novel approaches to expression and detection of oestrus in dairy cows

and insulin are all moderate h 2 =0.11 to 0.30, largely due to the influence
diet has on these variables (Hayhurst et al., 2007). Inclusion of this data
for genetic selection is relevant because of the relationship of these
hormones and metabolites to NEBAL and BCS. Circulating levels of these
hormones can be included in breeding values and can predict susceptibility
to NEBAL and low BCS at calving, early in the animals life, which can
impact upon fertility and oestrous expression (Flint et al., 2008).
There has been little genetic selection for oestrous expression but several
factors seem promising. Milk progesterone, GnRH response and metabolic
hormone levels have all been reported to influence oestrous expression and
are reported to be heritable. Inclusion of heritable estimates for indicators
of strong oestrous expression could aid oestrous detection.
1.6 AIMS & OBJECTIVES
Many existing methods of oestrous detection; visual, physiological and
automated, have flaws in either their accuracy, efficiency or both, and do
not meet the ideal requirements described by Senger (1994). Poor
oestrous expression is also a hindrance to effective oestrous detection; less
intense, shorter duration (Dransfield et al., 1998) and less than 50% seen
in standing oestrus (Dobson et al., 2008). However, due to the
multifactorial nature of the control of expression of oestrus it is difficult to
identify methods to improve expression. The work described within this
thesis focuses on the individual cow variation of oestrous expression. The
aim is to improve expression permanently through genetics therefore to
improve oestrous detection rates.
Ideally 24 hour continuous automated surveillance is required to minimise
labour requirements and cost. However a method that can accurately
detect reliable signs of oestrus to increase detection rates from 50% to the
current target of above 70% is required (DairyCo, 2009). Importantly to
improve herd fertility the ideal system for identifying cows in oestrus must
detect cows standing to be mounted, the definitive sign of oestrus
(Orihuela, 2000) and the period which is most significantly correlated with
the time of ovulation (Roelofs et al., 2005) resulting in improved
conception rates. Hence there is a need to develop a robust system to
identify both cows approaching oestrus and cows in oestrus (standing to be
mounted), in real-time to overcome the limitations of earlier systems, in
order to maximise pregnancy rates and thus profitability.
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