Non-Invasive Human-Free Diagnosis Methods for Assessing Pig Welfare at Abattoirs: A Systematic Review

Area of Science:

• Animal Science
• Veterinary Medicine
• Food Safety

Background:

• Traditional pig welfare and health assessments at abattoirs rely on subjective, time-consuming human observation.
• High-throughput facilities require scalable, objective, and non-invasive methods for efficient evaluation.
• Ensuring animal well-being and food safety necessitates improved diagnostic tools in commercial settings.

Purpose of the Study:

• To systematically review and evaluate non-invasive, human-free diagnostic methods for pig welfare and health assessment in abattoirs.
• To identify and categorize emerging technologies applicable to commercial slaughter operations.
• To assess the implementation potential and practical challenges of these novel methods.

Main Methods:

• Systematic literature review adhering to PRISMA guidelines.
• Inclusion of 102 articles evaluating diagnostic methods for pig welfare and health.
• Classification of identified methods into biological sample analysis, imaging/computer vision, and sensor-based systems.

Main Results:

• Thirteen distinct non-invasive methods were identified across three categories.
• Blood analysis (glucose, lactate), convolutional neural networks (lesion detection), and automated camera systems show the most promise.
• No single method currently offers both high implementation and practicality, with challenges in automation and standardization.

Conclusions:

• Non-invasive diagnostic methods offer significant potential for improving pig welfare and health assessment in abattoirs.
• Continued research and validation are crucial for overcoming technical hurdles and enabling routine adoption.
• Automated, human-free technologies are key to enhancing objectivity and efficiency in abattoir practices.