Sensitivity and specificity of a tail-activity measuring device for calving prediction in dairy cattle

Efficient calving surveillance is essential for avoiding stillbirth due to unattended dystocia. Calving sensors can help detect the onset of parturition and thus ensure timely calving assistance if necessary. Tail-raising is an indicator of imminent calving. The objective of this study was to evaluate a tail-mounted inclinometer sensor (Moocall Ltd., Dublin, Ireland) and to monitor skin integrity after sensor attachment. Cows (n = 157) and heifers (n = 23) were enrolled at 275 d post insemination, and a sensor was attached to each cow's tail. Investigators checked for signs indicating the onset of stage II of parturition, verified the position of the sensor, and evaluated the skin integrity of the tail above and below the sensor hourly for 24 h/d. We used 5 different intervals (i.e., 1, 2, 4, 12, and 24 h until calving) to calculate sensitivity and specificity. Sensors continuously remained on the tail (i.e., within 3 cm of the initial attachment position) after initial attachment until the onset of calving in only 13.9% of animals (n = 25). Sensors were reattached until a calving event occurred (51.6%) or the animal was excluded for other reasons (34.4%). In 31 animals the sensor was removed because the tail was swollen or painful. Heifers were significantly less likely than cows to lose a sensor but more likely to experience tail swelling or pain. Depending on the interval preceding the onset of parturition, sensitivity varied from 19 to 75% and specificity from 63 to 96%.     

Influence of denaverine hydrochloride on calving ease in Holstein-Friesian heifers

Calving is assumed to be an exhausting and painful event. A drug that eases the calving procedure and alleviates pain would help cows, especially those suffering from dystocia. In a randomized, controlled, and blinded trial, we measured the effect of denaverine hydrochloride on physical and physiological calving parameters. Eighty-three Holstein-Friesian heifers were included in the analysis. Pulling force was measured using a digital force gauge interposed between the calf and a mechanical calf puller. The concentration of cortisol was measured in serum before and after parturition. There was no effect of treatment group on calving modality (i.e., spontaneous vs. assisted calving), duration of calving, and cortisol concentration. The area under the curve of pulling force × time (n = 44), however, was significantly smaller in the treatment group compared with the placebo group. Also, duration of calving assistance was numerically shorter in the treatment group compared with the placebo group. The results provide evidence that calving ease can be influenced by denaverine hydrochloride during calving assistance.     

A comparison of 4 predictive models of calving assistance and difficulty in dairy heifers and cows

The aim of this study was to build and compare predictive models of calving difficulty in dairy heifers and cows for the purpose of decision support and simulation modeling. Models to predict 3 levels of calving difficulty (unassisted, slight assistance, and considerable or veterinary assistance) were created using 4 machine learning techniques: multinomial regression, decision trees, random forests, and neural networks. The data used were sourced from 2,076 calving records in 10 Irish dairy herds. In total, 19.9 and 5.9% of calving events required slight assistance and considerable or veterinary assistance, respectively. Variables related to parity, genetics, BCS, breed, previous calving, and reproductive events and the calf were included in the analysis. Based on a stepwise regression modeling process, the variables included in the models were the dam's direct and maternal calving difficulty predicted transmitting abilities (PTA), BCS at calving, parity; calving assistance or difficulty at the previous calving; proportion of Holstein breed; sire breed; sire direct calving difficulty PTA; twinning; and 2-way interactions between calving BCS and previous calving difficulty and the direct calving difficulty PTA of dam and sire. The models were built using bootstrapping procedures on 70% of the data set. The held-back 30% of the data was used to evaluate the predictive performance of the models in terms of discrimination and calibration. The decision tree and random forest models omitted the effect of twinning and included only subsets of sire breeds. Only multinomial regression and neural networks explicitly included the modeled interactions. Calving BCS, calving difficulty PTA, and previous calving assistance ranked as highly important variables for all 4 models. The area under the receiver operating characteristic curve (ranging from 0.64 to 0.79) indicates that all of the models had good overall discriminatory power. The neural network and multinomial regression models performed best, correctly classifying 75% of calving cases and showing superior calibration, with an average error in predicted probability of 3.7 and 4.5%, respectively. The neural network and multinomial regression models developed are both suitable for use in decision-support and simulation modeling.     

