International Bull Evaluation Service Research Articles

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.

Keep Diversity––Make Standards! Spaces of Standardization for Diversity Analyzed through Cattle Breeding Industry

Standardization as spaces of diversity was introduced by Loconto and Demortain (2017) to advance the sociology of standards. Their analytical framework for studying standardization processes in interactive spaces is mobilized and expanded upon in this article in order to address the problematic relationship between standards and diversity. Studying industrialized animals highlights the existing tensions between these opposing forces and the socio-technical attempts to reconcile them. Using a socio-historical approach, we analyze cattle breeding standards as they pass through three interactive spaces of standards: “standards in the making,” “standards in action,” and “standards in circulation.” Drawing from the notion of ecology, we highlight the need for contextualization in order to better understand processes of standardization in a fourth space of “standards in interaction.” The contours of this space are demonstrated through an analysis of the International Bull Evaluation Service (Interbull), which is a space of commensuration for cattle breeding values. Linear interpretations of standardization processes are thus challenged with an empirical demonstration of how standardization can be harnessed to preserve and even enhance diversity.

COMPARATIVE ANALYSIS OF DAIRY PRODUCTIVITY OF FIRSTBORNS OBTAINED FROM SEXED AND TRADITIONAL SPERM OF BULLS

COMPARATIVE ANALYSIS OF DAIRY PRODUCTIVITY OF FIRSTBORNS OBTAINED FROM SEXED AND TRADITIONAL SPERM OF BULLS

홀스타인의 국제유전평가를 위한 모형개발에 관한 연구

본 연구는 국내 국가단위 평가결과의 문제점을 해결하면서 유전 능력평가시스템을 고도화하고 우리나라가 국제유전평가에 참여하기 위하여 국제평가기구에서 요구하는 검증작업을 통과하기 위하여 수행하였다. 본 연구에 이용된 자료는 농협중앙회 젖소개량부에서 수집한 분만일이 2001년부터 2009년까지의 검정성적으로 총 1,416,589개이며 산차는 5산으로 제한하였으며, 누적착유일은 75~305일로 제한하였고, 전체 혈통자료는 2,279,741개이며 부모를 갖는 개체는 535,409개이고 아비소는 2,467두로 구성되어 있는 기록들을 이용하였다. 유량, 유지방, 유단백에 대한 육종가는 신규로 개발한 다형질모형(Multiple traits model)을 이용하여 육종가를 구하였으며 기초작업은 SAS version 9.2와 R프로그램을 이용하였으며 유전모수를 추정하기 위하여 VCE 6.0을 이용하였다. 전반적으로 유전적 추세는 꾸준히 지속되어 오고 있으며 산차별 차이가 두드러지게 나타나지는 않았다. 유지방을 제외하고 유량과 유단백 형질의 추세가 잘 추정되었음을 알 수 있다. 유전평가분석결과 상위 1000두의 랭킹안에 최근의 생년을 갖는 딸소가 기존에 사용한 모수로 분석한 결과보다 딸소가 증가했음을 알 수 있다. 국제유전평가모형을 통해 새로 평가한 결과 씨수소상위 100두를 기존 평가모형에 의한 평가결과와 비교했을 때, 2006년생은 23두에서 28두로 2007년생은 12두에서 20두로 2008년생은 2두에서 8두로 증가하였다. 이는 최근의 딸소나 씨수소의 유전능력이 우수함에도 불구하고 상위에 랭크되지 못했던 결과가 새 모형의 적용으로 보완하여 새로운 평가분석에 적용할 수 있을 것으로 판단된다. 따라서 기존의 단형질 모형 대신 다형질 모형을 이용한 분석방법으로 평가를 실시하고 국제유전평가에도 다형질 모형을 이용한 육종가를 제시함으로써 다형질 선발의 정확도가 향상될 수 있을 것이다. This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

Cluster analysis on across-country genetic correlations for overall type traits and body condition score of Holstein bulls

