@conference {3678,
	title = {Crossbred cows exceed production expectation in high producing herds},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {74},
	year = {2014},
	month = {06/2014},
	pages = {41-45},
	address = {Napier},
	abstract = {New Zealand dairy production per cow has increased by over 33\% in the past fifteen years. Consequently, animal breeders are interested in understanding how expression of heterosis for dairy production traits is affected in higher-production systems. To investigate this question a natural-experiment approach was taken, utilising herd-testing records in the 2010-11 dairy production season in herds that contained two breeds, Holstein-Friesian cows ({\textquoteright}control{\textquoteright} breed) and Holstein-Friesian x Jersey cows ({\textquoteright}treatment{\textquoteright}). Herds were divided into two production system classes. The system classes were national-average herd production per cow ({\textquoteright}control{\textquoteright} system) and high per cow production ({\textquoteright}treatment{\textquoteright}). Per cow yields were over 45\% higher in the treatment herds than in national-average herds. Herd test records were analysed for 29,329 two-year-old heifers, and for 20,753 five-or six-year-old mature cows. Dependent variables for the statistical models were deviations from contemporary group means for 270-day yields for production traits. Explanatory variables included Breed, System, and individual cow Production Values as estimated in the national genetic-evaluation system (which include genetic, permanent environment and heterosis effects on yields). In the high-performance production systems the crossbred cows had higher yields than the Holstein-Friesian cows (compared with Production Value predictions) by 5.7 kg milksolids (heifers) and 1.9 kg milksolids (mature cows). This study indicates that heterosis for dairy production traits is more fully expressed in production systems that favour higher per cow yields than in the more restrictive production systems common in the 1990s.},
	issn = {1176-5283},
	author = {Montgomerie WA}
}
@conference {41744,
	title = {Effect of increased somatic cell count on lactation yields of milk , fat and protein},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {293-296},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {The purpose of this study was to estimate the effect of increased SCC on production in New Zealand dairy farms. Herd test data from lactations one through six were used in the study. Herd test milk, fat and protein yields were modelled as a function of days in milk at the time of the herd test and the logarithm (base 2) of SCC. The model estimates were used to obtain the predicted value for each observation using the actual log SCC and again where the log SCC was increased by one (i.e. doubling the SCC level). For first-lactation cows, the reduction in a 270-day lactation yield from a doubling of the SCC was estimated to be 78 litres, 2.39 kilograms and 2.04 kilograms for milk, fat and protein yield, respectively. Herd SCC level also influenced the extent to which a doubling of SCC decreased production. For first-lactation cows every doubling of SCC was predicted to result in an average loss of 67 and 90 litres in the lowest and highest quartiles, respectively.},
	issn = {1176-5283},
	author = {Winkelman AM and Montgomerie WA and Johnson DL}
}
@conference {41760,
	title = {Multiple trait national genetic evaluation for cow longevity},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {377-381},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {In New Zealand genetic evaluation for cow longevitywas based on a single trait model where the phenotypic record was actual or predicted days survived in the milking herd. Cows which were yet to express their actual longevity received a predicted phenotypic record based on the milk production and liveweight production values, traits other than production (TOP), and fertility breeding values. The prediction equation was a proxy for a multiple trait model. At the time of implementation a full multiple trait model was not computationally feasible. A study was undertaken to investigate the feasibility of developing a full multiple trait model. The multiple trait model has the advantage of incorporating the appropriate genetic relationships among the predictor traits and the longevity traits, as well as allowing different genetic correlations among the individual longevity traits. The first stage of the study was to estimate the genetic correlations among all traits under genetic evaluation and two longevity traits; survival from first to second lactation and first to fifth lactation. Data used for genetic correlation estimation was from first lactation records from the Sire Proving Scheme herds for seasons 1987 to 2005. The two fertility traits, 42 day calving rate and percent mated in the first 21 days, had the highest genetic correlations with the longevity traits, ranging from 0.84 to 0.27. Body condition score, management TOP and the milk production traits had moderate genetic correlations with the longevity traits, ranging from 0.42 to 0.24. Somatic cell score, udder support, udder overall, legs, capacity and dairy conformation had low genetic correlations with the longevity traits but were significantly greater than zero. Four longevity traits, and 9 predictor traits were included in a national genetic evaluation for cow longevity. The 9 predictor traits were chosen from the traits that had significant genetic correlations with cow longevity and contained genetic information that was not already included in other predictor traits. Comparisons between sire breeding values from the single trait model and the multiple trait model show good agreement with a correlation of 0.95 for Animal Evaluation enrolled sires. Investigation of the sire breeding values shows that the multiple trait model puts a greater emphasis on cow fertility than the single trait model.},
	issn = {1176-5283},
	author = {Harris BL and Montgomerie WA}
}
@conference {41761,
