Overview of progeny-test programs of artificial-insemination organizations in the United States

Characteristics of progeny-test (PT) programs of artificial insemination (AI) organizations in the United States were examined for changes since 1960. Mean number of bulls that were progeny tested annually by major AI organizations during the mid 1990s was 11 for Ayrshires, 24 for Brown Swiss, 21 for Guernseys, 1261 for Holsteins, 112 for Jerseys, and 3 for Milking Shorthorns. Mean parent age at progeny-test (PT) bull birth decreased except for Milking Shorthorns; mean age of maternal grandsire at bull birth decreased for Holsteins and Jerseys but increased for other breeds. For Holsteins, mean ancestor ages at PT bull birth were 85 mo for sires, 47 mo for dams, and 136 mo for maternal grandsires during the mid 1990s. Percentage of PT bulls that resulted from embryo transfer increased to 78% for Brown Swiss and 80% for Holsteins by 1999. Inbreeding in PT bulls increased over time and ranged from 3.8% for Brown Swiss to 6.4% for Jerseys (5.6% for Holsteins) during the mid 1990s. Mean numbers of daughters and herds per PT bull generally declined except for Holsteins, which increased during the early 1990s to 61 daughters and 44 herds. Mean number of states in which PT daughters are located increased; for Holstein PT bulls during 1994, 22% of daughters were in California, 13% in Wisconsin, 12% in New York, and 10% in Pennsylvania and Minnesota. Percentage of first-lactation cows that were PT daughters increased and ranged from 6% for Milking Shorthorns to 22% for Ayrshires (14% for Holsteins) during 1998. Percentage of PT daughters that were registered declined and was 19% for Holsteins and around 80% for other breeds.     

Alternatives for examining daughter performance of progeny-test bulls between official evaluations

In August 2007, the USDA changed from calculating official genetic evaluations quarterly to triannually in conjunction with the schedule change for international evaluations. To offset part of the delay in providing genetic information because of the reduced frequency of official evaluations, industry cooperators requested that interim evaluations be initiated for progeny-test (PT) bulls based on first-lactation records from PT daughters and their contemporaries that calved recently in cooperator herds. Alternatives for interim evaluations were studied to determine which would characterize genetic merit of PT bulls most accurately. Four alternative Holstein data sources were examined based on maximum data interval (most recent 12 or 18 mo of first calvings) and minimum number of PT daughters in herd (≥1 or ≥ 5). The highest correlation between August 2006 interim and official evaluations for milk yield was 0.980 for interim evaluations based on the most recent 18 mo of first calvings from cooperator herds with ≥1 PT daughter. That high correlation confirmed that interim evaluations based on limited data could provide genetic estimates of value between official evaluations. With the support of the Council on Dairy Cattle Breeding, the USDA initiated 3 interim evaluations each year with release limited to PT bulls with ≥10 daughters and an increase in reliability since the most recent official evaluation.     

Selection of bulls for progeny testing using pedigree indices and characteristics of potential bull-dams' herds

A total of 209 bulls selected from herds in the northeastern US by Eastern AI Coop., Inc. from 1978 to 1981 were identified. The DHI data were obtained for the 145 herds from which these bulls were sampled. Also acquired were evaluations from both Modified Contemporary Comparison and animal model on these bulls and their ancestors and on cows and their sires in the bull-dam herds. From evaluation by animal model, animals appeared to have contributed information to each other effectively through relationship matrix, and thus the accuracy of cow evaluation has been improved. Bulls selected from herds of high genetic level were genetically superior to those from herds of low genetic level. However, there was no evidence that bulls from low intraherd milk variation herds were superior to those from high variation herds in the northeastern population, as was the case in Michigan herds. Parent indices were greater than bull PTA in herds of lower genetic level but less than bull PTA in herds of higher genetic level. The correlation between herd yield average and herd genetic level and that between herd yield average and intraherd yield SD were moderate but significantly different from zero. Other correlations between phenotypic and genetic measures of bull-dam herds were negligible. None of the herd characteristics showed promise in characterizing herds that were more successful in having their sampled bulls returned by AI organization after progency test.     

