@conference {41762,
	title = {The genetic relationship between heifer and cow fertility},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {388-391},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {Initial predictors of dairy bulls{\textquoteright} fertility proofs are currently limited to body condition score (BCS), milk yield and success of mating in the first 21 days (PM21) for their two-year-old lactating daughters. The first calving rate trait (CR42) is available after a cow has calved for a second time. Obtaining an earlier indication of fertility would be useful for genetic evaluation purposes. The aim of this study was to investigate the genetic and phenotypic control of heifer fertility in addition to investigating the relationship between heifer fertility and traits already included in the prediction ofthe fertility breeding value. Data were available on LIC{\textquoteright}s Sire Proving Scheme animals born from 1989 to 2003 and included records on 244,453 animals. Using data on the first calving, planned start of calving was defined as the day within contemporary group when greater than 10\% of animals had calved. A multivariategenetic analysis was undertaken with the traits PM21, CR42, BCS and 270-day milk yield recorded in lactating cows, in addition to a heifer fertility trait where success is defined as heifers that calve within21 days from the planned start of calving (CR21). The model fitted to these traits included contemporary group of the milking herd, breed proportions and age at first calving as linear and quadratic effects. The mean CR21 in this dataset was 71\%. Heifers failing to calve within 21 days of the herd{\textquoteright}s planned start of calving for heifers also had poorer fertility in first lactation, with a least-squares-mean of 75.5\% (s.e. 0.2) versus 81.5\% (0.1) for PM21 and 54.2\% (0.22) and 62.4\% (0.1) for CR42. The heritability estimate of CR21 was low (0.012), yet the genetic variation was comparable to other fertility measures. CR21 had a positive genetic correlation with CR42, indicating that CR21 may be a useful early indicator of fertility for use in genetic evaluations.},
	issn = {1176-5283},
	author = {Pryce JE and Harris BL and McNaughton LR}
}
@conference {42015,
	title = {Metabolic feed efficiency - opportunities for selection in dairy cows},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {392-398},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {A literature review and simulation study is presented to investigate the potential role of metabolic feed efficiency in dairy cattle breeding programmes. Metabolic efficiency is generally calculated as the difference between actual feed intake and expected feed requirements and as a result is a residual term, hence it is often referred to as residual feed intake (RFI). There is evidence of genetic variation in RFI in poultry, sheep and beef cattle. Heritability estimates inbeef cattle are moderate (0.14 to 0.43). Heritability estimates in dairy cattle range from zero (no genetic variation) to moderate (0.38). RFI is positively genetically correlated with feed intake, so more efficient animals tend to eat less. Information is sparse, but suggests there is no genetic correlation between milk production and RFI. Genetic correlations between health and fertility traits and RFI in cattle have not been established, but evidence frommice and pigs suggests unfavourable correlations between RFI and fertility. Estimating the genetic relationships between RFI and health and fertility in dairy cattle is required. The identification of genetic markers that explain sizeable variation in RFI, or an easily measured correlated trait would be the preferred options to enable selection for RFI in dairy cattle, ideally breeding values for RFI would be estimated and included as part of a multiple-trait selection index.},
	issn = {1176-5283},
	author = {McNaughton LR and Pryce JE}
}
@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 {41874,
	title = {Genetics of stillbirth in dairy calves},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {66},
	year = {2006},
	month = {Jan},
	pages = {98-102},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Napier},
	abstract = {The aim of this study was to investigate factors affecting, and estimate variance components of, stillbirth using data collected as part of Livestock Improvement{\textquoteright}s Sire Proving Scheme. Only calves that reached full-term of gestation were considered (i.e. abortions and inductions were excluded). After editing there were 773,904 records on calf-fate collected from 1987 to 2004. The mean incidence of stillbirth was 7.2\%. The fixed effect model fitted to the data included the effects of contemporary group, birth assistance code, the sex of the calf, the gestation length of the dam, whether the dam was primiparous or multiparous and mating type e.g. a Jersey cow mated to a Holstein-Friesian sire etc. Breed proportions of New Zealand (NZHF) and North American (OSHF) origin Holstein-Friesian and Jersey were also fitted in addition to the proportion of heterosis expected in the calf. Data were analysed by considering stillbirth as a binomial trait using the logit