Multiparity evaluation of calving ease and stillbirth with separate genetic effects by parity

Evaluations that analyze first and later parities as correlated traits were developed separately for calving ease (CE) from over 15 million calving records of Holsteins, Brown Swiss, and Holstein-Brown Swiss crossbreds and for stillbirth (SB) from 7.4 million of the Holstein CE records. Calving ease was measured on a scale of 1 (no difficulty) to 5 (difficult birth); SB status was designated as live or dead within 48 h. Scores for CE and SB were transformed separately for each trait by parity (first or later) and calf sex (male or female) and converted to a unit standard deviation scale. For variance component estimation, Holstein data were selected for the 2,968 bulls with the most records as sire or maternal grandsire (MGS). Six samples were selected by herd; samples ranged in size from 97,756 to 146,138 records. A multiparity sire-MGS model was used to calculate evaluations separately for CE and for SB with first and later parities as correlated traits. Fixed effects were year-season, calf sex, and sire and MGS birth years; random effects were herd-year interaction, sire, and MGS. For later parities, sex effects were separated by parity. The genetic correlation between first and later parities was 0.79 for sire and 0.81 for MGS for CE, and 0.83 for sire and 0.74 for MGS for SB. For national CE evaluations, which also include Brown Swiss, a fixed effect for breed was added to the model. Correlations between solutions on the underlying scale from the January 2008 USDA CE evaluation with those from the multiparity analysis for CE were 0.89 and 0.91 for first- and later-parity sire effects and 0.71 and 0.88 for first- and later-parity MGS effects; the larger value for later parity reflects that later parities comprised 64% of the data. Corresponding correlations for SB were 0.81 and 0.82 for first- and later-parity sire effects and 0.46 and 0.83 for first- and later-parity MGS effects, respectively. Correlations were higher when only bulls with a multiparity reliability of >65% were included. The multiparity analysis accounted for genetic differences in calving performance between first and later parities. Evaluations should become more stable as the portion of a bull's observations from different parities changes over his lifetime. Accuracy of the net merit index can be improved by adjusting weights to use evaluations for separate parities optimally.     

Phenotypic effects of calving ease on the subsequent fertility and milk production of dam and calf in UK Holstein-Friesian heifers

The effect of calving ease on the fertility and production performance of both dam and calf was studied in approximately 50,000 and 10,000 UK Holstein-Friesian heifers and heifer calves, respectively. The first objective of this study was to estimate the effect of a difficult calving on the subsequent first-lactation milk production by estimating lactation curves using cubic splines. This methodology allows the estimation of daily milk, protein, and fat yields following calvings of differing degrees of difficulty. Losses in milk yield after a difficult calving have been quantified previously; however, estimates are generally restricted to the accumulated yields at specific days in lactation. By fitting cubic splines, gaps (in which the shape of the lactation curve can be merely guessed) between estimations were avoided. The second objective of this study was to estimate the effect of a difficult birth on the subsequent performance of the calf as an adult animal. Even though the calving process is known to involve cooperation between dam and calf, the effect of a difficult calving has, until now, only been estimated for the subsequent performance of the dam. Addressing the effects of a difficult birth on the adult calf strengthens the importance of calving ease as a selection trait because it suggests that the benefit of genetic improvement may currently be underestimated. The effect of calving ease on the subsequent reproductive performance of dam and calf was analyzed using linear regression and with calving ease score fitted as a fixed effect. Dams with veterinary-assisted calvings required 0.7 more services to conception and 8 more days to first service and experienced a 28-d longer calving interval in first lactation compared with dams that were not assisted at calving. Effects of calving ease on the reproductive performance of the adult calf in first lactation were not detected. Losses in milk yield of the dam were significant between d 9 to 90 in milk subsequent to a veterinary-assisted calving, creating a loss of approximately 2 kg of milk per day, compared with a nonassisted calving. Calves being born with difficulties showed a significant reduction in milk yield in first lactation, demonstrating the lifelong effect of a difficult birth. Compared with nonassisted calves, veterinary-assisted calves showed a loss of 710 kg in accumulated 305-d milk yield, which was significant from 129 to 261 d in milk. This suggests that from birth to production, physiological effects of a bad calving are not negated. Results furthermore suggest a beneficial effect of farmer assistance at calving on the milk yield of both dam and calf, when moderate difficulties occurred.     

