Technical note: A digital technique and platform for assessing dairy cow teat-end condition

Area of Science:

• Veterinary Medicine
• Animal Science
• Digital Imaging Technology

Background:

• Mastitis in dairy cows is primarily caused by bacterial infections entering through the teat canal.
• Maintaining teat canal integrity is crucial for preventing infections and ensuring udder health.
• Current methods for assessing teat-end condition rely on time-consuming and costly visual inspections.

Purpose of the Study:

• To develop and demonstrate a digital workflow for assessing dairy cow teat-end condition using images and software.
• To evaluate the feasibility and reliability of an image-based system for monitoring teat health.

Main Methods:

• A digital workflow was designed to capture, process, and display digital images of dairy cow teats.
• A graphical user interface was developed for evaluators to assess teat-end condition remotely.
• The study involved 194 dairy cows, comparing image-based assessments with traditional cow-side visual inspections by 2 expert evaluators.

Main Results:

• Substantial agreement was found between an evaluator's cow-side and image-based assessments for both quarter and cow-level evaluations.
• Moderate agreement was observed between evaluators using the image-based assessment method at both quarter and cow levels.
• Near perfect agreement was noted between evaluators for cow-side assessments at the quarter level.

Conclusions:

• Image-based classification of teat-end condition in dairy cows is feasible and shows promising results.
• The developed digital workflow offers a systematic and convenient approach to udder health management.
• Further improvements in image acquisition and processing could enhance the utility of this digital assessment method.