Progeny testing and selection intensity for Holstein bulls in different countries

International Bull Evaluation Service (Interbull) Holstein evaluations from February 1995 through February 2003 were used to determine characteristics of progeny testing for Holstein bulls in Australia, Canada, Denmark, France, Germany, Italy, New Zealand, Sweden, The Netherlands, and the United States. The decision to graduate a bull from progeny test (PT) was assumed to have been made based on the second Interbull evaluation, and graduation was defined as the addition of 200 daughters in the period 2.5 to 4.5 yr later. Mean bull age at PT decision varied across countries by 12 mo. Mean numbers of herds and daughters ranged from 39 to 111 and 54 to 144, respectively. Countries with higher requirements for official evaluations generally had more herds and daughters but older bulls at PT decision. Mean estimated breeding values for yield traits of sires of tested bulls were most similar across countries for fat, differing by only 6.4 kg. The four countries highest for sire protein differed only by 1 kg; however, the range was 12 kg. Percentages of bulls graduated ranged from 4.4 to 14.7 across countries. Selection intensities (standardized selection differentials) tended to be about 1.0 for yield traits. Selection intensities for somatic cell score were generally unfavorable, reflecting selection for negatively correlated yield traits. Reflecting variation in national breeding goals, selection intensities for stature were positive for most countries and highly negative for New Zealand. Selection intensity for fore udder was generally the lowest among the traits examined. All but one country showed positive selection for udder support. These statistics permit comparison of the components of PT programs across country, illustrating possible opportunities for improvement.     

Impact of estimated genetic correlations on international evaluations to predict milk traits

The Interbull procedure for combining dairy bull evaluations uses estimated genetic correlations between countries. It is important to know whether the resulting difficulties from differences in ranking in each country are justified by improved accuracy relative to a system assuming unity correlations. Data submitted for the May 2001 yield and somatic cell score (SCS) Interbull evaluations were processed once with the usual estimated genetic correlations (E01) and again assuming these correlations to be essentially unity (0.995; U01). The 2 sets of resulting evaluations were compared with August 2004 national evaluations (N04) for bulls not having local evaluations used in the 2001 evaluations. Thus, the examination was of Interbull evaluations from foreign data in predicting national evaluations. Countries in the study for yield were Australia, Canada, France, Germany, Great Britain, Ireland, Italy, The Netherlands, New Zealand, and the United States. Countries included for SCS were Canada, France, Germany, Great Britain, The Netherlands, and the United States. For most countries’ evaluations, standard deviations of differences between E01 or U01 and N04 were smaller for E01 by about 5 to 7% and correlations between E01 and N04 were higher by 0.01 or the same as for U01 and N04. Although use of estimated correlations tended to improve prediction, the advantage was small. A previous study had concluded no difference in accuracy for yield but did not include Australia and New Zealand, countries with the lowest correlations with other countries. Excluding bulls from those countries produced results for the other 8 countries more like the previous study, but still favoring E01 slightly. Those 2 countries were not in the SCS data. Estimated genetic correlations improved the prediction of future national evaluations slightly in most countries but more substantially for the evaluations and bulls of Australia and New Zealand.     

International dairy bull evaluations expressed on national,subglobal, and global scales

Genetic evaluations on a global scale were calculated for Holstein bulls using the May 2001 International Bull Evaluation Service (Interbull) evaluations expressed on each of 27 national scales. National scale data were weighted by the country's proportion of total daughters from all bulls (population size) to represent market share. Correlations between Interbull evaluations on national scales and evaluations on a global scale ranged from 0.961 to 0.998 (mean of 0.988). Number of top 100 bulls for protein yield that were in common between national and global scales ranged from 54 to 94 and was related significantly to mean genetic correlation between a country and the other 26 countries. Weighting of evaluations on national scales by population size, inverse of population size weight, or equal weight produced practically the same group of top bulls and correlations among the three global scales were 0.999. Thus, the method for combining Interbull evaluations expressed on national scales had only minor impact and was much less important than use of all data. Subglobal scales were established by a clustering technique that gave two to five groups. For grazing countries or other atypical systems, a subglobal scale may provide better guidance, although a scale representing three grazing countries did not provide the expected improvement over a global scale in the relationship with the three country scales. If conditions in non-participating countries are generally represented by participating countries, most needs are met by a global scale.     