Factors affecting calving interval in Italian Holstein-Friesian heifers

Effect of rump conformation on calving interval of 520 Italian Holstein Friesian heifers was evaluated with simultaneous adjustment for herd, year of birth, calving month, age at first parturition, and milk production. All factors, except age at first parturition, were important sources of variation. Heifers with narrow rumps at the pins had the longest calving interval. There were significant differences among the herds. Cows born between 1979 and 1981 had shorter calving intervals, probably resulting from a national plan against bovine infertility initiated in 1981. Cows calving in July had better reproductive performance. There was positive relationship between milk production and calving interval.     

Assessment of calving progress and reference times for obstetric intervention during dystocia in Holstein dairy cows

The objectives of this observational study were (1) to assess the time from the appearance of the amniotic sac (AS) or feet outside the vulva to birth in Holstein cows (primiparous and multiparous) with (dystocia) or without assistance (eutocia) at calving, and (2) to estimate reference times to be used as guidelines for obstetric intervention in Holstein cows that need assistance during difficult births. Cows (n = 92) from 1 commercial dairy operation were used in this study. Periparturient dairy cows (primiparous, n = 58; multiparous, n = 34) were placed in a maternity pen and constantly monitored until birth. The calving ease of cows, time from AS or feet appearance to birth, calving progress from a subset of 15 cows (frequency and duration of abdominal contractions during labor), calf birth weight, calf sex, and stillbirths (born dead or died within 24 h after birth) were recorded. The reference times for obstetric intervention during dystocia were estimated based on values from unassisted births (normal). The normal range of times from the appearance of AS or feet outside the vulva to birth was estimated based on the mean + 2 standard deviations (SD) of unassisted births. According to farm protocol, assistance was provided to cows without calving progress 80 min after AS appearance or earlier (e.g., to correct malpositions). Cows with dystocic births had a longer time from AS appearance to birth and increased incidence of stillbirth compared with cows with eutocic calvings. After the appearance of the AS, calving progress was evident every 15 min for eutocic births. The estimated reference times (mean + 2 SD) from AS appearance to birth were 69.7 min and from feet appearance to birth were 64.6 min for eutocic births. Findings from this study suggested that calving personnel should start assisting cows 70 min after AS appearance (or 65 min after feet appearance) outside the vulva. The time spent in labor (straining) combined with the time from the appearance of the AS or feet to birth, and the assessment of calving progress (as described for eutocic births) should be used as guidelines for obstetric intervention during difficult births under field conditions. These reference times should be interpreted in combination with adequate obstetrical knowledge and examination.     

Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States

The objective of this study was to add a maternal grandsire (MGS) effect to the existing sire model for national calving ease genetic evaluations. The Animal Improvement Programs Laboratory (AIPL) of USDA assumed responsibility for conducting the national genetic evaluation for calving ease and maintaining the associated database in 1999. Existing evaluations used a sire threshold model. Adding an MGS effect to the model was expected to improve accuracy by partially accounting for merit of mates and differences in maternal ability of the dams. Dystocia data were migrated to a relational database integrated with the AIPL production database. This database design allowed more rigorous data edits by comparison with the production data and improved MGS identification (ID) rate by utilizing pedigrees from the production records. Integration of dystocia data with production data increased MGS ID rate from 58 to 73%. In addition, nearly 200,000 duplicate records were identified using the new edit system. Sire and sire-MGS models were compared using over 10 million observations available for the August 2002 national genetic evaluation. The sire model included herd-year, season, sex of calf, parity of dam, birth year group of sire, and sire. For the sire-MGS model, MGS and birth year group of MGS were added, year-seasons rather than seasons were used, and sex of calf and parity of dam were combined into a single interaction effect. Herd-year, sire, and MGS were random effects. Variance components used for the sire model were those previously used in the national evaluation and for the sire-MGS model were estimated in a separate study. Correlations between predicted genetic merits for service sire calving ease from the two models was 85%, indicating general agreement, but with some significant differences in evaluations. A sire-MGS model was implemented in August 2002 for the national calving ease genetic evaluation system.     

