Using multiple objective programming in a dairy cow breeding program

Multiple-objective programming was used to examine the effects various objectives had on the optimal portfolio of sires chosen for a given breeding problem in a Jersey cow dairy herd. It was assumed that the dairy producer had the following three objectives in the breeding decision: to maximize Net Merit, to minimize inbreeding, and to minimize total expenditure on semen. Integer programming models of these three single objectives were estimated to provide the ideal and anti-ideal values for use in several multiple-objective programming models. The integer multiple-objective models examined the interactions and costs of tradeoffs between the three single objectives in a model framework designed to minimize the maximum deviations from the single-objective optima. A model with equal weights on each objective resulted in a decrease of 3% in average inbreeding but also reduced average Net Merit by $170 from the single-objective optima. A second model, where the weight on Net Merit was twice that of inbreeding and semen cost, decreased Net Merit by $100 and reduced inbreeding by 2% from the single objective optima. The results of the multiple-objective programming models show that reducing the inbreeding coefficient for a group of sires purchased will decrease the Net Merit. However, the results generated also demonstrate that the weights placed on each objective by the dairy producer substantially affect the optimal levels of each objective within the multiple-objective model.     

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.     

Use of computerized mate selection programs to control inbreeding of Holstein and Jersey cattle in the next generation

The expected role of computerized mate selection programs with regard to inbreeding and lifetime profitability of Holstein and Jersey cattle was examined using data from 25 large registered herds of each breed. Sire selection and mate allocation were carried out using linear programming with the following objectives: 1) minimum inbreeding, 2) maximum net merit subject to a fixed inbreeding threshold, and 3) maximum expected lifetime profit after adjustment for inbreeding depression. Inbreeding of actual matings was similar to inbreeding from random matings, indicating that current inbreeding avoidance programs in these herds are ineffective. Inbreeding was reduced by 1.6 and 1.9% in Holsteins and Jerseys, respectively, when a mate allocation program was applied with service sires and usage levels fixed at the actual values. Benefits of mate selection programs increased when both sire selection and mate pair allocation were considered. Maximization of mean net merit with inbreeding restricted to a fixed level (5% in Holsteins and 8% in Jerseys) led to decreases in inbreeding of 0.9 and 1.4% and increases in lifetime profit of $16.66 and $26.86 in Holsteins and Jerseys, respectively, relative to programs that ignored inbreeding. Maximization of mean expected lifetime profit after adjustment for inbreeding depression decreased inbreeding by 1.8 and 2.8% and increased lifetime profit by $37.37 and $59.77 in Holsteins and Jerseys, respectively. Inbreeding coefficients estimated with pedigree traced to 1985 were inadequate predictors of inbreeding coefficients estimated with pedigrees traced to 1960. Mate selection programs cannot function optimally unless extensive historical pedigree data are available, particularly for service sires. Computerized mate selection programs can reduce inbreeding in the next generation, which will lead to an increase in farm profitability. However, if genetic diversity is to be maintained in the long term, procedures for selecting parents of AI sires must also be considered.     

Evaluating sire selection practices using lifetime net income functions

Dairy farmers do not take full advantage of opportunities available for genetic improvement through use of artificial insemination, perhaps because economic advantages of good sire selection may not be fully recognized or understood. This study was undertaken to document differences between use of AI and non-AI bulls and to develop prediction equations to compare lifetime economic merit of future progeny from alternative sire selection policies. We describe the use of two methods of measuring lifetime economic merit, with and without adjustment for opportunity cost of a postponed replacement. Comparison of lifetime relative net income adjusted for opportunity cost on groups of cows sired by different kinds of bulls showed that daughters of proven AI bulls generated $148 and $120 more lifetime net income under fluid and manufactured milk market conditions than daughters of non-AI bulls. Daughters of proven AI bulls produced $60 more than daughters of AI young sires in progeny testing programs at the time of daughter conception. We developed prediction equations from combinations of genetic evaluations for production, productive life, SCS, and linear type traits on sires to predict lifetime relative net income of progeny produced from alternative sire selection strategies. Prediction equations explained 14 to 18% of variation in relative net income (not adjusted for opportunity cost), but herd and year of first freshening accounted for considerably more variation than did genetic evaluations on the sire of the cow. Finally, two independent data sets were used to develop and test predictions of lifetime relative net income adjusted for opportunity cost using genetic evaluations based on the eight traits included in the Merit indexes for the sire of each cow. Prediction equations from odd numbered herds were used to predict lifetime economic merit in even numbered herds and vice versa. Coefficients of determination ranged from 0.088 to 0.103 and averaged 0.004 higher than prediction equations with Net or Fluid Merit. Accuracy of predictions showed that Net and Fluid Merit were robust and useful indexes that accurately identified bulls whose daughters generated highest lifetime economic merit.     

Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information

In this study, 3 strategies for controlling progeny inbreeding in mating plans were compared. The strategies used information from pedigree inbreeding coefficients, genomic relationships, or shared runs of homozygosity. The strategies were compared for the reduction in genetic gain and progeny inbreeding that would be expected from selected matings, and for the decrease of homozygosity of deleterious recessive alleles. Using real pedigree, genotype [43,115 single nucleotide polymorphism (SNP) markers], and estimated breeding value data from Holstein cattle, mating plans were derived for herds of 300 cows with 20 sires available for mating, replicated 50 times. Each of the 300 individuals allocated as dams were matched to 1 of 20 sires to maximize genetic merit minus the penalty for estimated progeny inbreeding, and given the restriction that the sire could not be mated to more than 10% of the cows. The strategy that used a genomic relationship matrix (GRM) was the most effective in reducing average progeny inbreeding; this strategy also resulted in fewer homozygous SNP out of 1,000 low-frequency SNP compared with the strategy using pedigree information. In the future, large numbers of cattle may be genotyped for low-density SNP panels. A GRM constructed using 3,123 SNP produced results similar to a GRM constructed using the full 43,115 SNP. These results demonstrate that using GRM information, a 1% reduction in progeny inbreeding (valued at around $5 per cow) can be made with very little compromise in the overall breeding objective. These results and the availability of low-cost, low-density genotyping make it attractive to apply mating plans that use genomic information in commercial dairy herds.     

Effects of Planning Horizon and Conception Rate on Profit-Maximizing Selection of Artificial Insemination Sires

Net present values of semen were calculated for alternative generations of descendants in the planning horizon, conception rate to first service, and selection policy for milk income and type score for retail semen prices and real interest 3%. Data were active Holstein and Jersey artificial insemination sires whose semen was available for purchase after the January 1984 USDA Sire Summary. Objectives were to determine effects of length of planning horizon and conception rate on rankings of sires for profit.Two generations (daughter and granddaughter) for Holstein and one generation of descendants for Jersey sires were sufficiently long planning periods, because sires ranked nearly the same (rank correlation >.99) with longer horizons. Misspecification of conception rate (largest cost), planning horizon, or both reduced profitability of sire selection by .4 to 1.2 standard deviations of net present value. Because of modest semen prices of most profitable sires, the largest cost of inefficient sire selection by inaccurate specification of conception rate and planning horizon is the opportunity loss of future net income. Interaction of optimal sire selection with herd management is analogous to interaction of genotype by environment for profit.     

