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In Inde dexes es to se o select lect Angus gus si sires es for or us use e on on dai airy y co cows ws Stephen Miller Angus Genetics Inc. Jason Archer AbacusBio Ltd Beef on dairy a growing market Understanding the US


  1. In Inde dexes es to se o select lect Angus gus si sires es for or us use e on on dai airy y co cows ws Stephen Miller – Angus Genetics Inc. Jason Archer – AbacusBio Ltd

  2. Beef on dairy – a growing market

  3. Understanding the US beef x dairy system and issues Study tour in December • Packers Feeders • • Dairy operations • Calf ranches USDA dairy genetic • evaluation scientists

  4. Key messages Dairy sector • Calving ease a priority for dairy sector Feed yard • Growth and conversion in feed yard is an issue for Angus x Jersey – Longer on feed, finished at lighter weights • Need to look like beef animals – Tall and narrow don’t fit Processor • Carcass length can be a problem in Angus x Holstein • Sunken strips can be a problem – more-so in Angus x Jersey • Quality grade is generally acceptable

  5. Wish-lists • Calving ease a priority Calving ease a priority • • Need additional growth • Avoid bulls which are too tall (height penalty) • Need additional muscle • Extra muscle desirable • Height not an issue “Moderate framed, easy calving, “High growth, easy calving, very muscular bull, with marbling muscular bull, with growth prioritized over growth” prioritized over marbling”

  6. $Value – birth to carcase $M $M $B $B Calving Ease ✔︐ Growth to weaning ✔︐ Milk ✔︐ Mature weight ✔︐ Fertility ✔︐ Docility ✔︐ Foot score ✔︐ Post-weaning growth ✔︐ Post-weaning intake ✔︐ Carcase weight ✔︐ Yield Grade ✔︐ Quality Grade ✔︐

  7. $Value – birth to carcase $M $M $B $B $AxH $AxJ Calving Ease ✔︐ ✔︐ ✔︐ Growth to weaning ✔︐ ✔︐ ✔︐ Milk ✔︐ Mature weight ✔︐ Fertility ✔︐ Docility ✔︐ Foot score ✔︐ Post-weaning growth ✔︐ ✔︐ ✔︐ Post-weaning intake ✔︐ ✔︐ ✔︐ Carcase weight ✔︐ ✔︐ ✔︐ Yield Grade ✔︐ ✔︐ ✔︐ Quality Grade ✔︐ ✔︐ ✔︐

  8. $Value – birth to carcase $M $M $B $B $AxH $AxJ Utilises economics from USA Net Merit Calving Ease ✔︐ ✔︐ ✔︐ assumptions Growth to weaning ✔︐ ✔︐ ✔︐ Milk ✔︐ Mature weight ✔︐ Fertility ✔︐ Docility ✔︐ Foot score ✔︐ Post-weaning growth ✔︐ ✔︐ ✔︐ Post-weaning intake ✔︐ ✔︐ ✔︐ Carcase weight ✔︐ ✔︐ ✔︐ Yield Grade ✔︐ ✔︐ ✔︐ Quality Grade ✔︐ ✔︐ ✔︐

  9. $Value – birth to carcase $M $M $B $B $AxH $AxJ Calving Ease ✔︐ ✔︐ ✔︐ Growth to weaning ✔︐ ✔︐ ✔︐ Milk ✔︐ Mature weight ✔︐ Growth from birth Fertility ✔︐ to slaughter Docility ✔︐ Foot score ✔︐ Post-weaning growth ✔︐ ✔︐ ✔︐ Post-weaning intake ✔︐ ✔︐ ✔︐ Carcase weight ✔︐ ✔︐ ✔︐ Yield Grade ✔︐ ✔︐ ✔︐ Quality Grade ✔︐ ✔︐ ✔︐

  10. $Value – birth to carcase $M $M $B $B $AxH $AxJ Calving Ease ✔︐ ✔︐ ✔︐ Growth to weaning ✔︐ ✔︐ ✔︐ Milk ✔︐ Re-parameterized for Mature weight ✔︐ dairy beef system Fertility ✔︐ - Slower growth Docility ✔︐ - Poorer conversion Foot score ✔︐ - Less fat cover - Fed for longer Post-weaning growth ✔︐ ✔︐ ✔︐ - Slaughtered lighter Post-weaning intake ✔︐ ✔︐ ✔︐ Carcase weight ✔︐ ✔︐ ✔︐ Yield Grade ✔︐ ✔︐ ✔︐ Quality Grade ✔︐ ✔︐ ✔︐

