Simulation of genetic control of reproduction in beef cows. III. Within-herd breeding value estimation with known breeding dates.

D. R. Notter, M. H. Johnson

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Procedures for breeding value estimation for reproductive traits with known breeding dates were developed and tested using results of a computer simulation model of genetic control of bovine reproduction. The model generated realized reproductive outputs as a function of underlying genetic variation in two independent traits: conception rate (CR), which was indicative of the ability to conceive given estrus, and PPI, the postpartum interval from calving to first estrus. Two scenarios were considered. In the first, all cows were assumed to be cycling at the start of breeding and to be bred artificially. For this scenario, breeding values for CR could be estimated from information on observed breeding and calving dates by using a categorical trait, multi-stage selection model. Breeding value estimation for PPI, however, required actual measurement of PPI because if PPI and CR are genetically independent and if all cows are cycling at the beginning of breeding, subsequent breeding and calving dates are independent of PPI. The second scenario recognized that not all females would be cycling at the start of breeding. For this scenario, the categorical trait, multi-stage selection model could still be applied for breeding value estimation for CR, but accumulation of data across years was complicated by a need to consider the lifetime reproductive pattern of the individual rather than just the sum of each year's performances. Breeding value estimates for PPI could be obtained from observed breeding and calving dates for this scenario, but required consideration of the distributional properties of PPI.

Original languageEnglish (US)
Pages (from-to)88-98
Number of pages11
JournalJournal of animal science
Volume65
Issue number1
DOIs
StatePublished - Jul 1987
Externally publishedYes

ASJC Scopus subject areas

  • Food Science
  • Animal Science and Zoology
  • Genetics

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