Opportunities for selection to improve steer and cow productivity in northern Australia

This thesis analysed carcass records from 2180 tropically adapted, steers (986 Brahman (BRAH) and 1194 Tropical Composite (TCOMP)) describing weight, eye muscle area, P8 and 12/13th rib fat depth, percent intramuscular fat and retail beef yield, with tenderness assessed as shear force. All steers were feedlot finished with a subset (680 BRAH and 783 TCOMP) recorded for individual feed intake. Female reproductive performance in the half-sib sisters of these steers (1007 BRAH and 1108 TCOMP) was evaluated as outcomes of their first (Mating 1: when females averaged 27 months of age) and second (Mating 2) annual matings, and averaged over up to 6 matings (termed 'lifetime' reproduction traits). Heifer and cow weight, eye muscle area, P8 and 12/13th rib fat depth, body condition score and hip height were recorded at 18 months of age, immediately prior to first calving and at Mating 2. The maternal genetic component of weaning weight (Maternal WWT) was estimated based on weaning weight records available for these steers and females and the progeny of females (N = 12528)

Issues and Options for Global Evaluations

Although the occasional outbreak of a disease like FMD results in some restrictions, the international trade of beef cattle genetic material in form of semen, embryos and live cattle is increasing world wide and with it comes the exchange of information from the exporting country's genetic evaluation system. During the last 15 years the larger dairy breeding countries, with their huge market for semen, have developed across country evaluations for a number of breeds and nearly all economically important traits through an organisation called INTERBULL which operates out of Sweden. The beef industries don't want to stay behind and the question has been asked could beef cattle breeding benefit from global evaluations. As a consequence of this, discussions and research are under way to implement global evaluations for various breeds

Impact of addition of new herds on genetic parameter estimates in the Australian Brahman population

The impact of new herds joining BREEDPLAN in recent years was investigated by comparison of genetic parameters estimated from old and new herds over the same time period. New herds tended to be smaller than older herds, but no difference was observed in average contemporary group size between the two groups. Some difference was observed between the two groups in direct genetic and residual variances, most likely due to less information available from new herds. Despite these differences, genetic parameters for the trait of 200-day weight for the two groups were very similar, indicating the data could be successfully combined for genetic evaluation purposes

The effect of age slicing interval on the variance components and data effectiveness for birth and 200 day weights in Angus cattle

In BREEDPLAN analyses, contemporary groups for birth weight and 200d weight are sliced at 45 day intervals to avoid possible inaccuracies in age adjustment, rapid changes in environmental conditions and confounding of sires and seasons biasing the estimated breeding values. However age slicing can have a significant impact on data structure and effectiveness of records. The aim of this study was to re-estimate the variance components and examine the effectiveness of the data for birth and 200day weights from Angus cattle with different contemporary group slicing intervals. The result showed that altering the slicing interval from 15 to 60 days did not have a significant impact on the variance components for birth or 200day weight. However increasing slice interval significantly improved the average effectiveness of the data for both traits. On average the animal record effectiveness increased by 10% and the average total effective progeny records per sire more than doubled. The results suggest that the age slicing interval could be altered from 45 to 60 days to increase the effectiveness of the data available without impacting on the genetic parameters. However altering the contemporary group structure will cause changes to the existing estimated breeding values

Economic evaluation of beef cattle breeding schemes incorporating performance testing of young bulls for feed intake

A model beef cattle breeding scheme consisting of a breeding unit and a commercial unit was used to evaluate the impact on genetic gain and profitability of incorporating feed intake measurements as an additional selection criterion in breeding programmes. Costs incurred by the breeding unit were compared with returns generated in the commercial unit, with bulls from the breeding unit being used as sires in the commercial unit. Two different market objectives were considered - a grass-fed product for the Australian domestic market, and a grain-fed product for the Japanese market. Breeding units utilising either artificial insemination or natural service were also considered. A base scenario was modelled incorporating a range of criteria available to Australian cattle breeders. A second scenario incorporated selection of sires for the breeding unit using a 2-stage selection process, with a proportion of bulls selected after weaning for measurement of (residual) feed intake. Measurement of feed intake of bulls improved accuracy of breeding unit sire selection by 14–50% over the equivalent base scenario, and genetic gain in the breeding objective was improved for all scenarios, with gains ranging from 8 to 38% over the base scenario. After accounting for the cost of measuring feed intake ($150–450), additional profit was generated from inclusion of feed intake measurement on a proportion of bulls for all breeding schemes considered. Profit was generally maximised where 10–20% of bulls were selected at weaning for measurement of intake, with improvement in profit ranging from 9 to 33% when optimal numbers of bulls were selected for intake measurement