Mating programs including genomic relationships and dominance effects

Computerized mating programs using genomic information are needed by breed associations, artificial-insemination organizations, and on-farm software providers, but such software is already challenged by the size of the relationship matrix. As of October 2012, over 230,000 Holsteins obtained genomic predictions in North America. Efficient methods of storing, computing, and transferring genomic relationships from a central database to customers via a web query were developed for approximately 165,000 genotyped cows and the subset of 1,518 bulls whose semen was available for purchase at that time. This study, utilizing 3 breeds, investigated differences in sire selection, methods of assigning mates, the use of genomic or pedigree relationships, and the effect of including dominance effects in a mating program. For both Jerseys and Holsteins, selection and mating programs were tested using the top 50 marketed bulls for genomic and traditional lifetime net merit as well as 50 randomly selected bulls. The 500 youngest genotyped cows in the largest herd in each breed were assigned mates of the same breed with limits of 10 cows per bull and 1 bull per cow (only 79 cows and 8 bulls for Brown Swiss). A dominance variance of 4.1 and 3.7% was estimated for Holsteins and Jerseys using 45,187 markers and management group deviation for milk yield. Sire selection was identified as the most important component of improving expected progeny value, followed by managing inbreeding and then inclusion of dominance. The respective percentage gains for milk yield in this study were 64, 27, and 9, for Holsteins and 73, 20, and 7 for Jerseys. The linear programming method of assigning a mate outperformed sequential selection by reducing genomic or pedigree inbreeding by 0.86 to 1.06 and 0.93 to 1.41, respectively. Use of genomic over pedigree relationship information provided a larger decrease in expected progeny inbreeding and thus greater expected progeny value. Based on lifetime net merit, the economic value of using genomic relationships was >$3 million per year for Holsteins when applied to all genotyped females, assuming that each will provide 1 replacement. Previous mating programs required transferring only a pedigree file to customers, but better service is possible by incorporating genomic relationships, more precise mate allocation, and dominance effects. Economic benefits will continue to grow as more females are genotyped.     

A mating advice system in dairy cattle incorporating genomic information

This study investigated the effects of alternative mating programs that incorporate genomic information on expected progeny herd performance and inbreeding, as well as methods to include un-genotyped animals in such mating programs. A total of 54,535 Holstein-Friesian cattle with imputed high-density genotypes (547,650 SNP after edits) were available. First, to quantify the accuracy of imputing un-genotyped animals (often an issue in populations), a sub-population of 729 genotyped animals had their genotypes masked, and their allele dosages were imputed, using linear regression exploiting information on genotyped relatives. The reference population for imputation included all genotyped animals, excluding the 729 selected animals and their sires, dams, and grandsires, and had either (1) their sires' genotypes, (2) their dams' genotypes (3) both their sires' and their dams' genotypes, or (4) both their sires' and maternal grandsires' genotypes introduced into the reference population. The correlations between true genotypes and the imputed allele dosages ranged from 0.58 (sire only) to 0.68 (both sire and dam). A herd of 100 cows was then simulated (1,000 replicates) from the sub-population of 729 imputed animals. The top 10 bulls from the genotyped population, based on their total genetic merit index (TMI) were selected to be used as sires. Three mating allotment methods were investigated: (1) random mating, (2) sequential mating based on maximizing only the expected TMI of the progeny, and (3) linear programming to maximize a generated index constructed to maximize genetic merit and minimize expected progeny inbreeding as well as intra- and inter-progeny variability in genetic merit. Relationships among candidate parents were calculated using either the pedigree relationship matrix or the genomic relationship matrix; the latter was constructed using either the true genotypes of both parents or the true genotypes of the sire plus the imputed allele dosages of the dam. Using the genomic co-ancestry estimates resulted in lower average herd expected genomic inbreeding levels compared with using the pedigree-based co-ancestry estimates. Additionally, if the dams were not genotyped, using their imputed allele dosages also resulted in lower average herd expected inbreeding levels compared with using the pedigree co-ancestry estimates. The inter-progeny coefficient of variation for selected traits, milk and fertility, estimated breeding values were reduced by 12 to 65% using the linear programing method compared with sequential mating.     