transformation in ASReml that included a sire-maternal-grandsire pedigree. The direct heritability of stillbirth was estimated to be 0.010 (s.e. 0.009). It was not possible to estimate the maternal heritability using this dataset. Estimates of fixed effects were obtained from ASReml by analysing stillbirth as a continuous trait, as back-transformed fixed effect estimates obtained using a binomial model are unreliable when the incidence is small. The largest effect on the probability of stillbirth was calving difficulty. Compared to no assistance at calving, the two categories of greatest calving difficulty resulted in 22\% and 41\% mortality. The next largest effect on stillbirth was gestation length, with longer gestations being associated with more stillbirths. Males were 1\% more likely to be stillborn than females. OSHF were most likely to be stillborn, followed by Jerseys and then NZHF. Heterosis effects were significant and favourable, except between the two strains of Holstein-Friesians where there was no significant heterosis. The largest heterosis estimate was between NZHF and Jerseys. Unlike some overseas programmes, genetically selecting for reduced stillbirths would not be effective in New Zealand, crossbreeding and devising strategies to manage calving assistance and gestation length appear to be more worthwhile. },
	issn = {1176-5283},
	author = {Pryce JE and Harris BL and Sim S and McPherson AW}
}
@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 {41534,
	title = {Impact of farm management decision rules on the production and profit of different strains of Holstein-Friesian dairy cows},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {65},
	year = {2005},
	month = {Jan},
	pages = {40-45},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {Management decision rules ({\textquoteleft}old{\textquoteright} rules) have been used at the Dexcel No. 2 Dairy Farm to remove subjectivity from the management of farm systems research and have also been promoted to the dairy industry. A trial involving these rules where three strains of Holstein-Friesian (HF) cows were compared has completed its third season. The trial included two high breeding worth (BW) strains of either North American (OS90) or New Zealand (NZ90) genetics, and one low BW strain of NZ genetics (NZ70). Under the {\textquoteleft}old{\textquoteright} rules the OS90 cows had fewer days in milk than the other two strains, mainly because they were dried off earlier due to their lower body condition score (BCS). In the third lactation {\textquoteleft}new{\textquoteright} rules were applied that allowed cows at the higher feed allowances to be dried off later (but at the same BCS) than would have been allowed under the {\textquoteleft}old{\textquoteright} rules. For the herds receiving the higher feed allowances, this change resulted in increased days in milk (NZ90 + 2 days; OS90 + 17 days) more milksolids (MS) per cow (NZ90 +2 kg; OS90 +21 kg), and more feed required (NZ90 + 10 kg; OS90 + 157 kg DM/cow) with all herds reaching target BCS by their next calving. It is calculated that this reduced the difference in economic farm surplus (EFS) per ha between the NZ90 and OS90 from $488 to $219. These results indicate the need to alter management rules to get the best performance from North American HF genetics.
KEYWORDS: Holstein-Friesian; body condition score; drying-off decision rules. },
	issn = {1176-5283},
	author = {MacDonald KA and Thorrold BS and Glassey CB and Holmes CW and Pryce JE}
}
@conference {41488,
	title = {Genetic and phenotypic relationships between milk protein percentage, reproductive performance and body condition score in New Zealand dairy cattle},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {64},
	year = {2004},
	month = {Jan},
	pages = {127-131},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Hamilton},
	abstract = {Recent research from the Australian In-Calf and New Zealand Monitoring Fertility projects have demonstrated that low milk protein percentage in early lactation is phenotypically linked to poor reproductive performance. The purpose of this study was to quantify the phenotypic and genetic relationship between body condition score (BCS), protein percentage (and other milk production traits) and the reproductive measures used to predict the female fertility breeding value in New Zealand{\textquoteright}s Animal Evaluation System: probability of mating in the first 21 days of a herd{\textquoteright}s mating period (PM21) and the probability of having a calf born to AI (CAI). Data on 99,870 first lactation cows, recorded as part of Livestock Improvement{\textquoteright}s and Ambreed{\textquoteright}s progeny test schemes were used for both a phenotypic analysis and to estimate genetic parameters. Effects of breed, heterosis, BCS, protein percentage and dairy conformation were statistically significant in logistic regression analyses on both CAI and PM21. Genetic correlations between protein percentage and PM21 and CAI were 0.18 and 0.20 respectively and genetic correlations of BCS and PM21 and CAI were 0.48 and 0.38 respectively. These results show that selection for protein percentage is unlikely to have a large effect on reproductive performance, while BCS is a promising tool to aid in selection for improved fertility. },
