# Genetic associations between feed efficiency traits and breeding goal traits in Nordic Holsteins

**Authors:** R.B. Stephansen, B.G. Poulsen, J. Lassen, J. Jensen

PMC · DOI: 10.3168/jdsc.2025-0898 · JDS Communications · 2025-12-01

## TL;DR

This study examines how improving feed efficiency in dairy cows affects other traits like milk production and health, finding minimal trade-offs for most traits.

## Contribution

The study provides new genetic correlation insights between feed efficiency traits and breeding goals in Nordic Holsteins.

## Key findings

- Lower body weight in cows is linked to improved longevity without affecting milk yield.
- Genetic Feed Saved (gFS) aligns with the Nordic Saved Feed index and shows minimal trade-offs with other traits.
- Early lactation gRFI in multiparous cows shows a slight negative correlation with longevity.

## Abstract

Summary: Enhancing feed efficiency in dairy cattle is essential for a more sustainable milk production. However, understanding how genetic selection for feed efficiency affects other important traits (e.g., production, health, and fertility) is not well explored. This study explored that for the feed efficiency traits: body weight (BW), genetic residual feed intake (gRFI), and genetic Feed Saved (gFS). Using data from >5,100 cows in commercial herds, we found that BW was slightly unfavorably associated with productive lifetime and showed no benefit for 305-day yield, suggesting that selecting smaller cows may enhance lifespan. Both gRFI and gFS showed low correlations with 305-day yield and functional traits, indicating minimal trade-offs. However, early lactation gRFI in multiparous cows had a slight negative correlation with longevity, warranting further investigation. The gFS index showed strong alignment with the current Nordic Saved Feed index and selection for gFS is unlikely to negatively affect other traits in the breeding goal.

Summary: Enhancing feed efficiency in dairy cattle is essential for a more sustainable milk production. However, understanding how genetic selection for feed efficiency affects other important traits (e.g., production, health, and fertility) is not well explored. This study explored that for the feed efficiency traits: body weight (BW), genetic residual feed intake (gRFI), and genetic Feed Saved (gFS). Using data from >5,100 cows in commercial herds, we found that BW was slightly unfavorably associated with productive lifetime and showed no benefit for 305-day yield, suggesting that selecting smaller cows may enhance lifespan. Both gRFI and gFS showed low correlations with 305-day yield and functional traits, indicating minimal trade-offs. However, early lactation gRFI in multiparous cows had a slight negative correlation with longevity, warranting further investigation. The gFS index showed strong alignment with the current Nordic Saved Feed index and selection for gFS is unlikely to negatively affect other traits in the breeding goal.

•gRFI showed no clear associations with yield, functional traits, and longevity.•gFS showed no clear associations with yield, functional traits, and longevity.•gFS align well with Nordic Saved Feed index, included in the Nordic breeding goal.•Selecting for defined feed efficiency traits did not show trade-offs in breeding goal traits.•Lower BW is linked to improved longevity and has no effect on yield.

gRFI showed no clear associations with yield, functional traits, and longevity.

gFS showed no clear associations with yield, functional traits, and longevity.

gFS align well with Nordic Saved Feed index, included in the Nordic breeding goal.

Selecting for defined feed efficiency traits did not show trade-offs in breeding goal traits.

Lower BW is linked to improved longevity and has no effect on yield.

Genetic selection is a viable tool for improving feed efficiency due to its cumulative nature. However, it has not been investigated how selection for feed efficiency affects other breeding goal traits. This work investigated associations between the feed efficiency–related traits BW (representing energy requirement for body maintenance), genetic residual feed intake (gRFI; representing deviations from expected feed intake calculated from milk yield, maintenance, and changes in BW), genetic Feed Saved (gFS; representing deviations from expected feed intake calculated from milk yield, and changes in BW), and all breeding goal traits in the Nordic Total Merit (NTM) index. Phenotypic data were collected from 5,104 cows across 8 commercial herds using the Cattle Feed InTake system, and GEBVs for feed efficiency were estimated using the single-step genomic BLUP methodology. Genetic correlations were approximated using Pearson correlation between GEBVs for different traits. The genetic correlations were weakly negative between BW and NTM (−0.15 to −0.18) or longevity (−0.13 to −0.15), and it was not associated with the yield index. The genetic correlations were generally moderate between BW and conformation traits such as stature and chest width but not with dairy form. The genetic correlations for gRFI in different lactation stages were weakly to moderately correlated with the yield index (−0.23 to 0.21) and weakly correlated with functional traits (−0.10 to 0.10; e.g., mastitis, female fertility). Furthermore, gRFI in early lactation of multiparous cows was weakly and unfavorably correlated with longevity (−0.14). The genetic correlations between gFS and yield, functional traits, and longevity were low (−0.13 to 0.16). However, the moderate negative genetic correlation between gFS and frame (−0.37 to −0.28) indicated that more efficient cows have a smaller frame. In conclusion, our results indicated that feed efficiency traits such as gRFI and gFS can be integrated into breeding goals with limited adverse effects on yield, functional traits, and longevity. Selection for lower BW may enhance longevity without compromising yield.

## Full-text entities

- **Diseases:** mastitis (MESH:D008413), gFS (MESH:D001068)
- **Chemicals:** carbon (MESH:D002244)
- **Species:** Bos taurus (bovine, species) [taxon 9913]

## Full text

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## Figures

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## References

27 references — full list in the complete paper: https://tomesphere.com/paper/PMC12958172/full.md

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Source: https://tomesphere.com/paper/PMC12958172