Controlling inbreeding by constraining the average relationship between parents of young bulls entering AI progeny test programs

In breeding is known to impair the health, fertility, and productivity of dairy cattle and other livestock species. Mating programs can address inbreeding concerns on the farm, at least in the short term, but long-term control of inbreeding in a dairy population requires consideration of relationships between young bulls entering AI progeny test programs. The present study discusses an application of optimal contribution methodology to selection of young AI bulls in the five major US dairy breeds. Elite cows and active AI sires from the Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey breeds were considered as potential bull parents. Genetic merit of selected sires and dams was maximized subject to various constraints on the mean additive genetic relationship within the selected group. Relationships between selected parents can be reduced substantially relative to current levels, but the corresponding reduction in genetic merit may be large. This loss in genetic merit occurs due to lower selection intensity, although it is mainly a reflection of a larger number of bull parents (with progeny more evenly distributed among these parents), rather than selection of genetically inferior "outcross" parents that wouldn't otherwise have been considered. Selected parents were generally older and slightly less inbred than those that would have been chosen had inbreeding been ignored. Although severe restrictions on relationships can be costly, in terms of lost genetic progress, it appears that moderate constraints can keep relationships at a manageable level without a significant loss in genetic merit. Cooperation between breed associations and several competing AI companies may be required to facilitate implementation of this methodology in dispersed populations, but if this can be accomplished, prospects for achieving a balance between inbreeding and selection seem positive.     

Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves on commercial dairy farms

The objective of this study was to quantify the gains in genetic potential of replacement females that could be achieved by using genomic testing to facilitate selection and culling decisions on commercial dairy farms. Data were simulated for 100 commercial dairy herds, each with 1,850 cows, heifers, and calves. Parameters of the simulation were based on the US Holstein population, and assumed reliabilities of traditional and genomic predictions matched reliabilities of animals that have been genotyped to date. Selection of the top 10, 20, 30, …, 90% of animals within each age group was based on parent averages and predicted transmitting abilities with or without genomic testing of all animals or subsets of animals that had been presorted by traditional predictions. Average gains in lifetime net merit breeding value of selected females due to genomic testing, minus prorated costs of genotyping the animals and their unselected contemporaries, ranged from $28 (top 90% selected) to $259 (top 20% selected) for heifer calves with no pedigrees, $14 (top 90% selected) to $121 (top 10% selected) for heifer calves with known sires, and $7 (top 90% selected) to $87 (top 20% selected) for heifer calves with full pedigrees. In most cases, gains in genetic merit of selected heifer calves far exceeded prorated genotyping costs, and gains were greater for animals with missing or incomplete pedigree information. Gains in genetic merit due to genomic testing were smaller for lactating cows that had phenotypic records, and in many cases, these gains barely exceeded or failed to exceed genotyping costs. Strategies based on selective genotyping of the top, middle, or bottom 50% of animals after presorting by traditional parent averages or predicted transmitting abilities were cost effective, particularly when pedigrees or phenotypes were available and a relatively small proportion of animals were to be selected or culled. Based on these results, it appears that routine genotyping of heifer calves or yearling heifers can be a cost-effective strategy for enhancing the genetic level of replacement females on commercial dairy farms. Increasing the accuracy of predicted breeding values for young females with genomic testing might lead to synergies with other management tools and strategies, such as propagating genetically superior females using advanced reproductive technologies or selling excess females that were generated by the use of sex-enhanced semen.     

Factors affecting economics of using sexed semen in dairy cattle

The use of sexed semen in the dairy industry has grown rapidly. However, high costs and low fertility have limited the use of this potentially valuable tool. This study used simulation to evaluate 160,000 combinations of key variables in 3 spheres of influence related to profit feasibility: (1) market (e.g., milk and calf prices), (2) dairy farm management (e.g., conception rates), and (3) technology (e.g., accuracy of sexing). These influential variables were used to determine the most favorable circumstances in which managers or technicians can effect change. Three distinct scenarios were created to model 3 initiatives that a producer might take with sexed semen: (1) using sexed semen on heifers, (2) using sexed semen on heifers and a fraction of the genetically superior cows, and (3) using sexed semen on heifers and a fraction of the genetically superior cows, and breeding all other cows with beef semen. Due to the large number of management, market, and technology combinations, a response surface and interpretive graphs were created to map the scope of influence for the key variables. Technology variables such as the added cost of sexed semen had relatively little effect on profitability, defined as net present value gain per cow, whereas management variables such as conception rate had a significant effect. Milk price had relatively little effect within each scenario, but was important across scenarios. Profitability was very sensitive to the price of dairy heifer calves, relative to beef and dairy bull calves. Scenarios 1 and 2 added about $50 to $75 per cow in net present value, which ranged from $0 to $200 and from $100 to $300, respectively. Scenario 3 usually was not profitable, primarily because fewer excess dairy replacement heifers were available for sale. Dairy heifer price proved to be the most influential variable, regardless of scenario.     

