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Journal of Animal Science Abstract - Quantitative Genetics

Study of codes of disposal at different parities of Large White sows using a linear censored model


This article in

  1. Vol. 83 No. 9, p. 2052-2057
    Received: Apr 08, 2005
    Accepted: June 10, 2005

    1 Corresponding author(s):

  1. J. Arango*12,
  2. I. Misztal*,
  3. S. Tsuruta*,
  4. M. Culbertson and
  5. W. Herring
  1. Department of Animal and Dairy Science, The University of Georgia, Athens 30602-2771; and
    Smithfield Premium Genetics, Roanoke Rapids, NC 27870


To study the genetic relationship between three grouped reasons for sow removal (SR) in consecutive parities, accounting for censoring, 13,838 records from Large White sows were analyzed. Data were from seven pure-line farms having, on average, 5.9% unknown SR. Three traits were subjectively defined, each corresponding to a classification of SR (reproductive [RR], nonreproductive [RN], and others [RO]). Records for each trait could take one of five categories, according to parity at removal (0 to 4 or later). A multivariate linear censored model was implemented. The model to estimate (co)variance components and parameters included the effects of year-season, region, contemporary group, and additive genetic effects. The most common SR was related to reproduction (48.5%). Diseases of different origin and cause, old age/parity, and sow death or loss accounted for about 18, 7, and 4% of total culls, respectively. Estimates of variance components showed heterogeneity of additive genetic and residual variances for the three traits. Estimates of heritability were 0.18, 0.13, and 0.15 for RR, RN, and RO, respectively. Genetic correlations between removal codes were high (≥0.90). Results suggest sizeable additive genetic variances exist for parity at removal and different codes of removal. Different SR reasons seem to operate similarly or as a closely related genetic trait associated with fitness. In particular, RN and RO seem to be genetically indistinguishable. Data structure, definition, and volume are major limitations in studies of sow survival. A multiple-trait censored model is preferred to evaluate reasons of sow disposal. Grouped removal causes seem to be strongly genetically correlated but with heterogeneous variances, suggesting that combining all removal causes and treating the trait as parity at disposal is an alternative approach.

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