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Nutrient partitioning between physiological functions in the dairy cow depends on the genotype and its expression through time

INRA Prod Anim 26(2) 101-116


1INRA, UMR0791 MoSAR, 16 rue Claude Bernard, F-75231 Paris, France

2AgroParisTech, UMR0791 MoSAR, 16 rue Claude Bernard, F-75231 Paris, France

3INRA, UMR1348 PEGASE, F-35590 Saint-Gilles, France

4Agrocampus-Ouest, UMR1348 PEGASE, F-35000 Rennes, France

5Institut de l’Élevage, F-35652 Le Rheu, France


It has become increasingly clear that understanding nutrient partitioning is central to a much broader range of issues than just being able to predict productive outputs. The extent to which nutrients are partitioned to other functions such as health and reproduction is clearly important, as are the efficiency consequences of nutrient partitioning. Further, there is mounting evidence that reliance on body reserves is increased and that robustness of dairy cows is reduced by selection for increased milk production. There is a need to incorporate in nutritional models the innate driving forces that alter nutrient partitioning according to physiological state i.e., the role of both the cow’s genotype (genetic make-up), and the expression of this genotype through time on nutrient partitioning. This paper summarizes work carried out to extend nutritional models to incorporate these trajectories, and how they affect the homeostatic capacity of the animal. There are now models that can predict the partition of nutrients throughout lactation for cows of differing milk production potentials. However, genotype and stage of lactation effects on homeostatic capacity has not yet been explicitly included in metabolic models that predict nutrient partition, although recent results suggest that this is achievable. These developments considerably extend the generality of nutrient partitioning models with respect to the type of animal and its physiological state. However, these models remain very largely focussed on predicting partition between productive outputs and body reserves and, for the most part, remain research models although substantial progress has been made toward developing models that can be applied in the field. The challenge of linking prediction of nutrient partitioning to its consequences on health, reproduction, and longevity, although widely recognised, is only now beginning to be addressed. This is an important perspective for future work on nutrient partitioning.

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