@conference {3678,
	title = {Induction of delayed-type hypersensitivity reactions to Candida albicans in pasture-based dairy cows},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {74},
	year = {2014},
	month = {06/2014},
	pages = {233-238},
	address = {Napier},
	abstract = {Delayed-type hypersensitivity (DTH) reactions to Candida albicans are regularly used as an in-vivo indicator of cell-mediated immune function in cattle. Prior immunisation against C. albicans ensures a large clone of antigen-specific memory T cells, resulting in larger DTH responses and positive responses from a greater proportion of cows. Previous experimental results indicate that natural exposure to C. albicans is minimal in cows housed indoors and does not interfere with the interpretation of DTH responses to C. albicans in pre-immunised cows. However, housed cows may have different natural exposure to C. albicans than cows grazing fresh pasture outdoors. To determine if C. albicans is an appropriate antigen for inducing measurable DTH responses in pasture-based cows, DTH responses to C. albicans were assessed in ten cows pre- immunised with C. albicans and ten unimmunised control cows. A greater proportion of immunised versus unimmunised cows mounted a positive DTH response (90\% vs. 70\%), and responses were larger (P<0.01) and more variable (P<0.05) in immunised cows. Maximum relative double skinfold thickness increased 4.3 mm ({\textpm}0.7; SEM) and 1.4mm ({\textpm}0.2) in immunised and unimmunised cows, respectively. The results of this experiment suggest that pasture-based dairy cows in New Zealand have a low background exposure to C. albicans and pre-immunisation with C. albicans is required when using DTH responses as an indicator of cell-mediated immune function in pasture-based cows.},
	issn = {1176-5283},
	author = {McGowan JE and Hine BC and Mallard BA and Verkerk GA}
}
@conference {69529,
	title = {Improving the power of activity-based heat detection using additional automatically captured data},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {70},
	year = {2010},
	month = {Jun},
	pages = {299-302},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Palmerston North},
	abstract = {The purpose of this study was to determine the current performance of activity monitoring devices on New Zealand pasture-based farms and investigate the potential for improved detection using additional automatically captured data. The data consisted of heat events that were assigned from pregnancy diagnosis and mating records, and from milk progesterone levels collected twice weekly during mating period. Daily milk production, milking order, milk flow rate and milk conductivity records were also collected during the mating period. The best single predictor of oestrus was 24 hour milk yield difference (P <0.01) for Herd 1 and normalised milking order (P <0.01) for Herd 2. The normalised pedometer data was the next best predictor of oestrus in both herds (P <0.01). A linear logistic regression model was fitted within each herd. The best model included normalised milk production, milking order, milk flow rate and pedometer variables. Machine learning models with balanced bagging were also fitted to the data. The machine learning models provided a better fit than traditional statistical models. Pedometer data can aid in the detection of cow oestrus, however the power of detection improves significantly with the addition of milk yield, milk flow and milking order data.},
	issn = {1176-5283},
	author = {Harris BL and Hempstalk K and de le Rue BT and Jago JG and McGowan JE}
}
@conference {41967,
	title = {Validation of a technology for objectively measuring behaviour in dairy cows and its application for oestrous detection},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {136-142},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {Devices (IceTag{\textregistered}ActivityMonitor) using accelerometer technology to determine the behaviour of cows (proportion of time lying, standing, active and step count) were attached to 15 cows (2 per cow) and validated between devices and against observed behaviour. For standing and active, 95\% of paired (within cow) one minute data points were within 7\% points, 95\% of the lying data points were within 1\% point, and 95\% of stepping data were within 3 steps. The device recorded 100\% of lying bouts within {\textpm}1 minute of visually observed data. In a second experiment, 16 lactating dairy cows were fitted with IceTag{\textregistered}s and the relationship between behaviour profiles and oestrus evaluated. Blood progesterone concentration and twicedaily visual observations were used to identify precisely ovulation events and four algorithms, based on active and lying behaviour, were developed. A 24 hour rolling mean of activity and a slope threshold of 0.2 calculated for either the previous 10 hours (Activity24/10) or 5 hours (Activity24/5) correctly identified 93\% of oestrous events, with 21\% and 18\% false positive alerts, respectively. Two further algorithms, Lying<20\% or Active>5.5\% between midnight and 05:00hrs identified 50\% and 64\% of oestrous events, with 36\% and 18\% false positive alerts, respectively. In a third experiment using 30 cows, 56 oestrous events were identified through milk progesterone profiles and  visual observation. Algorithm Activity24/10 and Activity24/5 identified 84\% and 76\% of oestrous events respectively. The IceTag{\textregistered}accurately recorded several types of cattle behaviour suggesting useful applications as both a research and industry tool.},
	issn = {1176-5283},
	author = {McGowan JE and Burke CR and Jago JG}
}
@conference {41905,
	title = {Mastitis in cows milked in an automated or conventional milking system in New Zealand},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {66},
	year = {2006},
	month = {Jan},
	pages = {252-257},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Napier},
	abstract = {The viability of automated milking systems (AMS) for pasture-based dairying has been studied in New Zealand in the past four years. Automatic milking differs from conventional milk harvesting systems (CMS) in a number of ways, which may impact on udder health. These include fewer machines/cow, distributed vs. batch milking, variable milking intervals, automatic udder health monitoring systems, and pre and post-milking teat sanitation procedures. Three seasons of data from two pasture-based research farms that milked cows with either a two unit AMS or a 30 bail rotary CMS were compared. Quarter milk samples were collected routinely from all cows for bacteriological analysis during the 2002-03, 2003-04 and 2004-05 seasons, with sampling occurring throughout lactation and at detection of clinical mastitis (CM) cases. The number of cows in the AMS herd ranged from 94 to 196 and in the CMS herd, from 289 to 324 across the seasons. Clinical mastitis affected 7, 11, and 15 cows/100 cows/season in the AMS herd and 24, 23 and 14 cows/100 cows/season in the CMS across the three seasons, with Streptococcus uberis isolated from approximately 50\% of CM cases from both herds. Prevalence of S. uberis post-calving averaged 8\% of cows for the AMS and 16\% for the CMS across the three seasons. We compared several indicators of udder health between an AMS and a CMS herd managed under pastoral conditions. },
	issn = {1176-5283},
	author = {Lopez-Benavides MG and Williamson JH and McGowan JE and Lacy-Hulbert SJ and Jago JG and Davis KL and Woolford MW}
}
