Seedstock Herds Research Articles

Multivariate analysis of herd structure and genetic resource indicators in seedstock beef cattle herds.

Genetic, environmental, technological and financial resources are used differently in cattle herds that participate in the same breeding programme. The percentages of calves sired by sires within their own herd or from external herds vary across herds, as do the intensities of use of reproductive biotechnologies. These divergences may be related to differences in the indicators of genetic performance for economic traits. The aim of this study was to determine the factors related to herd structure and genetic resource utilization that exert the greatest influence on the genetic merit of seedstock herds within a Nellore breeding programme. The database comprised 21 factors, along with genomic-enhanced expected progeny differences (GE-EPDs) for growth, reproductive and carcass traits, as well as a selection index of animals from 128 herds. By combining principal component analysis and cluster analysis, we were able to group the herds. We identified statistically significant differences (p < 0.05) in the mean values of the factors, GE-EPDs and genetic trends among the groups of herds. Differences in the percentage of sires from external herds and in sire age between the groups of herds were the factors most associated with differences in mean GE-EPDs and genetic trends. Using young sires from other herds or lineages is an effective strategy in animal breeding. By enhancing genetic variability, this approach does not only improve the genetic quality of herds but also accelerates genetic progress in desired traits over time. Therefore, to ensure the success of this strategy, it is crucial that seedstock herds undergo a thorough selection process aimed at maximizing the genetic potential of future generations of beef cattle.

Maternal body composition in seedstock herds. 3. Multivariate analysis using factor analytic models and cluster analysis

Considerable information exists on genetic relationships of body composition and carcass quality of young and finished beef cattle. However, there is a dearth of information on genetic relationships of cow body composition over time and, also, relationships with young-animal body-composition measures. The aim of the present study is to understand genetic relationships among various cow body-composition traits of Angus cows over time, from yearling to weaning of a second calf at ~3.5 years. To determine genetic correlations among various composition traits over time, a multi-trait–multi-time analysis is required. For the Maternal Productivity Project, this necessitates modelling of five traits (namely weight and ultrasound measure for loin eye muscle area (EMA), rib fat, P8 rump fat and intramuscular fat) by five time combinations (recordings at yearling then pre-calving and weaning in first and second parity). The approach was based on including all 25 trait-by-time combinations in an analysis using factor analytic models to approximate the genetic covariance matrix. Various models for the residual covariance structure were investigated. The analyses yielded correlations that could be compared with those of past studies reported in the literature and, also, to a set of bivariate analyses. Clustering of the genetic multi-trait–multi-time correlation structure resulted in a separation of traits (weight and EMA, and the fat traits) and also of time effects into early (heifer = before first lactation) and late (cow = post-first lactation) measurements.

Genesis, design and methods of the Beef CRC Maternal Productivity Project

Australian seedstock cattle breeders have expressed concerns that while there has been genetic improvement in feedlot and abattoir performance of cows, it could have led to a decline in maternal productivity, especially under variable nutritional conditions. This paper describes a substantial project with two components designed to address these issues. The first sub-project was to monitor bodyweight and composition of 7760 young Angus and Hereford cows as they experience variable physiological states (pregnancy and lactation) and seasons. This was conducted on large numbers in seedstock herds. The second sub-project was to monitor more regularly bodyweight, body composition, and calf rearing performance of 500 Angus cows that are genetically divergent for either fat or residual feed intake at two research centres. This also included two levels of nutrition and recording of weekly feed intake of small groups of cows for at least three parities to allow reporting of genotype × nutrition effects on maternal productivity and efficiency. Results from the project are reported in a series of papers with each one having a defined focus.

