Female fertility is a fundamental trait for a profitable dairy herd enterprise. Studies have shown a decline in fertility probably because of dedicated selection for increased milk production. Age at first calving (AFC) and calving interval (CI) are prominent indicator traits to improve fertility, but these traits are greatly affected by management decisions. Service data present additional selection criteria with minimum bias. Service data are not recorded routinely into the national database but are kept on farm for management purposes, but should be useful to the selection effort. Therefore, the aim of the study by the authors cited below was to estimate genetic parameters for AI service-based heifer and cow fertility traits in Holstein herds.
Service records were obtained from an on-farm management system, consisting of 64 464 records from 18 herds. Pedigree data included animals born between 1992 and 2013. Data were edited to remove outliers and allow for an acceptable threshold for each trait. The final data set used for analysis included 10 017 heifer and 24 909 cow traits. The traits analysed were age at first service (AFS) and number of services per conception (SPCh) for heifers, and calving to first service (CFS), number of days open (DO), and number of services per conception (SPC) for cows. Model effects for genetic evaluations were tested where the fixed effects of herd, year, season of birth or calving, age at insemination or calving and lactation number were fitted. The model for heifers included random animal effect and for cows it included the random effects of animal and permanent environment. Genetic variances and heritabilities were estimated using appropriate programs.
The means ± Standard Deviation for the analyzed traits were for CFS 89 ± 36 days, DO 137 ± 72 days, SPC 2.18 ± 1.57, AFS 16 ± 3.51 months and SPCh 1.52 ± 0.91. The mean SPC was lower in heifers (1.52) and higher in cows (2.18), possibly because heifers haven’t started lactating. Phenotypic correlations were -0.06 in heifers (AFS and SPCh) while they varied from -0.15 (CFS and SPC) to 0.71 (SPC and DO) in cows. Genetic correlations were 0.73 in heifers (SPCh and AFS) while in cows they varied from -0.62 (SPC and CFS) to 0.19 (CFS and DO). Negative phenotypic correlations were observed between AFS and SPCh, although they were weaker than genetic correlations. This means that younger animals conceived from fewer inseminations. The observed negative phenotypic and genetic correlations between CFS and SPC indicate that if CFS is lengthened, a dam would have more time to recover from lactation, and hence will conceive from fewer inseminations after calving. Estimated heritabilities ranged from low (0.02) to moderate (0.26), indicating that to some extent there is a genetic aspect for these traits.
It was concluded that the low to moderate heritability indicates that there is potential in some of these traits for use in selection programmes, in addition to age at first calving and inter-calving period. Further research should investigate a multi-trait analysis of the defined traits and their associations with production traits.
Reference:
R.D. Kgari, K. Dzama, C.J.C. Muller & M.L. Makgahlela, 2019. Estimation of genetic parameters for female fertility traits derived from on-farm service records in South African Holstein cattle.In: Proc. of the 51st Annual Congress of the SASAS, Bloemfontein, 10-12 June 2019.