Genetic parameters of milk yield and fertility traits in Moroccan Holsteins - Chafai, Narjice; Badaoui, Bouabid; Rekaya, Romdhane (Frontiers in Animal Science, 2024)
Relatively high milk-producing cows in Morocco are culled at an elevated rate due to poor fertility. This situation is due to genetic, environmental, and management-related factors. To remedy this situation or prevent an additional decline in reproductive performance, using locally produced replacement heifers with good fertility and yield traits was proposed as a solution. Identifying these animals requires estimating the genetic parameters of the relevant reproduction and production traits in order to develop a genetic evaluation. Three reproduction traits (number of inseminations per conception, success of first insemination, and days open) and 305-d milk yield were used in this study. Two datasets of 4,186 records (first parity cows) and 5,511 records (first and multi-parity cows) were used. The pedigree files for both datasets consisted of 8,758 and 9,935 animals, respectively. A threshold-linear model was used for the analyses. For the first parity, estimates of heritability for 305-day milk yield (MY), days open (DO), number of inseminations per conception (NIC), and success of first insemination (SFI) were 0.26 ± 0.04, 0.17 ± 0.04, 0.10 ± 0.03, and 0.10 ± 0.04, respectively. For multi-parity data, the estimates were 0.19 ± 0.03, 0.12 ± 0.02, 0.10 ± 0.02, and 0.09 ± 0.02 for MY, DO, NIC, and SFI, respectively. The genetic correlations between MY and reproduction traits were 0.15 ± 0.11, 0.38 ± 0.12, and -0.43 ± 0.11 for DO, NIC, and SFI respectively. Overall, the heritability estimates of fertility traits were low. The genetic correlations of DO, NIC, and SFI with MY were moderately negative allowing for further selection for milk production without an additional deterioration in reproductive performance. The relative impact of using high fertility bulls compared to low fertility bulls on the success of first insemination ranged between 1.2% and 6.3% depending on the production environment. Collectively, these results confirm the possibility of implementing a viable selection program based on an appropriate weighted selection index.