Energy Balance Profiles for the First Three Lactations of Dairy Cows Estimated Using Random Regression

Abstract
Daily animal solutions were predicted using random regression analysis for feed intake, milk yield, live weight, and condition score recorded on 189 cows at the Langhill Dairy Cattle Research Centre. All cows had three successive lactations. Energy balance for days 1 to 305 of each of the three lactations was calculated both from daily measures of feed intake and milk output and from weekly measures of live weight and condition score. Cows returned to positive energy balance at days 72, 75, and 95 in lactations 1, 2, and 3, respectively, based on energy balance calculated from feed intake and milk output records (EB1), and at days 77, 83, and 73 based on energy balance calculated from body energy state changes (EB2). Correlations between energy balance at the same time in successive lactations ranged from 0.01 to 0.66 depending on the method of calculation and the stage of lactation. Energy balance over three lactations was modelled using sinusoidal functions which were associated with individual cows and allowed to vary between cows. The parameters of these curves are potentially useful since they have a biological interpretation. The phase relates to the period from calving to return to positive energy balance, and the amplitude relates to the degree of body energy loss (and recovery). The sinusoidal functions fitted to the curve removed a significant proportion of the variation, but accounted for only 45% and 40% of the variation in EB1 and EB2, respectively. The relationship between energy balance in the first three lactations is likely to be more complex than a simple linear function, but the profile of energy balance over the first three lactations may be a useful selection criteria in a multi-trait index. Energy balance profile over lactations one to three can be modelled with moderate accuracy using sinusoidal functions, and this warrants further research.
Funding Information
  • Scottish Executive Environment
  • Rural Affairs Department