Maternal body composition in seedstock herds. 5. Individual-trait selection direction aligns with breeder perspectives on maternal productivity

The present paper quantifies the variation in selection direction and genetic merit for the 10 Angus seedstock herds that contributed the majority of the data to the industry herd component of the Beef CRC Maternal Productivity Project. Differences in multi-trait selection direction for 17 BREEDPLAN estimated breeding values (EBVs) ranged between 16 and 63 degrees. Important differences among herds for selection direction for individual EBVs were identified. Specifically, some herds had been selecting to increase rib-fat and rump-fat EBV, while others were decreasing them. On the basis of a principal component analysis, 78% of the between herd difference in genetic merit as assessed by 17 EBVs was accounted for by two principal components. For 2000-born calves, the first principal component accounted for 50% of the genetic variation between herds and was most closely associated with days to calving EBV. Of the genetic merit for 2009-born calves, the first principal component accounted for 49% of the between herd variation and had the strongest weightings with BREEDPLAN rib-fat and rump-fat EBVs. The second principal component accounted for 29% of the variation and was most strongly related with BREEDPLAN EBVs for traits gestation length, milk and eye muscle area and 200-, 400- and 600-day weight. The variation at 2009 is consistent with outcomes from qualitative research that hypothesised that the main differences in genetic merit among herds are associated with rib-fat and rump-fat EBVs, but there were also differences in selection emphasis for weight traits. Despite differences in genetic merit among herds being generally small, they will manifest themselves in different productivity outcomes depending on the management system. Seedstock breeders and bull buyers should be aware of this and target their animal selection accordingly.

Maternal body composition in seedstock herds. 2. Relationships between cow body composition and BREEDPLAN EBVs for Angus and Hereford cows

Relationships between BREEDPLAN estimated breeding values (EBVs) for 600-day weight, maternal effect on calf weaning weight (Milk), fat depth at P8 site (Rump), 12/13th rib fat depth (Rib), eye muscle area (EMA), and intramuscular fat (IMF) with body composition measures in first- and second-parity Angus and Hereford cows were investigated. More than 4000 Angus and 1000 Hereford cows were measured for weight, height, ultrasound P8 fat depth (P8), 12/13th rib fat depth (RIB), loin EMA and IMF (%) at pre-calving and weaning. The body composition measurements were then regressed against mid-parent BREEDPLAN EBVs. Increased 600-day weight EBV was associated with increased weight and height but decreased P8 and rib fat depths and EMA when considered on a weight-constant basis. BREEDPLAN EBVs for Rump, Rib, EMA and IMF were closely related to the equivalent ultrasound measure in Angus and Hereford cows at pre-calving and weaning in the first two parities. These results indicate that current BREEDPLAN carcass EBVs are associated with cow body composition, so if producers want to change the body composition of their cows, they can do so using existing BREEDPLAN carcass EBVs, and there appears no requirement for additional EBVs to describe cow body-composition traits for subcutaneous fat, EMA and IMF.

Maternal body composition in seedstock herds. 4. Genetic parameters for body composition of Angus and Hereford cows

The genetics of body composition traits measured before calving and at weaning in the first and second parities were evaluated in 5975 Angus and 1785 Hereford cows. Traits measured were liveweight, body condition score and hip height and ultrasound scanned measurements of subcutaneous P8 and 12/13th rib fat depth, loin eye muscle area and intramuscular fat percentage. Corresponding yearling measures on these animals were obtained for analyses of relationships between yearling information with later-in-life traits. There was moderate genetic variation in all body composition traits measured at pre-calving and weaning in Angus (h2 = 0.14–0.59) and Hereford (h2 = 0.14–0.64) cows. Genetic correlations between measurements of the same trait at pre-calving and weaning were consistently positive and high in both parities for both breeds, indicating animals were ranking similarly for the same trait measured over time. Genetic correlations between measurements of different traits were generally consistent over time (pre-calving and weaning) in both breeds, indicating genetic relationships between traits were not changing significantly over time. Genetic correlations with corresponding yearling measures of body composition were consistently positive and high for the first parity, and lower for the second parity. The results of this study indicate that genetic improvement in body composition traits in cows is possible, and that body composition information recorded at yearling age is a reasonably good predictor of later in life performance for these traits.