Comparison of genetic evaluations from animal model and modified contemporary comparison

Comparisons were made between characteristics of Modified Contemporary Comparison and animal model evaluations with data available for January 1989 USDA-DHIA genetic evaluations. The animal model system's requirement that cows have a valid first lactation record resulted in a decrease in cows and daughters included. New flexible comparison groups were slightly larger for small herds and much smaller for large herds, which resulted in overall smaller and more uniform-sized comparison groups. Determining the optimal method of defining management groups was not undertaken. Correlations between bull evaluations from the two procedures ranged from .92 to .95 across breeds. Increases in reliability over repeatability were substantial for bulls with limited daughter information and small for widely used bulls. Correlations between evaluations for cows born in 1985 were .92 to .96, whereas those for cows born in 1980 (old enough to have daughters affecting animal model evaluations) were lower (.90 to .93), as expected. Reliabilities for cows were .02 to .05 higher than repeatabilities. Cows with more daughters increased more in evaluation and accuracy between the two procedures and were genetically superior. Bulls and cows with more prior information, cows with higher past evaluations, and Holstein bulls with higher past evaluations tended to have larger increases in PTA. Genetic trend estimates were different for the animal model, which resulted in changes in evaluations of various magnitudes depending on breed, sex, and birth year of animal.     

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.     

The distribution of Mycobacterium avium ssp. paratuberculosis in the environment surrounding Minnesota dairy farms

The objective of this study was to characterize the distribution of Mycobacterium paratuberculosis (Map) in the environment of infected and uninfected Minnesota dairy farms. Eighty herds known to be infected from Minnesota's Johne's Disease Control Program (JDCP) and 28 herds known to be uninfected from Minnesota Voluntary Johne's Disease Herd Status Program (VJDHSP) were sampled. Fecal samples from up to 100 cows in each herd were cultured in pools of 5 cows. Two environmental samples were obtained from each farm from various locations. All samples were tested using bacterial culture for Map. Eighty percent of the JDCP herds had at least one positive pool. Environmental samples were cultured positive in 78% of the JDCP herds. Two (7%) of the VJDHSP herds had one positive pool, and one herd had one positive environmental sample. Environmental samples were cultured positive in cow alleyways (77% of the herds), manure storage (68%), calving area (21%), sick cow pen (18%), water runoff (6%), and postweaned calves areas (3%). There was an association between maximum level of colonies per tube from cow alleyways and manure storage and fecal pool prevalence. Herds with both areas cultured negative were estimated to have 0.3 to 4% fecal pool prevalence. Herds with both areas having a heavy load of bacteria were estimated to have 53 to 73% fecal pool prevalence. The study results indicate that targeted sampling of cow alleyways and manure storage areas appears to be an alternative strategy for herd screening and Johne's infection status assessment and for estimating herd fecal prevalence.     

Effect of milking frequency on DHI performance measures

Increasing production by increasing milking frequency (MF) is a management option available to dairy producers. This study examined effects of MF and interactions with region and herd size on measures of herd performance. Dairy Herd Improvement (DHI) Holstein herd summary records (n = 10,754, 10,550, and 10,438) for the years 1998, 1999, and 2000 were classified by MF: two times a day (2X) milking vs three times a day (3X); herd size: small (< 250 cows) and large (> or = 250 cows); and region: North and South. Percentage of herds milking 3X by year were 7.0, 6.7, and 7.1. Rolling herd average milk production was 16, 16, and 15% higher for herds milking 3X than herds milking 2X for the respective years. Herds milking 3X in the North region outproduced herds milking 3X in the South region. Milk fat and protein percentages were lower for herds milking 3X during all 3 yr. Differences in energy-corrected milk production between herds milking 3X and herds milking 2X were 14.5, 13.4, and 13.4% during the respective 3 yr as a result of lower component percentages for herds milking 3X. Herds milking 3X had more days open and higher actual calving intervals than herds milking 2X. Services per pregnancy for herds breeding primarily by artificial insemination were higher for herds milking 3X than for herds milking 2X. Somatic cell scores and weighted somatic cell counts were lower for herds milking 3X than herds milking 2X. Herds milking 3X had a higher percentage of somatic cell scores in the low range (0 to 3) and a lower percentage in the high range (7 to 9). Mean percentages of cows entering and leaving the herd were higher for herds milking 3X during all 3 yr.     

