A comparison of methods for ranking boars from different central test stations.
Data were received from 24 test stations on 3,999 boars tested in fall 1984 and spring 1985. In an effort to increase the connectedness between stations, one reference sire was selected to produce sons (reference boars) through artificial insemination to be tested in the different stations. Fifty-two reference boars were placed across 17 of the test stations. The performance traits analyzed were average daily gain (ADG) and backfat adjusted to 105 kg ( ABF). The methods used to rank boars were: 1) individual record (ADG, ABF), 2) individual record deviated from the contemporary group mean, and 3/4) individual record plus performance of relatives (including/excluding reference boars) using expected progeny differences (EPD) estimated from a reduced animal model (RAM) statistical procedure. Ranks of boars using these four methods of genetic evaluation were compared using Spearman rank correlation methodology. The ranks of the boars changed significantly as the complexity of analysis increased for both ADG and ABF. Rank correlations between individual record and contemporary group deviations for ADG and BF were .47 and .20, respectively. Rank correlations between contemporary group deviations and RAM estimates of EPD for ADG and ABF were .53 and .41, respectively. These were significantly different from 1. 0. However, there was no significant difference between rankings based on EPD including vs excluding the reference boars. The importance of rank changes coupled with the increased accuracy of these more complex evaluation methods strongly suggest that best linear unbiased predictors of genetic value be utilized in comparing boars in central test stations.[1]References
- A comparison of methods for ranking boars from different central test stations. Mabry, J.W., Benyshek, L.L., Johnson, M.H., Little, D.E. J. Anim. Sci. (1987) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