Identification of factors that cause genotype by environment interaction between herds of Holstein cattle in seventeen countries

Currently, the International Bull Evaluation Service calculates international dairy sire evaluations using the multiple-trait across country evaluation procedure. This method depends implicitly on political boundaries between countries, because the input data are national evaluations from each participating country. Therefore, different countries are treated as different production environments. The goal of this study was to identify factors that describe the production system on each farm. Such factors could be used to group herds across countries for borderless genetic evaluations. First lactation milk records of Holstein cows calving between January 1, 1990 and December 31, 1997 in Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the USA were used in this study. Thirteen genetic, management, and climatic variables were considered as potential indicators of production environments: peak milk yield, persistency, herd size, age at first calving, seasonality of calving, standard deviation of milk yield, culling rate, days to peak yield, fat to protein ratio, sire PTA milk, percentage of North American Holstein genes, maximum monthly temperature, and annual rainfall. Herds were grouped into quintiles based on herd averages for each of these variables. Genetic correlations for lactation milk yield between quintiles were significantly less than one for maximum monthly temperature, sire PTA milk, percent North American Holstein genes, herd size, and peak milk yield. The variables can be used to group herds into similar production environments, regardless of country borders, for the purpose of accounting for genotype by environment interaction in international dairy sire evaluation.     

Characterization of dairy production systems in countries that participate in the International Bull Evaluation Service.

The International Bull Evaluation Service Centre has routinely calculated international dairy sire evaluations since 1994. Production systems vary between countries and between herds within a country, and these differences can cause significant genotype x environment interactions. First-lactation records of Holstein cows calving from January 1, 1990 through December 31, 1997, were used in this study. Countries that provided data for this study included Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the United States. Country means were calculated for 13 variables related to climate, herd management, and genetic background. These variables were considered as possible causes of genotype by environment interaction. Highest peak yields were found in Israel and the United States at 31.4 and 30.5 kg, respectively. New Zealand and Estonia had the lowest daily peak yields at 17.1 and 18.9 kg, respectively. This was consistent with genetic differences between these countries, because Israel had the highest average predicted transmitting abilities (PTA) milk among sires, while Estonia had the lowest PTA milk. Persistency of lactation, defined as milk yield at 240 d postpartum divided by milk yield at 60 d postpartum, was highest in the Czech Republic and Estonia at 1.34, and lowest in Israel at 1.05. Herd size also varied substantially between countries, ranging from 2.3 first-lactation cows per herd-year in Finland to 62 per herd-year in Hungary. In summary, tremendous variation exists between the leading dairy countries in management, genetic, and climatic factors.     

Extent and benefits of multi-country progeny testing of young dairy sires

One of the current trends within the artificial insemination industry is to progeny test young dairy bulls in multiple countries. The objectives of this study were to assess the extent of multi-country progeny testing and to measure the corresponding gains in reliability of international breeding value estimates. Data of Holstein bulls that were born between July 1, 1992, and December 31, 1994, and progeny tested in countries that participate in the International Bull Evaluation Service were used in the present study, because these were the youngest bulls that had completed multi-country progeny testing before the study. Based on August 1999 international sire evaluation data, a total of 562 bulls from 10 countries were multi-country sampled for production traits during this 2.5-yr period, and 233 bulls from seven countries were multi-country sampled for type traits. The United States, Canada, The Netherlands, France, and Germany were most active in multicountry progeny testing, and Germany, New Zealand, Australia, France, and The Netherlands were the most common countries of foreign sampling. Mean reliabilities of international breeding values were calculated within each country. Means for milk yield were 0.89 for single-country sampled bulls with local progeny (i.e., progeny in the home country), 0.71 for single-country sampled bulls with no local progeny, 0.90 for multicountry sampled bulls with local progeny, and 0.78 for multi-country sampled bulls with no local progeny. Mean reliabilities for teat placement for these groups of bulls were 0.80, 0.71, 0.88, and 0.83, respectively, and means for rear udder width were 0.79, 0.60, 0.85, and 0.68, respectively. Gains in reliability in the country of foreign sampling were greatest when foreign progeny were located in countries that had low genetic correlations with the home country.     

