Use of computed tomography based predictors of meat quality in sheep breeding programmes
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Date
28/06/2016Author
Clelland, Neil
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Abstract
One of the main drivers influencing consumers in the purchasing of red meat is the level of
visible fat, and this is particularly important in lamb, with lamb often being perceived as
fatty. Consumer-driven preference for leaner meat, coupled with the meat processing
industries preference for a reduction in carcass fat, increasing lean meat yield and reducing
waste, have led to continued selection for lean growth and reduced fatness in several meat
producing species The perception of lamb being fatty could be directly targeted in isolation
by reducing overall fat levels, however there are related effects on meat (eating) quality, and
the combined improvement and consistency of meat (eating) quality and the reduction of
overall fatness is more complicated.
It is apparent that fat content plays a significant role in meat (eating) quality. Generally four
major fat depots are recognised in animal carcasses, these are: subcutaneous (under the skin);
internal organ associated; intermuscular (between muscles and surrounding muscle groups);
and intramuscular (marbling, between muscle fibres), the latter generally regarded as having
the greatest association with meat (eating) quality.
X-ray computed tomography (CT) can measure fat, muscle and bone in vivo in sheep and CT
predictions of carcass composition have been used in commercial UK sheep breeding
programmes over the last two decades. Together with ultrasound measures of fat and muscle
depth in the loin region, CT measured carcass fat and muscle weights have contributed much
to the success of breeding for leaner carcasses and increased lean meat yield. Recently it has
also been considered that x-ray computed tomography provides the means to simultaneously
estimate IMF and carcass fat in vivo.
Thus the aim of this project is to investigate the use of two and three-dimensional x-ray
computed tomography techniques in the estimation of meat (eating) quality traits in sheep,
and to further investigate the genetic basis of these traits and the possibility of their inclusion
into current breeding programmes. The primary approach was the use of two-dimensional x-ray computed tomography, determining the most accurate combination of variables to
predict IMF and mechanical shear force in the loin. The prediction of mechanical shear force
was poor with accuracies ranging from Adj R2 0.03 – 0.14, however the prediction of IMF in
the loin was more promising. CT predicted carcass fat weight accounted for a moderate
amount of variation in IMF (R2 =0.51). These accuracies were significantly improved upon
by including other information from the CT scans (i.e. fat and muscle densities, Adj R2
>0.65). Average muscle density in a single or multiple scans accounted for a moderate
amount of the variation in IMF (Adj R2 = 0.51-0.60), and again accuracies R2 >0.65 were
achieved, independent of CT-measured fat areas or predicted fat weights. Similar results
were achieved with the use of three-dimensional CT scanning techniques (Adj R2 0.51 –
0.71), however, there was a dramatically increased requirement for image analysis when
compared to two-dimensional techniques, and the increase in accuracy was not significant.
This suggests that the current method of two-dimensional image capture is sufficient in the
estimation of IMF in vivo in sheep.
The prediction equations developed as part of this work were applied across divergent breed
types (Texel, Scottish Blackface and Texel cross mule), to investigate the transferability of
the prediction equations directly across to other breeds of sheep. As part of this study, the
IMF levels across the breed types and sexes were also compared and found that IMF was
significantly affected by breed type (P<0.001) with Scottish Blackface lambs having higher
levels of IMF when compared to Texel cross mule lambs, and the lowest levels of IMF were
in the purebred Texel lambs at the same liveweight or similar levels of carcass fatness. Sex
also had a significant effect on IMF across breeds (P<0.001) with females having higher
levels of IMF at similar levels of both carcass fat and liveweight, and within breed, females
had significantly higher levels of IMF in both the purebred Texel and Scottish Blackface
lambs, when compared at similar levels of carcass fat and liveweight (P<0.05). Using the
models previously developed in purebred Texel to predict IMF in the Scottish Blackface and
Texel cross mule, accuracies were found to be R2 = 0.57 – 0.64 and R2 = 0.37 – 0.38
respectively. Providing evidence that the equations are transferable across to some breeds
more successfully than others, however, given that there is currently no method of accurately
estimating IMF in vivo, accuracies across to both breeds are acceptable.
The genetic parameter estimation was unsuccessful using the same research-derived dataset
as previously employed in the study. However the ambition was always to investigate the
genetic relationships between traits in a large industry dataset, exploiting the wealth of
commercial CT information available. These investigations were considerably more
successful, and among the first to present genetic parameters of novel CT-derived IMF
estimates. The results found moderate heritability estimates of h2 0.31 and 0.36 for the final
selected prediction equations, with clear indications that one model not including CT
predicted carcass fat or any other fat measures, was more independent of these measures and
the two separate prediction methods were highly genetically correlated with each other (rg =
0.89).
The results from this study show that not only is it possible to accurately estimate IMF levels
in the loin of Texel sheep using CT scanning, but that, until breed specific predictions are
developed, the methods developed in this study are transferable across some breed types.
The results also show that CT predicted IMF is heritable, independent of overall fatness and
has the potential to be included in current breeding programmes. These findings can now be
used to develop breeding programmes which enable breeders to make the best use of CT
scanning technology to improve carcass composition while maintaining or possibly
improving aspects of meat (eating) quality.