Title of article :
Prediction equations for Warner–Bratzler shear force using principal component regression analysis in Brahman-influenced Venezuelan cattle
Author/Authors :
N. and Jerez-Timaure، نويسنده , , N. and Huerta-Leidenz، نويسنده , , N. and Ortega، نويسنده , , J. and Rodas-Gonzلlez، نويسنده , , A.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
A database consisting of 331 beef animals (Brahman-crossbred) was used to determine the multivariate relationships between carcass and beef palatability traits of Venezuelan cattle and to develop prediction equations for Warner–Bratzler shear force (WBSF). The first three principal components (PC) explained 77.53% of the standardized variance. Equations were obtained for each sex class and the total variability observed in WBSF could be explained by its orthogonal regression with carcass weight (CW), fat cover (FC), fat thickness (FT), and skeletal maturity (SM). Prediction equations were: WBSFsteers = 3.566 + 0.003(CW) − 0.033(FC) − 0.015(FT) + 0.0004(SM); WBSFheifers = 4.824 + 0.002(CW) − 0.229(FC) + 0.096(FT) − 0.064(SM); WBSFbulls = 3.516 + 0.009(CW) + 0.154(FC) − 0.129(FT) − 0.006(SM). A higher proportion of the variation was explained by the PC when variables of greater weight were selected to define each PC. The equation set presented herein could become an important tool to improve the Venezuelan carcass grading system.
Keywords :
Tenderness , Prediction Equation , Carcass , Quality , Principal Component regression
Journal title :
Meat Science
Journal title :
Meat Science