Assessment of the value of international genetic evaluations for yield in predicting domestic breeding values for foreign Holstein bulls

International genetic evaluations are a valuable source of information for decisions about the importation of (the semen of) foreign bulls. This study analyzed data from 6 countries (Australia, Canada, Italy, France, the Netherlands, and the United States) and compared international evaluations for production traits of foreign bulls (i.e., when no national daughter information was available) to their national breeding values in August 2009, which were based only on domestic daughters’ data. A total of 821 bulls with highly reliable estimated breeding values (EBV) for milk, fat, and protein yield were analyzed. No evidence of systematic over- or underestimation was found in most of the countries analyzed. Observed correlations between national and international evaluations were close to 0.9 and, for most countries, generally close to their expected values (calculated from national and international EBV reliabilities). In Italy, however, higher differences between observed and expected correlations and significant mean differences between EBV for more than one trait were observed in bulls progeny-tested in the United States and in other European countries (with differences up to 33.1% of the genetic standard deviation). These results were probably induced by a relatively recent change in the model for national evaluation. The findings in this study reflect a conservative estimate of the real value of international evaluations, as changes in methodologies in either the national or the international evaluations decreased the ability of past international evaluations to predict current national evaluations. Nevertheless, our results indicate that international evaluations based on foreign information for Holstein bulls were reasonably accurate predictors of the future national breeding values based only upon domestic daughters.     

Direct and indirect conversion of bull evaluations for yield traits between countries.

Genetic evaluations of Holstein bulls from the US were matched with Canadian, Italian, Mexican, and Netherlands evaluations for the same bulls. Conversion equations for milk yield were computed by least squares, Goddard, and Wilmink methods. Accuracy was assessed by splitting data and applying equations developed from one subset to the other subset. Methods were judged by mean differences between actual and converted evaluations and standard deviation of that difference. Imperfection of conversions appeared to be due to inherent characteristics (variation and bias) of data rather than to inadequacy of conversion methodology. Least squares was slightly better than other methods but is not recommended by the International Bull Evaluation Service. The Goddard method was generally superior to the Wilmink method, but data often are not available for its application. A variation of the Goddard method was equal in accuracy to the Wilmink method. Daughter yield deviation as both dependent and independent variables was examined for only one data set and was little different from the Goddard method. Indirect equations were quite accurate for US to Mexico and US to the Netherlands but much less accurate for US to Italy conversion. Indirect conversions still would be useful until evaluations of bulls in common allow for direct conversions. For all three countries, a variation on indirect methodology was slightly superior to the usual indirect equations.     

Genetic evaluation of bulls and cows with single- and multiple-country test-day models

First-lactation milk yield test-day records on cows from Australia, Canada, Italy, and New Zealand were analyzed by single- and multiple-country random regression models. Models included fixed effects of herd-test day and breed composition-age at calving-season of calving by days in milk, and random regressions with Legendre polynomials of order four for animal genetic and permanent environmental effects. Milk yields in different countries were defined as genetically different traits for the purpose of multiple-trait model. Estimated breeding values of bulls and cows from single- and multiple-trait models were compared within and across countries for two traits: total milk yield in lactation and lactation persistency, defined as the linear coefficient of animal genetic curve. Correlations between single- and multiple-trait evaluations within country for total yield were higher than 0.95 for bulls and close to 1 for cows. Correlations for lactation persistency were lower than respective correlations for total yield. Between country correlations for lactation yield ranged from 0.93 to 0.96, indicating different ranking of bulls on different country scales under multiple-trait model. Lactation persistency had in general lower between-country correlations, with the highest values for Canada-Italy and Australia-New Zealand pairs, for both single- and multiple-country models. Although multiple-country random regression test-day model was computationally feasible for four countries, the same would not be true for routine international genetic evaluation in the near future.     