	title = {Test-day model for national genetic evaluation of milk production traits},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {382-387},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {Genetic evaluation for milk, fat and protein yields, using 270-day lactation yields in an across-breed animal model (AM), has been performed in New Zealand since 1996. A new system has been developed to calculate breeding values from herd-test data. In the current AM, a 270-day lactation yield record is calculated based on 1 to 10 test-day records. The environmental effect of herd-test-day (HTD) is removed during the 270-day lactation yield calculation. However, this is done outside the AM, without reference to the genetic level of the HTD contemporary group. A test-day model (TDM) can simultaneously account for the fixed effects such as HTD contemporary groups,and the genetic, permanent environmental (PE) and temporary environmental randomeffects that affect the trait. By including the effect in the model, the TDM allows the environment specific to each test-day to be better taken into account, resulting in an improved accuracy of evaluation. A TDM can accommodate changes in the genetic and PE effects over time by fitting polynomials of time to these effects. A random regression (RR) TDM can accommodate changes in the genetic and PE effects overtime by fitting Legendre polynomials of days in milk (DIM) to these random effects. The RR TDM allows each cow{\textquoteright}s lactation curve to have a different shape. TDM evaluations are more stable than evaluations obtained using 270-day lactations because they account for genetic differences in maturity rate and persistency of lactation. The sire breeding values (BVs) from the TDM were compared to those from the AM. For sires with more than 30 daughters, the correlations between the BVs from the two models were 0.990, 0.988 and 0.990 for milk, fat and protein yields, respectively. The TDM demonstrated improved stability for sires undergoing their widespread proof. There was less variation in the change in BVs for reproof sires from August through to October compared to the AM. The sires that show the greatest change during early reproof under the AM were sires that were outliers for their TDM persistency breeding values for their breed.},
	issn = {1176-5283},
	author = {Harris BL and Winkelman AM and Johnson DL and Montgomerie WA}
}
@conference {41875,
	title = {Body condition score as a candidate trait in the breeding worth dairy index},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {66},
	year = {2006},
	month = {Jan},
	pages = {103-106},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Napier},
	abstract = {Body condition score (BCS) has been proposed for inclusion in the New Zealand national dairy index, Breeding Worth (BW), to account for replenishment of body tissue. Currently, the breeding objectives model positively accounts for body tissue mobilisation (through extra yield), but not the negative cost of replenishing body tissue. Two methods have been proposed: 1) Including BCS directly into BW by calculating and assigning an economic value to BCS and 2) Adjusting liveweight Breeding Values (BVs) for BCS, which would mean that liveweight BVs would be expressed at a constant BCS (indirect method). Energy equations were used to calculate the direct economic value for BCS and included a sensitivity analysis. With an economic weight of $25, the percentage emphasis of BCS in BW would be 3.4\%. Including BCS in BW, either directly or indirectly, had little impact on sire rankings (rank correlations with and without BCS within breed were >0.99) and would only have a small impact on the economic response of BW ($0.02 net /cow/annum) and the improvement in BCS (0.006 BCS units/cow/annum). It is concluded that there would be little benefit to including BCS as an independent trait in BW. Body condition score is already included as a predictor in the genetic evaluation of fertility and breeding values for BCS will be estimated routinely from the fertility model.},
	issn = {1176-5283},
	author = {Pryce JE and Harris BL and Johnson DL and Montgomerie WA}
}
@conference {41876,
	title = {Development of new fertility breeding values in the dairy industry},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {66},
	year = {2006},
	month = {Jan},
	pages = {107-112},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Napier},
	abstract = {This paper provides the basis for a new method for calculating fertility breeding values. The objective of this study was to: firstly, investigate the data extract of mating and calving records from Livestock Improvement{\textquoteleft}s national database to identify improvements, secondly investigate the definition of the fertility trait from percent of calves born from artificial insemination (AI) to 42 day calving rate, and thirdly explore the inclusion of milk production and body condition score information. The overall aim was to improve the accuracy of the fertility breeding values available when a sire{\textquoteleft}s daughters have completed their first lactation (i.e., the time of the sire{\textquoteleft}s first proof). A new procedure for routine national evaluation of these traits is outlined. Results from the new system are given. Possible future enhancements to the new system are discussed. The new method improves the accuracy of the fertility breeding value for first crop sires with 80 daughters from 45\% to 52\%. The inclusion of body condition score and milk production in the calculation of the fertility breeding value improves the response to selection for fertility within breeding worth index by 34\% per annum. The improvement in response to selection is worth 0.18 $/cow/year or approximately $700,000 annually to the dairy industry. },
	issn = {1176-5283},
	author = {Harris BL and Pryce JE and Xu ZZ and Montgomerie WA}
}
@conference {41572,
	title = {Comparing feed allowances to inferred energy intake using data from a dairy grazing farm trial},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {65},
	year = {2005},
	month = {Jan},
	pages = {225-230},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {The main objective of this research was to investigate whether calculating intake of dairy cows using equations to predict energy requirements provides a good alternative to conventional ways of estimating intake. The method was applied to data from the Dexcel Holstein-Friesian strain trial over three seasons. Feed intake per cow was calculated as the sum of the energy requirements for maintenance, milk production, pregnancy, growth and body tissue mobilisation using measured yields of milk, fat, protein and lactose, live weight and body condition score of cows and calf live weights. In order to compare the estimates of feed intake to the amount of feed offered, linear regressions of calculated (ME) intake (grouped by farmlet) on the amount ME offered per farmlet were performed by season. The relationship between ME intake and ME offered was weak in the first year, with a limited response to increasing the amount of feed offered. This was because all the cows were two-year-olds with lower live weights and milk yields and consequently lower feed intakes. In the subsequent two years of the trial, the relationship between ME intake calculated using the energy equations were 67\% and 72\%. The modern strains of dairy cows responded well to higher levels of feed offered, while the 1970s strain of New Zealand dairy cows failed to increase intake when offered diets of higher total ME. Our results show that energy prediction equations offer a viable and cheap alternative of estimating ME intake of lactating dairy cows.
