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Genetic parameter estimation and dry matter intake calculation as it applies to feed utilization in beef cattle

Date

2010

Authors

Pendley, Cory T., author
Crews, Denny, advisor
Enns, R. Mark, advisor
Carstens, Gordon E., committee member
Pendell, Dustin, committee member

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Abstract

The majority of mating systems in the U.S. beef industry have focused on increasing revenue by applying selection pressure to economically relevant traits (ERT) for outputs such as growth, calving ease, and carcass quality. There are other ERTs that affect profitability that can be improved through selection like feed intake, heifer pregnancy, and longevity. The purpose of this thesis was to expand the effective use of residual feed intake (RFI) in two distinct manners. Therefore, the objectives of the first study were to compile published estimates of heritability and genetic correlations of feed conversion ratio (FCR), RFI, average daily gain (ADG), metabolic body weight (MBW) and dry matter intake (DMI). These estimates were used to calculate weighted estimates of the respective genetic parameters. Twenty-five sets of estimates involving more than 40,000 cattle published between 1961 and 2010 were included in a meta-analysis of genetic parameters for feed intake and related traits. A generalized least squares approach was used to compute weighted mean heritability and genetic correlation estimates, as well as their SE, where weights were a function of inverse SE. Weighted heritability estimates for FCR, RFI, ADG, MBW and DMI were 0.28±0.06, 0.38±0.08, 0.32±0.08, 0.39±0.08, and 0.38±0.06, respectively. Weighted genetic correlations of FCR with RFI, ADG, MBW, and DMI were 0.60±0.07, -0.31±0.14, 0.03±0.14, and 0.35±0.11, respectively. Weighted genetic correlations of RFI with ADG, MBW were near zero, but were correlated 0.38±0.11 with DMI. The weighted genetic correlation of ADG with MBW was 0.45±0.13. These weighted heritability and genetic correlation estimates may be more useful in the design of genetic improvement programs than relying on estimates from individual studies with low numbers of feed intake observations. For the second study, daily feed intakes were recorded on 3,702 bulls and 314 heifers across nine tests between 2007 and 2010 at Midland Bull Test in Columbus, Montana. Daily feed intake was recorded and from this DMI was calculated. Genetic variances were estimated using a multiple trait animal model and average information REML. The model was equivalent for DMI, ADG, MBW and RFI which included a fixed effect of contemporary group (breed x test x pen, n=112) and a linear covariate for age at start of test (=298.28d, SD=36.65). The heritability estimate for RFIp was 0.17 ± 0.05. Genetic correlations among growth traits (ADG, MBW and DMI) were moderate to high and positive, ranging from 0.33 to 0.70. The model including DMI and RFIp failed to converge. This resulted in the need for estimation of genetic residual feed intake (RFIg), defined as the difference between DMI EBV and expected DMI EBV. Genetic regression was used to predict expected DMI EBV from the EBVs of ADG and MBW. This approach to the genetic evaluation of RFIg allows for the estimation of breeding values that may truly reflect feed utilization differences among animals without simultaneously affecting growth or body size.

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Department Head: William R. Wailes.

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