Genomic prediction of bull fertility in US Jersey dairy cattle

Service sire has a major effect on reproductive success in dairy cattle. Recent studies have reported accurate predictions for Holstein bull fertility using genomic data. The objective of this study was to assess the feasibility of genomic prediction of sire conception rate (SCR) in US Jersey cattle using alternative predictive models. Data set consisted of 1.5k Jersey bulls with SCR records and 95k SNP covering the entire genome. The analyses included the use of linear and Gaussian kernel-based models fitting either all the SNP or subsets of markers with presumed functional roles, such as SNP significantly associated with SCR or SNP located within or close to annotated genes. Model predictive ability was evaluated using 5-fold cross-validation with 10 replicates. The entire SNP set exhibited predictive correlations around 0.30. Interestingly, either SNP marginally associated with SCR or genic SNP achieved higher predictive abilities than their counterparts using random sets of SNP. Among alternative SNP subsets, Gaussian kernel models fitting significant SNP achieved the best performance with increases in predictive correlation up to 7% compared with the standard whole-genome approach. Notably, the use of a multi-breed reference population including the entire US Holstein SCR data set (11.5k bulls) allowed us to achieve predictive correlations up to 0.315, gaining 8% in accuracy compared with the standard model fitting a pure Jersey reference set. Overall, our findings indicate that genomic prediction of Jersey bull fertility is feasible. The use of Gaussian kernels fitting markers with relevant roles and the inclusion of Holstein records in the training set seem to be promising alternatives to the standard whole-genome approach. These results have the potential to help the dairy industry improve US Jersey sire fertility through accurate genome-guided decisions.     

Short communication: Genetic analysis of dairy bull fertility from field data of Brown Swiss cattle

The aim of this study was to estimate heritability and repeatability of dairy bull fertility in Italian Brown Swiss cattle. Bull fertility indicators were calving per service and nonreturn rate at 56 d after service. Data included 124,206 inseminations carried out by 86 technicians on 28,873 heifers and cows in 1,400 herds. Services were recorded from 1999 to 2008 and were performed with semen from 306 AI Brown Swiss bulls. Data were analyzed with a threshold animal model, which included the fixed effects of parity by class of days in milk of the inseminated cow (age at insemination for heifers), year-season of insemination, and status of the service bull at the time of insemination (progeny testing or proven), and the random effects of herd, technician, additive genetic, and permanent environment of inseminated heifer/cow and service bull, and residual. Also, genetic covariance between heifer/cow and service bull effects was considered in the model. Heritability and repeatability were 0.0079 and 0.0100 for nonreturn rate at 56 d after service, and 0.0153 and 0.0202 for calving per service, respectively. The low estimates obtained in the present study indicate that selection for male fertility using field data is hardly pursuable.     

Predicting bull fertility using genomic data and biological information

The genomic prediction of unobserved genetic values or future phenotypes for complex traits has revolutionized agriculture and human medicine. Fertility traits are undoubtedly complex traits of great economic importance to the dairy industry. Although genomic prediction for improved cow fertility has received much attention, bull fertility largely has been ignored. The first aim of this study was to investigate the feasibility of genomic prediction of sire conception rate (SCR) in US Holstein dairy cattle. Standard genomic prediction often ignores any available information about functional features of the genome, although it is believed that such information can yield more accurate and more persistent predictions. Hence, the second objective was to incorporate prior biological information into predictive models and evaluate their performance. The analyses included the use of kernel-based models fitting either all single nucleotide polymorphisms (SNP; 55K) or only markers with presumed functional roles, such as SNP linked to Gene Ontology or Medical Subject Heading terms related to male fertility, or SNP significantly associated with SCR. Both single- and multikernel models were evaluated using linear and Gaussian kernels. Predictive ability was evaluated in 5-fold cross-validation. The entire set of SNP exhibited predictive correlations around 0.35. Neither Gene Ontology nor Medical Subject Heading gene sets achieved predictive abilities higher than their counterparts using random sets of SNP. Notably, kernel models fitting significant SNP achieved the best performance with increases in accuracy up to 5% compared with the standard whole-genome approach. Models fitting Gaussian kernels outperformed their counterparts fitting linear kernels irrespective of the set of SNP. Overall, our findings suggest that genomic prediction of bull fertility is feasible in dairy cattle. This provides potential for accurate genome-guided decisions, such as early culling of bull calves with low SCR predictions. In addition, exploiting nonlinear effects through the use of Gaussian kernels together with the incorporation of relevant markers seems to be a promising alternative to the standard approach. The inclusion of gene set results into prediction models deserves further research.     