International genetic evaluations of Holstein sires for milk somatic cell and clinical mastitis

International genetic evaluations for milk somatic cell and clinical mastitis have been implemented on a routine basis by Interbull. This paper examines possible genetic consequences of such evaluations. Holstein data from 12 countries were used for this purpose. Trait definitions and national genetic evaluation procedures were first summarized and showed that differences between countries existed. Estimated genetic correlations among milk somatic cell in these countries ranged from 0.47 to 0.97, with a median of 0.88. Estimated genetic correlations among clinical mastitis in three Nordic countries ranged from 0.59 to 0.83, and estimated genetic correlations between clinical mastitis in the three Nordic countries and milk somatic cell in the non-Nordic countries ranged from 0.37 to 0.78 with a median of 0.55. Bulls without daughter information in the Nordic countries had low reliabilities on the Nordic clinical mastitis scales. International genetic evaluations for milk somatic cell and clinical mastitis enable a broader selection among foreign bulls, and higher selection differentials were found when using international evaluations compared with national evaluations.     

Comparison of Procedures to Convert Sire Evaluations Between Countries

Four methods for determining intercepts and regression coefficients of formulas to convert sire evaluations from one country to another were applied to data from Canada to estimate US PD. Four data sets were used: information from bulls with 1) Repeatabilities of at least 55%, 2) Repeatabilities of at least 75%, 3) Repeatabilities of at least 75% and initially sampled in the exporting country, and 4) Repeatabilities of at least 75% and young enough so that daughters with records used in calculating evaluations could not have resulted from decisions based on an evaluation in the other country. Use of assumed scale relationships of 53, 1.96, and 1.68 kg/ breed class average unit for milk, fat, and protein was found inappropriate, especially for fat. Ordinary least squares method produced reasonable intercepts but small regression coefficients. Methods attributed to Goddard and Wilmink and recommended by the International Bull Evaluation Service generally produced similar equations and were of similar accuracy in predicting PD from independent samples. The Goddard method is recommended on an intuitive basis. Results were affected more by choice of data than by choice of method. The data set judged most appropriate contained information for bulls with Repeatabilities of at least 75% that were initially sampled in Canada, the exporting country.     

Effectiveness of national and regional sire evaluations in predicting future-daughter milk yield

National and regional bull evaluations were compared for ability to predict standardized milk yield of future daughters. Correlations between evaluations and first-, second-, and third-parity yields of future daughters were calculated within herd-year-month group. Mean correlations with predicted yield of future daughters across the United States were higher for national (0.109, 0.111, and 0.082 for first, second, and third parities, respectively) than for Northeast (0.098, 0.085, and 0.061) Holstein evaluations; corresponding correlations for future Northeast daughters were similar. Bull evaluations based on the first 5 parities of daughters that first calved through 1991 from either California, North Central, Northeast, or Southeast regions as well as from the entire United States were compared with standardized milk yields of daughters that calved later. Correlations with first-, second-, and third-parity yields of future daughters were higher (from 0.001 to 0.011) for national than for regional evaluations. National evaluations were better predictors of future-daughter yield, especially for California and the Southeast. Evaluations based on only first parity were slightly better than those based on the first 5 parities in predicting first-parity yield for 3 of 4 regions but were far less useful in predicting second-or third-parity yield regardless of region. Regional evaluations included fewer bulls because of limited numbers of daughters in each region. The top 100 bulls for genetic merit for milk yield based on regional rankings were inferior to the top 100 bulls based on national ranking by 25 to 173 kg. Reliance on regional rather than national evaluations would reduce current US genetic gains.     

