Potential of Using New Technology for Estimating Body Condition Scores

Although the benefits of body condition scoring (BCS) are intuitive to most dairy industry professionals, relatively few dairy farms have incorporated it as part of their routine management strategy. The lack of adoption of this technique is largely attributable to subjectivity and time requirements. An automated BCS system would be less demanding of time by trained personnel, less stressful to cattle, more objective and consistent, and possibly more cost effective. The technical feasibility of utilizing digital images (IceScore, Ice Robotics Ltd., Midlothian, UK) to determine BCS was assessed for lactating dairy cows at the Scottish Agricultural College (SAC) Crichton Royal Farm. Up to 23 anatomical points were manually identified on dorsal images (N = 3332) captured automatically from above as cows passed through a weigh station. All identifiable points were utilized to define and formulate measures describing the cow’s contour. Hook angle and posterior hook angle were significant predictors of BCS (P < 0.05), and 100% of predicted BCS were within 0.50 points of actual BCS and 93% were within 0.25 points. The economic feasibility of investment in an automated BCS system was also explored using a dynamic, stochastic simulation dairy model designed to examine investments in dairy intervention technologies. The model was created in Microsoft Excel using the @Risk add-in to consider the stochastic nature of key variables with Monte Carlo simulation. Benefits of the BCS system were considered by estimating potential improvements resulting from technology adoption through reduced disease incidence, reduced days open, and increased energy efficiency. The simulation resulted in a series of net present values used to identify the probability of observing a positive net present value. Future efforts should explore ways to facilitate extraction of information from images automatically using a larger number of animals to accurately predict scores of cows across all levels of BCS. With further development and refinement, automated BCS may become an integral part of decision making on modern dairy farms with applications in nutrition, genetics, and animal well-being.