23  Introduction to Precision Livestock Farming

23.1 Overview

This chapter provides an overview of precision livestock farming (PLF) technologies and their role in phenotyping for animal breeding.

23.2 Learning Objectives

By the end of this chapter, you should be able to:

  1. Define precision livestock farming and its objectives
  2. Identify major PLF technologies and their applications
  3. Explain how PLF enables high-throughput phenotyping for breeding
  4. Understand data management challenges with PLF
  5. Recognize opportunities for PLF to accelerate genetic improvement

23.3 What is Precision Livestock Farming (PLF)?

Chapter Status

This chapter is currently under development.

Definition: Using sensors, automation, and data analytics to monitor and manage individual animals

Objectives: - Improve animal welfare - Increase productivity - Enhance efficiency - Promote sustainability

23.4 PLF Technologies Overview

23.4.1 Sensors

  • Wearables (collars, ear tags, leg bands)
  • Cameras (2D, 3D, thermal)
  • Microphones
  • Environmental sensors
  • Feeding systems

23.4.2 Data Collection

  • Continuous, automated, high-resolution
  • Massive datasets requiring careful management

23.4.3 Data Analytics

  • Machine learning
  • Computer vision
  • Predictive models

23.5 PLF for Phenotyping in Animal Breeding

23.5.1 Advantages

  • High-throughput phenotyping: Measure thousands of animals automatically
  • New traits: Traits difficult or expensive to measure traditionally
    • Individual feed intake
    • Activity and behavior
    • Health indicators
  • Precision: Reduced measurement error
  • Longitudinal data: Repeated measurements over time

23.6 Key Application Areas

  1. Feed efficiency: Individual feed intake (RFI, FCR)
  2. Health monitoring: Early disease detection, lameness, mastitis
  3. Reproduction: Estrus detection, calving/farrowing monitoring
  4. Behavior and welfare: Activity, lying time, social interactions
  5. Growth and body composition: Automated weighing, 3D imaging
  6. Environmental impact: Methane emissions, nitrogen excretion

23.7 Data Management Challenges

  • Volume: Massive datasets (terabytes per farm)
  • Quality control: Sensor errors, missing data, outliers
  • Integration: Linking sensor data with pedigree and genomic data
  • Privacy and security: Data ownership, sharing, security

23.8 PLF and Genetic Improvement

PLF enables:

  • Selection for hard-to-measure traits (feed efficiency, methane, health)
  • Increased accuracy of genetic evaluations (more data per animal)
  • Identifying new traits (resilience, robustness, stress response)
  • Genotype-by-environment interactions

23.9 Challenges and Opportunities

23.9.1 Challenges

  • Cost of sensors and infrastructure
  • Validation of sensor data accuracy
  • Farmer adoption and training
  • Integration with breeding programs

23.9.2 Opportunities

  • Accelerate genetic improvement
  • Novel phenotypes for selection
  • Improved animal welfare monitoring

23.10 Summary

Precision livestock farming enables automated, high-throughput phenotyping that can accelerate genetic improvement.

23.11 Key Points

  • PLF technologies generate vast amounts of data requiring careful management
  • PLF enables genetic selection for traits previously too expensive to measure
  • Integration of PLF data with breeding programs is an active research area