Akademik Veri Yönetim Sistemi
FRONTIERS IN VETERINARY SCIENCE, cilt.13, 2026 (SCI-Expanded, Scopus)
Artificial insemination in cattle relies on laboratory semen evaluation, yet field fertility often diverges from laboratory-based expectations. This study compared spermatological and computer-assisted sperm analysis (CASA) kinematic traits of commercially frozen-thawed semen from dairy and beef bulls and examined their associations with pregnancy outcome under commercial conditions. Frozen semen from 11 bulls (beef: Angus, n = 5; dairy: Holstein, n = 6) was obtained through the Amasya Cattle Breeders' Association; six straws from the same batch per bull were analysed and averaged at the bull level. After thawing (37 degrees C, 30 s), motility, sperm concentration, and kinematic parameters were assessed using CASA under standardized settings. Field inseminations were performed by a single veterinarian in healthy multiparous cows showing spontaneous estrus. A total of 413 inseminations were conducted (beef semen: 194; dairy semen: 219); pregnancy diagnosis was available for 409 inseminations at day 60. Mean daily milk yield (days 5-305) was derived from association records (beef females, n = 194; dairy females, n = 219). Semen from beef bulls showed higher total motility (83.59 +/- 2.08% vs. 56.24 +/- 2.42%; p < 0.0001) and higher progressive motility (58.54 +/- 3.01% vs. 48.25 +/- 9.57%; p = 0.0475) than semen from dairy bulls. Dairy bulls had higher STR and LIN and lower ALH, whereas velocity descriptors differed modestly and did not show consistent between-group separation. Mean bull-level pregnancy rate was numerically higher for beef than dairy bulls (68.06% vs. 63.71%), without a significant between-group difference at the insemination level. Daily milk yield differed markedly between female groups (18.47 +/- 0.38 vs. 6.21 +/- 0.19 kg/d; p < 0.001). Within-group Pearson correlations indicated that motility was positively associated with pregnancy rate in both production types, while several kinematic descriptors exhibited production-type-specific correlation directions. These findings suggest that production context may modulate how CASA phenotypes relate to field fertility, supporting cautious interpretation of single-parameter semen metrics in commercial AI systems.