Systematic environmental, direct, and service sire effects on conception rate in artificially inseminated Holstein cows

Result of insemination was verified for 329,314 artificial inseminations by 882 service sires to 97,245 Holstein cows in 1,075 herds between May 1970 and December 1983. Estimates of systematic environmental and genetic components of cow and service sire components of conception rate were obtained preliminary to development of a fertility monitoring system. Conception rate was 2.9% higher in stanchion than loose housed herds and 2.3% higher in grade than registered cows. Fall months were superior to winter months, the greatest difference being 6.1% between October and January. Conception rate increased with herd milk production, decreased with both increased cow age, and increased herd size in mature and old cows. Regions and inseminators within regions were highly variable. Conception may be influenced by semen price; however, week day of insemination and duration of semen storage had no effect. Conception rate decreased for semen by bulls 8 yr and older, was lowest for semen harvested in June, but no season of collection effect was detected. No genetic trends for cow and service sire conception rate were found; heritability and repeatability were .08 and .06, respectively. Genetic correlations between cow and service sire conception rate and these components with first lactation production and semen output measures were all near zero. Therefore, the relationship between sire fertility and daughter fertility is near zero.     

Use of insemination data for joint evaluation of male and female fertility in predominantly seasonal-calving dairy herds

Conception in dairy cattle is influenced by the fertility of the cow and the bull and their interaction. Despite genetic selection for female fertility in many countries, selection for male fertility is largely not practiced. The primary objective of this study was to quantify variation in male and female fertility using insemination data from predominantly seasonal-calving herds. Nonreturn rate (NRR) was derived by coding each insemination as successful (1) or failed (0) based on a minimum of at least 25 d. The NRR was treated as a trait of the bull with semen (male fertility) and the cow that is mated (female fertility). The data (805,463 cows that mated to 5,776 bulls) were used to estimate parameters using either models that only included bulls with mating data or models that fitted the genetic and permanent environmental (PE) effects of bulls and cows simultaneously. We also evaluated whether fitting genetic and PE effects of bulls as one term is better for ranking bulls based on NRR compared with a model that ignored genetic effect. The age of cows that were mated, age of the bulls with semen data, season of mating, breed of cow that mated, inbreeding of cows and bulls, and days from calving to mating date were found to have a significant effect on NRR. Only about 3% of the total variance was explained by the random effects in the model, despite fitting the genetic and PE effects of the bull and cow. The 2 components of fertility (male and fertility) were not correlated. The heritability of male fertility was low (0.001 to 0.008), and that of female fertility was also low (~0.016). The highest heritability estimate for male fertility was obtained from the model that fitted the additive genetic relationship matrix and PE component of the bull as one term. When this model was used to calculate bull solutions, the difference between bulls with at least 100 inseminations was up to 19.2% units (−9.6 to 9.6%). Bull solutions from this model were compared with bull solutions that were predicted fitting bull effects ignoring pedigree. Bull solutions that were obtained considering pedigree had (1) the highest accuracy of prediction when early insemination was used to predict yet-to-be observed insemination data of bulls, and (2) improved model stability (i.e., a higher correlation between bull solutions from 2 randomly split herds) compared with the model which fitted bull with no pedigree. For practical purposes, the model that fitted genetic and PE effect as one term can provide more accurate semen fertility values for bulls than the model without genetic effect. To conclude, insemination data from predominantly seasonal-calving herds can be used to quantify variability between bulls for male fertility, which makes their ranking on NRR feasible. Potentially this information can be used for monitoring bulls and can supplement efforts to improve herd fertility by avoiding or minimizing the use of semen from subfertile bulls.     

