Vasse presentation stephen lee


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Vasse presentation stephen lee

  1. 1. Reporting outcomes from social science and industry herd data analysis Stephen Lee Ian Nuberg Wayne Pitchford
  2. 2. Maternal Productivity Difficult to define:  the outputs in the beef production system relative to the inputs • weight of calf weaned / MJ energy cow calf unit • cow weight change (kg) Traits include: Reproductive performance (no. of calves weaned per cow exposed) Pre-weaning growth of progeny Change in size and body composition of the cow Motivating concern  How does increasing production potential impact on breeding herd efficiency?
  3. 3. Research Approach In-depth interviews with seedstock breeders on role and key influencers of maternal productivity Maternal Productivity Data from 4500 industry animals over first and second parity •hypotheses generating – logic of breeding and management Management and breeding implications for cows differing in genetic potential 1. associations between performance potential (EBVs) and body energy reserves 2. genetic parameter estimates 3. reproduction differences 4. output traits (calf weaning weight, cow weight change)
  4. 4. Breeding goals • Majority of breeders had similar goals: – low cost of production – high quality product (marbling and yield) – multiple end market specifications – structural soundness – temperament • Contrasting on-farm animal management approach
  5. 5. Diverse management
  6. 6. Controlled input ‘I have a real problem with fat and I touched on this before in regard to cow condition. Fat is expensive to put on, you put it on, the animal goes to the processor and they cut if all off. When you feed it (fat) on and it costs you somewhere in the vicinity of 40% of every mega- joule you end up using in the process of putting it on and then re-metabolising it again, that’s just crazy’ ‘If you couldn’t do it any other way and we were dropping 10% conception rate, then you have to have that fat there. If you can have yield and have efficient cows, then to me the wrong thing for a seedstock business to do is to push positive fat.’
  7. 7. Variable input ‘We have done a study of what it costs us to produce dry matter during the year and it is about 4 times as cheap during spring compared to autumn. So that says a lot about when you put condition on and when you can let the cows coast through. The ones that have stayed in the system have this ability where they can put weight on quickly in spring when there is compensatory growth and they can draw down on those reserves when things are tougher and then gain weight quickly when the feed is available.’ ‘I use the carcass traits more for maternal productivity than for carcass. It is huge, rib and rump, whenever I use an AI sire I have a really good look at his fat EBVs. When I use a negative fat bull the drop out rate in our maternal side is too high.’ ‘I know the feedlot buyer wants high yielding steers but I can’t afford that in the cow herd.’
  8. 8. Maternal Productivity Fertility – 365 day breeding cycle Calving ease Calf growth Pre-calving energy reserves P8 and Rib EBVs 600d Wt EBV EMA EBV Feed Intake (energy) Milk EBVFrame Maturity pattern
  9. 9. EBV Standard Deviations P8 RIB 600d Wt MILK EMA IMF DC EBV Mat Pat. Angus 1.1 1.0 13.2 3.9 1.9 0.7 1.4 1.0
  10. 10. Sire 600d Wt MCWt Milk (kg) DC (days) Rib Fat (mm) Rump Fat (mm) RBY (%) IMF % Long Fed Index ($) 1 +122 +119 +20 -8.7 -3.2 -3.2 +1.6 +0.6 +103 2 +57 +50 0 -4.7 +4.5 +3.6 -2.0 +3.7 +98 Breed Av. +86 +80 +12 -2.5 -0.1 -0.1 +0.2 +0.8 +87 962 progeny 77 herds 623 progeny in 20 herds
  11. 11. Percentage increase in P8 fat depth for 1mm increase in P8 EBV %change in P8 fat depth A 1mm increase in P8 fat EBV for Angus at pre-calving first parity (PC1) increased scanned P8 fat depth by 14.6% 13.1 12.3 11.9 14.6 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 W2 PC2 W1 PC1 P8 P8
  12. 12. Maternal Productivity Fertility – 365 day breeding cycle Calving ease Calf growth Pre-calving energy reserves P8 and Rib EBVs 600d Wt EBV EMA EBV Feed Intake (energy) Milk EBVFrame Maturity pattern
  13. 13. Relationship between Rib and P8 EBVs and observed days to calving A 1mm increase in P8 EBV resulted in reduced observed DTC by 0.95 days in Spring and 2.45 days in Autumn -2.93 -2.45 -1.22 -0.95 -4.00 -3.00 -2.00 -1.00 0.00 Rib P8 Days to calving Spring Autumn
  14. 14. -4 -3 -2 -1 0 Rib Days Autumn Spring Relationship between pre-calving rib fat depth and observed days to calving In Spring calving cows for every extra millimetre pre-calving scan rib fat depth, observed days to calving was reduced by 0.39 days, this effect was larger in Autumn calving cows (-2.89).
  15. 15. Summary Cow management approach differed between breeders (CONTROL vs. VARIABLE) Cow management approach was linked with attitude to optimal EBVs for traits including fat, growth and milk Body composition • EBVs for P8 and Rib impact cow fat depth at pre- calving and weaning (approx 15% per standard deviation) • Body composition traits are phenotypically repeatable for pre-calving and weaning
  16. 16. Summary Days to calving and Rib and P8 EBVs Approx 1.0 days shorter DTC in spring Approx 2.5-2.9 days shorter DTC in autumn Pre-calving but not weaning cow fat depth impacts subsequent days to calving Approx 2.89 days/mm rib fat in autumn and Approx 0.39 days/mm rib fat in spring. For control input management, where it is cost effective to increase inputs (feed), the effect of increasing genetic potential for yield (leanness) is unlikely to compromise observed pre-calving energy reserves However, in variable input systems, the ability for young cows with high potential for leanness and growth to attain sufficient pre-calving energy reserves in adverse seasons may be compromised
  17. 17. Acknowledgements Ian Nuberg Wayne Pitchford Angus Australia Herefords Australia Collaborating herds!