Artificial Insemination Studs Research Articles

Relationship between pubertal testicular ultrasonographic evaluation and future reproductive performance potential in Piétrain boars

New ways of predicting sperm quality and output performance in young artificial insemination (AI) boars are important for breeding companies to ensure that the pubertal boars delivered to the AI studs have a high chance of meeting minimum quality standards to be used for insemination and therewith dissemination of desirable characteristics. The aim of the current study was to characterize the testicular development of 218 pubertal Piétrain boars (Line 408, Pig Improvement Company) to identify traits with predictable characteristics relative to their sperm quality as an adult AI boar. Scrotum, testes and epididymis were examined ultrasonographically at day (d) 100 (on-test) and 170 (off-test) followed by a computer-assisted grayscale analysis (GSA). Over the test period, paired testicular volume increased 7.3-fold from 22.7 ± 10.8 cm3 to 166.6 ± 62.2 cm3. The right testis was significantly (P = 0.014) larger than the left one at the off-test. Based on the sperm quality (ejaculate volume, sperm concentration, total sperm number, morphologically abnormal sperm and total sperm motility at day 3 of semen storage), 82.11% (n = 179) of the boars were classified as “productive” boars. These boars had a significantly (P = 0.039) larger paired testicular volume than “non-productive” boars (45.9 ± 19.9 cm3vs. 38.5 ± 12.6 cm3) at the on-test. For the right testis at on-test, significant differences for the standard deviation of mean gray value (P = 0.022), area under the curve (P = 0.004) and mean gradient value (GRAD, P = 0.030) regarding the future sperm production capacity (SPC) were shown. At off-test, there was a significant difference for minimum gray value (MIN GV, P = 0.003) and mean gray value (P = 0.001) related to SPC. To find SPC related cut-off values for GSA data, a two segmental non-linear regression analysis was carried out indicating breakpoints for GRAD ≥12 and MIN GV ≥ 40 for boars with low SPC. Off-test boars with MIN GV ≥ 40 showed a 2.4 higher risk to display low SPC (Odds ratio = 2.4 [1.1, 5.4]; P = 0.024). The results may enable breeding companies to include new sperm quality associated traits in their boar testing and selection programs.

Insemination of sows with seminal doses prepared by a two-step hypothermic dilution does not impair the reproductive performance at farm.

Reproduction in swine is mostly carried out through artificial insemination (AI). For this purpose, AI studs collect the ejaculates, analyse the sperm quality, dilute and package to produce seminal doses and ship them to sow farms to carry out the AI. Temperature is controlled during the process to avoid sperm damage. Semen is diluted in the extender in a one-step or a two-step process where the second can be isothermic (approximately 32°C) or hypothermic (room temperature 21-22°C). Both techniques are currently performed, and the latter could reduce time and costs, but the literature available comparing the processes is scarce and presents discrepancies. To date, there are no studies about its impact in fertility. This study compared hypothermic two-step dilution (HTSD) and isothermic two-step dilution (ITSD) in laboratory and field trial to elucidate whether HTSD has any effect. Ejaculates from 72 boars in nine AI studs were split and processed with both techniques using a high-performance extender and evaluated in laboratory. Four farms inseminated 345 sows with samples of four of these AI studs, and their fertility and prolificacy were registered. Results show no significant differences between doses prepared by HTSD and ITSD technique, having no impact in laboratory results (percentage of motile sperm, short hypoosmotic swelling test (sHOST) and short osmotic resistance test (sORT), viable sperm, damaged acrosomes, sperm under early apoptosis, high mitochondrial membrane potential (p>.1), fertility (92.2% versus 94.1%, p=.45) or farrowing rate (15.8±0.3 versus 16.1±0.3 p=.46). In conclusion, our results suggest that HTSD of semen on extender could be safely implemented in AI studs under the conditions tested.

Generation intervals in Canadian dairy cattle herds

Genetic evaluation records for the Canadian Holstein, Ayrshire, Jersey, and Brown Swiss bulls and cows born from 1950 and 1960, respectively, were used to study the generation intervals (L) along the four-path selection model. The objectives of the study were to determine the L in the four dairy cattle breeds and the effects of some environmental factors and variations among herds or artificial insemination (AI) studs on the L achieved. Total L of the four selection paths was reduced by 55% from 29.2 yr in 1980 to 13.2 yr in 2016 in the Holstein breed. Substantial reductions in total L were also observed in the Ayrshire, Jersey, and Brown Swiss populations between 1980 and 2016. Unlike progeny year of birth, housing system, agricultural region in Québec (region) — as well as their interaction — were not important on realised L of sires and dams used on Canadian dairy farms. There were significant variations among herds and AI studs on the age of sires and dams used for breeding. The considerable variations in realised L among herds and AI studs offer opportunities to increase the annual rate of genetic progress in the four Canadian dairy cattle populations.