Genomic evaluation,breed identification,and discovery of a haplotype affecting fertility for Ayrshire dairy cattle

Genomic evaluations of dairy cattle in the United States have been available for Brown Swiss, Holsteins, and Jerseys since 2009. As of January 2013, 1,023 Ayrshires had genotypes in the North American database. Evaluation accuracy was assessed using genomic evaluations based on 646 bulls with 2008 traditional evaluations to predict daughter performance of up to 180 bulls in 2012. Mean gain in reliability over parent average for all traits was 8.2 percentage points. The highest gains were for protein yield (16.9 percentage points), milk yield (16.6 percentage points), and stature (16.2 percentage points). Twelve single nucleotide polymorphisms were useful for Ayrshire breed determination. Fewer breed-determining SNP were available for Ayrshires than for Holsteins, Jerseys, and Brown Swiss because of the similarity of Ayrshires and Holsteins. A haplotype that affects fertility was identified on chromosome 17 and traces back in the genotyped population to the bull Selwood Betty’s Commander (born in 1953). The haplotype carrier frequency for genotyped Ayrshires was 26.1%. Sire conception rate was decreased by 4.3 ± 2.5 percentage points for carriers of the haplotype as determined by 618 matings of carrier sire by carrier maternal grandsire. Genomic evaluations for Ayrshires were officially implemented in the United States in April 2013.     

Effects of sire fertility and daughter stayability on profitability of sire selection.

Holstein sires (n = 340) with milk, milk fat, semen unit fertility, daughter stayability evaluations, and semen price for 1986 were studied. Effects of variation in sire fertility and daughter stayability on profitability of sire selection using the net present value criterion were estimated. The model estimated expected profit from a cow bred to pregnancy from future production and from cattle disposal and replacement after discounting costs and returns to the time of insemination. Effects of semen sexing and semen unit dilution on profitability to determine optimal breeding strategies for dairy herds were examined. Sire profitability increased with herd average conception rate and sire selection intensity. Daughter stayability had a greater impact on profitability than semen unit fertility when profit maximization was computed under the criterion of breeding a cow to pregnancy. Genetic progress for production was compromised when selecting to maximize profit. Dilution of semen units seems profitable only when semen availability is limited for high demand sires. The use of sexed female semen may only be appropriate when it can generate additional income from the sale of surplus heifers.     

Results of a producer survey regarding crossbreeding on US dairy farms

Comprehensive surveys were sent to 528 US dairy producers who are currently practicing crossbreeding in their herds. Fifty usable surveys were returned, and the resulting data included qualitative responses regarding facilities, milk recording plans, milk pricing, crossbreeding goals, breed selection, advantages, disadvantages, and future plans. Quantitative variables included producer scores on a 1 to 5 scale for questions regarding ability to fit into the free stalls and milking parlor, milk volume, component percentages, involuntary culling rate, conception rate, calving difficulty, calf mortality, and prices for breeding stock, cull cows, market steers, and bull calves. The most common first generation crosses involved Jersey and Brown Swiss bulls mated to Holstein cows, and backcrosses to one of these parental breeds were most common in the next generation. Producers who responded to this survey desired, and indicated that they achieved, improvements in fertility, calving ease, longevity, and component percentages through crossbreeding. Respondents indicated that crosses involving the Jersey and Brown Swiss breeds had a clear advantage in longevity relative to purebred Holsteins, and conception rates for crosses of Jersey or Brown Swiss sires on Holstein cows were similar to the (high) conception rates typically achieved in purebred Jersey matings. Respondents also indicated that milk composition was improved in the crossbred cattle, but producers cited some difficulties in marketing crossbred breeding stock and bull calves, and noted that the lack of uniformity within the milking herd created management challenges. Based on results of this survey, it appears that crossbreeding can improve the health, fertility, longevity, and profitability of commercial dairy cattle. However, further research is needed regarding specific heterosis estimates for functional traits in crosses involving each of the major dairy breeds, and improvements are needed in systems for recording the ancestry and breed composition of crossbred animals.     