Consistency of maturity rate for milk yield across countries and generations

Differences among bulls in maturity rate of their daughters for milk yield were investigated. Milk records for US Holsteins with first-parity calving dates between 1960 and 1998 were used to calculate 3 evaluations for bulls based on daughter records from parity 1, parities 1 and 2, and parities 1, 2, and 3. The 3 evaluations were used to estimate parity-specific evaluations for parities 2 and 3. Maturity rate of Holstein bull daughters in Canada and the Netherlands was compared with that for daughters of the same bulls in the United States by using official November 2004 Canadian and August 2005 Dutch parity-specific evaluations. For bulls with ≥500 first-parity daughters, correlations among parity-specific evaluations within country and birth year of bull were 0.88 between parities 1 and 2, 0.84 between parities 1 and 3, and 0.96 between parities 2 and 3 for the United States; 0.90, 0.86, and 0.97, respectively, for Canada; and 0.92, 0.89, and 0.98, respectively, for the Netherlands. Correlations between Canada and the United States for within-country differences between evaluations for parities 1 and 2 were 0.72 for bulls with ≥50 first-parity daughters and 0.89 for bulls with ≥500 first-parity daughters; corresponding correlations between the Netherlands and the United States were 0.66 and 0.82. Correlations between countries for differences between evaluations for parities 1 and 3 were slightly less, and corresponding correlations between evaluations for parities 2 and 3 were still lower. To establish whether differences between parity-specific evaluations were genetic, comparisons were made across a generation. Coefficients for regression of son on sire within country and birth years of sire and son for parity-specific evaluations and differences between parity-specific evaluations ranged from 0.35 to 0.53, with standard errors of ≤0.04. Differences in maturity rate of bull daughters were quite consistent across country, and those differences were transmitted to the sons’ daughters. Modeling to account for maturity differences should increase the accuracy of US evaluations and reduce fluctuation between evaluations, especially for bulls with daughters that deviate substantially from the population mean for maturity rate for milk yield.     

Major advances in globalization and consolidation of the artificial insemination industry

The artificial insemination (AI) industry in the United States has gone through many consolidations, mergers, and acquisitions over the past 25 yr. There are 5 major AI companies in the United States today: 3 large cooperatives, 1 private company, and 1 public company. The latter 2 have majority ownership outside of the United States. The AI industry in the United States progeny-tests more than 1,000 Holstein young sires per year. Because healthy, mature dairy bulls are capable of producing well over 100,000 straws of frozen semen per year, only a relatively small number of bulls are needed to breed the world's population of dairy cows. Most AI companies in the United States do not own many, if any, females and tend to utilize the same maternal families in their breeding programs. Little differences exist among the selection programs of the AI companies in the United States. The similarity of breeding programs and the extreme semen-production capabilities of bulls have contributed to difficulties the AI companies have had in developing genetically different product lines. Exports of North American Holstein genetics increased steadily from the 1970s into the 1990s because of the perceived superiority of North American Holsteins for dairy traits compared with European strains, especially for production. The breeding industry moved towards international genetic evaluations of bulls in the 1990s, with the International Bull Evaluation Service (Interbull) in Sweden coordinating the evaluations. The extensive exchange of elite genetics has led to a global dairy genetics industry with bulls that are closely related, and the average inbreeding level for the major dairy breeds continues to increase. Genetic markers have been used extensively and successfully by the industry for qualitative traits, especially for recessive genetic disorders, but markers have had limited impact for quantitative traits. Selection emphasis continues to migrate away from production traits and towards nonproduction traits, especially towards health and fitness traits. Specifically, fertility has arguably become the major breeding and management issue facing dairy farmers today. Some producers have implemented crossbreeding programs in an effort to capitalize on heterosis, and crossbreeding will almost certainly need to be a bigger part of the AI companies business in the years ahead.     

