The Relationship of Different Measures of Growth with Feed Efficiency in Central Highland Buck

Authors

  • Zeleke Tesema Sirinka Agricultural Research Center, P.O.Box 74, Woldia, Ethiopia
  • Solomon Tiruneh Sirinka Agricultural Research Center, P.O.Box 74, Woldia, Ethiopia

Keywords:

feed efficiency, growth efficiency, Kleiber ratio, relative growth rate, residual feed intake

Abstract

Improving the efficiency of feed utilization is a primary goal in goat breeding strategies. Thus, different measures of
feed efficiency were evaluated, their relationships with growth-related traits of the Central Highland bucks were
estimated, and estimation equations for feed efficiency were developed. The measures of growth such as initial
weight (IWT), final weight (FWT), absolute growth rate (AGR), relative growth rate (RGR), growth efficiency (GE),
and Kleiber ratio (KR) were measured from twenty-four bucks. The feed efficiency traits were dry matter intake
(DMI), feed conversion ratio (FCR), feed efficiency (FE), residual feed intake (RFI), and residual weight gain
(RWG). Data were analyzed using the GLM procedure of statistical analysis system. The mean FWT, DMI, AGR,
FCR, FE, RGR, GE, KR, RFI, and RWG of bucks were 26.1±2.73 kg, 801.2±102.1 g/day, 54.8±23.6 g/day,
17.6±9.44 g DMI/g AGR, 0.07±0.02 g AGR/g DMI, 321.7±10.4%/day, 22.1±10.6%, 4.73±1.87 g/kg 0.75, 0.46±0.07
g/day and -0.50±0.02 g/day, respectively. The result showed that FCR was highly correlated with AGR (r=-0.78),
GE, (r=-0.77) and KR (r=-0.81). Moreover, strong correlations were observed among FE and growth-related traits
(r=0.95 for FE-AGR, 0.97 for FE-GE and 0.96 for FE-KR). The FWT (R2=0.47) and GE (R2=0.94) were the
important predictors for DMI and FE, respectively. The combination of GE, KR, and RGR appeared to be more
useful traits in predicting the FCR (R2=0.86). The GE and IWT were significantly predicted the RWG with higher
accuracy (R2=0.95). The efficiency of feed utilization of bucks can be estimated with high accuracy using some
growth-related traits. However, further research using enough sample size is imperative to ensure reliability and to
enhance the accuracy of prediction.

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Published

2023-09-05