Characterizing Foot and Leg Scores for Montana’s Registered Angus Cattle

SIMPLE SUMMARY: As the beef industry continues to become more efficient and profitable, structural soundness will be important for the longevity of forage-based beef cattle. This study characterized the effects of age, sex, and sire line on mean foot angle and claw set scores of registered Angus cattle in Montana, USA. In our study, yearling bulls had greater mean foot angle and claw set scores than yearling heifers. Likewise, a greater proportion of yearling bulls had foot scores that were not ideal compared to yearling heifers. In addition, mean foot angle and claw set scores increased with increasing cow age, as well as the proportion of cattle with nonideal foot scores. The location of the combined worst foot was also influenced by cow age, with yearling cattle having predominantly front foot issues whereas mature cows often experienced hind foot issues. These data could potentially be used to improve the current American Angus Association (AAA) models and protocols for foot scoring. ABSTRACT: The objective of this study was to characterize foot angle and claw set scores of Montana’s (USA) registered Angus cattle using a total of 4723 cattle scored: 1475 yearling bulls, 992 yearling heifers, 1044 2- and 3-year-old cows, and 1212 cows ≥ 4 years old. Yearling bulls had a 0.12 and 0.20 greater mean foot angle and claw set score, respectively, compared to yearling heifers (p < 0.01). Foot angle and claw set scores increased (p < 0.01) with advancing cow age. The combined worst foot changed quadratically with age (p < 0.01) with the majority of problem feet in cows aged 2 to 3 years and older being hind feet issues. The proportion of foot angle and claw set scores not equal to 5 increased quadratically with age (p < 0.01), with heifers having the lowest proportion of scores not equal to 5 (15.8 and 31.7%, respectively) compared to cows aged 4 years and older. Sire lines had an effect on progeny claw set (p < 0.05) and foot angle scores (p < 0.05), as well as variation of progeny foot scores. These data could potentially be used to refine expected progeny difference models.