Analysis of factors affecting the pregnancy rate of mares after inseminations with cooled transported stallion semen

Artificial insemination (AI) with cooled stallion semen has increased markedly during the last decades in all countries, but fertility is often lower than when fresh semen or natural mating is used. The objective of this study was to examine field data (1634 ,cycles 523 Standardbred (SB) mares, 575 Finnhorse (FH) mares, and 90 stallions) using multivariable logistic regression for factors influencing the pregnancy rate (PR) after AI with cooled transported semen from SB and FH stallions. The PR per cycle for the material was 47%: Finnhorses 42% and Standardbreds 53%. When assessed with multivariable logistic regression analyses with a generalized linear mixed model, variables that affected the PR were breed, the number of inseminated estrus cycles, the percentage of progressively motile sperm (PMOT) in the ejaculate/AI dose at the time of shipment, and the number of progressively motile sperm in the AI dose at the time of insemination. In Standardbreds, variables that increased the per cycle PR were the number of AI per estrus cycle (multiple inseminations increasing the probability of pregnancy compared to only one insemination), the number of inseminated cycles, and PMOT in the AI dose at the time of insemination. In Finnhorses, the number of AI per estrus cycle (two and three inseminations increasing the probability of pregnancy compared to only one), the number of spermatozoa in the ejaculate and in the AI dose, and PMOT in the ejaculate/AI dose at the time of shipment increased the per cycle PR. Non-significant factors for the whole material included the type of artificial vagina (open-ended or closed), transport time, place of AI (stud farm or home stable), insemination done by veterinarian or technician, weekday, month, age of the mare (all age classes combined), age of the stallion, ejaculate parameters (sperm concentration, total number of sperm), and insemination dose parameters (volume proportion of seminal plasma, sperm concentration, PMOT, total number of sperm). In conclusion, breed, breeding opportunity in more than one cycle, more than one insemination/estrus, PMOT of the ejaculate/AI dose and the number of progressively motile sperm in the AI dose at the time of insemination are important for the outcome of inseminations with cooled semen.

Purchaser Response for Genetically Different Boars and Boar Semen

Summary Sales records on boars sold from a breeding company and semen sold from a boar artificial insemination stud were evaluated to assess the emphasis placed on performance data and costs by buyers of semen and boars, and to determine what affects boar semen price. Two data sets, that consisted of (1) numbers of boars sold in a given breed and genetic evaluation subclass and (2) units or dollars of semen sold for a boar over a specific sales period, were used. These sales were expressed as a percentage (market share) of the total sales over the 2-yr period. Equations to predict percentage market share (% MS) for boar sales included the fixed effects of period and breed and covariates for boar price and genetic evaluation within breed. All effects were important (P<.01), and R 2 was .83. Percentage MS for units of semen sold was estimated using a model that included the fixed effects of period and breed and the covariates for cost per unit (CPU) of semen and backfat and gain within breed. Individual performance was more useful in predicting % MS and CPU than was any index. Subjective scores on mothering ability, size, soundness and libido were useful in predicting % MS units and CPU. For predicting % MS units, R 2 values were as high as .44 for models with scores. Results indicated that buyers were willing to pay more per unit and purchase more volume of semen from boars that had test information.

Temperature management during semen processing: Impact on boar sperm quality under laboratory and field conditions