Duration of herd participation in dairy herd improvement milk recording in the United States

Participation in milk-recording programs that provide data for national genetic evaluations of dairy cattle in the United States is voluntary, but the effectiveness of the evaluation system increases with the number of herds that contribute data. To investigate patterns of herd participation in Dairy Herd Improvement (DHI) testing, periods of continuous testing were computed based on the year that a herd initiated or terminated testing and by geographical region. Continuous testing was defined as at least one test per 6-mo period. Some herds discontinued testing and then re-enrolled. Across all years (1960 through 2002), 65% of herds had one period of continuous testing (no testing lapse). The percentage of herds with testing lapses decreased as the number of lapses increased and as the initial test year became more recent; overall, only 1.5% of herds had more than 6 continuous testing periods. For herds that terminated DHI testing from 1960 through 2002, 64% were on continuous test for <3 yr. In general, herd frequencies decreased as continuous test period increased except for continuous testing of > or =20 yr, which increased to 13% for years 2000 to 2002. Herds with more recent termination dates had remained on continuous test longer, and one-third of herds that were still on test after June 2002 had been on test for at least 20 yr. The duration of herd participation was longest for the northeastern and mideastern United States and shortest for the southeastern United States. Multiple periods of testing with lapses of >6 mo between test periods represent a loss of data that could have enhanced the study and evaluation of genetic characteristics of US dairy cattle.     

Potential bias in genetic evaluations from differences in variation within herds

Evidence is reviewed that indicates substantial differences among herds in variation for production traits in dairy cattle. Examples are given to illustrate the overevaluation and selection of higher proportions of individuals from more variable herds, which reduces response to selection if greater variability is not due in part to greater additive genetic variance. Differences in heritability according to herd mean and variance are examined. Potential bias is substantial in genetic evaluations of cows and may increase over generations where, if the model is realistic, evaluations of dams are used in evaluations of daughters. Possible methods of adjustment are discussed.     

Estimation of genetic (co)variances for milk yield in first three lactations using an animal model and restricted maximum likelihood

Genetic relationships among lactation records are of interest because most selection of bulls is on first lactations. Selection also complicates estimation of genetic parameters. Techniques unbiased by selection should be used. Estimation of genetic and environmental (co)variances was done using restricted maximum likelihood with an expectation-maximization algorithm for an animal model. The algorithm involved solving mixed model equations by direct inversion of coefficient matrix that became feasible by neglecting relationships across herds. From data consisting of first to third lactation milk records of New York Holsteins, two computationally manageable subsets were selected of 15 herds each totaling 3070 and 2900 cows. Each cow had a recorded first lactation and a recorded second lactation if she had a recorded third record. Herds were chosen according to frequency of related animals and about 200 cows per herd. After 18 rounds of iteration, changes in estimates between successive rounds were constantly decreasing and small. Estimates averaged from both subsets gave heritabilities of h1(2) = .33, h2(2) = .33, h3(2) = .34, genetic correlations of rg12 = .86, rg13 = .85, rg23 = .87, and phenotypic correlations of rp12 = .57, rp13 = .52, rp23 = .65.     

Mastitis control practices: differences between herds with high and low milk somatic cell counts

Effects of differences in herd mastitis control management in maintaining low herd average SCC, was studied. Washington State DHI herds with Holstein cattle and enrolled in the SCC program (n = 309) were ranked by percentage of cows in their herd with SCC less less than or equal to 283,000 cells/ml. "Low herds" (n = 28) were among the 56 herds with the highest percentage of cows with SCC less than or equal to 283,000 cells/ml and "high herds" (n = 31) were among the 75 with the lowest percentage of cows with SCC less than or equal to 283,000 cells/ml. Herds were visited annually for 2 yr by a technician who collected samples and recorded data. Geometric mean bulk tank SCC during the year between herd visits was 175,000 and 460,000 cells/ml for low and high herds. Milking time hygiene practices, teat dipping, and dry cow therapy were practiced with equal frequency on low and high herds. Differences in function and maintenance of milking equipment did not discriminate between herd groups. Differences in mastitis control management of low versus high SCC herds were that managers of excellent control herds more frequently had highest producers milked first and clinical cows milked last; had automatic milking unit detachers; kept moisture content of cow bedding lower; and had workers disinfect teat ends prior to intramammary antibiotic treatment. Managers of low herds were more likely to use computers and attend dairy informational meetings. Results suggest subtle differences in mastitis control strategies differentiate the low and high SCC herd groups.     