The aim of the study is to examine the progress in trait harmonization among member countries participating in the International Bull Evaluation Service Organization (Interbull) for overall conformation score (OCS), overall udder score (OUS), overall feet and legs (OFL), and body condition score (BCS) of Holstein bulls. Input values for the cluster analysis were across-country genetic correlations estimated among 8 countries from 2001 to 2011 for overall type traits and among 12 countries from 2009 to 2011 for BCS. Changes in evaluation procedure and trait definition affected the clustering of countries. For OCS, the evolution was clear, particularly for Australia; the genetic correlations between this country and the majority of other members decreased during the years. Other changes in clustering were due to modifications in trait definitions introduced by France (2004), Germany (2007) and United Kingdom–Ireland (2005, 2008 and 2011). The genetic correlations for OUS were generally higher than those for OCS, and changes in clustering were less pronounced: the structure of clusters remained unchanged from 2004 to 2007. For OFL, Australia was even more distant than for the other two composite traits, probably due to the use of “side view foot diagonal” as best predictor of OFL. The changes in trait definition introduced by France Black and White Holstein (2001) and Italy (2003 and 2007) entailed modifications in the structure of dendrograms. The cluster analysis well depicts the difference among countries that sent information on BCS to Interbull and countries that sent angularity as predictor of BCS, as they were grouped in two distinct clusters and the correlations between them were negative. Major effort is needed to harmonize the traits among countries.

International cooperation: The pathway for cattle genomics

• Genomic selection tools are radically changing the way dairy cattle genetics is organized worldwide by providing the means to reduce generation intervals and accelerate genetic progress. As a result, young genomically selected bulls are quickly replacing progeny-tested bulls in the top lists. • To achieve moderate reliabilities in genomic predictions, large reference populations of progeny-tested animals have to be assembled, and this number increases dramatically for traits with low heritability. International cooperation becomes imperative, both for joining databases of genotypes and for obtaining phenotypic information translated into the respective national scale (Interbull multiple-trait across-country evaluation estimates). • Keeping the Interbull conventional international evaluations (based on national conventional estimated breeding values) as a source of phenotypic information for the national genomic predictive models requires maintaining conventional evaluation models at the national level. • Interbull is establishing a new framework to incorporate genomics into international evaluations. The main actions include intensifying networking opportunities; validating national genomically enhanced breeding values; and developing genomically enhanced multiple-trait across-country evaluations, Intergenomics, and a genomic data repository. to express their estimated breeding values (EBV) in the scales adopted by the importing countries. Without a common basis for comparing breeding animals from different origins, the genetic merit of bulls used for artifi cial insemination has been derived from their progeny information, obtained, in most cases, only in the country of origin of the bull while ignoring differences in trait defi nition, evaluation model, measurement scale, management practices, environmental conditions, genetic makeup, and selection goals. Members of the scientifi c community and the dairy breeding industry acknowledged this challenge as early as 1975, and after years of cooperative work, the International Bull Evaluation Service (Interbull) was created in 1983 (Philipsson, 2005). The objective was to support the dairy industry with accurate genetic information on bulls of the major dairy breeds for use by importers and exporters, thereby facilitating selection of the best genetics for different countries, environments, or breeding goals. Interbull was developed as a joint effort of the International Committee for Animal Recording; the European Federation of Animal Science, or EAAP; and the International Dairy Federation to become the main international forum for the development and standardization of methods and procedures in dairy cattle evaluation. The information exchange promoted by Interbull has clearly helped participating countries improve national systems and benefi t greatly from the international genetic evaluations carried out by the Interbull Centre. As a cooperative action between the participating countries, Interbull does not compete with the national genetic evaluation centers, but is rather an auxiliary service. The authority over publication of breeding values in national scales remains with each of the countries. This very successful partnership among competitors, exporters, and importers is a result of permanent and intense networking, making all the actors involved jointly responsible for the choice of methods and for the quality of the results obtained. The Interbull international evaluations are computed by a linear multiple-trait across-country evaluation (MACE) of national conventional EBV from the participating countries (Schaeffer, 1994). In MACE, bull progeny contributions from different countries are treated as different traits, with genetic correlations lower than unity. Consequently, the use of foreign information is accounted for by considering genotype-environment interaction, as well as differences in modeling, the genetic base, and trait defi nitions. Currently, Interbull MACE evaluations yield international EBV (IEBV) for a range of 34 traits and 6 breeds, expressed on as many as 30 national scales (currently, data from 73 populations are included) that are used extensively worldwide for semen marketing. Interbull has been a reference for international cooperation since 1983 at both the scientifi c and the industry levels, but the dawn of genomic selection in dairy cattle has taken this cooperation to a completely new level. The aim of this article is to present how dependent the “genomic

Principal component approach in variance component estimation for international sire evaluation

BackgroundThe dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE) for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model.MethodsThis article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC) and the so-called bottom-up REML approach (bottom-up PC), in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (co)variance matrix.ResultsOur study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (co)variance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in bias, but increased standard errors of the estimates and notably the computing time.ConclusionsIn terms of estimation's accuracy, both principal component approaches performed equally well and permitted the use of more parsimonious models through random regression MACE. The advantage of the bottom-up PC approach is that it does not need any previous knowledge on the rank. However, with a predetermined rank, the direct PC approach needs less computing time than the bottom-up PC.

