Dairy cattle

Genomic Prediction of Age at First Calving in Ethiopian Crossbred Cattle

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Abstract

Age at first calving (AFC) is an economic trait that directly influences the lifetime productivity and reproductive efficiency of dairy operations. Early calving of dairy farms shortens the time between investment and milk production, boosting overall profitability and sustainability. This study aimed to estimate the heritability and genomic prediction of AFC in crossbred Ethiopian dairy cattle. This study utilized 1,290 AFC records from cows born between 2011 and 2019, encompassing a total of 7,019 genotyped animals, including those with recorded data. Following the quality control procedures, the analysis incorporated a dataset comprising 85,126 SNPs. The exotic breed proportions for each animal were derived using maximum-likelihood unsupervised model-based clustering. The animal model included birth season and the scaled exotic breed proportion as fixed effects and covariates, respectively, with herd-birth-year and animal incorporated as random effects. Genomic estimated breeding values (GEBVs) were calculated using GBLUP and later, G-matrix weighted based on the SNP effects. The non-weighted and weighted GBLUP methods were evaluated by correlation and regression between adjusted phenotype and GEBVs in a validation population. Additionally, prediction accuracy was computed as the correlation between the adjusted phenotypes and the GEBVs, divided by the square root of the AFC heritability. For this validation, a population of 200 cows was randomly chosen, which were subsequently excluded from the analysis. Analyses were performed using the BLUPF90 software suite. The mean AFC was 1032 days, with a range of 608 to 1460 days. The heritability of AFC was estimated at 0.28 with a standard error of 0.06. The GEBVs varied from animals predicted to calve 269 days earlier to those predicted to calve 300 days later than the average. The correlation between adjusted phenotypes and GEBVs was 0.26 for the non-weighted GBLUP model and increased to 0.29 when SNP-effect weighting was applied. The prediction accuracy was 0.49 for non-weighted GBLUP, which improved to 0.55 (a 6% increase) with the weighted GBLUP approach. The regression of adjusted phenotypes on GEBVs resulted coefficients of 1.08 for the non-weighted and 1.03 for the weighted model, values close to unity and indicative of good agreement between predictions and observed performance. Given the relatively limited dataset, the accuracy of 0.55 obtained is encouraging towards providing breeders with information for informed breeding decisions in Ethiopia. Continual refinement of reference populations and methodologies offers the prospect of achieving enhanced accuracy of GEBVs in the future.

Keywords: 2026

How to Cite:

Meseret, S., Gebreyohanes, G., Ekine-Dzivenu, C., Mamo, S., Jufar, B., Tera, A., Ojango, J. & Mrode, R., (2026) “Genomic Prediction of Age at First Calving in Ethiopian Crossbred Cattle”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2284543. doi: https://doi.org/10.31274/wcgalp.23584

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