Evaluation of Sires for Traits Associated with Herdlife of Grade and Registered Holstein Cattle

Six traits concerning herdlife of daughters of 199 widely used Holstein bulls were evaluated by best linear unbiased prediction methodology. Trait 1 indicated presence of DHIA termination code 3 through 7 in first lactation; trait 2 was trait 1 plus cows sold for dairy. Survivals to 48, 54, and 84 mo were traits 3 to 5. Age when last in herd was in months using the final lactation. Independent data sets were based on whether cows were grade or registered and different herds. All models included age at calving and herd-year born; some models included an indicator of whether a cow was registered. Grade cows left herds at younger ages. Correlations of separate sire estimates of each trait were less than 1 in each case, even after adjustment for numbers of daughters and heritabilities. Survival of grade and registered daughters may be different genetic traits. Estimates for traits of herdlife of sires were favorably related to Predicted Differences for yields and percent culled; the relationship to Predicted Differences for type depended on which daughters were evaluated.     

Influence of Reproductive Management Factors on Genetic Merit of Service Sires

Records were terminated (by sale or dry date) lactation records for cows on DHI test in Virginia for 1982 through 1984. July 1986 production evaluations, most recent type evaluations, and appropriate semen prices for date of service for AI bulls were merged with service sire identification from 384,990 DHI records. Repeat breedings and multiple lactations per cow were used. Least squares procedures revealed significant influences of season, mate's sire's PD for type and dollars, mate's milk yield deviation, registry status, and insemination number on production evaluations, PD type, and semen price of service sire. Significant effects of several of the same variables on linear type traits were observed. Season effects were possibly due to genetic trends. Genetic merit for production and type of service sire declined for daughters of sires with missing or low type and production evaluations, for mates with low or missing herdmate deviations, for grade cows, and for repeat services, especially fourth and later. Days between breedings were nonsignificant or of limited importance in predicting genetic merit of service sires. Proven bulls in AI accounted for 76.3% of all breedings, AI sample sires for 6.3%, and non-AI or unknown sires for 17.4% of breedings in these data.     

Estimates of genetic trend in an artificial insemination progeny test program and their association with herd characteristics.

Individual lactation records from Holstein cows in 3449 herds participating in an AI stud's young sire sampling program from 1971 to 1987 were used to characterize the sampling program and to estimate genetic merit and trend. Average genetic merit of cows in sampling program herds was consistently superior to the average genetic merit of cows in the US population. Genetic trend of sires of first-crop cows was 58 kg of milk and 1.5 kg of fat/yr from 1971 to 1978 and 176 kg of milk and 5.5 kg of fat/yr from 1979 to 1987. The average genetic merit of sires of first-crop cows born after 1983 was equivalent to or exceeded the genetic level of sires of other cows in the herd. Within-herd-year means and standard deviations of yield, genetic evaluation, and management traits (herd-year characteristics) were computed for a subset of 341 herds contributing first-crop daughters for at least 10 yr. The average of each herd-year characteristic during 10 or more years was used to predict within-herd genetic trend. Herd characteristics explained up to 51% of differences in within-herd genetic trends. Average sire genetic merit of daughters other than first-crop daughters accounted for up to 80% of the explained differences. Other herd characteristics suggested that herds with larger within-herd standard deviation milk yields, a larger number of young sires represented, younger cows, and greater percentage of cows sired by AI sires made greater genetic improvement. Results indicated that the average genetic merit of cows and the rate of within-herd genetic improvement are higher in herds that participate in a young sire sampling program.     

Consequence of alternative standards for bulk tank somatic cell count of dairy herds in the United States

Noncompliance with current US and European Union (EU) standards for bulk-tank somatic cell count (BTSCC) as well as BTSCC standards recently proposed by 3 US organizations was evaluated using US Dairy Herd Improvement Association (DHI) herds and herds supplying milk to 4 Federal Milk Marketing Orders (FMO). Herds with 15 to 26 tests (frequently monthly) from January 2009 through October 2010 were included. Somatic cell scores (SCS) from 14,854 herds and 164,794 herd-tests were analyzed for DHI herds with ≥10 cows for all tests. Herd test-day SCC was derived as a proxy for BTSCC and was the basis for determining noncompliance and percentage of the milk it represented. For FMO herds, actual milk marketed and BTSCC were available from 27,759 herds and 325,690 herd-tests. A herd was noncompliant for the current EU BTSCC standard after 4 consecutive rolling 3-test geometric means (geometric method) were >400,000 cells/mL. A herd was noncompliant for the current US BTSCC standard after 3 of 5 consecutive monthly BTSCC shipments (frequency method) were >750,000 cells/mL. Alternative proposed standards (600,000, 500,000, or 400,000 cells/mL) also were examined. A third method designated noncompliance when a single 3-mo geometric mean of >550,000 or >400,000 cells/mL and a subsequent test exceeded the same level. Results were examined based on herd size or milk shipped by month. Noncompliance for the current US standard for the 12 mo ending October 2010 in DHI and FMO herds was 0.9 and 1.0%, respectively, compared with 7.8 and 16.1% for the current EU standard. Noncompliance was always greater for the frequency method than for the geometric method and was inversely related to herd size or milk shipped. Using the frequency method at 400,000 cells/mL, noncompliance was 19.1% for DHI herd-tests in herds with <50 cows compared with 1.1% for herds with ≥1,000 cows. For FMO herds shipping <900 t, noncompliance was 44.5% using the frequency method at 400,000 cells/mL compared with 8.0% for herds marketing >9,000 t. All methods proposed increased the percentages of herds and shipped milk that exceeded the regulatory limit. Producers will need to place more emphasis on reducing the incidence and prevalence of subclinical mastitis through known management practices such as proper milking techniques, well-functioning milking machines, postmilking teat disinfectant, dry cow treatment, and culling of problem cows to meet any of the proposed new standards.     

