93 Feeding behavior as predictive traits of fertility and lifetime productivity in replacement beef heifers. (5th December 2019) - Olson, Cameron A; McKeown, Lisa; Block, Hushton; Li, Changxi; Basarab, John
Abstract: Fertility and longevity traits in beef cows are difficult and expensive to measure. The use of other traits to predict fertility and longevity traits in beef cows will enable selection for efficient reproduction earlier in an animal's life. The objective of this study is to identify feeding behaviours with predictive relationships to fertility, longevity, and lifetime productivity in beef cows. This study used 421 Bos taurus commercial replacement heifers born from 2004 to 2014 and followed over 1050 mating opportunities, 11 production cycles and 5 parities. Heifers were weaned at 6–7 mo of age and developed on a 90% barley silage, 10% rolled barley diet in pens equipped with 16 electronic feed bunks to monitor feed intake and feeding behaviors. Feed intake (FI), feeding frequency (FREQ), duration (DUR), head-down time (HD) and time-to-bunk (TTB) were collected over the course of the feeding trial. Phenotypic correlations indicate that as FI increased during the heifer development stage, so did subsequent cow pre-breeding and pre-calving body condition score (BCS; r = 0.43, 0.36 respectively) and total lifetime productivity (r = 0.40). As FREQ increased, pre-breeding and pre-calving BCS decreased (r = -0.16 and -0.20, respectively), as did calf birth weight (r = -0.15). As DUR increased, weak positive correlations were observed with days in herd (r = 0.10), age at first calving (r = 0.17) and calf birth weight (0.13). Increased HD would lead to increased pre-breeding and pre-calving BCS (r = 0.16, 0.23 respectively), and greater lifetime productivity (r = 0.16). Time-to-bunk was positively correlated with days in the herd (r = 0.15), and with decreased calf birth weight (r = -0.23) and pre-calving cow weight (r = -0.33). These feeding behaviour traits, collected early in life, are worthy of further investigation into multi trait regression, genetic correlations and genomic selection.