Predicting Holstein Heifer Growth by Genomic Traits
Assessment of heifer weights and ADG is a recommended practice for managing dairy heifers, however the genetic variance of mature animal size obfuscates the meaning of a limited number of measured weights and ADG on a commercial dairy. The objective of this study was to use type traits and PTA milk from the heifer’s first genomic test to predict the 24-month body weight. This would allow an adjusted growth curve to be applied to heifers individually and management decisions made on the animal’s current body weight status or deviation or both from its genetic potential. A database of heifers (n=802, genotyped n=561) and their body weights (n=2373, ranging from 4 months of age to 26 months) was used in this study. An exponential model for heifer growth by age was made for all body weights, to fix the shape of the growth curve. A non-linear regression was then fitted using the exponential model and the individual animal’s measurements to solve for the model coefficient, setting the amplitude of the growth curve by animal. This resultant coefficient was regressed against the animal’s PTA milk and type traits, using a criteria of P>0.20 for removal of variables. The resultant regression equation (R2=0.12) consisted of terms: PTA milk, final score, stature, body depth, rear leg side and rear view, udder height, udder depth, front and rear teat placement, and teat length. Using the genomic model by animal the mean square error for the growth model was reduced from 4937 to 4451. The present model, based on genomic body traits, did not yield the desired level of body size prediction to be utilized as an on-farm heifer assessment tool.
Heifer, Growth, Management