Effect of region, herd size, and milk production on reasons cows leave the herd

Dairy Herd Improvement Holstein herd summary records (n = 11,259) were obtained for the year ending 1998. Reasons cows reportedly left the herd based on termination codes were analyzed for the effect of region, herd size, and herd milk production level. Regions were: North, Midsouth, and South. Herd sizes were: small (25 to 99), low medium (100 to 149), high medium (150 to 299), and large (greater than or equal to 300 cows). Milk production levels were: low (less than 7258 kg), medium (7258 to 9072 kg), and high (greater than 9072 kg). The overall percentage of cows leaving the herd was higher in the Midsouth than the South and increased with herd size. Low producing herds reported a lower percentage of cows left than high producing herds. Herds in the South reported more cows leaving for reproduction, death, and low production and fewer leaving for mastitis. Herds in the North and Midsouth reported more cows leaving for injury/other and disease, respectively. Cows left herds for disease less frequently in the North. Large herds in the South had a higher percentage leaving for low production than any herd size group in the North. Small herds reported more cows leaving for reproduction and mastitis than high medium and low medium size herds. The percentage of cows leaving for feet and leg problems was lowest for small size herds. High producing herds reported more cows leaving for reproduction, mastitis, feet and legs and disease.     

Effect of region and herd size on dairy herd performance parameters

Differences in selected Dairy Herd Improvement (DHI) performance parameters among regions and herds of different size categories were evaluated. DHI records from herds in 37 states were grouped into North, Midsouth, and South regions, and six herd size categories (20 to 49, 50 to 99, 100 to 149, 150 to 249, 250 to 449, and > or = 450 cows). The North region had higher income over feed costs (IOFC); milk, fat, and protein rolling herd averages; summit milk; standardized 150-d milk; and percentage of cows in milk, than the other regions. These variables were lowest for the South region. Cost/45.4 kg of milk, days open, days dry, and somatic cell counts were lowest in the North region and were highest in the South. Percentage of cows entering and leaving the herd were highest in the Midsouth and were lowest in the South. Larger herds had higher total feed cost, IOFC, milk, fat, and protein rolling herd averages, summit milk, standardized 150-d milk, percentage of cows entering and percentage leaving the herd than smaller herds. Larger herds had lower somatic cell counts than smaller herds. Cost/45.4 kg of milk, days dry, days open, days in milk, and percentage of cows in milk did not show clear trends among different herd sizes. There were significant interactions between region and herd size for some of the variables.     

The impact of 3 strategies for incorporating polled genetics into a dairy cattle breeding program on the overall herd genetic merit

