Abstract/Summary

Estimating the efficiency of N utilization for milk production (MNE) of individual cows at a large-scale is difficult, particularly because of the cost of measuring feed intake. Nitrogen isotopic discrimination (Δ15N) between the animal (milk, plasma or tissues) and its diet was proposed as a biomarker of the efficiency of N utilization on a range of production systems and ruminant species. The aim of this study was to assess the abilityof Δ15N to predict the between-animal variability in MNE in dairy cows using an extensive database. For this, 20 independent experiments conducted as either changeover (n = 14) or continuous (n = 6) trials were available and comprised an initial data set of 1,300 observations. Between-animal variability was defined as the variation observed among cows sharing the same contemporary group (CG; individuals from the same experimental site, sampling period, and dietary treatment). Milk N efficiency was calculated as the ratio between mean milk N (MN, g of N in milk/d) and mean N intake (NI, g of N intake/d) obtained from each sampling period, which lasted 9.0 ± 9.9 d (mean ± SD). Samples of milk (n = 604) or plasma (n = 696) and feeds (74 dietary treatments) were analyzed for natural 15N abundance (δ15N) and then the N isotopic discrimination between the animal and the dietary treatment was calculated (Δ15N = δ15Nanimal − δ15Ndiet). Data were analyzed through mixed-effect regression models considering the experiment, sampling period and dietary treatment as random effects. In addition, repeatability estimates were calculated for each experiment to test the hypothesis of improved predictions when MNE and Δ15N measurements errors were lower. The considerable protein mobilization in early lactation artificially increased both MNE and Δ15N leading to a positive rather than negative relationship and this limited the implementation of this biomarker in early lactating cows. When the experimental errors of Δ15N and MNE decreased in a particular experiment (i.e., higher repeatability values) we observed a greater ability of Δ15N to predict MNE at the individual level. The predominant negative and significant correlation between Δ15N and MNE in mid and late lactation demonstrated that on average Δ15N reflects MNE variations both across dietary treatments and between-animals. The root mean squared prediction error as a percentage of average observed value was 6.8% indicating that the model only allowed to differentiate 2 cows in terms of MNE within a CG if they differed by at least 0.112 g/g of MNE (95% confidence level) and this could represent a limitation to predict MNE at the individual level. However, the one-way ANOVA performed to test the ability of Δ15N to differentiate within-CG the top 25% from the lowest 25% individuals in terms of MNE was significant indicating that it is possible to distinguish extreme animals in terms of MNE from their N isotopic signature, which could be useful to group animals for precision feeding.