Freshly collected boar spermatozoa are sensitive to a fast reduction in temperature because of lipid phase transition and phase separation processes. Temperature management during semen processing may determine the quality of stored samples. The aim of this study was to evaluate the influence of isothermic and hypothermic semen processing protocols on boar sperm quality under laboratory and field conditions. In the laboratory study, ejaculates (n = 12) were first diluted (1:1) with Beltsville Thawing Solution (BTS) at 32 °C, then processed either with isothermic (32 °C) or hypothermic (21 °C) BTS, stored at 17 °C, and assessed on days 1, 3, and 6. Temperature curves showed that 150 minutes after the first dilution, semen doses of both groups reached the same temperature. Two-step hypothermic processing resulted in lower sperm motility on days 1 and 6 (P < 0.05). Concomitantly, hypothermally processed samples contained less membrane intact sperm on days 3 and 6 (P < 0.05). Using AndroStar Plus extender instead of BTS reduced the negative effect of hypothermic processing. In the field study, 15 semen samples from each of 23 European artificial insemination studs were evaluated as part of an external quality control program. Semen quality based on motility, membrane integrity, mitochondrial activity, and a thermoresistance test was higher for stations using one-step isothermic dilutions (n = 7) compared with artificial insemination centers using two-step hypothermic protocols (n = 16). Both studies show that chilling injury associated with hypothermic dilution results in lower quality of stored boar semen compared with isothermic dilution and that the type of semen extender affects the outcomes.

Factors affecting daughters distribution among progeny testing Holstein bulls

The aim of this study was to investigate factors influencing the number of daughters of Holstein bulls during the progeny testing using data provided by the Italian Holstein Friesian Cattle Breeders Association. The hypothesis is that there are no differences among artificial insemination studs (AIS) on the daughters distribution among progeny testing bulls. For each bull and beginning from 21 months of age, the distribution of daughters over the progeny testing period was calculated. Data were available on 1973 bulls born between 1986 and 2004, progeny tested in Italy and with at least 4 paternal half-sibs. On average, bulls exited the genetic centre at 11.3±1.1 months and reached their first official genetic proof at 58.0±3.1 months of age. An analysis of variance was performed on the cumulative frequency of daughters at 24, 36, 48, and 60 months. The generalized linear model included the fixed effects of year of birth of the bull (18 levels), artificial insemination stud (4 levels) and sire of bull (137 levels). All effects significantly affected the variability of studied traits. Artificial insemination stud was the most important source of variation, followed by year of birth and sire of bull. Significant differences among AI studs exist, probably reflecting different strategies adopted during progeny testing.

Sperm morphology and fertility of progeny-tested AI dairy bulls in Sweden

Use of bull semen with high levels of sperm abnormalities, reflecting genital dysfunction, is not recommended for artificial insemination (AI) since it would most likely lead to subfertility. Sperm quality, including sperm morphology, may deteriorate with increasing age of the bull thus becoming a source of concern when using older, progeny-tested AI bull sires. Although a relationship between sperm morphology and fertility after AI in progeny-tested bull sires has been reported, it is yet unclear which sperm abnormalities are most critical. This constituted the core aim of a 22-month long retrospective study in proven (aged 60-84 months at the start of the study) AI sires of the Swedish Red (SR, n=8) and Swedish Holstein (SLB, n=4) breeds where their semen (107 freezing batches in total, built by a single ejaculate (n=3) or pooling two consecutive ejaculates (n=104) collected at 1-3 months interval), were subjected to detailed morphological examinations on wet- and dry, stained smears. Attention was paid to between- and within-bull variations with regard to presence and level of sperm abnormalities. Sperm morphology differed significantly between sires and ejaculates, with 6/12 sires having ejaculates containing >10% of morphologically deviating sperm head shapes, a commonly used threshold for young AI bulls in Sweden. However, with the exception of pear-shaped or narrow-at-the-base anomalies, the mean values for individual defects were always within the limits expected for a normal bull sire, and were therefore considered acceptable. The percentage of morphologically normal spermatozoa was positively related to fertility, whose output differed significantly among bulls. Among sperm abnormalities, the proportion of morphologically deviating sperm head shapes were negatively correlated with fertility, pear-shaped sperm heads in particular. In conclusion, the relationship between sperm morphology and fertility after AI calls for frequent (2-3 months interval) detailed assessments of sperm morphology in AI stud bull sires.

Relationship of environment temperature and boar facilities with seminal quality

The objective in this experiment was to determine the effect of controlling the ambient temperature and housing facilities on boar seminal quality preserved at 15°C for 24 h. The seminal doses used ( n=5736) were refrigerated at 15°C and transported from the studs to the laboratory for semen assessment. Motility and acrosome status were evaluated. Artificial insemination studs with and without ambient temperature control were studied and the facilities evaluated independently within each group. Seminal quality was better in studs with controlled temperature ( P<0.001). In studs without control of ambient temperature the straw bedding improved semen quality. In general, higher variation and lower semen quality was observed in boars during the summer, compared to other seasons. In studs with ambient temperature control, wall/gate division and concrete floor improved seminal quality. The same tendency was observed when straw bedding was used. This study confirms the need to create conditions in the environment of the boar stud, according to its location and climatic characteristics. To design housing facilities taking into consideration the type of division, floor and bedding will help to increase the reproductive results, and improve the efficiency of the artificial insemination studs.