Maternal body composition in seedstock herds. 1. Grazing management strategy influences perspectives on optimal balance of production traits and maternal productivity

Seedstock breeders’ perspectives on topics associated with maternal productivity in beef cattle were investigated through the use of qualitative in-depth semi-structured interviews. Given the complexity of maternal productivity, it is possible that some issues may not be fully captured by recording performance and data analysis. This paper discusses theory emerging from content analysis of interview data on management and genetic factors affecting maternal productivity as detailed by seedstock breeders in southern Australia. Overall, 24 interviews were conducted as part of an intensive field-work component with seedstock breeders involved with the Cooperative Research Centre for Beef Genetic Technologies’ Maternal Productivity Project. Qualitative content analysis of interview data revealed a considerable divergence in attitudes to cow management with regards to grazing management, body condition fluctuation and the utilisation of body fat reserves. Specifically, production systems diverged on the basis of animal management characterised by either ‘controlled’ or ‘variable input’ feeding strategies. Variation in management approach was associated with different perspectives on the perceived importance of selecting for production traits including growth, beef yield and milk compared with selection for perceived resilience traits including increased subcutaneous fat. The results demonstrated that among seedstock breeders targeting similar end markets, substantial variation in animal selection and management exists and this requires further characterisation to ensure breeding programs and animal management are optimal.

Frequency of the malignant hyperthermia gene in the South African pig industry

Porcine stress syndrome (PSS) is a genetic disorder caused by a recessive mutation in the halothane (HAL) gene and results in sudden death of pigs when placed under stress during transport and pre-slaughtering conditions. Animals that are affected by this mutation tend to develop pale, soft and exudative (PSE) meat, which results in an economic loss. In South Africa, the frequency of the number of carriers (Nn) and recessive (nn) pigs has increased by 21% to 30% from 2000 to 2003. This study aims to determine the prevalence of the malignant hyperthermia (MH) gene in breeding boars at nucleus or seed-stock level, and the prevalence at commercial abattoirs across the South African pig industry. Results indicate a low number of carriers (Nn = 17) and recessive (nn = 1) pigs at seed-stock level. For commercial abattoirs, 96.4% of the pigs tested did not carry the mutation. The low incidence of the MH mutation from breeding stock should eliminate a contributory factor to PSE meat in South Africa. Transport over long distances to abattoirs may ultimately have an effect on pork obtained even from non-carriers of the MH mutation. Keywords : MH gene, halothane gene, PSE meat, ryanodine receptor, seed stock herds

Modelling interdependent participation incentives: dynamics of a voluntary livestock disease control programme

With focus on seedstock herds selling replacements and a qualified class of diseases, this paper models producers' interdependent incentives to participate in a voluntary livestock disease control programme. Under strategic complementarity among participation decisions, momentum can build such that market premium for participation and participation rate increase sequentially. Non-participation, partial participation and full participation can all be Nash equilibria. Participation cost heterogeneity will dispose the outcome towards incomplete participation. We find plausible conditions under which temporary government subsidies cause tipping towards full participation. Applying parameters from the literature on Johne's disease, we illustrate factors that may affect participation.

Perceptions of veterinarians and producers concerning Johne’s disease prevalence and control in US beef cow-calf operations

