Combined mechanistic and genetic modelling to benchmark body reserve traits as proxies of dairy cows' lifetime efficiency in grass-based production systems.

Improving lifetime lactation efficiency of dairy cows by selection is difficult due to the complexity of this trait and the existence of genotype-by-environment interactions. This study aimed at assessing the relevance of traits derived from body reserves as lifetime efficiency indicators under contrasting nutritional environments. Given the absence of large-scale datasets covering a panel of feeding regimes, phenotypes were simulated for populations of 20 000 dairy cows using a mechanistic bioenergetic model. Ten phenotypes were computed for third-lactation cows. Analysed phenotypes comprised total milk production, lactation efficiency, BW at calving (BWcalv), DM intake (DMI) and interval between first insemination and conception. Five traits described levels and changes of body reserves at different periods during lactation. Lifetime lactation efficiency was computed for all cows (Life_Eff). Three nutritional environments were defined considering a grass-based production system with seasonal calving: a high non-limiting scenario (HS) mimicking ad libitum access to feed and two limiting environments with moderate (MS) and low (LS) feed offer. Variance components were estimated for all traits within and between environments using REML. Heritabilities estimated for milk production, lactation efficiency, BWcalv and DMI were moderate in the different environments (0.27-0.35 ± 0.04). The heritability of body reserve levels and dynamics were moderate in the HS and MS scenarios (0.23-0.30 ± 0.03) and lower in the LS scenario (0.14-0.25 ± 0.03). The heritability of Life_Eff was low in the HS environment (0.07 ± 0.01) and slightly increased in the limiting environments. All genetic correlations estimated between environments were moderate to high (≥0.66 ± 0.07), suggesting low to moderate genotype-by-environment interactions. Estimated genetic correlations were moderate between Life_Eff and body reserve levels (from 0.39 to 0.51 ± 0.08) and moderate but negative between Life_Eff and change in body reserves traits (-0.27 to -0.37 ± 0.09) in the HS environment. The genetic correlations between Life_Eff and body reserve levels increased to higher values in the limiting environments. In contrast, genetic correlations between Life_Eff and the changes in body reserves were closer to zero. In conclusion, this study showed that body reserve levels were relevant proxies of lifetime irrespective of the environment. In contrast, changes in body reserves that reflected energy mobilisation in early lactation were less informative about lifetime efficiency in environments with severe feed restrictions.