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An Example from Dairy Cattle Selection: The Net Merit Index

An Example from Dairy Cattle Selection: The Net Merit Index. The Old Way of Selecting Cattle. Objectives. Document USA Net Merit index Compare national selection indexes for dairy cattle Discuss traits that affect profit and direction of selection

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An Example from Dairy Cattle Selection: The Net Merit Index

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  1. An Example from Dairy Cattle Selection: The Net Merit Index

  2. The Old Way of Selecting Cattle

  3. Objectives • Document USA Net Merit index • Compare national selection indexes for dairy cattle • Discuss traits that affect profit and direction of selection • Outline approach for estimating economic values

  4. Selection Theory • Progress = accuracy  intensity  genetic SD / generation interval • Multiply above by directional loss Accuracy = Corr (EBV, BV) Directional loss = Corr (e EBV, a EBV) Estimated (e) vs. actual (a) economic values • Direction may be the most important factor

  5. Direction of Selection Trait 1 Animals selected Trait 2 Accuracy contours

  6. Trait Direction Not Clear • Concentrated (less) or diluted (more) milk? • Large or small cows? • Skinny or fat cows? • Dairy or beef or dual purpose? • Can change direction by replacing a population instead of selecting within • Specialized populations can be useful

  7. Coefficients of variation (CV)

  8. Measures of accuracyAverages for recently proven Holstein bulls

  9. Relative Emphasis • Easily compare selection goals independent of trait units • Trait economic value times genetic SD • Divide by the sum across all traits • Multiply by 100 • Expresses relative emphasis as percent of total selection • Added traits decrease emphasis on others • Convenient way to display indexes

  10. History of USDA economic indexes(PD$, MFP$, CY$, and NM$)and Holstein Association TPI

  11. Current National Selection Indexes:Yield and Health Traits

  12. Current National Selection Indexes:Conformation and Management Traits

  13. Milk Pricing and Feed Cost($ per pound)

  14. Value of Cow Fertility • Daughter pregnancy rate (DPR) • Pregnancies achieved per 21-day cycle • 1% higher DPR = 4 fewer days open • Fertility expenses per day open • Heat detection ($20 / lact  .005) = $.10 • Semen ($15 / unit + $5 labor) *.025 = $.50 • Pregnancy exam ($10 / exam)*.012 = $.12 • Lactations too long or short = $.75 • Relative value of DPR = 7% of total

  15. Value of Calving Ease • Daughter CE value / difficult birth • Veterinary, labor costs = $50 • Calf death (20% prob) = $25 • Cow deaths before 1st test (1% prob) = $15 • Service sire CE also includes • Yield losses / lactation = $40 • Fertility and longevity losses = $30 • Relative values of each are 2% of total

  16. Linear vs Non-linear ProfitCalculation of Net Merit $ • Non-linear profit = (income – expense per lactation) number of lactations + cull value – raising cost • Linear profit obtained by taking partial derivatives at trait means • Corr (linear, non-linear) = .999

  17. Lifetime Net Merit $ • Incomes and expenses estimated from yield traits, SCS, longevity, fertility, conformation, calving ease • Example: body size • Convert from visual scores to weight • Cull price - growth cost + lactations  (calves – maintenance) = $-1.28 / kg • Less beef = more profit to dairy farmer

  18. Goals of Index Calculation • Give breeders the index they want • Breed association or AI committees • Emotional approach (TPI) • Give scientists the index they want • Add incomes, subtract expenses • Mathematical approach (NM$) • Future prices difficult to prove

  19. Top Net Merit BullsMay 2005

  20. Trait HarmonizationMark, 2003 EAAP meeting

  21. Paul’s Beef Experience

  22. Interbull Beef Proposal • Provide international evaluations within ICAR subcommittee • Combine raw data files instead of national evaluations • Favorable responses received from many countries • Charolais, Limousin most likely

  23. Conclusions - Dairy • Many traits in addition to yield contribute to dairy cattle profit • Longevity, fertility, health, and type traits get half of emphasis • Direction unclear for some traits • Indexes began in 1970’s and have improved rapidly in recent years

  24. Conclusions - Beef • An official, published goal: • Stimulates economic research • Gives breeders direction • An overall index helps breeders: • Promote their own animals • Locate superior breeding stock • Compete to improve the breed

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