BackgroundEfforts to educate producers and veterinarians in the United States regarding the management, prevention and control of Mycobacterium avium subspecies paratuberculosis (MAP) infection have increased over recent years. While nationwide awareness about MAP infection is improving, current level of awareness among beef producers and veterinarians is largely unknown. This study compares the perceptions of beef producers and veterinarians on the burden of MAP infection in cow-calf herds and on measures to control new infections. Questionnaires were mailed to 989 US beef producers through state Designated Johne’s Coordinators and to 1080 bovine veterinarians belonging to a US nationwide professional association.ResultsTwenty-two percent (34/155) of producers reported having infected animals in their herds. The mean (minimum, median, maximum) prevalence reported by producers was 0.8% (0, 0, 10). Twenty-seven percent (27/100) of producers had at least one clinical animal during the previous year. Compared to the small herds (<50 head), the mean test-positive percentages and estimated prevalences were higher in medium (50–149) and highest in large (≥150) herds. Seedstock herds had a lower prevalence and these producers were more likely to enroll in Johne’s disease (JD) control programs and test their herds. Veterinarians reported a mean overall animal level prevalence in their client herds of 5% (0, 2, 60). Similarly, 26% (0, 10, 100) of client herds had at least one infected animal. Mean percentage of infected cows within infected herds was 9% (0.01, 5, 80). Producers generally performed activities to control MAP transmission more frequently than perceived by veterinarians. Compared to veterinarians’ opinions, producers were less likely to cull cows with signs consistent with JD (P < 0.01), but more likely to test purchased additions (P < 0.01). Testing recommendations by veterinarians (n = 277) for beef cow-calf herds were bacterial culture of feces (3%), PCR (14%), ELISA (35%) and a combination of these tests (47%). Seventy-nine percent of veterinarians recommended a 12-month interval between testing.ConclusionsSeedstock producers who had had JD risk assessments performed on their farms were more supportive of JD control programs and had a correspondingly lower prevalence. It is important to increase educational activities to provide relevant information to veterinarians and producers for better management and control of JD. Educational programs should target larger herds to maximize the impact.

Factors affecting beef cattle producer perspectives on feed efficiency1

To establish the basis for implementation of a producer education program, a social assessment of the willingness and barriers to adoption of a measure of feed efficiency in beef cattle [residual feed intake (RFI)] was conducted. A 35-question mailed survey was sent to 1,888 producers acquired from the stratified random sample of the Idaho Cattle Association member list (n = 488), Red Angus Association of America member list (n = 2,208), and Red Angus Association of America bull buyer list (n = 5,325). The adjusted response rate for the survey was 49.9%. Of the survey respondents, 58.7% were commercial cow/calf producers and 41.3% were seedstock producers or operated a combination seedstock/commercial operation. Commercial operations had an average of 223 ± 17 cows and 13 ± 3 bulls, whereas seedstock herds (including combination herds) had slightly fewer cows (206 ± 24) and more bulls (23 ± 6). Both commercial and seedstock operators indicated that calving ease/birth weight was the most important trait used to evaluate genetic merit of breeding bulls. Only 3.8 and 4.8% of commercial and seedstock producers indicated that feed efficiency was the most important characteristic used for bull selection. Binary logistic regression models were used to predict willingness of seedstock producers to begin collecting data for the calculation of RFI on their bulls, or to predict willingness of commercial producers to begin selecting bulls based on RFI data. In response, 49.1% of commercial producers and 43.6% of seedstock producers indicated they were willing to adopt RFI as a measure of feed efficiency. These data indicate that feed efficiency was one of the traits that producers consider important; those who perceive feed efficiency as important tended to be actively involved in data collection on their herds, underpinning the notion that objective assessment was valued and used by some. Additional data collection in a future social assessment will continue to elaborate the proportion of producers who perceive feed efficiency as an increasingly important decision and management tool for beef production.

Relationships Between Charolais Sire Expected Progeny Differences and Progeny Performance in Commercial Beef Herds

Data on Charolais-sired calves in 31 commercial herds were analyzed to evaluate progeny performance relative to sire expected progeny differences (EPD). The traits analyzed were BW at birth (BBW; n = 3554) and at weaning (WBW; n = 3604) of crossbred progeny from nationally evaluated sires. Sire BBW EPD and WBW EPD were evaluated as predictors of performance in these commercial herds. Published sire BBW EPD and WBW EPD were averaged and weighted on the numeric accuracy published for each EPD. The average weighted sire BBW EPD was 0.4 kg, and the WBW EPD was 7.0kg with an average accuracy of 0.79 and 0.75, respectively. Random regression coefficients were estimated for progeny BBW on sire EPD of 1.03 ± 0.09 kg/kg of BBW EPD, and for progeny WBW, 0.66 ± 0.11 kg/kg of WBW EPD. Correlations for sire effect solutions in commercial herds with published sire BBW and WBW EPD were 0.59 and 0.39, respectively. Sire BBW EPD and WBW EPD were favorably related to actual progeny performance. Therefore, selection based on sire EPD should result in change of crossbred progeny performance. This further validates use of EPD as a selection tool for BBW and WBW in commercial herds. However, WBW response was less than expected, possibly a result of management practices in commercial herds compared with seedstock herds.