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.     

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls

Genomic selection has the potential to revolutionize dairy cattle breeding because young animals can be accurately selected as parents, leading to a much shorter generation interval and higher rates of genetic gain. The aims of this study were to assess the effects of genomic selection and reduction of the generation interval on the rate of genetic gain and rate of inbreeding. Furthermore, the merit of proven bulls relative to young bulls was studied. This is important for breeding organizations as it determines the relative importance of progeny testing. A closed nucleus breeding scheme was simulated in which 1,000 males and 1,000 females were born annually, 200 bulls were progeny tested, and 20 sires and 200 dams were selected to produce the next generation. In the “proven” (PROV) scenario, only cows with own performance records and progeny-tested bulls were selected as parents. The proportion of the genetic variance that was explained by simulated marker information (M) was varied from 0 to 100%. When M increased from 0 to 100%, the rate of genetic gain increased from 0.238 to 0.309 genetic standard deviations (σ) per year (+30%), whereas the rate of inbreeding reduced from 1.00 to 0.42% per generation. Alternatively, when young cows and bulls were selected as parents (YNG scenario), the rate of genetic gain for M = 0% was 0.292 σ/yr but the corresponding rate of inbreeding increased substantially to 3.15% per generation. A realistic genomic selection scheme (YNG with M = 40%) gave 108% higher rate of genetic gain (0.495 σ/yr) and approximately the same rate of inbreeding per generation as the conventional system without genomic selection (PROV with M = 0%). The rate of inbreeding per year, however, increased from 0.18 to 0.52% because the generation interval in the YNG scheme was much shorter. Progeny-testing fewer bulls reduced the rate of genetic gain and increased the rate of inbreeding for PROV, but had negligible effects for YNG because almost all sires were young bulls. In scenario YNG with M = 40%, the best young bulls were superior to the best proven bulls by 1.27 σ difference in genomic estimated breeding value. This superiority increased even further when fewer bulls were progeny tested. This stochastic simulation study shows that genomic selection in combination with a severe reduction in the generation interval can double the rate of genetic gain at the same rate of inbreeding per generation, but with a higher rate of inbreeding per year. The number of progeny-tested bulls can be greatly reduced, although this will slightly affect the quality of the proven bull team. Therefore, it is important for breeding organizations to predict the future demand for proven bull semen in light of the increasing superiority of young bulls.     

Economic and genetic performance of various combinations of in vitro-produced embryo transfers and artificial insemination in a dairy herd