Investigation of Country Bias in International Genetic Evaluations Using Full-Brother Information

International Bull Evaluation Service evaluations from May 2005 were examined for country bias by comparing Holstein full-brother families. Countries with ≥25 bulls in multicountry full-brother families were included. The model fit evaluations of US estimated breeding values (EBV) by absorbing full-brother family and producing solutions for country of brothers. For yield and somatic cell score, 24,611 and 22,802 bulls, respectively, were included in the analysis. The study was repeated fitting evaluations on the scales of 9 countries other than the United States. On all countries’ scales, bulls from Australia, Germany, Great Britain, and Japan had greater EBV for milk yield than did their full brothers from the United States; Italian bulls had lower EBV. Bulls from Australia, Great Britain, and South Africa had an advantage in EBV for fat yield. For EBV for protein yield, bulls from Germany, Great Britain, Japan, and South Africa had an advantage, whereas bulls from the Netherlands were disadvantaged. For somatic cell score, US bulls were advantaged compared with bulls from South Africa. Significance and rankings of apparent biases were similar across country scales of the international evaluations. Causes of those differences are unknown; differences in incorporation of parental data in national and International Bull Evaluation Service evaluations are a possibility.

Test-day models for South African dairy cattle for participation in international evaluations

Variance components and breeding values of production traits and somatic cell score of South African Guernsey, Ayrshire, Holstein and Jersey breeds have been estimated using a multi-lactation repeatability test-day model, including tests of the first three lactations as repeated measures and fitting the permanent environmental effect across lactations. Multitrait evaluations were done for the production traits (milk, butterfat and protein) and single trait evaluations for somatic cell score. Heritability estimates were comparable with yield and somatic cell score estimates obtained by test-day models from other countries (17-24% for milk yield; 10-13% for butterfat yield; 14-19% for protein yield and 6-8% for somatic cell score). Proofs of qualifying sires were sent to the International Bull Evaluation Service (INTERBULL) for participation in the March 2005 test runs. Genetic correlations between South Africa and other participating countries, estimated by INTERBULL, compared well with those amongst the other participating countries. Trend validation tests were successful using this methodology for all traits and breeds except for somatic cell score of the Guernsey breed, due to insufficient data for this trait. South Africa can now participate in routine INTERBULL evaluations to obtain Multiple Across Country Evaluation (MACE) breeding values, using this methodology.

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.

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 6.4kg. The four countries highest for sire protein differed only by 1kg; however, the range was 12kg. 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.

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.

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 nonparticipating countries are generally represented by participating countries, most needs are met by a global scale.

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 multi-country 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 multi-country 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.

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 × 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. Highestpeak yields were found in Israel and the United States at 31.4 and 30.5kg, respectively. New Zealand and Estonia had the lowest daily peak yields at 17.1 and 18.9kg,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 PTAmilk. 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.

Impact of Genetic Correlations on Accuracy of Predicting Future Evaluations

International evaluations for Holstein bulls were calculated by the International Bull Evaluation Service with data available in February 1995 from Canada, Denmark, France, Germany, Italy, Sweden, The Netherlands, and the US using current methodology with either correlations between countries of unity (0.995) or estimates of less than unity. To determine which of the two evaluation methods was most accurate, results of the two sets of evaluations for milk, fat, and protein yields for each country were compared with national evaluations in 1999. The 1999 national evaluations were assumed to be the best estimates of true genetic merit on a particular national scale. To reduce the impact of the part-whole relationship that results from earlier national data, a key part of the study was restricted to bulls with data from at least twice as many daughters for 1999 national evaluation as for 1995. Correlations and standard deviations of differences from later national evaluations showed no advantage to accounting for genetic correlations between countries. For bulls without national data in the earlier international evaluations and, therefore, no data in common with the later national evaluation, the advantage from using variable genetic correlations for yield was small. Thus, the use of variable genetic correlations had marginal value.

