Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle.

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

Milk production of Jersey and Fleckvieh × Jersey cows in a pasture-based feeding system.

Milk production parameters of purebred Jersey (J) cows and Fleckvieh × Jersey (F × J) cows in a pasture-based feeding system were compared using standard milk recording procedures. Milk, fat and protein production was adjusted to 305 days per lactation and corrected for age at calving. Effects of breed, parity, month and year were estimated for milk, fat and protein yield as well as fat and protein percentage, using the general linear model procedure. Fixed effects identified as affecting milk production parameters significantly were breed, parity and year. F × J cows produced significantly more milk than J cows (6141 ± 102 and 5398 ± 95 kg milk, respectively). Similarly, fat and protein yields were significantly higher in F × J (272 ± 4 and 201 ± 3 kg, respectively) than in Jersey cows (246 ± 3 and 194 ± 2 kg, respectively). Fat and protein percentages only differed slightly in absolute terms being 4.61 ± 0.04% fat in the Jersey compared to 4.47 ± 0.04% fat in the F × J. Protein levels for J and F × J cows were 3.62 ± 0.03 and 3.51 ± 0.03%, respectively. Despite a lower fat percentage, F × J crossbred cows may be more productive than purebred Jersey cows which may be due to heterotic effects.

Suitability of GWAS as a Tool to Discover SNPs Associated with Tick Resistance in Cattle: A Review.

Understanding the biological mechanisms underlying tick resistance in cattle holds the potential to facilitate genetic improvement through selective breeding. Genome wide association studies (GWAS) are popular in research on unraveling genetic determinants underlying complex traits such as tick resistance. To date, various studies have been published on single nucleotide polymorphisms (SNPs) associated with tick resistance in cattle. The discovery of SNPs related to tick resistance has led to the mapping of associated candidate genes. Despite the success of these studies, information on genetic determinants associated with tick resistance in cattle is still limited. This warrants the need for more studies to be conducted. In Africa, the cost of genotyping is still relatively expensive; thus, conducting GWAS is a challenge, as the minimum number of animals recommended cannot be genotyped. These population size and genotype cost challenges may be overcome through the establishment of collaborations. Thus, the current review discusses GWAS as a tool to uncover SNPs associated with tick resistance, by focusing on the study design, association analysis, factors influencing the success of GWAS, and the progress on cattle tick resistance studies.

Integrating economic parameters into genetic selection for Large White pigs.

The objective of the study was to integrate economic parameters into genetic selection for sow productivity, growth performance and carcass characteristics in South African Large White pigs. Simulation models for sow productivity and terminal production systems were performed based on a hypothetical 100-sow herd, to derive economic values for the economically relevant traits. The traits included in the study were number born alive (NBA), 21-day litter size (D21LS), 21-day litter weight (D21LWT), average daily gain (ADG), feed conversion ratio (FCR), age at slaughter (AGES), dressing percentage (DRESS), lean content (LEAN) and backfat thickness (BFAT). Growth of a pig was described by the Gompertz growth function, while feed intake was derived from the nutrient requirements of pigs at the respective ages. Partial budgeting and partial differentiation of the profit function were used to derive economic values, which were defined as the change in profit per unit genetic change in a given trait. The respective economic values (ZAR) were: 61.26, 38.02, 210.15, 33.34, -21.81, -68.18, 5.78, 4.69 and -1.48. These economic values indicated the direction and emphases of selection, and were sensitive to changes in feed prices and marketing prices for carcasses and maiden gilts. Economic values for NBA, D21LS, DRESS and LEAN decreased with increasing feed prices, suggesting a point where genetic improvement would be a loss, if feed prices continued to increase. The economic values for DRESS and LEAN increased as the marketing prices for carcasses increased, while the economic value for BFAT was not sensitive to changes in all prices. Reductions in economic values can be counterbalanced by simultaneous increases in marketing prices of carcasses and maiden gilts. Economic values facilitate genetic improvement by translating it to proportionate profitability. Breeders should, however, continually recalculate economic values to place the most appropriate emphases on the respective traits during genetic selection.