Timeliness and effectiveness of progeny testing through artificial insemination

Progeny-test (PT) programs of US artificial-insemination (AI) organizations were examined to determine timeliness of sampling, PT daughter distribution, rate of return of PT bulls to widespread service, and genetic merit of PT bulls compared with AI-proven and natural-service (NS) bulls. Bull age at semen release and at birth and calving of PT daughters was documented by breed (Ayrshire, Brown Swiss, Guernsey, Holstein, Jersey, and Milking Shorthorn) for bulls that entered AI service since 1960. Mean Holstein bull age at semen release (16 mo) changed little over time, but standard deviations (SD) decreased from 4.0 mo during the 1960s to 2.4 mo during the 1990s. Most Holstein bulls (80%) had semen released by 18 mo. Mean age of Holstein bulls at birth and calving of PT daughters during the 1990s was 29 and 56 mo, respectively (a decline of 4 mo from the 1960s); SD decreased from 6 to 3 mo. Bulls of other breeds usually were older at birth and calving of PT daughters, and SD were larger. Mean Holstein bull age when 80% of PT daughters had been born declined from 36 mo during the 1960s to 31 mo during the early 1990s; for other breeds, bulls showed the same trend but at older ages. Mean Holstein bull age when 80% of PT daughters had calved declined from 65 mo during the 1960s to 59 mo during the 1990s; for other breeds, bulls were older. Percentage of herds with PT daughters has increased over time. For Holsteins, herds with five or more usable first-parity records that had PT daughters with usable records increased from 15% during 1965 to 61% during 1998; percentage of herds with from 1 to 19% PT records increased from 11 to 38%, and percentage of herds with >50% PT daughters increased from 1 to 5%. Percentage of Holstein PT bulls returned to AI service declined to about 12% for bulls with PT entry around 1990; for other breeds, 12 to 23% of most recent PT bulls were returned to service. Percentage of milking daughters that had records usable for genetic evaluation that were sired by PT bulls increased steadily from 10 to 18%, whereas percentage of daughters with usable records that were sired by NS bulls declined from 14 to 7%. Milk yield of daughters of AI-proven bulls was 107 to 200 kg greater than for daughters of PT bulls and 366 to 444 kg greater than for daughters of NS bulls for all years. More extensive and rapid sampling and increased selection intensity of PT programs have led to more rapid genetic progress. More extensive use of AI could increase US producer income by millions of dollars annually.     

Genetic parameters for fertility of dairy bulls

Genetic parameters for male fertility and fertility ratings of AI bulls were obtained by analyzing 298,013 service records of cows with successive calving records. Cows were mated to 746 service bulls, which were progeny of 126 sires. The model for variance component estimation accounted for fixed effects of herd-year-seasons, sire of the service bull, age of mates, and random effects of service bull and residual error. Estimates of variances of service bulls and residual error components for bull fertility indicated almost 10% of the phenotypic variation for fertility is among AI bulls. Best linear unbiased prediction of fertility ratings of individual bulls with inclusion of sire and maternal grandsire relationships on these data permitted the evaluation of 886 AI bulls for bull fertility. Heritability for bull fertility computed as twice the regression of son on sire was .158. Differences in fertility ratings of AI bulls ranged from -.29 to .19. Prediction of fertility of young AI bulls and more accurate rating of proven bulls might be useful to the industry.     

