Articles | Volume 53, issue 4
https://doi.org/10.5194/aab-53-415-2010
https://doi.org/10.5194/aab-53-415-2010
10 Oct 2010
 | 10 Oct 2010

Relationships of sire breeding values and cutting parts of progeny in Czech Fleckvieh bulls

J. Bezdíček, J. Říha, J. Kučera, A. Dufek, M. Bjelka, and J. Šubrt

Abstract. The aim of this study was to assess the effect of the meat yield breeding values of sires on highly valued parts of carcasses in their progeny. The study was carried out on Czech Fleckviehs, a breed dual purpose milk-beef production. Cutting parts evaluated were: round, strip loin and tender loin (first-class meat); rib, shoulder blade (boneless), fore shank, flank, chuck roll + neck (second-class meat) and separable fat.

The correlation analysis showed significant negative relationships only for the relative breeding values of trading classes and the rib (r=−0.2079); relative breeding values of net daily gain with strip loin (r=−0.2433). Although strip loin is an important first-class meat cut, the correlation is rather low. Correlations between other meat cuts with breeding values were non-significant. The correlation between meat cuts and age showed the same pattern as correlations between meat cuts and weight at slaughter. Significant negative correlations were found between first-class meat and increasing age (r=−0.1979) and weight (r=−0.2884). In contrast, for second-class meat there were positive correlation with increasing age and weight (r=0.3489 for age, r=0.4495 for weight). This also corresponds with the correlation between age or weight and specific first-class meat cuts (tender loin r=−0.2804, r=−0.3413, strip loin r=−0.3710, r=−0.2012) and second-class meat (sep. fat r=+0.2360, r=+0.2951, r for correlation with age and weight respectively).

Based on the calculations of canonical analysis 27.75 % explained variability was found for variables relative breeding value of net daily gain (RBVndg), relative breeding value of trading class (RBVtc), age and weight using a linear combination of variables for individual cuts. At the same time, 14.25 % explained variability was found for cut variables which can be expressed using linear combinations of RBVndg, RBVtc, age and weight.