Genetic analyses of live-animal ultrasound and abattoir carcass traits in Australian Angus and Hereford cattle.

In order to estimate genetic parameters, abattoir carcass data on 1,713 Angus and 1,007 Hereford steers and heifers were combined with yearling live-animal ultrasound measurements on 8,196 Angus and 3,405 Hereford individuals from seedstock herds. Abattoir measures included carcass weight (CWT), percentage of retail beefyield (RBY), near-infrared measured intramuscular fat percentage (CIMF), preslaughter scanned eye muscle area (CEMA), and subcutaneous fat depth at the 12th rib (CRIB) and at the P8 site (CP8). Ultrasound scans on yearling animals included 12th-rib fat depth (SRIB), rump fat depth at the P8 site (SP8), eye muscle area (SEMA), and percentage of intramuscular fat (SIMF). Records on CWT were adjusted to 650-d slaughter age, and the remaining abattoir traits were adjusted to 300-kg CWT. Scan data were analyzed treating records on males and females as different traits. Multivariate analyses were performed on a variety of trait combinations using animal model and REML algorithm. Heritability (h2) estimates for CWT, RBY, CIMF, CP8, CRIB, and CEMA were .31, .68, .43, .44, .28, and .26, respectively, for Angus and .54, .36, .36, .08, .27, .38, respectively, for Hereford. Pooled across sexes, h2 estimates for SIMF, SP8, SRIB, and SEMA were .33, .55, .51, and .42, respectively, for Angus and .20, .31, .18, and .38, respectively, for Hereford. Genetic correlations (r(g)) between the same pair of carcass traits measured at yearling through scanning and directly at the abattoir were moderate to strongly positive, suggesting that selection using yearling ultrasound measurements of seedstock cattle should result in predictable genetic improvement for abattoir carcass characteristics. Estimates of r(g) between the scanned fat measurements and RBY were negative, ranging from -.85 for Angus heifers to -.05 for Hereford heifers. Also, the estimates of r(g) between SEMA and the fat records measured at the abattoir were negative and ranged from -.94 in Hereford heifers to -.02 in Angus heifers.

Genetic parameters for cow weight and condition score in Angus, Hereford, and Poll Hereford cattle

Heritabilities and genetic correlations for cow weight and body condition score were estimated from field data for 3 beef breeds in Australia. In all, 8177 cows of mixed ages were weighed and scored for body condition at calf weaning time in seedstock herds as part of a large research project. The average weaning age was 212, 221, and 218 days for Angus, Hereford, and Poll Hereford, respectively. Cow weights and condition scores were analysed separately for each breed and estimates of genetic parameters were obtained by Restricted Maximum Likelihood (REML). Cow weight and condition score were moderately heritable: h2 = 0.43 and 0.21 for Angus, 0.39 and 0.14 for Hereford, and 0.48 and 0.17 for Poll Hereford. The genetic correlation between CW and CS was 0.49, 0.65, and 0.58 for Angus, Hereford, and Poll Hereford, respectively. There is potential for providing a genetic evaluation for cow weight using field data in Australian beef cattle. Its modelling for inclusion in a multiple trait genetic evaluation system such as BREEDPLAN is discussed.

