Genetic correlations were estimated among retail colour stability and fresh meat colour traits assessed on Merino lamb loins, as well as genetic correlations of the colour traits with lean meat yield and objective eating quality traits of intramuscular fat and shear force. The meat colour traits were confirmed to be heritable. Improving intramuscular fat or shear force is expected to lead to less redness and faster rate of browning of the meat during retail display. Selection for lean meat yield is expected to improve slightly retail colour stability.

The objective of this study was to estimate genetic correlations between mature cow traits: body condition (MBC), weight (MCW), hip height (MCH), and live animal ultrasound scan and carcass fat depth traits: P8 fat (P8) and rib fat (RIB) in Australian Angus cattle. Genetic parameters were estimated using univariate animal models, and up to four records per cow were used in the analyses for MBC, MCW, and MCH. The heritability estimates for MBC, MCW, and MCH were 0.21 ± 0.01, 0.43 ± 0.01, and 0.55 ± 0.03, respectively. The strongest genetic correlation was observed between the MBC and MCW (0.87 ± 0.01), followed by MCW and MCH (0.83 ± 0.01). Moderate genetic correlations were observed between MBC and ultrasound scan P8 fat (0.35 ± 0.03) and rib fat (0.31 ± 0.03) traits measured on heifers and steers. Genetic correlations between MBC and carcass P8 fat (0.19 ± 0.08) and rib fat (0.30 ± 0.15) were low to moderate. Progress from selection for MBC based on live animal ultrasound scan and carcass fat depth traits measured on young cattle would be slow due to low genetic correlations. Since MBC is adequately heritable, this trait could be used as a direct measure to improve cow condition through selection.

Eating quality is the primary factor influencing consumer purchasing decisions for beef products. Consumer-derived sensory eating quality traits capture the actual eating experience and are directly aligned with consumer expectations. Accurate genomic prediction of these traits can enable selective breeding, allowing for continuous genetic improvement and consistent consumer satisfaction. In this study we used an international dataset from Australia, the USA and Ireland to estimate genetic parameters for five meat eating quality traits and to evaluate the accuracy of genomic estimated breeding values under different cross-validation scenarios. Heritability estimates ranged from 0.19 to 0.31 for Australia, 0.07 to 0.20 for the USA, 0.09 to 0.17 for Ireland, and 0.14 to 0.22 for the combined dataset. Prediction accuracies for all traits were moderate when using the Australia-only reference population but increased to high accuracies when international data were included. This highlights the value of incorporating international data into the reference population, creating a larger and more diverse dataset, and ultimately improving prediction accuracies.

Recent efforts to combine the Sheep Genetics LAMBPLAN maternal and terminal sire analyses presented the opportunity to review the genomic model used in single-step genomic BLUP. This paper uses forward validation to examine the suitability of different genomic models, including metafounders, a genomic relationship matrix (GRM) constructed from a single set of allele frequencies and a breed-adjusted GRM using allele frequencies for each identified subpopulation. The metafounder model yielded slightly higher stability values and was slightly less biased than the other genomic models. Metafounders also largely resulted in higher within-breed stabilities. These results support the use of a metafounder model for the combined LAMBPLAN analysis.