Effects of nonadditive genetic interactions, inbreeding, and recessive defects on embryo and fetal loss by seventy days

Lethal recessive genes that cause early embryo loss are difficult to detect. Nonreturn rate at 70 d after first insemination (NR) was evaluated as a trait of the embryo using 1,739,055 first-service records from 1,251 Holstein bulls represented as both service sires and sires of cows. Effects modeled included herd-year-season, parity of cow, sire of cow, service bull, interaction of service bull with sire of cow, and regression on inbreeding of embryo. Variances of service bull and sire of cow were estimated using REML and estimated effects were removed from the data. Interaction variance was estimated from the residuals using the tilde-hat approximation to REML. An additive relationship matrix was used for sire of cow and a dominance relationship matrix for the interaction term. Service bull effects were assumed constant across time and unrelated. For each 10% increase in inbreeding, NR percentage declined by an estimated 1%. A regression of this size could be explained by > 20% of animals carrying defects that cause early embryo loss. Of the total variance, service bull contributed 0.36%; sire of cow, 0.24% (heritability of 1.0%); and interaction, 0.18% (dominance variance of 2.8%). Numbers of records exceeded 500 for 50 bull pair subclasses. Predicted interactions that included effects of inbreeding ranged from − 3.6% to + 2.9%, compared with the mean NR of 56%. The largest negative interactions were not caused by known recessive defects. Complex vertebral malformation generally causes loss of pregnancies later in gestation, and few current bulls carry the gene for deficiency of uridine monophosphate synthase. Further study of the families with largest negative interactions could uncover new recessive defects.     

Application of controlling instruments for improvements in cow sire selection

National estimated breeding values of bulls from 1998 through 2006 from 12 different German artificial insemination (AI) organizations were used to determine the differences in expected and realized selection intensities for cow sire selection, considering the total merit index as well as subindexes for production, conformation, somatic cell count, fertility, and functional herd life. The expected selection intensity was derived from a Gaussian distribution and from the replacement rate describing the percentage of bulls graduated as cow sires from the total amount of progeny-tested young bulls within the AI organization and by birth year. Realized selection intensities for all indexes were derived from the selection differential of cow sires, defined as the deviation of the average index of selected cow sires from the average index of the total number of progeny-tested young bulls. A low replacement rate of cow sires was associated with relatively high realized selection intensities for the total merit, production, and conformation indexes, but was not related to the somatic cell count, fertility, and functional herd life indexes. The controlling value, defined as the ratio of realized to expected selection intensities, indicates the effectiveness of cow sire selection for different traits. Low controlling values (i.e., low realized selection intensities in combination with moderate or high expected selection intensities) suggest improvements in the step of cow sire selection, especially when discussing the total merit index. Analysis of variance revealed significant differences in expected selection intensities, realized selection intensities, and controlling values for the total merit, production, and conformation indexes between AI organizations and birth years of bulls. Artificial insemination organizations applying well-defined breeding policies (e.g., high controlling values for the total merit index) were successful in the national competition when evaluated according to the national top lists for the respective indexes, regardless of the active population size. The suggested method also allows for comparison of the importance of different indexes in selection decisions. Furthermore, controlling values can monitor additional potential in the improvement of cow sire selection with respect to improvement of the genetic level in the whole population. The development of appropriate selection tools or controlling instruments is of increasing concern for monitoring selection policies in the short term as well as for establishing sustainable breeding policies.     

Evaluations for service-sire conception rate for heifer and cow inseminations with conventional and sexed semen

