2010 10 14_Repro


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2010 10 14_Repro

  1. 1. Can we use milk recording data to predict reproduction?An improvement on the fat to protein ratio<br />A. Madouasse, J.N. Huxley, W.J. Browne, A.J. Bradley, M.J. Green<br />
  2. 2. Background<br />Start of lactation:<br />Massive increase in energy demand<br />Limited appetite<br /><ul><li>Negative Energy Balance</li></ul>41.5 days (de Vries and Veerkamp, 2000)<br />Up to 8 weeks for most cows (Heuer et al, 2000)<br />
  3. 3. Background<br />Poor reproductive performance in dairy cows:<br />Later resumption of luteal activity in cows in NEB (Heuer et al, 1999)<br />Milder oestrus expression with increasing milk yield (Cutullic et al, 2009)<br />Negative correlation between milk yield and calving interval (Haile-Mariam et al, 2003) <br />Genetic selection on yield and composition has been accompanied by poorer reproduction (Lucy, 2001)<br />
  4. 4. Background<br />Link between energy balance and milk composition at the start of lactation<br />NEB associated with:<br />Increase in milk butterfat percentage <br />(de Vries and Veerkamp, 2000)<br />Decrease in milk protein percentage<br />(Duffield, 1997)<br />Increase in the fat to protein ratio <br />(Grieve, 1986)<br />
  5. 5. Question<br />Can we predict the calving to conception interval from milk recording data?<br />
  6. 6. Materials<br />Selection from NMR data collected in 2004-2006:<br />8,211,988 individual cow recordings<br />992,625 lactations<br />483,474 cows<br />2,128 herds<br />
  7. 7. What do we want to look at?<br /><ul><li>Milk yield
  8. 8. Butterfat (% or kg)
  9. 9. Protein (% or kg)
  10. 10. Fat to Protein ratio
  11. 11. Somatic cell count</li></li></ul><li>When?<br />First 2 test-days of lactation<br />
  12. 12. How ?<br />Do you really want to know?<br />
  13. 13. Outcome: calving to conception interval<br />Calculated from recalving dates<br />Gestation length of 280 days assumed<br />Intervals categorised as:<br />[20-60] ; [61-81] ; [82-102] ; [103-123] ; [124-144]<br />Calving 1<br />Conception<br />Calving 2<br />280days<br />Calving to Conception<br />Interval<br />
  14. 14. Cumulative Probability of Conception per Interval<br />
  15. 15. How does it work?<br />
  16. 16. Can we include raw data in our model?<br />Variation in the percentage of butterfat<br />
  17. 17. Can we include raw data in our model?<br />Variation in the percentage of protein<br />
  18. 18. Can we include raw data in our model?<br />Variation in the fat to protein ratio<br />
  19. 19. Model Results<br />
  20. 20. Does the model work?<br />
  21. 21. Model Predicted Effects<br />
  22. 22. Interlude<br />The parable of the <br />jet assisted take-off<br />Darwin award, 1995<br />
  23. 23. Interlude<br />A US sergeant had fitted a jet-assisted take-off unit onto his car<br />Went to a long straight road in the Arizona desert<br />Put the gas on<br />
  24. 24. Interlude<br />The vehicle quickly reached a speed of between 250 and 300 mph <br />Continued at that speed, under full power, for an additional 20-25 seconds <br />
  25. 25. Interlude<br />The car remained on the straight highway for approximately 2.6 miles <br />The driver applied the brakes<br />Completely melting them<br />Blowing the tires<br />Leaving thick rubber marks on the road surface <br />
  26. 26. Interlude<br />The vehicle then became airborne for an additional 1.3 miles<br />Impacted a cliff face at a height of 125 feet<br />Left a blackened crater 3 feet deep in the rock<br />
  27. 27. Interlude<br />The Arizona Highway Patrol were mystified when they arrived at the site<br />The folks in the lab tried to figure it out<br />Impact on a cliff face at a height of 125 feet<br />Rubber marks on the road<br />Straight road in the Arizona desert<br />Blackened crater 3 feet deep in the rock<br />
  28. 28. End of the <br />interlude<br />
  29. 29. Have we fitted jet engines on our cows?<br />Ketosis<br />Poor reproduction<br />Uncoupling of the somatotropic axis<br />Displaced abomasum<br />Early lactation<br />Negative energy balance<br />Delayed uterine involution<br />Impaired immunity<br />Changes in milk constituents<br />Lameness<br />Insulin resistance<br />Low T3/T4<br />Steatosis<br />
  30. 30. Have we fitted jet engines on our cows?<br />Cows selected on milk production for decades<br /><ul><li>Selected for yield and constituents
  31. 31. Much of the cow resources directed toward milk production as opposed to reproduction and other functions
  32. 32. Range of metabolic perturbations</li></li></ul><li>What happens?<br />Massive quantity of energy mobilised at the start of lactation<br /><ul><li>More milk  More energy</li></ul>Fat mobilised to get energy<br />Fat present in milk<br />But <br />Fat percentage influenced by time of the year<br /><ul><li>So is the fat to protein ratio
  33. 33. Fat and fat to protein ratio unreliable as predictors of conception</li></li></ul><li>What happens?<br />Percentages of protein and lactose have much stronger associations with the probability of conception<br />Probably because of endocrine perturbations (Insulin ???)<br />They are less dependent on season<br />
  34. 34. Conclusion<br />
  35. 35. Take home!<br />Cows producing more milk at the peak synthesise less lactose and protein and mobilise more fat at the start of lactation <br />These cows: <br />Could be more likely to get mastitis and other health disorders<br />Conceive later … or not!<br />
  36. 36.
  37. 37. Acknowledgments<br />This work was funded by the <br />University of Nottingham<br />Thanks to the <br />National Milk Records <br />for providing the data<br />
  38. 38. Thanks to…SVMS Population Health<br />Special Profs / Lecturers:<br />Sheep<br /><ul><li>JasmeetKaler</li></ul>Dairy Herd Health Group:<br />Post graduate researchers<br /><ul><li>Simon Archer
  39. 39. David Black
  40. 40. Peter Down
  41. 41. Helen Higgins
  42. 42. Chris Hudson
  43. 43. AurélienMadouasse
  44. 44. Sarah Potterton
  45. 45. Adam Spencer
  46. 46. Jenny Wills
  47. 47. Paula Wilson</li></ul>Cattle<br />James Breen<br />Marnie Brennan<br />Andrew Bradley<br />Tracey Coffey<br />Richard Emes<br />Martin Green<br />Chris Hudson<br />James Husband (Special Lecturer)<br />Jon Huxley<br />JasmeetKaler<br />Nigel Kendall<br />Jamie Leigh<br />WendelaWapenaar<br />Dairy Herd Health Group:<br />Horses<br /><ul><li>John Burford
  48. 48. Sarah Freeman
  49. 49. Emma Shipman</li></ul>Aurelien.Madouasse@nottingham.ac.uk<br />http://aurelienmadouasse.wordpress.com/<br />