Modeling Feed Efficiency over Productive Lifetime and Integrating a Sub-Model for Body Reserve Management in Nordic Dairy Cattle

• Published in: Journal of dairy science 2024-12
• Main Authors: Stephansen, R.B., Lassen, J., Thorup, V.M., Poulsen, B.G., Jensen, J., Sahana, G., Christensen, O.F.
• Format: Article
• Language: English
• Subjects: feed efficiency; genetic residual feed intake; multi-variate analysis; productive lifetime efficiency
• ISSN: 0022-0302; 1525-3198; 1525-3198
• DOI: 10.3168/jds.2024-25383

Genetic enhancement of feed efficiency can improve the economic sustainability and environmental responsibility of dairy farming. While genetic selection holds promise for improving feed efficiency across the lifespan of dairy cows, comprehensive data spanning whole lactations or even a productive lifetime are currently limited. To address this, we used production data and data from a camera-based feed intake and body weight recording system, along with records of production, feed intake, and weight on Holstein cows from a research herd. We aimed to estimate variance components for a multi-variate multi-parity model of production, feed intake, and body weight data to calculate genetic residual feed intake (gRFI) for each of the Nordic breeds (Holstein, Jersey, and Red Dairy Cattle). Our approach included investigating a new definition of energy balance (EBbody) calculated from changes in body reserves, serving as an energy sink in gRFI. The data in our analysis consisted of 4,751 Holstein cows (7,851 lactations), 2,068 Jersey cows (3,486 lactations), and 3,235 Red Dairy Cattle cows (5,419 lactations). We used Gibbs sampling to estimate posterior means and standard deviations for all model parameters. Our findings revealed moderate lactation-wise heritability of gRFI (0.15 to 0.38) across all breeds and parities. Moreover, gRFI genetic correlations varied (−0.2 to 0.4) between early and mid to late lactation stages across all breeds, and for lactation-wise gRFI there were moderately high genetic correlations (0.39 to 0.59) between primi- and multiparous lactations across the 3 breeds. Those results suggest the importance of recording phenotypes in most time periods within and across lactations. Our analysis indicated that improving gRFI with one genetic standard deviation unit corresponded to a 2–3% gain in net return profit per cow-year, with no or minimal impact on production and body reserve management. We demonstrated the feasibility of incorporating EBbody into gRFI. Comparing gRFI calculated with EBbody or changes in body weight as an energy sink trait for body reserve management were highly genetically correlated (>0.95). This result shows that the choice of the energy sink trait for body reserve management in gRFI will yield limited reranking among cows and sires when based on body weight records only. However, EBbody offers an opportunity to incorporate body condition score information without increasing the number of genetic parameters to be estim