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Estimation of genetic parameters for primal tissue component traits in commercial crossbred beef cattle
Knowledge of genetic parameters is required to select for optimal yield of primal cuts that may be used as the selection criteria for designing future breeding programs. This study aimed to estimate the heritability, as well as genetic and phenotypic correlations of primal cut lean and fat tissue co...
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Published in: | Meat science 2023-08, Vol.202, p.109200-109200, Article 109200 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Knowledge of genetic parameters is required to select for optimal yield of primal cuts that may be used as the selection criteria for designing future breeding programs. This study aimed to estimate the heritability, as well as genetic and phenotypic correlations of primal cut lean and fat tissue components, and carcass traits in Canadian crossbred beef cattle. All tissue component traits presented a medium to high heritability (lean 0.41 to 0.61; fat 0.46 to 0.62; bone 0.22 to 0.48), which indicates a probable increase in their response to genetic selection. In addition, high genetic correlations were found among the primal cut lean trait group (0.63 to 0.94) and fat trait group (0.63 to 0.94), as well as strong negative correlations between lean and fat component traits (−0.63 to −1). Therefore, results suggested inclusion of primal cut tissue composition traits as a selection objective in breeding programs with consideration of correlations among the traits could help in optimizing lean yield for the highest carcass value.
•Primal tissue components had higher heritable estimates than primal weights.•All lean and fat traits showed high genetic correlations among the tissue group.•Loin lean and fat correlated more strongly with estimated lean yield than other primals.•Chuck lean and fat correlated the most with total lean and fat in the carcass.•The accuracy of prediction could be increased by including tissue component data. |
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ISSN: | 0309-1740 1873-4138 |
DOI: | 10.1016/j.meatsci.2023.109200 |