Dehorning in cattle has been associated with behavioral, physiological, and neuroendocrine responses indicative of pain. Unaddressed, the pain associated with a routine production procedure could contribute to a negative public perception of livestock production practices. Alternative considerations of dehorning include the selection of polled cattle within herds, thereby avoiding pain and production loss. As polledness results from an autosomal dominant pattern of inheritance, genetic selection for polled cattle could reduce the prevalence of the horned trait. Herein we discuss 3 strategies to incorporate polled genetics into a cow herd and the estimated impact on the overall genetic merit of the herd. Furthermore, the availability and genetic merit of polled artificial insemination bulls in the United States is summarized. Both Holstein and Jersey dairy bulls registered with the National Association of Animal Breeders from December 2010 through April 2013 were queried. Polled bulls were identified as either being homozygous (PP) or heterozygous (Pp) and the average net merit (NM) predicted transmitting ability (PTA) of each sire group was calculated. The percentage of polled calves born each year over a 10-yr period was calculated for the following 3 scenarios: (A) various percentages of horned cows were randomly mated to Pp bulls, (B) various percentages of horned cows were preferentially mated to Pp bulls, and (C) horned cows were selectively mated to PP bulls, heterozygous cows to Pp bulls, and homozygous polled cows to horned bulls. Additionally, the change in NM PTA of the cow herd was calculated over the same period. The highest percentage of polled animals (87%) was achieved in scenario C. An evaluation of the herd NM PTA highlights the trade-offs associated with increasing polled genetics. Given the current genetic merit of horned and polled bulls, increasing the percentage of polled calves will decrease the NM PTA in Holstein, but may have minimal impact in Jersey herds. Decisions regarding selective breeding to increase polled genetics will need to be evaluated in the context of production objectives, cost of dehorning, and impact on overall genetic merit.     

Short communication: Genetic evaluation of milking speed for Brown Swiss dairy cattle in the United States

Genetic parameters and relative breeding values were estimated for milking speed of US Brown Swiss dairy cattle. Owner-recorded milking-speed scores on a scale of 1 (slow) to 8 (fast) were collected by the Brown Swiss Association as part of its linear type appraisal program starting in 2004. Data were 7,366 records for 6,666 cows in 393 herds. The pedigree file included information for 21,458 animals born in 1985 or later. Six unknown-parent groups that each included 4 birth years were defined. The model included fixed effects for herd appraisal date and parity-lactation stage and random effects for permanent environment, animal, and error. Within parity (1, 2, and ≥3), 6 groups were defined: unknown calving date, four 90-d lactation stages, and lactations with >400 d in milk. Heritability of 0.22 and repeatability of 0.42 were estimated by average-information REML; residual variance was 1.13. Little trend in estimated breeding value was found for cows born from 1999 through 2002. Although solutions increased with lactation stage for first-parity cows by 0.37, no clear trend was found for later parities. Genetic evaluations for milking speed were expressed as relative breeding values with a mean of 100 and a standard deviation of 5. The 121 bulls with ≥10 daughters had milking speed evaluations that ranged from 83 to 112 and had correlations of 0.56 with productive life evaluations and −0.40 with somatic cell score evaluations. The association of faster milking speed with lower somatic cell score was not expected. The moderate heritability found for milking speed indicates that the evaluations (first released in May 2006) should be useful in detecting bulls with slow-milking daughters.     

Associations between herd characteristics and reproductive efficiency in dairy herds

Dairy herds worldwide are experiencing a decline in reproductive efficiency at the same time as management methods are changing. This study aimed to investigate the extent to which herd-level characteristics were associated with reproductive performance. Data from herds using artificial insemination (AI) in the Swedish Official Milk Recording Scheme that had more than 45 cows were included in the study (total of 2,728 herds). Reproductive performance was measured as the average for each herd for the calving interval, calving to first AI interval, calving to last AI interval, number of AI per animal submitted for AI, and culling attributed to reproductive problems. Herds with mainly Swedish Holstein cows had longer calving intervals, calving to first AI, and calving to last AI compared with herds with mainly Swedish Red and White cows. Large herds had shorter calving to first AI but a greater number of AI than small herds, whereas small herds had greater culling attributed to reproductive problems than large herds. Low-yielding herds had longer calving intervals, calving to first AI, and calving to last AI and had greater culling attributed to reproductive problems than high-yielding herds, whereas herds with high milk yields had a greater number of AI than low-yielding herds. Herds with automatic milking systems had shorter calving intervals, calving to first AI, and calving to last AI and had lesser odds for culling attributed to reproductive problems when compared with herds with ordinary pipeline milking systems. Herds that used Advanced Feed Advisory Services had shorter calving to first AI but a greater number of AI and greater culling attributed to reproductive problems. Herds using TMR had longer calving intervals and calving to last AI than herds that did not. Herds with tie stalls had longer calving intervals, calving to first AI, and calving to last AI, and organic herds had shorter calving intervals, calving to first AI, and calving to last AI compared with conventional herds. We found that herds with do-it-yourself inseminations had longer calving intervals and calving to first AI. Our study showed numerous associations between herd characteristics and reproductive performance. When allocating advisory service resources to improve reproductive performance, the focus should be on herd characteristics that are easy to influence, such as TMR and do-it-yourself inseminations.