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Minor milk constituents are affected by protein concentration and forage digestibility in the feed ration

Published online by Cambridge University Press:  12 February 2016

Torben Larsen*
Affiliation:
Department of Animal Science, AU Foulum, Aarhus University, DK 8830 Tjele, Denmark
Lene Alstrup
Affiliation:
Department of Animal Science, AU Foulum, Aarhus University, DK 8830 Tjele, Denmark
Martin Riis Weisbjerg
Affiliation:
Department of Animal Science, AU Foulum, Aarhus University, DK 8830 Tjele, Denmark
*
*For correspondence; e-mail: Torben.Larsen@anis.au.dk

Abstract

The present study was conducted in order to investigate if selected minor milk components would be indicative for the nutritional situation of the cow. Forty-eight dairy cows were offered a high digestible ration vs. a lower digestible ration combined with 2 protein levels in a 4 × 4 Latin square design. Milk glucose, glucose-6-phosphate, cholesterol, triacylglycerides (TAG), uric acid and β-hydroxybutyrate (BHBA) were measured and correlated mutually and towards other milking parameters (yield, h since last milking, days in milk (DIM), urea, etc). The variation range of the suggested variables were broad, a fact that may support their utilisation as predictive parameters. The content of milk metabolites was significantly affected by the change in rations as milk glucose, glucose-6-phosphate, uric acid, and the ratio cholesterol: triacylglycerides increased with higher energy intake while BHBA and TAG decreased. The content of some of the milk metabolites changed during 24 h day/night periods: BHBA, cholesterol, uric acid and TAG increased whereas free glucose decreased in the night period. Certain associations between milk metabolites and calculated energy parameters like ECM, body condition score (BCS), and body weight gain were found, however, these associations were to some extent explained by an interaction with DIM, just as changes in milk metabolites during a 24 h period seems to interfere. It is concluded that the practical use of the suggested milk variables should be based on more than one metabolite and that stage of lactation and possibly time of the day where the milk is collected should be incorporated in predictive models.

Type
Research Article
Copyright
Copyright © Proprietors of Journal of Dairy Research 2016 

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