Prevention of Disease Transmission by the Use of Semen in the Porcine AI Industry

For more than 40 years the artificial insemination(AI) in pigs has been used on piglet producing farms. It has become predominant over natural service only in the last 20 years. Boar ejaculates can be extended on average 20 times or more. One boar can produce more than 2000 doses of semen annually. AI studs with more than 300 boars are therefore required to fulfill all regulations to prevent the spreading of diseases. Regulations of the Office International des Epizooties (OIE), a directive of the European Union (EU), are enforced to establish a common standard in semen production all over Europe. In addition, certain disease prevention programmes exist, e.g. against the Porcine Reproductive and Respiratory Syndrome (PRRS) or Parvo virosis. The methods of preventing the spread of diseases by AI centres are documented and valued. Both the animal hygiene and the personal hygiene of people working with the boars are required. To a large extent the success of a prevention programme is due to the regional situation of the diseases. Only when semen producing organisations value disease prevention methods highly in their work can infection of boars and semen doses be prevented.

Connectedness in the French Holstein cattle population

An analysis of connectedness in the French Holstein cattle population was carried out. This study was motivated by the fact that artificial insemination (AI) bulls are evaluated at the national level, whereas they are usually progeny tested only in the region of their AI stud. Connectedness among AI studs was measured by the generalised coefficient of determination (CD) of contrasts between mean breeding values of bulls from the different AI studs. Four connectedness components were distinguished. The relative influence of each component was assessed through the increase in prediction error variance (PEV) of the contrasts after this information was discarded. CDs of contrasts were always higher than 0.80. Therefore, connectedness level among AI studs was high and provided an accurate national genetic evaluation. Out of the different components of connectedness, withdrawing of proven bull connection data caused the greatest increase in PEV (+47.5 %) primarily due to the change in the connecting structure of the data. Genetic relationships among bulls were the next important source of information. In contrast, contributions from the planned use of the bulls progeny tested were quantitatively limited (8 % increase in PEV) and foreign semen had a minor contribution (2 % increase in PEV). However, in spite of its limited quantitative impact compared to the other components, planned sampling bull connectedness is recommended because it provides high quality data for model validation and bias investigations. © Inra/Elsevier, Paris

Effect of bull sire selection strategies on competitiveness of dairy AI studs

Artificial insemination (AI) studs need to have competitive breeding programs to stay in business. One way to be competitive is to use only the few top ranking bulls as sires of the next cohort of young bulls. This maximises average genetic merit of young bulls and increases the chance of producing outstanding bulls on progeny testing. Competitiveness of an AI stud with intense bull sire selection compared with a conventional stud was evaluated stochastically, by simulating the expected numbers of sons in the top ranking list. Utility theory and the probability of having no young bulls in the top ranks were used to consider risk. The maximum average number of bulls in the top ranks was achieved with use of the best bull sire and the number declined steadily as additional bull sires were used. Risk for the stud from using few bull sires was not high. Size of the stud had little effect on the results. With five competitors instead of two, risk was even less important because extra genetic merit has a higher utility when there is more competition for a limited market. Lower accuracy of bull sire selection (on sib records or on pedigree) was useful only if genetic trend was high. There is a conflict between the need for individual studs to be competitive by selecting few bull sires, and the long term need of the breed to retain genetic variation.

REGIONAL HETEROGENEITY OF VARIANCES AND ITS EFFECT ON CANADIAN HOLSTEIN SIRE EVALUATION

Heritabilities were estimated within each of four artificial insemination stud regions in Ontario and Quebec, based on a total of 880 329 records for milk and fat yield and 441 230 records for final class score. The pseudo-expectation (PE) and tilde-hat (TH) approaches were used. Estimates ranged from 0.32 to 0.46 for milk yield, from 0.31 to 0.53 for fat yield, and from 0.17 to 0.47 for final class score. Differences between methods (PE and TH) were as large as differences between regions for all traits. TH regional estimates were less variable than PE estimates. Changes in sire rankings were trivial when using regional estimates versus using a common variance ratio in each region during evaluation. Rank correlations were 0.98 and higher between evaluations based on heterogeneous regional variances and evaluations based on homogeneous variances. For all three traits, variance ratios that have previously been assumed for national evaluation were more appropriate than estimates obtained in this study. Use of the previously assumed values resulted in a greater consistency, measured by the correlation, between the regional proofs of a sire and between a sire's proof and pedigree index. Key words: Pseudo-expectation, tilde-hat, heterogeneous variances, Holstein, sire evaluation