Correcting bias from the standard linear adjustment of weaning weight to an age-constant basis for beef calves1

Standard linear adjustment of weaning weight to a constant age has been shown to introduce bias in the adjusted weight due to nonlinear growth from birth to weaning of beef calves. Ten years of field records from the five strains of Beefbooster Cattle Alberta Ltd. seed stock herds were used to investigate the use of correction factors to adjust standard 180-d weight (WT180) for this bias. Statistical analyses were performed within strain and followed three steps: 1) the full data set was split into an estimation set (ES) and a validation set (VS), 2) WT180 from the ES was used to develop estimates of correction factors using a model including herd (H), year (YR), age of dam (DA), sex of calf (S), all two and three-way interactions, and any significant linear and quadratic covariates of calf age at weaning deviated from 180 d (DEVCA) and interactions between DEVCA and DA, S or DA x S, and 3) significant DEVCA coefficients were used to correct WT180 from the VS, then WT180 and the corrected weight (WTCOR) from the VS were analyzed with the same model as in Step 2 and significance of DEVCA terms were compared. Two types of data splitting were used. Adjusted R2 was calculated to describe the proportion of total variation of DEVCA terms explained for WT180 from the ES. The DEVCA terms explained .08 to 1.54% of the total variation for the five strains. Linear and quadratic correction factors were both positive and negative. Bias in WT180 from the ES within 180 +/- 35 d of age ranged from 2.8 to 21.7 kg.(ABSTRACT TRUNCATED AT 250 WORDS)

Implementing Technology for Genetic Improvement: Industry's View

Decisions in the AI industry are driven by market forces and are relatively unencumbered by regulation in the United States. Breeders make their own buying decisions and their collective decisions determine selection goals and policy. Customer education is the key to directing change and must be synchronized with the changes that occur. Sound conformation is important to commercial dairy farmers. Commercial and seedstock sectors are highly integrated and share the same bulls, testing programs, and milk markets and have similar breeding goals. The breeder ultimately judges the bulls by his or her own standards – usually by the performance (phenotype) of their progeny. Selection has become more intense and the rate of genetic change continues to increase. Generation interval has little practical significance in the sire-of-sons and dam-of-sons pathways. Strong positive assortative mating exists in seedstock herds and has accellerated the rate of genetic change. The industry needs better implementation of existing technology, comparable genetic ratings for young and proven sires, better identification of sires of cows on DHI test, implementation of the animal model genetic evaluation procedures, and better definition of equal opportunity groups.

Economic evaluation of alternative crossbreeding systems involving four breeds of swine. I. The simulation model.

A static, deterministic computer model, programmed in Microsoft Basic for IBM PC and Apple Macintosh computers, was developed to calculate production efficiency (cost per kg of product) for nine alternative types of crossbreeding system involving four breeds of swine. The model simulates efficiencies for four purebred and 60 alternative two-, three- and four-breed rotation, rotaterminal, backcross and static cross systems. Crossbreeding systems were defined as including all purebred, crossbred and commercial matings necessary to maintain a total of 10,000 farrowings. Driving variables for the model are mean conception rate at first service and for an 8-wk breeding season, litter size born, preweaning survival rate, postweaning average daily gain, feed-to-gain ratio and carcass backfat. Predictions are computed using breed direct genetic and maternal effects for the four breeds, plus individual, maternal and paternal specific heterosis values, input by the user. Inputs required to calculate the number of females farrowing in each sub-system include the proportion of males and females replaced each breeding cycle in purebred and crossbred populations, the proportion of male and female offspring in seedstock herds that become breeding animals, and the number of females per boar. Inputs required to calculate the efficiency of terminal production (cost-to-product ratio) for each sub-system include breeding herd feed intake, gilt development costs, feed costs and labor and overhead costs. Crossbreeding system efficiency is calculated as the weighted average of sub-system cost-to-product ratio values, weighting by the number of females farrowing in each sub-system.