Heterogeneity of genetic parameters for calving difficulty in Holstein heifers in Ireland

Calving difficulty is a trait that greatly affects animal welfare, herd profitability, and the amount of labor required by cattle farmers. It is influenced by direct and maternal genetic components. Selection and breeding strategies can optimize the accuracy of genetic evaluations and correctly emphasize calving difficulty in multiple-trait indices provided there are accurate estimates of genetic parameters. In Ireland, large differences exist in the age at which heifers first give birth to calves. The objective of this study was to estimate genetic parameters for calving difficulty in first-parity Holsteins and to determine whether these differed with age of the heifer at calving. Transformed calving difficulty records for 18,798 Holstein heifers, which calved between January 2002 and May 2006, were analyzed using univariate, multitrait, and random regression linear sire-maternal grandsire models. The model that 1) fitted a second-order random regression of dam age at first parity for the direct component, 2) treated the maternal component as a single trait regardless of dam age, and 3) fitted a single residual variance component was optimal. Heritabilities for direct (0.13) and maternal (0.04) calving difficulty were significantly different from zero. These 2 components were moderately negatively correlated (−0.47). Estimates of direct genetic variance and heritability were heterogeneous along the dam age trajectory, decreasing initially with dam age before subsequently increasing. Heritability estimates ranged between 0.11 and 0.37 and were higher for records with younger and older dams at parturition. Genetic correlations between the direct components of calving difficulty decreased from unity to 0.5 with increasing distance between dam ages at parturition. The results of this study indicated that heterogeneity of direct genetic variance existed for calving difficulty, depending on dam age at first parturition.     

Genetic parameters of direct and maternal effects for calving ease in Dutch Holstein-Friesian cattle

Genetic parameters of direct and maternal effects for calving ease in Dutch dairy cattle were estimated using 677,975 calving ease records from second calving. Particular emphasis was given to the presence and impact of environmental dam-offspring covariances on the estimated direct-maternal genetic correlation. Moreover, a measure of heritability for traits affected by maternal effects was developed. In contrast to previous parameters, this parameter reflects the amount of genetic variance that can be used to generate a response to selection in maternally affected traits. Estimated genetic correlations between direct and maternal effects on calving ease have often been moderately negative, particularly in beef cattle. Environmental dam-offspring covariances have been put forward as an explanation for such estimates. We investigated the impact of environmental dam-offspring covariances by fitting correlated residuals between dam and offspring records in the statistical model, and by comparing results of a sire-maternal grandsire model with those of an animal model. Results show that calving ease in Dutch dairy cattle has a direct heritability of approximately 0.08, a maternal heritability of approximately 0.04, a direct-maternal genetic correlation of approximately −0.20, and a total heritable variance equal to approximately 11% of phenotypic variance. Results of animal models and sire-maternal grandsire models were very similar. The direct-maternal environmental covariance was near zero, and consequently had very little impact on the estimated genetic parameters. Transformation of observations to a liability scale did not affect the estimated genetic parameters and yielded a nearly identical ranking of sires.     

Short communication: Calving site selection of multiparous,group-housed dairy cows is influenced by site of a previous calving

A calving cow and her newborn calf appear to have an attracting effect on periparturient cows, which may potentially influence the functionality of future motivation-based calving pen designs. In this pilot study we examined whether calving site selection of group-housed Holstein dairy cows was affected by the site of a previous calving. Ten multiparous cows moved to 1 of 2 group pens 11 (range = 4–27) d before calving were included. Each pen consisted of an open area (9 × 9 m) connected to 6 secluded areas (4.5 × 3 m each), where cows could move freely between all areas. Time of calving, location of the breaking of the amniotic sac, as well as the place of birth were recorded. In all but 1 case cows calved within a distance of 1 cow length from where the previous calving took place, suggesting that the cows did not select calving site at random. These preliminary observations indicate that choice of calving site may be affected by the site of a previous calving, potentially explained by the presence of amniotic fluids.     