The effect of collection procedure on the sperm output and copulatory behavior of AI stud boars

Sixteen mature boars in routine use at an artificial insemination (AI) facility were subjected to routine semen collection (Control) or were sexually stimulated either by penile diversion prior to collection (DIV), by collection with a non-estrous gilt in the dummy sow (WG) or by collection with a non-estrous gilt in the dummy sow following physical contact with a non-estrous gilt for 2-h periods daily over the 3 days prior to collection (HWG). Each boar was subjected to all four collection procedures over a 4-week experimental period. While slight increases in sperm concentration and in the total yield of sperm were observed following sexual stimulation, neither of these parameters differed significantly ( P > 0.05) from those observed during Control collections. Boars on the HWG treatment produced a significantly larger ( P < 0.05) ejaculate volume than that recorded on the Control treatment. Boars on the WG treatment spent a significantly longer ( P < 0.05) time on the dummy compared to the Control treatment, with all other comparisons being non-significant. Boars when on WG and HWG treatments showed a greater degree of sexual arousal ( P < 0.05) compared to when collected on the Control treatment, as measured by the shorter interval from mounting to the initiation of pelvic thrusting, but other components of the copulatory behavior complex were not influenced by treatment. It is concluded that stimuli, additional to the visual stimulus of the dummy sow, produce only slight changes in the copulatory behavior and ejaculatory process of AI-experienced boars and that the provision of such stimuli is unlikely to enhance the short-term semen output of such boars.

Selecting Mating Pairs with Linear Programming Techniques

Mate selection can increase progeny merit if overall merit is nonlinear for one or more component traits. An index of expected progeny merit could be calculated for all possible mating pairs, and the set of pairs with the highest progeny mean could be selected. There are serious computational problems for more than a few males and females. To select and mate f, females, and m, males, from n of each, with k0 females per male, would require (fn)(mn)f!/(k0!)m evaluations. Linear programming algorithms can determine the optimal strategy efficiently by considering only a subset of these possibilities. Let πij be the index of progeny merit of the ith sire mated to the jth dam and Xij be the decision variable for that mating (restricted to 0 or 1). Then the problem of selecting mating pairs can be stated as: maximize ΣiΣjπijXij, subject to 1) ΣiXij ≤ 1, 2) ΣjXij ≤ k0, 3) ΣiΣjXij = f, and 4) Xij = 0 or 1. By including an artificial sire and an artificial dam and choosing appropriate merit values for the artificial matings, this problem can be solved by efficient “transportation” algorithms. These algorithms could be used to develop rational mating packages for dairy artificial insemination studs provided that an objective evaluation of progeny merit could be formulated, provided that merit is not simply additively inherited.

Purchaser Response for Genetically Different Boars and Boar Semen

Sales records on boars sold from a breeding company and semen sold from a boar artificial insemination stud were evaluated to assess the emphasis placed on performance data and costs by buyers of semen and boars, and to determine what affects boar semen price. Two data sets, that consisted of (1) numbers of boars sold in a given breed and genetic evaluation subclass and (2) units or dollars of semen sold for a boar over a specific sales period, were used. These sales were expressed as a percentage (market share) of the total sales over the 2-yr period. Equations to predict percentage market share (% MS) for boar sales included the fixed effects of period and breed and covariates for boar price and genetic evaluation within breed. All effects were important (P<.01), and R2 was .83. Percentage MS for units of semen sold was estimated using a model that included the fixed effects of period and breed and the covariates for cost per unit (CPU) of semen and backfat and gain within breed. Individual performance was more useful in predicting % MS and CPU than was any index. Subjective scores on mothering ability, size, soundness and libido were useful in predicting % MS units and CPU. For predicting % MS units, R2 values were as high as .44 for models with scores. Results indicated that buyers were willing to pay more per unit and purchase more volume of semen from boars that had test information.

