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Genetic evaluation and best prediction of lactation persistency

Genetic evaluation and best prediction of lactation persistency. Introduction. At the same level of production cows with high persistency milk more at the end than the beginning of lactation.

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Genetic evaluation and best prediction of lactation persistency

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  1. Genetic evaluation and best prediction of lactation persistency

  2. Introduction • At the same level of production cows with high persistency milk more at the end than the beginning of lactation. • Best prediction of persistency is calculated as a function of trait-specific standard lactation curves and the linear regression of a cow’s test day deviations on days in milk.

  3. Best Prediction • Selection Index • Predict missing yields from measured yields • Condense daily into lactation yield and persistency • Only phenotypic covariances are needed • Mean and variance of herd assumed known • Reverse prediction • Daily yield predicted from lactation yield and persistency

  4. Reliabilities • Definition • Squared correlation of estimated with true persistency • Same as Rel (breeding value) • Single-trait or multi-trait (M, F, P, SCS)

  5. PersistencyVanRaden 1998 6th WCGALP XXIII:347-350 • Definition • 305 daily yield deviations (DIM - DIMo) • Uncorrelated with yield by choosing DIMo • DIMo were 161, 159, 166, and 155 for M, F, P, and SCS • DIM0 have increased over time • Standardized estimate

  6. Statistical Properties

  7. Objective • Calculate (co)variance components and breeding values for persistency of milk (PM), fat (PF), protein (PP), and SCS (PSCS) in Holsteins • Estimate genetic correlations among persistency and yield traits

  8. Data • 8,682,138 lactation records from 4,375,938 Holstein cows calving since January 1, 1997 • Best prediction of persistency • Milk (M), fat (F), protein (P), SCS • Floor and ceiling of ± 4.0 • Phenotypic reliability ≥ 50% • 1st - 5th lactations (1st required)

  9. Cow with Average Persistency

  10. Highest Cow Persistency

  11. Lowest Cow Persistency

  12. Model Repeatability animal model: yijkl = hysi + lacj + ak + pek + β(dojk) + eijkl yijkl = persistency of milk,fat, protein, or SCS hysi = fixed effect of herd-year-season of calving I lacj = fixed effect of lactation j ak = random additive genetic effect of animal k pek = random permanent environmental effect of animal k dojk = days open for lactation j of animal k eijkl = random residual error

  13. (Co)variance Components

  14. Correlations Among Persistency Traits 1Genetic correlations above diagonal, residual correlations below diagonal.

  15. Phenotypic Correlations Among Persistency and Yield

  16. Genetic Correlations Among Persistency and Yield

  17. Distribution of Sire PTA

  18. Conclusions • Heritabilities and repeatabilities are low to moderate • Routine genetic evaluations for persistency are feasible • The shape of the lactation curve may be altered without affecting production

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