> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Agriculture Template

> Four-agent precision farming pipeline — multispectral imagery analysis, pest and disease detection, targeted spray recommendations, and yield forecasting.

Analyse drone or satellite imagery, detect crop stress and pests before they spread, and receive actionable treatment plans — all from a single workflow call.

Analyse drone or satellite imagery, detect crop stress and pests before they spread, and receive actionable treatment plans — all from a single workflow call.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.agriculture_template import precision_agriculture_workflow

result = precision_agriculture_workflow("Field 12 multispectral scan — NDVI drop in north quadrant")
print(result)
```

The user uploads crop imagery; agents detect stress, pests, and irrigation recommendations per field.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "Precision Agriculture Workflow"
        IN["🛸 Drone/Satellite"] --> MA["🤖 MultispectralAnalyzer"]
        MA --> DI["🤖 DiseaseIdentifier"]
        DI --> SR["🤖 SprayRecommender"]
        SR --> YP["🤖 YieldPredictor"]
        YP --> OUT["✅ Farmer App"]
    end

    classDef input fill:#6366F1,stroke:#7C90A0,color:#fff
    classDef agent fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff

    class IN input
    class MA,DI,SR,YP agent
    class OUT output

    classDef agent fill:#8B0000,color:#fff
    classDef tool fill:#189AB4,color:#fff
```

## Quick Start

<Steps>
  <Step title="Run the prebuilt workflow for multiple fields">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    from praisonaiagents import Agent, tool
    from examples.cookbooks.Industry_Templates.agriculture_template import precision_agriculture_workflow

    fields  = ["FIELD-001", "FIELD-002", "FIELD-003"]
    weather = {"temperature": 25, "humidity": 60, "wind_speed": 8, "precipitation": 0}

    result = precision_agriculture_workflow(fields, "wheat", weather)

    print(result["alerts"])
    print(result["yield_forecasts"])
    print(f"Sustainability score: {result['sustainability_score']:.0f}/100")
    ```
  </Step>

  <Step title="Use IoT sensor network agent for real-time data">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    from examples.cookbooks.Industry_Templates.agriculture_template import IoTSensorPatterns

    sensor_agent = IoTSensorPatterns.create_sensor_network_agent(
        sensor_types=["soil_moisture", "temperature", "humidity", "ph"]
    )

    status = sensor_agent.start("Collect sensor readings from all FIELD-001 nodes")
    print(status)
    ```
  </Step>
</Steps>

***

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant Drone as "Drone/Satellite"
    participant MultispectralAnalyzer
    participant DiseaseIdentifier
    participant SprayRecommender
    participant YieldPredictor
    participant FarmerApp as "Farmer App"

    Drone->>MultispectralAnalyzer: Raw multispectral imagery
    MultispectralAnalyzer-->>DiseaseIdentifier: MultispectralData schema (NDVI, NDRE, CCCI)
    DiseaseIdentifier-->>SprayRecommender: PestDiseaseReport schema
    SprayRecommender-->>YieldPredictor: SprayRecommendation schema
    YieldPredictor-->>FarmerApp: YieldForecast schema
```

| Agent                   | Responsibility                                                        | SLA               |
| ----------------------- | --------------------------------------------------------------------- | ----------------- |
| `MultispectralAnalyzer` | Calculate NDVI/NDRE/CCCI vegetation indices and identify stress zones | ≤ 2 min per field |
| `DiseaseIdentifier`     | AI-based pest and disease classification with severity level          | ≤ 30 s            |
| `SprayRecommender`      | Targeted spray strategy — product, rate, GPS zones, weather window    | ≤ 1 min           |
| `YieldPredictor`        | Harvest yield forecast with quality grade and market value estimate   | ≤ 45 s            |

***

## Configuration Options

Pydantic I/O schemas used by this template:

| Schema                | Key Fields                                                                                                                                                     |
| --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `MultispectralData`   | `field_id`, `ndvi_index`, `ndre_index`, `ccci_index`, `moisture_level`, `temperature`, `affected_area`, `gps_coordinates`                                      |
| `PestDiseaseReport`   | `report_id`, `field_id`, `pest_type`, `disease_type`, `severity`, `affected_crops`, `spread_rate`, `confidence_score`                                          |
| `SprayRecommendation` | `recommendation_id`, `field_id`, `treatment_type`, `product_name`, `application_rate`, `target_zones`, `optimal_time`, `cost_estimate`, `environmental_impact` |
| `YieldForecast`       | `forecast_id`, `field_id`, `crop_type`, `predicted_yield`, `confidence_interval`, `harvest_window`, `quality_grade`, `market_price_estimate`                   |

**Severity levels** (used in `PestDiseaseReport`)

| Level      | Meaning               | Typical action                    |
| ---------- | --------------------- | --------------------------------- |
| `none`     | No threat detected    | Routine fertiliser application    |
| `low`      | Early blight signs    | Organic treatment (e.g. Neem Oil) |
| `moderate` | Localised infestation | Targeted fungicide/pesticide      |
| `high`     | Spreading infestation | Systemic treatment + monitoring   |
| `severe`   | Field-wide outbreak   | Emergency intervention            |

***

## Common Patterns

**Integrated Pest Management (IPM) strategy by severity**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.agriculture_template import SustainableFarmingPatterns

strategy = SustainableFarmingPatterns.integrated_pest_management("moderate")
print(strategy)
```

**Precision irrigation based on soil moisture**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.agriculture_template import SustainableFarmingPatterns

irrigation = SustainableFarmingPatterns.precision_irrigation(
    moisture_level=25.0,
    crop_stage="flowering"
)
print(f"Irrigate: {irrigation['irrigation_needed']}, Amount: {irrigation['amount_mm']} mm")
```

**Recommend next crop for rotation**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.agriculture_template import SustainableFarmingPatterns

next_crop = SustainableFarmingPatterns.crop_rotation_optimizer("wheat", soil_data={})
print(f"Next crop: {next_crop}")
```

***

## Best Practices

<AccordionGroup>
  <Accordion title="Fly imagery in optimal lighting conditions">
    `MultispectralAnalyzer` accuracy degrades significantly in overcast conditions or when shadows cover more than 20 % of a field. Schedule drone flights within 2 hours of solar noon for best NDVI readings.
  </Accordion>

  <Accordion title="Act on high-severity alerts within 24 hours">
    `DiseaseIdentifier` reports `spread_rate` in % per day. At high severity (`spread_rate > 2 %`), a one-day delay can double the affected area. The workflow automatically generates a `SprayRecommendation` for high/severe findings.
  </Accordion>

  <Accordion title="Monitor the sustainability_score trend">
    The workflow calculates a `sustainability_score` (0–100) based on total chemical application. Track this per season — a declining score signals overuse of pesticides, which correlates with long-term soil health degradation.
  </Accordion>

  <Accordion title="Validate GPS spray zones before field application">
    `SprayRecommendation.target_zones` contains GPS polygon boundaries. Always cross-check these against your field boundary GIS layer to prevent off-target application near water bodies or buffer zones.
  </Accordion>
</AccordionGroup>

***

## Related

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