Accuracy of International Conversions of Elite Sires and Cows When Conversion Equations Are Based on Linear Regression

Conversion equations that are based on linear regression are used widely to transform estimated breeding values (EBV) of sires for production, type, health, and management traits from the genetic base, scale, and units of measurement of an exporting country to that of an importing country. One of the major deficiencies of these regression equations is that the accuracy of converted EBV of elite sires and cows, which are of primary interest in genetic selection programs, is lower than that for average animals. In this study, it is shown both mathematically and in practical examples that the standard error (SE) of prediction of elite dairy sires can be much larger than for average sires. When more than 100 sires are used to develop conversion equations, the SE of prediction for elite AI sires is up to 10% larger than for an average sire, and, when 50 sires are used to develop conversion equations, the SE of prediction is up to 25% larger than for an average sire. When fewer than 50 sires are used to develop conversion equations, the accuracy of converted EBV of elite sires is very poor, and SE can be 30 to 60% larger than for an average sire. Based on this study, it is recommended that international sire evaluations based on BLUP methodology (rather than linear regression) be made available as soon as possible for nonproduction traits in all countries and for production traits in countries that currently do not participate in routine INTERBULL (International Bull Evaluation Service) analyses.

Method and effects of incorporating foreign information into United Kingdom production evaluations

AbstractCountries, which import a significant amount of semen, embryos and animals, are faced with the problem of how properly to evaluate the animals in the national evaluation system when information on the foreign parents is generally missing. Additional problems arise when the foreign parents obtain an evaluation, usually on the basis of progeny, in the country of import with the result that there are two published evaluations for the animals in question. This paper presents a post-iterative method of incorporating foreign information into home country evaluations. The foreign information is initially converted to the same scale and base as in the home country using procedures recommended by the International Bull Evaluation Service. The method consists essentially of calculating a combined evaluation for animals with home and foreign information as a weighted average of yield deviations, parent averages and progeny contributions from the foreign and home countries. The combined evaluations are used to adjust the evaluations of progeny on the basis of formulae derived from the usual mixed model equations. The same principles were used to combine reliabilities from the respective home and foreign reliabilities. The results from the application of the method to the United Kingdom (UK) Holstein Friesian population are presented. There was re-ranking of both bulls and cows, especially foreign bulls with few UK daughters.

Examination of International Genetic Evaluations of Holstein Bulls

The first large-scale, international genetic evaluation of Holstein bulls computed by the International Bull Evaluation Service Centre in February 1995 was examined and compared with national evaluations from Canada, Denmark, Finland, France, Germany, Italy, Sweden, The Netherlands, and the US. Assumption of a genetic correlation of 0.995 between all countries and exclusion of bull daughters from a country in which the bull had not been sampled resulted in correlations of essentially unity between national and international evaluations. For the few bulls sampled in multiple countries, correlations were lower but still high (≤ 0.95). Genetic trend was more rapid for countries in which genetic merit for earlier years was lowest. Differences among countries in genetic merit of recent bulls have decreased markedly, especially between the US and other countries. Mean evaluation for bulls born during 1988 in the US surpassed means for bulls in France, Italy, and The Netherlands by <3kg for PTA for protein. Application of seven national economic indexes showed that some indexes with different mathematical forms can rank bulls similarly. If the official index for one country is assumed to be optimal, use of an index from another country could substantially reduce the mean merit of selected bulls by more than one-half an index standard deviation. Selection on either national or international genetic evaluations can give rapid genetic progress if the economic index is correct.

Accuracy of conversion of sire evaluations to united kingdom (uk) predicted transmitting ability (pta) equivalents (holstein friesian)

The International Dairy Cattle breeding industry characterises itself by ever increasing competition between countries. Frozen semen and embryos are easily transportable, providing breeders with access to bulls from almost anywhere in the world. Problems arise from the fact that each country produces genetic evaluations with different units, different expressions of genetic merit and different genetic bases. Without some means of standardisation it is very difficult to make the correct selection decisions.Procedures have been recommended and described by the International Bull Evaluation Service (INTERBULL) to convert foreign genetic evaluations to the genetic equivalents in the importing country (Philipsson et al. 1986). Previous research carried out in the UK has shown that converting foreign proofs to Improved Contemporary Comparisons (ICCs) worked well for Canada and New Zealand (Swanson et al, 1989). The change in the evaluation systems in the UK and elsewhere, to an Individual Animal Model, plus the availability of more data from more countries, were reasons to re-look at the accuracy with which the current conversion method predicts the actual PTA for milk, fat and protein within the UK.