Submitted to: Journal of Dairy Science
Publication Type: Abstract only
Publication Acceptance Date: 6/22/2003
Publication Date: N/A
Citation: Interpretive Summary:
Technical Abstract: Considerable attention is being focused on cow fertility because of the initiation of genetic evaluations for daughter pregnancy rate (DPR) in February 2003. In order for a new trait to be accepted, the industry needs to understand its characteristics. Properties of DPR evaluations were compared with those of evaluations for other fitness traits introduced during the last decade. For cows born during 1988, 1993, and 1998, predicted transmitting abilities (PTA) for DPR averaged 0.9, 0.5, and 0.4%, respectively, which reflected a negative genetic trend. Cow PTA for somatic cell score (SCS) also had a small unfavorable trend, but cow PTA for productive life (PL) has been improving. Mean reliability (REL) for cow PTA DPR is nearly as high as REL of PTA for PL and SCS even though based on a lower heritability (0.04 for DPR compared with 0.085 for PL and 0.10 for SCS), partly because of additional observations on fertility in later lactations, or because of its lower repeatability. For 1988, 1993, and 1998 birth years, cow REL DPR was 32, 32, and 30%, respectively, compared with REL PL of 33, 32, and 31% and REL SCS of 32, 35, and 34%. For artificial-insemination (AI) bulls born during 1984 through 1988 (n = 6037), 1989 through 1993 (n = 7247), and 1994 through 1998 (n = 5425), PTA DPR averaged 0.1, 0.0, and -0.2%, respectively. Similar to cow PTA, bull PTA SCS showed a small unfavorable trend (3.11, 3.11, and 3.13), whereas PTA PL have been improving (-0.47, 0.01, and 0.14 mo). Mean bull REL DPR were 67, 67, and 59%, respectively; mean REL PL were 67, 67, and 61%, and mean REL SCS were 68, 73, and 69%. Effects of birth year and AI sampling organization on bull PTA DPR was examined. Birth year accounted for 2.6% of variation in DPR; AI sampling organization accounted for additional 0.3%. Those same effects accounted for 5.8 and 0.1%, respectively, of PL variation and for 1.1 and 0.4% of SCS variation. For bulls in active AI service, no differences were found between AI sampling organizations for DPR, although an effect was found for PL and SCS. Based on REL alone, reservations about using PTA DPR in selection programs because of its limited accuracy appear to be unwarranted.