Technical note: Updating the inverse of the genomic relationship matrix

A computing strategy to update the inverse of the genomic relationship matrix when new genotypes become available is described. It is shown that re-using results of previous computations can result in substantial reductions in computing time required. For instance, when the number of individuals increased by about 1% for matrices larger than 15,000, the time required for updating was less than 7% of that used for direct inversion from scratch

Genetic relationships between live animal scan traits and carcass traits of Australian Angus bulls and heifers

Genetic parameters of four ultrasound live-scan traits and five carcass traits of Australian Angus cattle were examined with regard to sex and age of the scanned individuals. Live-scans were subdivided according to whether the observation was obtained from a bull or a heifer. In addition, two age subset ('young' and 'old') within sex were formed by k-means clustering around two centres within sex according to the age at scanning. REMLestimates for heritabilities, genetic, residual and phenotypic correlations for each trait and trait combination were derived from a series of uni-, bi- and tri-variate analysis. Statistically significant age effects could be found for heritablities of scan intra-muscular fat content in heifers and scan fat depth at P8 site and scan rib fat depth in bulls, and for genetic correlations between the scan traits fat depth at P8 site, rib fat depth and eye muscle area. However, differences in heritablities between age sets within sex did not exceed 0.05, and genetic correlations between scan traits of 'young' and 'old' animals were at least 0.9. Differences between genetic correlations of abattoir carcass traits and 'young' and 'old' live-scan traits, respectively, were not significant due to high standard errors but up to 0.44. The larger of these differences were found for combinations of scan-traits and non-target carcass traits and not for combination of scan-traits and their actual carcass target traits. Thus, although some results suggest an age effect on the genetic parameters of scan traits, the extent of this effect is of limited impact on breeding value accuracy and genetic gain of scan traits. Furthermore, a possible age effect on correlations to economically important carcass traits need to be underpinned by more carcass traits observations in order to get unambiguous results allowing to draw consequences of scanning younger individuals for accuracy of breeding values and genetic gain in carcass traits

Beef cattle genetic evaluation in the genomics era

Genomic selection is rapidly changing dairy breeding but to date it has had little impact on beef cattle breeding. The challenge for beef is to increase the accuracy of genomic predictions, particularly for those traits that cannot be measured on young animals. Accuracies of genomic predictions in beef cattle are low, primarily due to the relatively low number of animals with genotypes and phenotypes that have been used in gene discovery. To improve this will require the collection of genotypes and phenotypes on many more animals. Several key industry initiatives have commenced in Australia aimed at addressing this issue. Also, unlike dairy, the beef industry includes several major breeds and this will likely require the use of very dense SNP chips to enable accurate genomic prediction equations that are predictive across breeds. In Australia genotyping has been performed on all major breeds and research is underway to ascertain the effectiveness of a high density SNP chip (800K) to increase the accuracy of prediction. However, at this stage it is apparent, even in dairy breeding, that genomic information is best combined with traditional pedigree and performance data to generate genomically-enhanced EBVs, thus allowing greater rates of genetic gain through increased accuracies and reduced generation intervals. Several methods exist for combining the two sources of data into current genetic evaluation systems; however challenges exist for the beef industry to implement these effectively. Over time, as the accuracy of genomic selection improves for beef cattle breeding, changes are likely to be needed to the structure of the breeding sector to allow effective use of genomic information for the benefit of the industry

Body length and its genetic relationships with production and reproduction traits in pigs

Body length in pigs has been reported to be heritable with heritability estimates ranging from 0.12 to 0.62 (Kim et al., 1996; Cho et al., 1998; Johnson and Nugent, 2003; Hofer, 2004). Body length is directly associated with carcass length. Measuring body length is simple and not costly. Compared to reproduction traits body length can be measured on younger animals and from both sexes. Considering these characteristics, body length could be used as one of the selection criteria to improve production and reproduction traits in pigs. However, studies on genetic relationships between body length and other production and reproduction traits have not been found in the literature. The aim of this study was to estimate genetic correlations of body length with production and reproduction traits