International genetic evaluation of dairy sires using a multiple-trait model with individual animal performance records

The objectives of this study were to estimate variance components and predict sire breeding values for milk, fat, and protein yield by using a multiple-trait model in which lactation yield in each country was considered as a different trait. Data included first lactation records of 16,145,832 Holstein-sired cows that calved between January 1, 1990, and December 31, 1997, in 243,466 herds in Australia, Austria, Belgium, Canada, the Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the USA. Milk, fat, and protein were analyzed separately by using a 17-trait sire model; in this case, "traits" refer to measurements of the same biological parameter in different production systems. Our genetic model included the systematic effects of herd-year-season of calving, age at calving, milking frequency, and heterosis class (i.e., breed composition). Heritability estimates ranged from 0.24 in Australia (protein) to 0.34 in Israel (milk) and The Netherlands (fat). Genetic correlations between countries ranged from 0.77 for Austria-Czech Republic (protein), Estonia-Finland (fat), Estonia-Ireland (milk), Estonia-Israel (milk), and Hungary-New Zealand (fat), to 0.96 for Australia-Ireland (milk), Australia-New Zealand (milk), Belgium-Netherlands (milk), and Belgium-USA (fat). Correlations differed markedly from parameters used currently in international sire evaluations. In particular, genetic correlations were 0.91 to 0.96 between Australia, Ireland, and New Zealand; all of these countries rely heavily on rotational grazing. Correlations were also 0.91 to 0.96 between Belgium, Canada, Italy, The Netherlands, and the USA; all of these countries use intensive management systems. Correlations between these two groups of countries were 0.80 to 0.90. The percentage of elite bulls (top 1% for milk yield) selected in common by each pair of countries ranged from 0.42 for Germany-Estonia and Germany-Israel to 0.78 for Belgium-Netherlands.     

Genetic analysis of an artificial insemination progeny test program

The success of the progeny test (PT) program from one Spanish artificial insemination (AI) organization was evaluated. The annual genetic trend for the organization was compared with PT programs from other countries. The relationships among parents' estimated breeding values (EBV) and PT results for sons were also studied. Estimated breeding values for type and production traits were obtained from international genetic evaluations from February 2004. The annual genetic gain of the Spanish PT program was similar to that of other international programs. The Spanish AI organization graduated 13% of its sampled bulls, and 52% of primiparous cows were daughters of Spanish bulls (32% from proven bulls and 20% from sampling bulls).Correlations between EBV for PT bulls and their pedigree indices (0.52 to 0.70) were slightly lower than correlations between EBV for PT bulls and their parent averages (0.63 to 0.73). Both young and mature cows contributed to genetic progress. Success of PT bulls (defined by number of second-crop daughters) depended mainly on their EBV for final score, protein yield, and the type-production index. Significant correlations of sire EBV were found for final score and type-production index with the number of second-crop daughters (0.22 and 0.17). Likewise, significant correlations of dam EBV for final score and type-production index with the number of second crop daughters were found (0.25 and 0.18). Final score and protein yield were the main factors in success of a PT bull. The type-production index for PT bulls was not important for success unless it was 2.5 standard deviations above average. The PT bulls with low EBV for type-production index were used as proven bulls when they had higher EBV either for protein or final score.     

Estimation of genetic parameters for predicted nitrogen use efficiency and losses in early lactation of Holstein cows

