Skip to main content
ARS Home » Research » Publications at this Location » Publication #176920


item Cole, John
item Vanraden, Paul

Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 2/28/2005
Publication Date: 7/24/2005
Citation: Cole, J.B., Van Raden, P.M. 2005. Genetic evaluation and best prediction of lactation persistency [abstract]. Journal of Dairy Science. 88(Suppl. 1):379-380.

Interpretive Summary:

Technical Abstract: Cows with high persistency tend to milk less than expected at the beginning of lactation and more than expected at the end. Persistency was calculated as a function of a trait-specific standard lactation curve and the linear regression of a cow's test day deviations on days in milk. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of persistency of milk (M), fat (F), protein (P), and SCS in Jerseys. Heritabilities represent the additive genetic variance of persistency that is independent of yield and defined to have variance of 1. Data included 574,929 records for 252,669 Jersey cows calving since 1997. 3,193 AI sires received evaluations for persistency. Sire EBV for M, F, and P were similar and ranged from -0.70 to 0.75 for M; EBV for SCS ranged from -0.37 to 0.28. Regressions of sire EBV on birth year were near zero (< 0.003) but in favorable directions for all traits. Genetic correlations of M, F, and P with SCS were moderate and favorable, indicating that increasing SCS decreases yield traits, as expected. Genetic correlations among yield and persistency were low to moderate and ranged from -0.09 (SCS) to 0.18 (F). This definition of persistency is more desirable than those used in test-day models, which are often correlated with yield. A measure that is not confounded with yield may provide for simpler understanding of persistency. Routine genetic evaluations for persistency are feasible and may allow for improved predictions of yield traits.