The objective of this study was to find the optimal proportions of pregnancies from an in vitro-produced embryo transfer (IVP-ET) system and artificial insemination (AI) so that profitability is maximized over a range of prices for embryos and surplus dairy heifer calves. An existing stochastic, dynamic dairy model with genetic merits of 12 traits was adapted for scenarios where 0 to 100% of the eligible females in the herd were impregnated, in increments of 10%, using IVP-ET (ET0 to ET100, 11 scenarios). Oocytes were collected from the top donors selected for the trait lifetime net merit (NM$) and fertilized with sexed semen to produce IVP embryos. Due to their greater conception rates, first ranked were eligible heifer recipients based on lowest number of unsuccessful inseminations or embryo transfers, and then on age. Next, eligible cow recipients were ranked based on the greatest average estimated breeding values (EBV) of the traits cow conception rate and daughter pregnancy rate. Animals that were not recipients of IVP embryos received conventional semen through AI, except that the top 50% of heifers ranked for EBV of NM$ were inseminated with sexed semen for the first 2 AI. The economically optimal proportions of IVP-ET were determined using sensitivity analysis performed for 24 price sets involving 6 different selling prices of surplus dairy heifer calves at approximately 105 d of age and 4 different prices of IVP embryos. The model was run for 15 yr after the start of the IVP-ET program for each scenario. The mean ± standard error of true breeding values of NM$ of all cows in the herd in yr 15 was greater by $603 ± 2 per cow per year for ET100 when compared with ET0. The optimal proportion of IVP-ET ranged from ET100 (for surplus dairy heifer calves sold for ≥$300 along with an additional premium based on their EBV of NM$ and a ≤$100 embryo price) to as low as ET0 (surplus dairy heifer calves sold at $300 with a $200 embryo price). For the default assumptions, the profit/cow in yr 15 was greater by $337, $215, $116, and $69 compared with ET0 when embryo prices were $50, $100, $150, and $200. The optimal use of IVP-ET was 100, 100, 62, and 36% of all breedings for these embryo prices, respectively. At the input price of $165 for an IVP embryo, the difference in the net present value of yr 15 profit between ET40 (optimal scenario) and ET0 was $33 per cow. In conclusion, some use of IVP-ET was profitable for a wide range of IVP-ET prices and values of surplus dairy heifer calves.     

Ranking Dairy Sires by a Linear Programming Dairy Farm Model

Dairy sires were ranked for overall merit by an average daughter's contribution to farm net profit. Biological characteristics of sires and economic factors of a dairy farm were linked by linear programming. Availability and constraints of resources were in the model. Average daughter's returns over variable costs attributable to sire proofs for several traits was the measure of sire's net merit. The index of total economic merit for sires was the amount of change of net profit by milking progeny of different sires. Ranking considered sire's contribution to milk yield and feed intake of daughters caused by variations of proofs for milk, fat percent, and size, sire's nonreturn rate, veal calf sales of the offspring, and labor costs of slow versus fast milking daughters. Size of quota for daily milk shipments, cow housing capacity, labor for milking, and milk tank capacity were critical in determining ranking and forced greater emphasis on traits other than milk yield. Correlations between sire ranking on returns over variable costs and sire proofs were highest for milk and significant for fat percent, milking speed, size, and nonreturn rate. These traits had high standard partial correlations with and explained most of the variation of the index of total economic merit. This method aims at maximizing farm profits and may be applied to rank dairy sires on a national basis or to select sires for specific dairy farm operations. Production dollar index ratings on the same sires were closely correlated (?.87 to ?.96) with profit index ranking but are potentially misleading if constraints exist that limit maximum milk output per farm.     

Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model

Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations.     

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.     

Breakeven costs for embryo transfer in a commercial dairy herd

Differences in Estimated Breeding Values expressed in dollars were compared by simulation of two, 100-cow, closed herds. One herd practiced normal intensity of female selection. The other herd generated various herd replacements by embryo transfer by varying 1) selection rate of embryo transfer dams and 2) numbers of daughters per dam from which embryos were transferred, while varying the merit of mates of embryo transfer dams. Estimated Breeding Value dollars were compounded each generation and regressed to remove age adjustments and added feed and health costs. Beginning values in both herds included a standard deviation of 55 Cow Index dollars, herd average of -23 Cow Index dollars, and a 120 Predicted Difference dollars for mates of dams not embryo transferred. Average merit of all sires used increased $12 per year. Herd calving rate (.70), proportion females (.5), calf loss (.15), and heifer survival rate (.83) were used. Breakeven cost per embryo transfer cow entering the milking herd was computed by Net Present Value analysis using a 10% discount rate over 10 and 20 yr. Breakeven cost or the maximum expense that would allow a 10% return on the expenditure ranged from $135 to $510 per surviving cow, $24 to $125 per transfer, $47 to $178 per pregnancy, and $81 to $357 per female calf born. As the number of replacements resulting from embryo transfer increased, breakeven cost per embryo transfer cow decreased due to diminishing return.     