Service-sire conception rate (SCR), a phenotypic fertility evaluation based on conventional (nonsexed) inseminations from parities 1 through 5, was implemented for the United States in August 2008. The SCR model contains the categorical fixed effects of parity for lactations 1 to 5; state-year-month of insemination group; 6 standardized milk yield groups; service number for inseminations 1 to 7; cow age; and herd-year-season-parity-registry status class. Covariate effects for service-sire and mating inbreeding coefficients were linear regressions fit as deviations from the overall mean. Random effects included service-sire age group; AI organization-insemination year group; individual service sire; cow's genetic ability to conceive; cow's permanent environmental effect; and residual. Using insemination data from 2005 through 2009, the SCR procedure was applied separately for nulliparous heifer inseminations with conventional semen (SCRHconv), cow inseminations with conventional semen (SCRCconv), nulliparous heifer inseminations with sexed semen (SCRHsexed), and cow inseminations with sexed semen (SCRCsexed). Holstein and Jersey bulls with ≥300 and ≥200 artificial inseminations, respectively, in ≥10 herds and with ≥100 breedings during the 12 mo before evaluation were examined. The number of bulls evaluated for SCR in January 2010 was 270 Holsteins and 16 Jerseys for SCRHconv, 2,309 Holsteins and 214 Jerseys for SCRCconv, 114 Holsteins and 6 Jerseys for SCRHsexed, and 25 Holsteins and 7 Jerseys for SCRCsexed. The mean SCR for each evaluation category was set to 0; Holstein standard deviations were 2.55% for SCRHconv, 2.21% for SCRCconv, 4.29% for SCRHsexed, and 2.39% for SCRCsexed. The mean Holstein reliabilities were 82, 79, 75, and 73%, respectively. Correlations for Holstein SCR between conventional and sexed semen averaged near zero (−0.21 to 0.18). Predicted correlations between true SCR were −0.27 to 0.24. In contrast, correlations between Holstein heifers and cows were high (0.66 to 0.76), and predicted true correlations averaged near 1.0 (0.82 to 1.03). Correlations for Jerseys were often larger, although based on fewer inseminations and service sires compared with Holsteins. Some rankings for SCR could benefit from combining cow and heifer data but should be kept separate for conventional and sexed semen inseminations.     

Effect of synchronization and semen sorting on artificial insemination bull fertility

Field data were collected over a period of 2 yr by artificial insemination technicians for the purpose of evaluating differences among bulls in their fertility when synchronization and semen sorting were involved. First, main effects of synchronization and semen sorting were found to reduce bull fertility by 1.5 and 12.7%, respectively. Second, the interaction of both factors with bull fertility significantly enhanced the evaluation models. Differences between 2 sets of adjusted conception rates for synchronized and nonsynchronized services ranged from 0.5 to 2.9%, whereas differences between 2 sets of adjusted conception rates for sorted and conventional semen ranged from −1.8 to 15.2%. This implies that using conventional fertility models that ignore these effects may not be sufficiently accurate in situations where synchronization or semen sorting are involved. Accounting for synchronization and especially for semen sorting to evaluate bulls on their fertility and the production of separate sets of conception rates under each situation are essential.     

Genetic parameters of semen quality traits and genetic correlations with service sire nonreturn rate in Nordic Holstein bulls

Despite the importance of the quality of semen used in artificial insemination to the reproductive success of dairy herds, few studies have estimated the extent of genetic variability in semen quality traits. Even fewer studies have quantified the correlation between semen quality traits and male fertility. In this study, records of 100,058 ejaculates collected from 2,885 Nordic Holstein bulls were used to estimate genetic parameters for semen quality traits, including pre- and postcryopreservation semen concentration, sperm motility and viability, ejaculate volume, and number of doses per ejaculate. Additionally, summary data on nonreturn rate (NRR) obtained from insemination of some of the bulls (n = 2,142) to cows in different parities (heifers and parities 1–3 or more) were used to estimate correlations between the semen quality traits and service sire NRR. In the study, low to moderate heritability (0.06–0.45) was estimated for semen quality traits, indicating the possibility of improving these traits through selective breeding. The study also showed moderate to high genetic and phenotypic correlations between service sire NRR and some of the semen quality traits, including sperm viability pre- and postcryopreservation, motility postcryopreservation, and sperm concentration precryopreservation, indicating the predictive values of these traits for service sire NRR. The positive moderate to high genetic correlations between semen quality and service sire NRR traits also indicated that selection for semen quality traits might be favorable for improving service sire NRR.     