Trends in calving ages and calving intervals for dairy cattle breeds in the United States

Trends since 1980 for calving age and calving interval, 2 factors that influence herd life, were examined by parity for 5 breeds of US dairy cattle. Calving data were from cows with records that passed edits for USDA genetic evaluations and were in herds that remained on Dairy Herd Improvement test. First-calf heifers calved at progressively younger ages over time, but the age decline was less for later parities because of longer calving intervals. Breed differences for calving age were evident for all parities; current mean age at first calving ranged from 24 mo for Jerseys to 28 mo for Ayrshires. Mean calving age across all parities declined over time for all breeds, primarily because of increased turnover rate, and ranged from 48 mo for Holsteins to 54 mo for Ayrshires. Across parity, annual increase in calving interval was reasonably consistent (0.90 to 1.07 d/yr) for all breeds except Jersey (0.49 d/yr). Within parity, regressions of calving interval on year were generally similar to overall breed trend. Breed means for first calving interval across time ranged from 390 d for Jerseys to 407 d for Brown Swiss.     

Phenotypic and genetic relationships between age at first calving,its component traits,and survival of heifers up to second calving

The aim of this study was to answer the question whether models for genetic evaluations of longevity should include a correction for age at first calving (AFC). For this purpose, phenotypic and genetic relationships between AFC, its component traits age at first insemination (AFI) and interval from first to last insemination (FLI), and survival of different periods of the first lactation (S1: 0 to 49 d, S2: 50 to 249 d, S3: 250 d to second calving) were investigated. Data of 721,919 German Holstein heifers, being inseminated for the first time during the years from 2003 to 2012, were used for the analyses. Phenotypic correlations of AFI, FLI, and AFC to S1 to S3 were negative. Mean estimated heritabilities were 0.239 (AFI), 0.007 (FLI), and 0.103 (AFC) and 0.023 (S1), 0.016 (S2), and 0.028 (S3) on the observed scale. The genetic correlation between AFI and FLI was close to zero. Genetic correlations between AFI and the survival traits were ?0.08 (S1), ?0.02 (S2), and ?0.10 (S3); those between FLI and the survival traits were ?0.14 (S1), ?0.20 (S2), and ?0.44 (S3); and those between AFC and the survival traits were ?0.09 (S1), ?0.06 (S2), and ?0.20 (S3). Some of these genetic correlations were different from zero, which suggests that correcting for AFC in genetic evaluations for longevity in dairy cows might remove functional genetic variance and should be reconsidered.     

Machine-learning-based calving prediction from activity,lying, and ruminating behaviors in dairy cattle

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential.     

A descriptive study of the survival of Holstein-Friesian heifers through to third calving on English dairy farms

A short herd lifespan severely limits opportunities for on-farm selection of breeding cows in addition to causing financial losses on dairy farms and presenting welfare issues for individual animals. This prospective study monitored survival up to third calving and reasons for culling of a cohort of 468 Holstein-Friesian heifers on 18 dairy farms across southern England. Heifers born during 2003 and 2004 were monitored from 1 mo of age through to third calving. A longevity index was calculated as the proportion of days alive spent in milk production, a good measure of lifetime performance. On average, 11% of heifers recruited at 1 mo did not survive until first calving (0% longevity index). Of those that did calve, 19% were culled in lactation 1 (total average lifetime days in milk of 322 with a longevity index of 24%) and 24% were culled during lactation 2 (total average lifetime days in milk of 623 with a longevity index of 40%). The primary cause for culling was infertility. Only 55% of replacement heifers calved successfully for a third time, ranging from 80 to 32% across individual farms. These results show that on a selection of UK farms, a large number of heifers never become productive or are culled before they reach their full lactation potential. Increasing the productive lifetime of dairy cows would improve the efficiency of dairy production by lowering replacement costs and capturing a greater proportion of potential lactation milk yield from mature cows.     

