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Monitoring liveweight to optimise health and productivity in pasture[-]fed dairy herds : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University
Technological advances now make it possible to continuously record and monitor a range of outcomes
on dairy farms including individual cow milk yields, environmental temperature and rainfall.
These facilities enhance the ability of herd managers to recognise deviations from what is
accepted as normal, prompting timely corrective intervention. The objective of this thesis is to
demonstrate how liveweights recorded using walkover weighing (WoW) technology can provide
information that can be used to better-manage a range of activities on dairy farms, particularly
reproduction and herd health.
Analysis of daily WoW recorded over the first 100 days of lactation have shown that the standard
deviation of daily LW measurements across parities was 17 kg on average. A near perfect association
between liveweights measured statically and WoWs (concordance correlation coefficient
0.99, 95% CI 0.99 to 1.0) was observed. After controlling for the effect of liveweight at calving
and long term liveweight change using a mixed-effects linear regression model, the autocorrelation
between WoWs recorded on successive days was 0.21, decaying to zero by eight days. This
study showed that by using a standalone automatic WoW system positioned in the exit race of
a rotary milking parlour, it was possible to record LWs of individual cows on a daily basis and,
with controlled cow flow over the weighing platform (allowing for sufficient succession distance
to prevent congestion), results were similar to those recorded using conventional, static weighing
Two observational studies were conducted to investigate the relationships between LW, LWchange
( LW) and clinical lameness. In the first study, LW loss in the first 50 days in milk increased the
risk of a lameness event being diagnosed after 50 days in milk by a factor of 1.80 (95% CI 1.00 to
3.17). The risk of lameness was greatest for high yielding cows that lost excessive LW (risk ratio
4.36, 95% CI 4.21 to 8.19). The second study quantified LW immediately before and after the
diagnosis of lameness events. For lame cows, liveweight decreased up to three weeks before the
date of diagnosis and for up to four weeks after. The total liveweight loss arising from a single
lameness episode was, on average, 61 kg (95% CI 47 to 74 kg). The results of this study show
how liveweight records for individual animals can be used to enhance a herd manager’s ability
to detect lame cows and present them for treatment. Prompt detection and treatment of lame
cows presents an opportunity to shorten recovery times, with positive follow-on effects in terms
of animal welfare.
LW was assessed as a means for enahancing the sensitivity and specificity of oestrus detection.
The sensitivity and specificity of detecting true oestrus events using LW combined with tail
paint and visual observation was 0.86 and 0.94, respectively. The effect of LW in the first
four weeks after calving ( LWlong) and LW change around the time of the Planned Start of
Mating ( LWshort) on the time taken for cows to conceive relative to the Planned Start of Mating
was quantified. Planned Start of Mating to conception intervals were influenced by LW change
during both of these periods, though LWshort had a greater effect compared with LWlong.
The findings of this study better define the impact of long- and short-term liveweight change on
reproductive performance, providing the opportunity to design feeding programmes in pasture fed
dairy herds that have positive effects on fertility.
The studies presented in this thesis contribute knowledge to the role of LWmonitoring as a tool to
better-manage seasonally calving, pasture fed dairy herds. While ‘traditional’ usage of walkover
scales on dairy farms has involved the recording of LWand LWchange as a means for monitoring
and adapting changes to the herd feeding program, the studies presented here have shown how LW records have the potential to provide information that can be used to better manage a range of herd
level activities, particularly those related to reproductive management and health.