Nitrogen isotopic discrimination as a biomarker of between-cow variation in the efficiency of nitrogen utilization for milk production: A meta-analysis.

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 (ΔN) between the animal (milk, plasma, or tissues) and its diet has been proposed as a biomarker of the efficiency of N utilization in a range of production systems and ruminant species. The aim of this study was to assess the ability of ΔN 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 (grams of N in milk per day) and mean N intake (grams of N intake per day) 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 N abundance (δN), and then the N isotopic discrimination between the animal and the dietary treatment was calculated (Δn = δN - δN). 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 ΔN measurements errors were lower. The considerable protein mobilization in early lactation artificially increased both MNE and ΔN, 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 ΔN and MNE decreased in a particular experiment (i.e., higher repeatability values), we observed a greater ability of ΔN to predict MNE at the individual level. The predominant negative and significant correlation between ΔN and MNE in mid- and late lactation demonstrated that on average ΔN 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 differentiation between 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 in predicting MNE at the individual level. However, the one-way ANOVA performed to test the ability of ΔN 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.