Comparisons of Holsteins with Brown Swiss and Jersey cows on the same farm for age at first calving and first calving interval

Our objective was to evaluate breed differences for heat-stress resistance as reflected by age at first calving and first calving interval. We examined the effect of geographic location and birth season on age at first calving, and geographic location and first calving season on first calving interval on Holsteins and Jerseys, and Holsteins and Brown Swiss located on the same farm. We defined 7 regions within the United States: Northwest, Central north, Northeast, Central, Central south, Southwest, and Southeast, and analyzed 7 individual states: Ohio, Wisconsin, Oregon, California, Arizona, Texas, and Florida. Brown Swiss were older than Holsteins at first calving (833 +/- 2.4 vs. 806 +/- 2.0 d in regions, and 830 +/- 3.1 vs. 803 +/- 2.4 d in states), but Holsteins and Brown Swiss did not differ for first calving interval. Jerseys were younger than Holsteins at first calving and had shorter first calving intervals. In data from individual states, Holsteins housed with Brown Swiss were older at first calving than were Holsteins housed with Jerseys (800 +/- 2.7 vs. 780 +/- 2.5 d). Holsteins housed with one breed or the other were analyzed as a separate data set, and referred to as "type of Holstein." The interaction of "type of Holstein" with first calving season was highly significant for first calving interval. Geographic location and season effects were smaller for Jerseys than for Holsteins; thus, Jerseys showed evidence of heat-stress resistance with respect to Holsteins. Management modified age at first calving in Holsteins to more nearly match that of the other breed. Longer calving intervals might be partly due to voluntary waiting period to breed the cows.     

The genetic relationship between commencement of luteal activity and calving interval,body condition score,production, and linear type traits in Holstein-Friesian dairy cattle

The decline of fertility in the UK dairy herd and the unfavorable genetic correlation (r(a)) between fertility and milk yield has necessitated the broadening of breeding goals to include fertility. The coefficient of genetic variation present in fertility is of similar magnitude to that present in production traits; however, traditional measurements of fertility (such as calving interval, days open, nonreturn rate) have low heritability (h2 < 0.05), and recording is often poor, hindering identification of genetically superior animals. An alternative approach is to use endocrine measurements of fertility such as interval to commencement of luteal activity postpartum (CLA), which has a higher h2 (0.16 to 0.23) and is free from management bias. Although CLA has favorable phenotypic correlations with traditional measures of fertility, if it is to be used in a selection index, the genetic correlation (ra) of this trait with fertility and other components of the index must be estimated. The aim of the analyses reported here was to obtain information on the ra between lnCLA and calving interval (CI), average body condition score (BCS; one to nine, an indicator of energy balance estimated from records taken at different months of lactation), production and a number of linear type traits. Genetic models were fitted using ASREML, and r(a) were inferred from genetic regression of lnCLA on sire-predicted transmitting abilities (PTA) for the trait concerned by multiplying the regression coefficient (b) by the ratio of the genetic standard deviations. The inferred r(a) between lnCLA and CI and average BCS were 0.36 and -0.84, respectively. Genetic correlations between InCLA and milk fat and protein yields were all positive and ranged between 0.33 and 0.69. Genetic correlations between InCLA and linear type traits reflecting body structure ranged from -0.25 to 0.15, and between udder characteristics they ranged from -0.16 to 0.05. Thus, incorporation of endocrine parameters of fertility, such as CIA, into a fertility index may offer the potential to improve the accuracy of breeding value prediction for fertility, thus allowing producers to make more informed selection decisions.     

Genetic effects on stillbirth and calving difficulty in Swedish Holsteins at first and second calving

In Swedish Holstein dairy cattle, genetic effects on stillbirth and calving difficulty were studied in 411,409 first- and 281,193 second-calvers. A linear single-trait sire-maternal grandsire model and a threshold model using a Gibbs sampling technique were used to analyse calving data from 1985 to 1996. In first calving when using the linear model, the heritability of stillbirth on the visible scale was 4% for the direct effect and 3% for the maternal effect. For calving difficulty it was 6% and 5% for direct and maternal effects, respectively. In second calving the corresponding heritabilities for the two traits were considerably lower, less than 1%. Adjusting for calving difficulty in linear analysis of stillbirth halved the heritabilities for the direct and maternal effects in first calving. When using a threshold model, heritabilities for stillbirth in first-calvers were 12% and 8% for direct and maternal effects, respectively, and for calving difficulty they were 17% and 12%. At second calving corresponding heritabilities were 2 to 4% for stillbirth and 4 to 7% for calving difficulty. The correlation between direct and maternal effects was around -0.1, irrespective of whether the linear or the threshold model was used for first-calvers. The genetic correlations between bulls' EBV from first and second calving were 0.4 to 0.5 for direct and maternal effects in stillbirth, whereas they were 0.6 to 0.7 for calving difficulty. In first-calvers there was a substantial genetic variation in both traits, expressed by differences between breeding values of bulls, despite fairly low heritability. The results obtained in this study suggest that first-parity records should preferably be used for genetic evaluation of bulls for calving performance. In such routine evaluations both stillbirth and calving difficulty, and both direct and maternal effects, should be included.     

