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Utilising genetic markers to improve the understanding of the relationship between Bos indicus content and consumer eating quality
The MSA prediction model uses easily measured commercial predictors to estimate eating quality. One of the key animal predictors in the MSA model is Bos indicus content. In the early stages of implementation of MSA producers filled out a national vendor declaration (NVD) stating Bos indicus content. The option to use a prediction based on hump height and carcass weight (BB_Hump) rather than the NVD was then introduced as an option. Over time many producers have opted for this option rather than filing an NVD. In addition to pedigree it is also possible to use SNP genotyping to predict breed composition (BB_Genotype). A series of experiments performed by CRC and MSA provided the opportunity to explore the relationship between BB_Hump, BB_Genotype and Bos indicus content and further examine their relationships with eating quality.
Data from a series of five experiments were used to explore the relationship between Bos indicus content predicted from hump height (BB_Hump) and carcass weight and a genomic estimate of Bos indicus content (BB_Genotype). Using a number of MSA datasets the usefulness of these estimates of Bos indicus content to predict consumer eating quality was also examined.
The CRC III dataset was used to estimate Bos indicus content using SNP genotype data. A series of three MSA experiments was used to estimate the relationship between hump height and eating quality in addition to examining the relationship between Bos indicus content and eating quality. Lastly, a large set of commercial records on hump height and vendor declared Bos indicus content was provided to examine the relationship between hump height and Bos indicus content.
The genomic estimate of Brahman content using SNP data was shown to be closely related to Brahman content from pedigree (R2=98%). Using data from a number of MSA experiments BB_Hump tended to underestimate BB_Genotype at the lower levels of Bos indicus content. When used in a regression model with other MSA inputs both BB_Hump and BB_Genotype were similar in their ability to predict eating quality. Using an industry dataset from properties with stable breeding programs there was some bias in the current MSA equation used to estimate BB_Hump whereby Bos indicus content was underestimated at the lower Bos indicus levels. This bias was quantified by calculating the MSA Index using BB_Hump and BB_Genotype estimates. The difference in the MSA Index was found to increase up to 70% BB_Hump and then decreased as it was constrained at 100% Bos indicus content. By adjusting the coefficients in the MSA BB_Hump equation this bias was reduced. It was concluded that BB_Hump was sufficiently accurate to use with the MSA model.
Using several MSA Data sets the accuracy of predicting eating quality was similar regardless of whether it was estimated from genomics, or from hump height and carcass weight. The relationship between BB_Genotype and BB_Hump was not linear and therefore BB_Hump tended to underestimate Bos indicus content at the lower levels. Following a slight adjustment to its coefficients used to calculate Bos indicus content from hump and carcass weight this bias was small across the Bos indicus range.
This page was last updated on 16/06/2017
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