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Meat tenderness in Australian lamb: Data editing, environmental variation and their effects in genetic parameter estimation

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Breeding for meat quality increases the value of lambs and requires reliable genetic parameters to achieve balanced genetic progress. Meat tenderness, accomplished by selecting for lower shear force, is an important eating quality trait because of its relationship with consumer satisfaction. Factors influencing shear force, include the pH and temperature decline post-mortem which can contribute towards higher shear force values and increased variation across contemporary groups. This study explored if genetic parameters for shear force change when post slaughter covariates and heterogeneous variance are corrected for, using data from 32,223 animals from different sheep breeds. Results showed that removing extreme individuals and contemporary groups with high mean shear force values reduced residual variance, followed by a smaller reduction in additive genetic variance and little effect on heritability. Results show that edited data performed better at predicting progeny performance and reduced potential bias introduced in the genetic evaluation due to data quality. The effect of including post-slaughter covariates in the genetic analysis was tested by estimating different model predictability through regression of estimated breeding values against offspring performance, showing that the model including hot carcass weight performed better followed by the one including both carcass weight and C-site fat depth. Our results highlight that historic and current in-plant recording practices do not provide the capacity to account for non-genetic factors associated with abattoir environment that might be impacting the ability to accurately calculate shear force breeding values. In that sense, genetic evaluation can be improved by applying more rigorous data editing.

Original languageEnglish
Article number109678
Pages (from-to)1-7
JournalMeat Science
Volume219
DOIs
Publication statusPublished - 31 Jan 2025

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