The objective of this study was to estimate genetic parameters of predicted N use efficiency (PNUE) and N losses (PNL) as proxies of N use and loss for Holstein cows. Furthermore, we have assessed approximate genetic correlations between PNUE, PNL, and dairy production, health, longevity, and conformation traits. These traits are considered important in many countries and are currently evaluated by the International Bull Evaluation Service (Interbull). The values of PNUE and PNL were obtained by using the combined milk mid-infrared (MIR) spectrum, parity, and milk yield–based prediction equations on test-day MIR records with days in milk (DIM) between 5 and 50 d. After editing, the final data set comprised 46,163 records of 21,462 cows from 154 farms in 5 countries. Each trait was divided into primiparous and multiparous (including second to fifth parity) groups. Genetic parameters and breeding values were estimated by using a multitrait (2-trait, 2-parity classes) repeatability model. Herd-year-season of calving, DIM, age of calving, and parity were used as fixed effects. Random effects were defined as parity (within-parity permanent environment), nongenetic cow (across-parity permanent environment), additive genetic animal, and residual effects. The estimated heritability of PNUE and PNL in the first and later parity were 0.13, 0.12, 0.14, and 0.13, and the repeatability values were 0.49, 0.40, 0.55, and 0.43, respectively. The estimated approximate genetic correlations between PNUE and PNL were negative and high (from ?0.89 to ?0.53), whereas the phenotypic correlations were also negative but relatively low (from ?0.45 to ?0.11). At a level of reliability of more than 0.30 for all novel traits, a total of 504 bulls born after 1995 had also publishable Interbull multiple-trait across-country estimated breeding values (EBV). The approximate genetic correlations between PNUE and the other 30 traits of interest, estimated as corrected correlations between EBV of bulls, ranged from ?0.46 (udder depth) to 0.47 (milk yield). Obtained results showed the complex genetic relationship between efficiency, production, and other traits: for instance, more efficient cows seem to give more milk, which is linked to deeper udders, but seem to have lower health, fertility, and longevity. Additionally, the approximate genetic correlations between PNL, lower values representing less loss of N, and the 30 other traits, were from ?0.32 (angularity) to 0.57 (direct calving ease). Even if further research is needed, our results provided preliminary evidence that the PNUE and PNL traits used as proxies could be included in genetic improvement programs in Holstein cows and could help their management.     

Technical note: adjustment of traditional cow evaluations to improve accuracy of genomic predictions

Genomic evaluations are calculated using deregressed predicted transmitting abilities (PTA) from traditional evaluations to estimate effects of single nucleotide polymorphisms. The direct genomic value (sum of an animal's marker effects) should be consistent with traditional PTA, which is the case for bulls. However, traditional PTA of yield traits (milk, fat, and protein) for genotyped cows are higher than their direct genomic values. To ensure that characteristics of cow PTA for yield traits were more similar to those for bull PTA, mean and variance of cow Mendelian sampling (PTA minus parent average) were adjusted to be similar to those of bulls. The same adjustments were used for all genotyped cows in a breed. To determine gains in reliabilities, predictions were made for bulls with August 2010 evaluations that did not have traditional evaluations in August 2006. By adjusting cow PTA and parent averages of genotyped animals, Holstein and Jersey regressions of August 2010 deregressed PTA on genomic evaluations based on August 2006 data became closer to 1 for the adjusted predictor population compared with the unadjusted predictor population. Evaluation bias was decreased for Holsteins when the predictor population was adjusted. Mean gain in reliability over parent average increased 3.5 percentage points across yield traits for Holsteins and 0.9 percentage points for Jerseys when the predictor population was adjusted. The accuracy of genomic evaluations for Holsteins and Jerseys was increased through better use of information from cows.     

Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle

The objective of this research was to estimate heritabilities of milk urea nitrogen (MUN) and lactose in the first 3 parities and their genetic relationships with milk, fat, protein, and SCS in Canadian Holsteins. Data were a random sample of complete herds (60,645 test day records of 5,022 cows from 91 herds) extracted from the edited data set, which included 892,039 test-day records of 144,622 Holstein cows from 4,570 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. A total of 6 separate 4-trait analyses, which included MUN, lactose, or both (yield or percentage) with different combinations of production traits (milk, fat and protein yield, fat and protein percentages, and somatic cell score) were performed. Average daily heritabilities were moderately high for MUN (from 0.384 to 0.414), lactose kilograms (from 0.466 to 0.539), and lactose percentage (from 0.478 to 0.508). Lactose yield was highly correlated with milk yield (0.979). Lactose percentage and MUN were not genetically correlated with milk yield. However, lactose percentage was significantly correlated with somatic cell score (−0.202). The MUN was correlated with fat (0.425) and protein percentages (0.20). Genetic correlations among parities were high for MUN, lactose percentage, and yield. Estimated breeding values (EBV) of bulls for MUN were correlated with fat percentage EBV (0.287) and EBV of lactose percentage were correlated with lactation persistency EBV (0.329). Correlations between lactose percentage and MUN with fertility traits were close to zero, thus diminishing the potential of using those traits as possible indicators of fertility.