As the profitability of wool sheep farming is greatly influenced by the mutton price and as consumers become more discerning, finding ways to determine the heritability of meat quality of merino crossbred lambs is considered important.
a) To determine whether meat traits in the South African ovine genetic resource is affected by breed selection line and environmental effects in South African sheep
This study details slaughter and meat quality traits of lambs and yearlings from Merinos that were divergently selected for reproduction, Dormers and SA Mutton Merinos. It was found that there is a difference in carcass quality between the two most popular breeds used as terminal sires on merino ewe flocks. It appears as if selection for lean growth is required to improve the quality of mutton.
b) To determine whether meat traits in the South African ovine genetic resource is affected by additive and non-additive genetic effects in South African sheep
The previous genetic and crossbreeding parameters will be updated in the coming year to improve on the estimates reported in the 2018 executive summary. With the bigger dataset described under the previous heading it will be possible to obtain more accurate genetic parameters with smaller standard errors.
c) To determine whether access to genomic information using the Ovine SNP50K bead chip will add to breeding value predictions based on pedigree information alone
It was concluded that the continued generation of genomic data to allow for more fundamental analyses on this and other resource flocks should be prioritized.
d) Determining the accuracy of imputation from 12K to 50K using an Australian reference population
Following imputation from a 15k to 50k density, mean accuracy levels of below the required 90% was observed but the observed results suggest that across country imputation could remain useful. Imputation from reference panels genotyped at densities higher than 50k as well as research into across country prediction is recommended.
e) Prediction of genomic breeding values using combinations of South African and Australian genotypic information
The project team will continue collaboration with the Australian group in order to make progress with this objective.