Genetic analysis of fertility in the Italian Brown Swiss population using different models and trait definitions

The aim of this study was to estimate genetic parameters for fertility and production traits in the Brown Swiss population reared in the Alps (Bolzano-Bozen province, Italy). Fertility indicators were interval from parturition to first service, interval from first service to conception (iFC), and interval from parturition to conception, either expressed as days and as number of potential 21-d estrus cycles (cPF, cFC, and cPC, respectively); number of inseminations to conception; conception rate at first service; and non-return rate at 56 d post-first service. Production traits were peak milk yield, lactation milk yield, lactation length, average lactation protein percentage, and average lactation fat percentage. Data included 71,556 lactations (parities 1 to 9) from 29,582 cows reared in 1,835 herds. Animals calved from 1999 to 2007 and were progeny of 491 artificial insemination bulls. Gibbs sampling and Metropolis algorithms were implemented to obtain (co)variance components using both univariate and bivariate censored threshold and linear sire models. All of the analyses accounted for parity and year-month of calving as fixed effects, and herd, permanent environmental cow, additive genetic sire, and residual as random effects. Heritability estimates for fertility traits ranged from 0.030 (iFC) to 0.071 (cPC). Strong genetic correlations were estimated between interval from parturition to first service and cPF (0.97), and interval from parturition to conception and cPC (0.96). The estimate of heritability for cFC (0.055) was approximately double compared with iFC (0.030), suggesting that measuring the elapsed time between first service and conception in days or potential cycles is not equivalent; this was also confirmed by the genetic correlation between iFC and cFC, which was strong (0.85), but more distant from unity than the other 2 pairs of fertility traits. Genetic correlations between number of inseminations to conception, conception rate at first service, non-return rate at 56 d post-first service, cPF, cFC, and cPC ranged from 0.07 to 0.82 as absolute value. Fertility was unfavorably correlated with production; estimates ranged from −0.26 (cPC with protein percentage) to 0.76 (cPC with lactation length), confirming the genetic antagonism between reproductive efficiency and milk production. Although heritability for fertility is low, the contemporary inclusion of several reproductive traits in a merit index would help to improve performance of dairy cows.     

Selection of Young and Proven Holstein Artificial Insemination Sires to Maximize Profits from Milk

Net present values of genetic investments in young and proven artificial insemination Holstein sires were calculated to determine profit-maximizing proportions of these genetic resources. The sensitivity of profit from young sires was evaluated by varying semen cost from 0 to $5 per unit and comparing average net present values of young and proven sires. Data for proven sires were retail semen prices and Predicted Differences (1974 base) for yields of milk and fat of 449 bulls available for purchase after the July 1983 USDA sire summary. Data for young sires concurrently used in fall 1983 were Predicted Differences of sires and maternal grandsires of 260 bulls for random sampling and 32 bulls-in-waiting from four artificial insemination organizations. Net present values of milk income were calculated using a real interest rate of 3% with alternative conception rates to first service (30 and 50%) and number of generations (one and infinite) of descendants in the planning horizon.Relative rankings of young and proven bulls were same for each conception rate and planning horizon; thus, only net present values for 50% conception rate and one generation planning horizon are reported. Average profitability of young sires for sampling was equal to average profit from proven bulls when young sire semen cost $5/unit and was $36 (.7 standard deviation) more profitable than average proven sires when young sire semen cost was nil. Mean net present value of young sires for sampling ranked at 42nd percentile of proven sires when semen cost $5/unit or 69th percentile of proven sires when semen cost was nil. Therefore, profit-maximizing dairy producers have no economic incentive to mate cows to random young sires when free to select and obtain semen from at least the top 30% of proven bulls at current prices. For semen cost of $5/unit, there was incentive to replace with young sires up to 40% of the least profitable proven bulls. Decreases (increases) in cost of semen of young sires relative to the less profitable proven bulls would increase (decrease) the proportion of proven sires that should be replaced by random young sires.     

