In dairy cows, the failure or unwillingness to eat sufficient in early lactation when yield is high leads
to a state known as negative energy balance (NEB). In this state, cows mobilise body tissue mostly in
the form of body lipid in order to make up the difference in energy available from feed ingested and
that required to sustain obligatory requirements, such as maintenance, and milk production. A large
NEB is an undesirable state since it is associated with increased disease and reduced fertility.
Body lipid content can be predicted from visual assessment of the tailhead of cows using a system
known as body condition scoring (BCS). Changes in this score over time can therefore be used to
predict body lipid changes. I investigated the feasibility of automating the process of collecting
condition score using a digital camera and laser lights. The correlation between CS and shape over the
tail-head was 0.55 suggesting that it may be possible in future to include digital images in an
automated and integrated dairy farm management system.
Using random regression analysis, I analysed changes in milk production, feed intake, liveweight and
BCS over one to three lactations and calculated energy balance from these daily predictions. These
analyses showed that energy balance can be predicted from body measurements without the need to
measure feed intake making it practical to use nationally. Using these techniques enabled the genetic
analysis of large volumes of field data to predict daily breeding values for energy balance for 1250
progeny test sires. Substantial genetic variation was found in energy balance profiles. The mean total
daughter body energy loss at day 305 of lactation was 779 MJ (SD=224 MJ), equivalent in energy
terms to about 189 kg milk. Future selection indices may contain an adjustment for the amount of
body energy used to support the milk production of a bulls’ daughters leading to a more complete
assessment of the utility of a bull.
Analysis of data from the Langhill Dairy Research Centre demonstrated that there are differences in
the way dairy cows of differing genetic merit for production mobilise body lipid to support lactation
and that the amount of concentrate fed also affects the recovery of lost body lipid. Select cows
contained about 3200 MJ less energy than control cows at the end of the third lactation and lose and
gain body lipid in a cyclical way. Parameters of these curves may be used in future selection indices to
allow selection of genotypes that have profiles of body lipid loss and gain commensurate with high
yields and long herd life. This may also be useful in future when selection indices contain more traits
and farmers and advisors tailor their management to suit the type of cow. It may also provide guidance
on how future selection indices should be developed to incorporate traits such as body lipid, traits that
enable the robust cow to thrive over many high yielding lactations.