Calving interval and survival breeding values as measure of cow fertility in a pasture-based production system with seasonal calving

In a grass-based production system with seasonal calving, fertility is of major economic importance. A delay in conception due to poor fertility prolongs intercalving interval and causes a shift in calving pattern, which can lead to culling. Calving interval (CIV) information is readily available from milk records; analyzing it, however, presents a problem, as it is only available for cows that conceive and calve again. Calving interval should therefore be treated as a censored trait. In this study, survival to the next lactation (SUV) was analyzed jointly with CIV in a multivariate linear model to account for the selection in CIV data. Genetic parameters for first lactation calving interval were estimated with a sire model for Holstein Friesian cows in Ireland. SUV was preadjusted for production within herd-year-season (HYS), while milk yield was included as a third trait in the analysis to account for the large effect it has on both traits. The residual covariance between CIV and SUV was fixed as 3 times the sire covariance within the model, as it was inestimable because of the structure of the data. Breeding values were estimated with various models to test the effect of culling and milk yield. Heritability was 0.04 +/- 0.006 for CIV and 0.01 +/- 0.003 for SUV, while the genetic correlation between them was -0.28 (+/-0.11). The genetic standard deviation was around 4% for SUV and 7 d for CIV. Sire predicted transmitting abilities for progeny tested bulls ranged between -5 and 3% for survival rate and between -4 and 8 d for calving interval. Differences between the best and worst bull varied with model. Including SUV and milk yield as traits in the model reduced the mean and variance of sire predicted transmitting abilities but increased the coefficient of variation by 30% compared with the univariate model. The current model is expected to account for most of the genetic variation in fertility that is possible from calving dates and future extensions, such as the use of linear type trait or additional lactations for predicting survival, appear straightforward. These traits now form part of the national index for selecting dairy bulls in Ireland.     

Consequences of selection for yield traits on calving ease performance

The impact of different breeding goals on the genetic response for calving ease (CE) and yield traits was studied in the Basque Holstein cattle population. The economic value for CE was estimated with a bioeconomic model, using Basque production and market circumstances and taking into account the categorical nature of CE. The economic value for CE was −€18.03/cow per calving interval per liability unit. This value was relatively insensitive to changes in the market price of animals but was more sensitive to changes in the incidence of dystocia. Records from parities between 1995 and 2002 were used for the estimation of genetic parameters for yield (actual milk, fat, and protein yield) and CE using a multivariate model. Linear sire models for yield traits and a threshold sire-maternal grandsire model for CE were used. A Holstein population was simulated to determine the consequences of including CE in the breeding goal. Three selection strategies were considered: 1) selection only on yield traits, 2) selection on yield and direct CE (DCE), and 3) selection on yield, DCE, and maternal CE (MCE). Selection on yield traits only resulted in a slight reduction of dystocia. Selection strategies in which DCE or DCE and MCE were included in the breeding goal did not improve the genetic response for DCE and MCE obtained with the first selection strategy. Genetic responses were also calculated using the 2.5th, 50th, and 97.5th percentiles of posterior densities of genetic correlations between DCE and MCE and yield traits. Because responses in CE were sensitive to deviations in estimates of genetic parameters, the inclusion of CE in the monitoring scheme is recommended. Genetic evaluation of bulls for CE is of considerable value because it provides farmers with the opportunity to use assortative matings of sires with favorable estimated breeding values for DCE to primiparous cows.