
**Region**: [region]
**Date**: [current date]

### Analysis Results
[Key findings]

### Recommendations
[Actionable steps with priority levels]

### Data Sources
- [Source 1]
- [Source 2]

Notes

  • Soil and climate data accuracy depends on region coverage
  • Disease identification works best with clear, well-lit images
  • Market prices are delayed by 1-3 days depending on exchange
  • Free to use; no code execution required