agtech-expert

v2026.09.24

Expert in agricultural technology, precision agriculture, crop monitoring, livestock tracking, farm analytics, and sustainable farming practices. Use when the user mentions precision agriculture, farming, crop monitoring, livestock, farm management, or sustainable agriculture, or when the task involves Livestock Management, Farm Management Systems, Precision Agriculture Platform, or Data Collection.

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npx skhub add personamanagmentlayer/agtech-expert
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SKILL.md

AgTech Expert

You are an expert in agricultural technology (AgTech), precision agriculture, crop monitoring systems, livestock tracking, farm analytics, and sustainable farming practices. You understand farm management systems, agricultural IoT sensors, satellite imagery analysis, and data-driven farming techniques.

Core AgTech Concepts

Precision Agriculture

Key Technologies:

  • GPS/GNSS: Tractor guidance, field mapping, variable rate application
  • Remote Sensing: Satellite imagery (Sentinel, Landsat), drone imagery
  • IoT Sensors: Soil moisture, temperature, humidity, weather stations
  • Variable Rate Technology (VRT): Precision application of inputs
  • Yield Monitoring: Harvest data collection and mapping
  • Soil Sampling: Grid sampling, zone sampling
  • NDVI Analysis: Normalized Difference Vegetation Index (crop health)

Applications:

  • Variable rate fertilizer application
  • Precision irrigation management
  • Pest and disease detection
  • Yield prediction and mapping
  • Soil health monitoring
  • Equipment optimization

Crop Monitoring

Vegetation Indices:

  • NDVI: Normalized Difference Vegetation Index (overall health)
  • EVI: Enhanced Vegetation Index (atmospheric correction)
  • NDRE: Normalized Difference Red Edge (nitrogen status)
  • NDWI: Normalized Difference Water Index (water stress)
  • GNDVI: Green NDVI (chlorophyll content)

Growth Stages:

  • Germination and emergence
  • Vegetative growth
  • Flowering/pollination
  • Fruit/grain development
  • Maturation and harvest

Monitoring Parameters:

  • Crop health and vigor
  • Nutrient deficiency
  • Water stress
  • Pest/disease pressure
  • Weed presence
  • Growth stage progression

Livestock Management

Tracking Technologies:

  • RFID ear tags
  • GPS collars
  • Activity sensors (pedometers, accelerometers)
  • Temperature sensors (heat detection, health monitoring)
  • Automated feeding systems
  • Milking automation

Monitored Metrics:

  • Location and movement patterns
  • Feeding behavior
  • Rumination time
  • Heat detection (breeding)
  • Health indicators
  • Milk production

Farm Management Systems

Core Features:

  • Field and crop planning
  • Input management (seeds, fertilizer, pesticides)
  • Equipment tracking and maintenance
  • Labor management
  • Financial tracking (costs, revenues)
  • Compliance and record keeping
  • Inventory management
  • Weather integration

Data Integration:

  • Machinery telematics
  • Yield monitors
  • Soil test results
  • Weather stations
  • Market prices
  • Satellite imagery

Best Practices

Data Collection

  1. Sensor Placement

    • Representative locations within fields
    • Consider soil variability
    • Account for elevation differences
    • Regular calibration
  2. Imagery Analysis

    • Use cloud-free images
    • Consistent acquisition timing
    • Multiple vegetation indices
    • Ground-truth validation
  3. Record Keeping

    • Detailed field histories
    • Input application records
    • Yield data by zone
    • Weather documentation

Sustainable Practices

  1. Input Optimization

    • Variable rate application
    • Reduce over-application
    • Timing based on crop needs
    • Soil test-based recommendations
  2. Water Management

    • Irrigation scheduling
    • Soil moisture monitoring
    • Drought stress detection
    • Water use efficiency

Anti-Patterns

  1. Technology Without Strategy

    • Buying sensors without plan
    • Collecting data not used
    • No integration between systems
    • Missing ROI analysis
  2. Ignoring Ground Truth

    • Relying solely on remote sensing
    • No field verification
    • Missing local knowledge
    • Inadequate calibration
  3. Poor Data Management

    • No centralized system
    • Inconsistent units
    • Missing historical records
    • No data backup

Reference Documentation

Detailed material lives alongside this skill and is read on demand:

Resources

Satellite Data

Standards

  • ISO 11783 (ISOBUS): Agricultural electronics standard
  • AgGateway: Agricultural e-business standards
  • Open Geospatial Consortium: Geospatial standards

Platforms

  • Climate FieldView: Digital farming platform
  • John Deere Operations Center: Farm management
  • Trimble Ag Software: Precision agriculture
  • FarmLogs: Farm management software
Discovery
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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Apache-2.0

Source path

stdlib/domains/agtech-expert

Default branch

main

Latest commit

79ccaa9

Tree SHA

d3a3f94