The relationship between breeding soundness evaluation and fertility of beef bulls under group mating at pasture

The relationships between natural service fertility of beef bulls and the components of breeding soundness evaluation, age, preweaning average daily gain, yearling weight and scores of two libido tests were studied in two seedstock herds. In one of the herds (YBH), 15 yearling bulls were rotated during six-week breeding season so that each group of five bulls served the cows for a period of one week and rested for two weeks before the next exposure. Five older bulls (one 3-year old and four 2-year old) were assigned to the other herd (MBH) during the entire breeding season (six weeks). The progeny of each bull were identified by blood typing. Calf crop was 6.4% higher (P=0.14) in the MBH compared with that in the YBH. There were large differences in fertility between the bulls in the MBH. The 3-year old bull sired 40.9% of the calves, presumably due to his high social dominance order. The third group of yearling bulls, which served the herd during the third and sixth weeks of breeding, sired the highest number of calves (49.4%) compared with the other two groups (28.4% and 22.2%). In each of the groups one and two of the yearling bulls, one bull did not produce any progeny, while another one sired 44% of the calves. The correlation coefficients between fertility of the bulls and the traits used to predict their fertilizing capacity were generally small and inconsistent in different groups, when the effect of age in the mixed age group was removed. The correlation coefficients of bull fertility with scrotal circumference and reproductive system score were higher and more consistent in different groups as compared with the other traits studied.

SELECTION LIMITS: HAVE THEY BEEN REACHED WITH PIGS?

The likelihood of selection limits for performance traits of economic importance in pig production has been examined in the context of results from research with multiparous species and the context of the genetic improvement programs practiced in the industry. Research results with laboratory species (mice) have not identified insurmountable limits, either genetic or physiological, associated with intense unidirectional selection nor have such limits been identified in pig selection experiments spanning up to 12 generations. In terms of practical pig breeding this would represent approximately 25 yr. The evidence available on industry selection practices in Canada indicates that selection has been neither intense nor cohesive among breeders and that the criteria currently employed have been in place for less than one decade. For these reasons it appears that selection limits, if they exist, are unlikely to be evident for several more decades. This general outlook may not be applicable to all seed stock herds. Research evidence indicates that populations (e.g. fully closed herds) will show considerable individuality of response to selection which, coupled with variations among breeders in the intensity of selection and the performance criteria employed, will contribute to considerable divergence in the results obtained. While selection limits appear unlikely to compromise within-herd responses to sustained unidirectional selection, the universal adoption of specific criteria of performance merit, by fostering the progressive elimination of individual herds and breeds, diminishes the genetic flexibility of the population and restricts its potential to respond rapidly to changing production requirements. This aspect of genetic limits merits serious attention by the hog industry. Key words: Selection limits, pig breeding

PIG BREEDING: CURRENT PROGRAMS VS. FUTURE PRODUCTION REQUIREMENTS

Reports reported annually for the Canadian ROP swine testing program provide no evidence of genetic trends in the seed stock herds enrolled. Small herd size (&lt; 8 sows), short average life span of these herds (&lt; 5 yr) and the geographically diffuse nature of the seed stock industry appear to have been major impediments to the application of cohesive and sustained selection programs. The commercial industry, in contrast, has shown a marked improvement in average carcass merit during the past decade. This trend, stimulated and guided by the 1968 revision of carcass grading standards, has been accompanied by a 60% reduction in the number of commercial herds and a three-fold increase in the average number of pigs marketed annually per unit. The specific breeding programs employed by the commercial industry cannot be documented but there has been a steady growth in the use of systematic crossbreeding programs, and producer demand for boars with performance credentials has greatly intensified. This has fostered a fivefold increase in ROP testing activity since 1973, given impetus to the evolution of swine AI programs, and encouraged the development of large closed-herd seed stock operations with self-contained performance test facilities. The central objective of performance testing programs, both private and public, is the genetic improvement of traits directly relevant to efficient lean meat production. Future production requirements are unlikely to alter this basic objective but advances in the technology for live animal carcass evaluation and changing economic circumstances, specifically changes in rations to accommodate the increasing competition for cereal grain supplies, will necessitate continuous review and revision of testing procedures. Recent experimental evidence indicates that rate of feed ingestion is inversely related to efficiency of digestion and lean tissue feed conversion. This implies that testing programs which place a premium on rate of ingestion (e.g. "to appetite" or "scale" feeding) may be less suitable for purposes of measuring genetic differences in efficiency of lean production than programs which utilize ad libitum feeding.