The Genetics of Feed Efficiency in Cattle

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The Genetics of Feed Efficiency in Cattle

• Dr. D.H. Denny Crews, Jr.
• Research Scientist, Beef Quantitative Genomics
• National Study Leader, Livestock Genetics
  Genomics
• AAFC Research Centre, Lethbridge, Alberta

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Many Measures of Efficiency

• Probably two dozen measures of efficiency have
  been described in beef cattle
• Feed conversion ratio is a gross measure of
  efficiency
• Genetic trend has been positive along with growth
• Rg (FCR, growth) -0.61 to -0.95
• Related to increased mature weights and
  therefore, maintenance energy requirements
• Lends poorly to selection
• Most selection pressure on growth rate

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Reducing Inputs

• Very little genetic improvement has been aimed at
  reducing input costs
• Feed costs are the largest non-fixed cost of beef
  production
• gt70 of total variable costs
• Daily feed intake (dDMI) is heritable (h2 0.34
  based on 23 studies Koots et al., 1994a) and
  therefore likely to respond to selection

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Reducing Inputs Feed Efficiency

• Gross efficiency (Archer et al., 1999 gain/feed)
  and feed conversion ratio (FCR, feed/gain) have
  been discussed for more than 30 years, along with
  at least 20 other so-called efficiency
  measurements
• Most have at least moderate heritability (gt 0.32
  - 0.37) and strong genetic correlation with growth

?GFCR WWT (RgFCR,WWT) (h2 WWT) (i WWT)
(sg(FCR)) -0.21 kgd-1/gen
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Selection FCR

• Adding feed conversion ratio to breeding
  objectives would have the following implications
• Additional ?G for growth the most immediate
  concern is that with mature size (RgFCR,MWT gt
  0.50)
• Disproportionate selection on dDMI versus ADG.
  Gunsett (1984) discussed the problems associated
  with selection for ratio traits
• Negative genetic trend in FCR does not translate
  to incremental improvement in feed efficiency
• Changes in FCR can be made without changing
  efficiency ( ADG)
• Selection response is usually unpredictable
  (Gunsett, 1984)

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RFI Definition

• Residual feed intake (syn. net feed efficiency)
  is defined as the difference between actual feed
  intake and that predicted by regression
  accounting for requirements of production and
  body weight maintenance
• dDMI CG ADG BWT other production RFI
• Regression can be either phenotypic or genetic
• Forced independence with growth rate, stage of
  production and weight alleviates problems with
  correlated response
• RFI phenotypes are independent of age, stage of
  production, and previous plane of nutrition

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An Expensive Phenotype

• Cost of data collection is high
• 150-175 per head for equipment alone
• Intensive 70-90 d test period
• Limited numbers of animals with phenotypes
• Technology is still developing
• Reduction in altered feeding behavior Individual
  intake on group-fed cattle
• Commercial test facilities largely unavailable

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Potential Returns

• Most agree RFI is moderately heritable (0.30 to
  0.40)
• Can force independence with any production trait
• Typical RFI generally uncorrelated with body
  composition
• Preliminary research reports
• Uncorrelated with mature size
• Highly positive genetic correlation with mature
  cow efficiency
• No evidence of antagonism with reproductive merit
• Phenotypic and genetic variance
• 5-7 lb per day phenotypic difference among
  yearling bulls
• Similar variability among crossbred steers during
  finishing

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Differences in RFI groups
Crews et al., 2003
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Potential Industry Impact

• Our results show that the more efficient half of
  steers gained the same amount of weight, produced
  carcasses with the same yield and quality grades
  with the same amount of time on feed but consumed
  390 pounds less feed than the less efficient
  half.
• In a region with 2 million head processed per
  year, that 780 million pounds of feed costs
  almost 40 million.

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RFI Genetic Variability

• Several studies have estimated genetic variance
  and heritability for RFI

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RFI Adjusted for Body Composition
Trait
of DFI variance
Rank Correlation, RFI-1
MWT ADG
67.9 8.6
1.00
Gain in Empty Body Fat
3.9
0.92
1.1
0.90
Gain in Empty Body Water
Basarab et al. (2003)

• Adding gain in RTU rib fat and(or) RTU
  intramuscular fat provided similarly small
  increases in model R2

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RFI Genetic Correlations
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Phenotypic Regression RFI and Production

• RFI is defined as the component of feed intake
  that is phenotypically independent of production
• Recent studies have shown significant non-zero
  genetic correlation of RFIp with production, body
  weight, etc.
• RFIp usually contains a genetic component due to
  production
• The phenotypic variance of RFIp is completely
  described by
• Heritability of feed intake and production
• Genetic and environmental correlations of feed
  intake with production
• (Kennedy et al., 1993)

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Repeatability of RFIp

• Archer et al. (2002) measured intake and derived
  RFIp on heifers postweaning and then on open cows
  following weaning of their second calf
• dDMI, ADG, MWT, FCR and RFI considered different
  traits between cows and heifers to estimate
  genetic correlations
• Rg gt 0.85 strongly indicates genetic equivalence

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RFI and Multiple Trait Selection

• Single trait selection is not advisable
• Few attempts have been made to incorporate RFI
  into selection schemes
• An example multiple trait index was developed by
  Crews et al. (2006)

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Index Values
I -10.12 (RFI) 24.79 (ADG) 0.09 (YWT) N (
100 , 7.812 range 80.1 115.7)
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Correlations of Index Value with Component Traits
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Summary

• RFI may be a candidate for genetic evaluation and
  improvement systems
• Independence with growth, body weight, and any
  identifiable source of dDMI covariance can be
  forced
• Heritability is at least as high as early growth
  but genetic variance is limited
• Probably enough to make substantial economic
  improvement
• Multiple trait selection schemes still required

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Summary

• Genetic improvement in efficiency of feed
  utilization is higher-hanging fruit

John Pollak, BIF 2002
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Thank you

• dcrews_at_agr.gc.ca
• 403-317-2288