A comparison of dairy cattle breeding designs that use genomic selection

Different dairy cattle breeding schemes were compared using stochastic simulations, in which the accuracy of the genomic breeding values was dependent on the structure of the breeding scheme, through the availability of new genotyped animals with phenotypic information. Most studies that predict the gain by implementing genomic selection apply a deterministic approach that requires assumptions about the accuracy of the genomic breeding values. The achieved genetic gain, when genomic selection was the only selection method to directly identify elite sires for widespread use and progeny testing was omitted, was compared with using genomic selection for preselection of young bulls for progeny testing and to a conventional progeny test scheme. The rate of inbreeding could be reduced by selecting more sires every year. Selecting 20 sires directly on their genomic breeding values gave a higher genetic gain than any progeny testing scheme, with the same rate of inbreeding as the schemes that used genomic selection for preselection of bulls before progeny testing. The genomic selection breeding schemes could reduce the rate of inbreeding and still increase genetic gain, compared with the conventional breeding scheme. Since progeny testing is expensive, the breeding scheme omitting the progeny test will be the cheapest one. Keeping the progeny test and use of genomic selection for preselection still has some advantages. It gives higher accuracy of breeding values and does not require a complete restructuring of the breeding program. Comparing at the same rate of inbreeding, using genomic selection for elite sire selection only gives a 13% increase in genetic gain, compared with using genomic selection for preselection. One way to reduce the costs of the scheme where genomic selection was used for preselection is to reduce the number of progeny tested bulls. This was here achieved without getting lower genetic gain or a higher rate of inbreeding.     

Comparison of gene editing versus conventional breeding to introgress the POLLED allele into the US dairy cattle population

Disbudding and dehorning are commonly used cattle management practices to protect animals and humans from injury. They are unpleasant, costly processes subject to increased public scrutiny as an animal welfare issue. Horns are a recessively inherited trait, so one option to eliminate dehorning is to breed for polled (hornlessness). However, due to the low genetic merit and scarcity of polled dairy sires, this approach has not been widely adopted. In March 2018, only 3 Holstein and 0 Jersey active homozygous polled sires were registered with the National Association of Animal Breeders. Alternatively, gene editing to produce high-genetic-merit polled sires has been proposed. To further explore this concept, introgression of the POLLED allele into both the US Holstein and Jersey cattle populations via conventional breeding or gene editing (top 1% of bulls/year) was simulated for 3 polled mating schemes and compared with baseline selection on lifetime net merit (NM$) alone, over the course of 20 yr. Scenarios were replicated 10 times and the changes in HORNED allele frequency, inbreeding, genetic gain (NM$), and number of unique sires used were calculated. Gene editing decreased the frequency of the HORNED allele to <0.1 after 20 yr, which was as fast or faster than conventional breeding for both breeds. In the mating scheme that required the use of only existing homozygous polled sires, inbreeding reached 17% (Holstein) and 14% (Jersey), compared with less than 7% in the baseline scenarios. However, gene editing in the same mating scheme resulted in significantly less inbreeding, 9% (Holstein) and 8% (Jersey). Also, gene editing resulted in significantly higher NM$ after 20 yr compared with conventional breeding for both breeds. Additionally, the gene editing scenarios of both breeds used a significantly greater number of unique sires compared with either the conventional breeding or baseline scenarios. Overall, our simulations show that, given the current genetic merit of horned and polled dairy sires, the use of conventional breeding methods to decrease the frequency of the HORNED allele will increase inbreeding and slow genetic improvement. Furthermore, this study demonstrates how gene editing could be used to rapidly decrease the frequency of the HORNED allele in US dairy cattle populations while maintaining the rate of genetic gain, constraining inbreeding to acceptable levels, and simultaneously addressing an emerging animal welfare concern.