  11. $Value – birth to carcase $M $M $B $B $AxH $AxJ Calving Ease ✔︐ ✔︐ ✔︐ Growth to weaning ✔︐ ✔︐ ✔︐ Milk ✔︐ Mature weight ✔︐ Fertility ✔︐ Docility ✔︐ New traits added to penalize bulls with poor Foot score ✔︐ muscling or excessively tall Post-weaning growth ✔︐ ✔︐ ✔︐ Post-weaning intake ✔︐ ✔︐ ✔︐ Carcase weight ✔︐ ✔︐ ✔︐ Yield Grade ✔︐ ✔︐ ✔︐ Quality Grade ✔︐ ✔︐ ✔︐ Muscling ✔︐ ✔︐ Height ✔︐

  12. Determination of Muscling 1.8 1.6 1.4 1.2 Ultrasound RIB_EPD 1 0.8 0.6 0.4 0.2 0 0 20 40 60 80 100 120 140 160 -0.2 ScanWT EPD

  13. Determination of Muscling 1.8 1.6 1.4 1.2 Ultrasound RIB_EPD 1 0.8 0.6 0.4 0.2 0 0 20 40 60 80 100 120 140 160 -0.2 ScanWT EPD These animals all have similar Weight EPD, but vastly different Ultrasound RIB-EYE Area EPD

  14. REA EPD and Muscling 1.5 Poor muscling will lead to 1 increased Muscling EPD percent Sunken 0.5 Strips 0 0 0.5 1 1.5 -0.5 -1 REA EPD Sunken Strip discount is $20/CWT Sunken Strip frequency 3X higher in AxJ vs. AxH Creates a non-linear economic emphasis

  15. Modelling thresholds Threshold $V 1 $V 2 Rib Eye Area distribution of progeny

  16. Modelling thresholds Threshold $V 1 $V 2 Rib Eye Area distribution of progeny

  17. Modelling thresholds Rib Eye Area EPD Threshold -1 -0.5 0 0.5 1 $V 1 $V 2 Rib Eye Area distribution of progeny Penalty per carcase Proportion too flat

  18. Modelling thresholds Yearling Height EPD -1 0 1 2 Threshold Height Penalty Applied $V 1 $V 2 Height distribution of progeny

  19. Two Indexes in the end Coming later this summer 0.95 Correlation on Current $AxH $AxJ Sires Angus on Angus on Holstein Jersey Value Value

  20. Correlation to $B is moderate Result: significant re-ranking 0.95 Correlation $AxH on Current $AxJ Angus on Sires Holstein Angus on .72 .67 Value Jersey $B Value

  21. The dairy cow is to the beef industry what the laying hen is to the broiler industry Need to put a little meat on them bones

  22. Rib-eye is to the dairy indexes what carcass weight was to $B Correlations rrelations $B $B $AxH xH $AxJ CW EPD 0.74 0.41 0.54 REA EPD 0.54 0.73 0.81 Correlation across ~10,000 current sires

  23. $B and YH EPD are positively correlated (0.47) 250 200 150 $B 100 50 Top 1% Thresh hold for YH 0 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 YH EPD Correlation between YH EPD and $B is 0.47

  24. Can you see the rising fish? 250 200 150 $B 100 50 0 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 YH EPD

  25. $AxH Turns the fish from rising to level Correlation between YH EPD and $AxH is Zero

  26. Comparing Emphasis $AxH $B $AxJ Calving Ease Growth Marbling Yield Efficiency Muscling Height

  27. Poorest 10 CED from top 100 on $Value $B $B $AxH $Ax AxJ -11 3 -4 These -9 3 0 bottom 5% -7 3 1 of the breed -5 4 1 for CED -4 4 2 don’t make the top 100 -2 5 2 on AxJ or -1 5 3 AxH -1 6 3 1 6 4 1 6 4

  28. Highest 10 YH from top 100 on $Value $B $B $AxH xH 1.8 1.3 1.6 1.2 1.5 1.1 Top1% of the breed 1.4 1.1 for YH is 1.4 1 1.3. Far 1.4 1 fewer of 1.4 1 those in Top 1.3 1 10 on $AxH. 1.3 0.9 1.3 0.9

  29. Far Fewer Top $AxH bulls in Top 1% for YH 9,690 Current Sires 163 > 1.3 YH EPD 124 over 15 over 150 $B 150 $AxH

  30. More ways to fail Poor Calving Ease Poor Muscling Too much height Longer Feeding Period Bulls that tick all the “wrong boxes” will compound discounts and have a seriously negative $AxH or $AxJ -200 AxH or AxJ is possible.

  31. Average of Top 100 Current Sires on each index 250 200 150 100 50 0 -50 Top 100 $B Top 100 $AxH Top 100 $AxJ Compare within not Average EPD of Top 100 bulls on each index between indexes

  32. In a Nut Shell • Growth – Similar to $B – Highest in $AxJ • More CED • Muscle – more in $AxH and most in $AxJ • Height – High YH EPD penalized in $AxH • Similar CW • Similar MARB in $AxH, less in $AxJ

  33. Qu Questions/D tions/Discu iscussion ssion Stephen Miller, Ph.D. Genetic Research Director smiller@angus.org 816-383-5157

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