KEYWORDS: dairy cows; energy intake; strain comparison; efficiency. },
	issn = {1176-5283},
	author = {Pryce JE and Harris BL and Montgomerie WA and Jackson R and MacDonald KA and Glassey CB and Thorrold BS and Holmes CW}
}
@conference {41539,
	title = {Economic comparison of Holstein-Friesian strains},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {65},
	year = {2005},
	month = {Jan},
	pages = {68-73},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {The objective of this research was to identify major determinants of net profit per cow. Data were from the Dexcel strain trial over three seasons, in which Holstein-Friesian cows were managed in groups of 12 to 20 cows in eleven farmlets. Milk returns were calculated from lactation yields of milk, fat and protein. Net profit per cow was calculated as the net return from milk sales plus sales of calves minus feed, fertility, health, shed and working expense costs. Annualised present values were derived using asset replacement theory and discounting to account for different numbers of years of data according to the year in which an animal entered the herd. Net replacement costs and average replacement returns were included where animals were replaced before the end of the trial. Partition analysis was used to identify indicators of cow profitability. Partition analysis recursively sub-divides data creating a tree of partitions. Each split is chosen to maximise the difference in profitability between branches of the split. Variables on which data could be partitioned included breeding values, Breeding Worth and traits measured in first parity. The key determinants of profitability were lactation yield of protein and fat, percentage of fat and Breeding Worth. When these variables were fitted to a multiple regression model where the response was annualised present value, the adjusted R2 was 52\%.
KEYWORDS: asset replacement model; economics; dairy cattle. },
	issn = {1176-5283},
	author = {Pryce JE and Harris BL and Glassey CB and Montgomerie WA and Jackson R and MacDonald KA and Thorrold BS and Holmes CW}
}
@conference {41537,
	title = {National genetic evaluation for somatic cell score},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {65},
	year = {2005},
	month = {Jan},
	pages = {59-62},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {The method for the national genetic evaluation of somatic cell score (SCS) in New Zealand is described. Evaluation was done using a multiple-trait random regression test day animal model. Trait one was the first-lactation SCS record and trait two was the records from the second and third lactations. Third-order Legendre polynomials of days in milk were fitted to the genetic and cow effects. The evaluation was done across breed. In the first national evaluation, the pedigree contained 15.9 million animals. There were 22.7 million first lactation test day records and 35.4 million second/third lactation test day records. Solutions were obtained using a preconditioned conjugate gradient solver and iteration on data. The resulting breeding values (BVs) indicate a small annual increase (0.01 to 0.03 genetic standard deviation units) in SCS. The range in sire BVs indicate the potential to select for decreased SCS.
KEYWORDS: somatic cell score; genetic evaluation; test day model; dairy cows. },
	issn = {1176-5283},
	author = {Harris BL and Winkelman AM and Montgomerie WA}
}
@conference {41481,
	title = {Future genetic progress of dairy cattle in New Zealand},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {64},
	year = {2004},
	month = {Jan},
	pages = {96-100},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Hamilton},
	abstract = {  Significant lifts in profitability have been achieved by New Zealand dairy farmers through the inclusion of  increasing amounts of maize silage into a pasture based system. Most of this maize is grown off the dairy unit on  farmer owned or leased runoff blocks or by contract growers. While there is still significant scope to improve dairy  farm productivity by increasing maize silage input levels, there is considerable opportunity to also improve dairy farm  productivity by reducing feed costs through improving maize silage yields, increasing milk output by lifting maize  silage nutritional quality and improving  agronomic stability of maize silage  offering higher yields over a wider  environmental range. Traditional plant breeding, genetic engineering and advances in agronomic management all have  the potential to impact production potential and profitability of maize silage in New Zealand dairy farm systems.},
	issn = {1176-5283},
	author = {Montgomerie WA}
}