Effects of climatic and management factors on conception rate of dairy cattle in subtropical environment

Breeding records, representing 12,038 inseminations at Bassett's Dairy Farm (Monticello, FL), were analyzed to document effects of environmental and management factors on fertility of dairy cattle from January 1, 1975 to December 31, 1977. Conception rates of lactating cows decreased sharply when maximum air temperature on day after insemination exceeded 30 degrees C. In contrast, conception rates for heifers did not decline until 35 degrees C. Virgin heifers had higher conception rates for all services (50%) than lactating cows (34%) and suffered only slight depression of fertility during summer months. Heifers required 1.5 services per conception compared with 2.3 for lactating cows. Relationship between conception rate and rainfall on day after insemination was negative and curvilinear. Jerseys had higher conception rates (45%) than Holstein (39%) and Brown Swiss (41%). Services per conception were 1.7, 2.0, and 1.9. Substantial decreases of fertility were associated with advancing service number. Estrous status (standing; positive heat detection patch; mounting activity), inseminator, and year of service were related to variation of conception rate. Seasonal effects on fertility of lactating cows were marked. Thus, environmental management of the postpartum cow during hot summer months is warranted to maximize fertility.     

Analysis of reproductive performance of lactating cows on large dairy farms using machine learning algorithms

The fertility of lactating dairy cows is economically important, but the mean reproductive performance of Holstein cows has declined during the past 3 decades. Traits such as first-service conception rate and pregnancy status at 150 d in milk (DIM) are influenced by numerous explanatory factors common to specific farms or individual cows on these farms. Machine learning algorithms offer great flexibility with regard to problems of multicollinearity, missing values, or complex interactions among variables. The objective of this study was to use machine learning algorithms to identify factors affecting the reproductive performance of lactating Holstein cows on large dairy farms. This study used data from farms in the Alta Genetics Advantage progeny-testing program. Production and reproductive records from 153 farms were obtained from on-farm DHI-Plus, Dairy Comp 305, or PCDART herd management software. A survey regarding management, facilities, labor, nutrition, reproduction, genetic selection, climate, and milk production was completed by managers of 103 farms; body condition scores were measured by a single evaluator on 63 farms; and temperature data were obtained from nearby weather stations. The edited data consisted of 31,076 lactation records, 14,804 cows, and 317 explanatory variables for first-service conception rate and 17,587 lactation records, 9,516 cows, and 341 explanatory variables for pregnancy status at 150 DIM. An alternating decision tree algorithm for first-service conception rate classified 75.6% of records correctly and identified the frequency of hoof trimming maintenance, type of bedding in the dry cow pen, type of cow restraint system, and duration of the voluntary waiting period as key explanatory variables. An alternating decision tree algorithm for pregnancy status at 150 DIM classified 71.4% of records correctly and identified bunk space per cow, temperature for thawing semen, percentage of cows with low body condition scores, number of cows in the maternity pen, strategy for using a clean-up bull, and milk yield at first service as key factors.     

A field study on fertility and purity of sex-sorted cattle sperm

The study assessed the fertility and purity of sexed semen used for inseminating Holstein-Friesian heifers in commercial dairy herds. Sex-sorted semen from 4 proven Holstein-Friesian bulls and available under commercial conditions was used on nulliparous Holstein heifers reared on 61 dairy farms of northern Italy. Data from 536 artificial inseminations with pregnancy diagnosis and 258 calvings were analyzed using the logistic regression procedure. The effects of year and season of insemination or calving, age at insemination or calving, heifer inbreeding, and the sperm dose used for insemination on the probability of a positive pregnancy diagnosis or of the birth of a female calf, respectively, were studied. The overall pregnancy rate for sexed semen was 51% and was affected by year of insemination and bull. Heifers inseminated with sexed semen from 2 bulls had lower pregnancy rates than heifers inseminated with sexed semen from other bulls. Purity of the sexed sperm, based on the proportion of female calves, was 87% and this percentage was not affected by explanatory variables included in the logistic regression. The results demonstrate that bulls differ in terms of fertility of their sexed semen. Careful selection of the insemination sires used for sorted semen is advisable for avoiding low fertility inseminations.