	issn = {1176-5283},
	author = {Harris BL and Pryce JE}
}
@conference {41487,
	title = {Mate selection to control inbreeding and maximise farm profit of commercial dairy cattle},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {64},
	year = {2004},
	month = {Jan},
	pages = {122-126},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Hamilton},
	abstract = {The objective of this study was to demonstrate the potential benefits of computerised mate selection in a commercial crossbred dairy herd of 411 cows mated to 10 Holstein-Friesian and 10 Jersey bulls. Mate selection was carried out using an evolutionary algorithm to perform single- or multiple-objective optimisation to maximise farm profit ($/4.5 t DM) and/or minimise inbreeding level of progeny. Restrictions were placed on the total number of mating pairs, the maximum number of matings per bull and per cow. Selection and mate allocation of bulls and cows at random produced progeny with average farm profit of $94 and inbreeding level of 1.70\%. Mate selection applied to maximise farm profit yielded a mating set with an average farm profit of $181 and inbreeding level of 2.07\%. Mate selection applied to minimise inbreeding level selected a mating set with average farm profit of $65 and inbreeding level of 0.03\%. Mate selection applied to optimise farm profit and minimise level of inbreeding with a weighted ratio of 1:1, resulted in a mating set with average farm profit of $176 and inbreeding level of 0.44\%. The results demonstrate that in the short term, inbreeding can be controlled at the same time as maximising farm profit using a computerised mating selection program with multiple-objective optimisation. },
	issn = {1176-5283},
	author = {Lopez-Villalobos N and Harris BL and Pryce JE}
}
@conference {41486,
	title = {Use of breeding values for live weight to calculate individual live weight targets for dairy heifers},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {64},
	year = {2004},
	month = {Jan},
	pages = {118-121},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Hamilton},
	abstract = {Replacement heifers need to reach specific target live weights (LW) to ensure they calve as two year olds, and subsequently achieve high milk yields and good fertility. Currently, different LW targets are recommended for heifers based on their expected mature LW according to appearance or breed. However, the mature LW is difficult to estimate without knowledge of the animals. genetic potential for LW. The objective of this paper is to develop and validate a growth model which uses estimated breeding values for LW (EBV LW) of individual heifers of any breed to calculate target LW from birth to maturity. Predicted live weights are presented for a range of four EBV LW, from {\textendash}40 to 100 kg. These values were very similar to other published target values. Data from the Dexcel Holstein Friesian Strain Trial was used to validate the model with respect to LW and age at puberty. For LW at puberty the predicted values were significantly correlated (P<0.05), but were marginally higher (3-5\%) than the actual values. A report can be formulated to enable farmers to identify individual heifers which are below (or above) their target LW at any date },
	issn = {1176-5283},
	author = {Bryant JR and Holmes CW and Lopez-Villalobos N and McNaughton LR and Brookes IM and Verkerk GA and Pryce JE}
}
@conference {41417,
	title = {Comparison of multivariate statistical methods for the prediction of reproductive performance of Holstein Friesian cattle},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {63},
	year = {2003},
	month = {Jan},
	pages = {112-115},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Queenstown},
	abstract = {The objectives of this study were to predict success or failure at mating (1/0) using information on 168 first lactation dairy cows from the Dexcel Strain Trial. The farmlets were established by allocating heifers from three genetic strains to eleven groups. The groups were managed under a range of feeding systems, ranging from moderate to generous allowances. Measurements were taken on milk, fat and protein yields, liveweight and condition score and variables derived from these used as predictors of success at mating in a series of models. Reproductive measures used for analysis were cows in calf at 42, 49 and 56 days after the planned start of mating. Three statistical methods were used to determine suitable predictive models of success at mating: logistic regression, discriminant analysis and partition analysis. Partition analysis was the best method of prediction. Kappa values, measuring the degree of agreement between observations and predictions ranged between 0.32 and 0.38 for discriminant analysis, 0.41 and 0.44 for logistic regression and 0.70 and 0.74 for partition analysis. The partition analysis produced a set of rules for predicting likely success at mating. Important rules were CS > 4.75 in month three of lactation and calving before week four after the start of calving for the herd. },
	issn = {1176-5283},
	author = {Harris BL and Pryce JE and Verkerk G}
}