Progeny Tested Sires Compared with Pedigree Selected Young Sires

First lactation records of 109,589 cows in 1,978 Holstein herds cooperating with three artificial insemination studs in young sire sampling were studied to compare performance of progeny of approximately the upper 15, 2, and 25% of sires, dams, and maternal grandsires for milk yield with selection differentials of +350, +2735, and +268kg milk when the young sires entered sampling programs. The 315 young bulls were sired by 88 sires.Mean weighted Predicted Differences for sires proven through artificial insemination were 130kg milk and 4.0kg fat, whereas weighted averages for naturally proven sires were 13kg milk and .4kg fat. For young sires, pedigree index of sire, dam, and maternal grandsire averaged 347kg milk and 11.8kg fat, and for an index including sire and maternal grandsire averaged 242kg milk and 7.6kg fat. Annual trends for ancestors were +31.8kg milk and +.9kg fat for sires.Within herd-year-season, production of daughters of progeny tested sires exceeded that of daughters of young sires by 84kg milk and 2.4kg fat. Progeny of young sires produced 103kg more milk than daughters of naturally tested bulls.

Fluctuations in Sire Evaluations

Large fluctuations in an artificial insemination sire's evaluations concern both dairymen and artificial insemination studs. Characteristics of three bulls with high initial values which dropped on later evaluations were compared with those of 17 “normal” bulls. Characteristics included genetic yield, management, genetic trend, environmental trend, and size of herds where daughters freshened, genetic merit of mates, and average age at freshening of daughters in first lactation. Evidence suggests that fluctuations are from preferential treatment of daughters of some sires as well as randomness inherent in methods of sampling and evaluating sires.

EFFECTS OF SELECTIVE MATING ON SIRE PROOFS FOR MILK PRODUCTION, PERCENT MILK FAT AND FINAL TYPE SCORE

A study was made of the effects of selective mating on the milk yield and percent milk fat proofs of 325 sires and the final type score proofs of 434 sires. Sires were grouped by type of ownership into artificial insemination (AI) unit ownership, private ownership with daughters in 10 or fewer herds, private ownership with daughters in more than 10 herds and private then AI ownership categories. Each group of sires was mated to cows above average for milk yield. With one exception, each group was also mated to better than average cows for percent milk fat. The average weighted bias for AI sires with a first proof for milk yield was 0.16 and with a second proof, 0.18 breed class average (BCA) points. The average weighted bias for percent milk fat was zero for AI sires for both first and second proofs. The greatest average bias for a group of sire proofs in milk yield was 0.31 BCA points for the privately owned sires used in more than 10 herds and in milk fat percent was −0.02% for the privately owned sires used in 10 or fewer herds. Selection indices that included the dams’ deviation records for milk yield and percent milk fat were only slightly different from the indices using daughter records only. Failure to use the dams’ records led to a maximum bias of 1.64 BCA points in first milk yield proofs of AI sires. The difference between the two sires with the largest positive and negative biases led to a maximum bias of 0.14% in the milk fat proofs of the sires studied. With respect to final type score, mates of young AI sires were inferior to mates of privately owned sires. Mates of sires entering AI studs on the basis of a natural service proof were also superior to those of young AI sires. The average bias in first proofs for AI, [Formula: see text], private &gt; 10 herds, and private then AI sires, was 0.06, 0.09, 0.26, and 0.20 points, respectively, with significant differences in mate merit among and within sire groups. The maximum bias between two sires in final type score proofs was 0.94 points.

Evaluation of Ontario Holstein Dairy Sires for Milk and Fat Production

Milk and fat production records of 176,380 Ontario 2-yr-old Holstein cows from 1958 to 1972 were used to evaluate 433 Holstein sires. The objectives of the study were to utilize the sire comparison procedures currently used in the northeastern United States on Ontario Holstein data; to determine feasible strategies of grouping sires to account for genetic trend; to re-evaluate heritabilities for milk and fat production while simultaneously evaluating sires; and to measure genetic progress through change in weighted average of sire proofs over years. The two grouping strategies were years in which first daughter record appeared in the data and artificial insemination stud ownership by years of appearance of first daughter record. Sire proofs based on many progeny were essentially the same in either grouping procedure, but young bulls with less than 20 progeny differed considerably. Due to the structure of artificial insemination units in Ontario, unit differences were nonsignificant. Estimates of heritability for milk and fat yield were .29 and .28. The change in weighted average of sire proofs per year was 20.9kg for milk and .63kg for fat production.