Published April 28, 2022 | Version v3
Journal article Open

Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: A meta-analysis

  • 1. INRAE, Université Clermont Auvergne, Vetagro Sup, UMRH, 63122 Saint-Genes-Champanelle, France
  • 2. Agroscope, Route de la Tioleyre 4, 1725 Posieux, Switzerland
  • 3. INRAE, UE Herbipôle, 63122 St Genès Champanelle, France
  • 4. SRUC, West Mains Road, Edinburgh EH9 3JG, United Kingdom



The objective of this study was to test two candidate biomarkers of feed efficiency in growing cattle. A database was built using performance data from 13 trials conducted with growing heifers, steers and young bulls and testing 34 dietary treatments. Different breeds were used with Charolais (37%), Simmental (15%), and cross-bred (40%) cattle being the most numerous. The database included 759 individual records for animal performance and laboratory data for N isotopic discrimination measured in plasma or muscle (Δ15Nanimal-diet; n = 749) and plasma urea concentration (n = 659). Feed conversion efficiency (FCE) and residual feed intake (RFI) criteria were calculated for a duration ranging between 56 and 259 d, depending on the trial. For FCE prediction, mixed models included the random effects of study, treatment within-study and pen within-study (i.e. contemporary group; CG) allowing these effects to be progressively excluded from the relationship. For RFI prediction, simple linear regressions were tested with the CG effect removed from biomarker values before analysis. Better models were obtained with Δ15Nanimal-diet compared to plasma urea concentration, irrespective of using mean or individual values and regardless of the feed efficiency criterion. Prediction error (0.027 kg/kg) from mixed-effect models using mean FCE and Δ15Nanimal-diet values would allow discrimination of 2 dietary treatments or production conditions in terms of FCE if they differ by more than 0.10 kg/kg. The Δ15Nanimal-diet values showed a negative and significant (P<0.001) relationship with FCE at the individual level and results highlighted that it is possible to significantly discriminate two animals randomly selected from the same CG if they differ by at least 0.06 kg/kg FCE. In addition, the top 20% highest and lowest animals within-CG in terms of RFI and FCE (extreme animals) showed significant (P<0.001) differences in Δ15Nanimal-diet values, while only extreme FCE animals could be discriminated when using plasma urea concentrations (P=0.002). No gain in feed efficiency prediction was observed when combining candidate biomarkers. However, when average daily gain data was combined with Δ15Nanimal-diet, the prediction of FCE at the individual level was strengthened compared to using only one of them, in which case average daily gain was the best single predictor. Our findings confirm that Δ15Nanimal-diet may be useful to form groups of animals for precision feeding when feed intake and body weight gain are not available. Further studies are warranted, however, to evaluate the usefulness of this promising biomarker for genetic selection.


Files (3.0 MB)

Additional details


SmartCow – SmartCow: an integrated infrastructure for increased research capability and innovation in the European cattle sector 730924
European Commission