METHODOLOGY FOR ESTIMATION OF DAYS DRY EFFECTS

Authors: Kuhn, Melvin; Hutchison, Jana

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/17/2004
Publication Date: 4/1/2005
Citation: Kuhn, M.T., Hutchison, J.L. 2005. Methodology for estimation of days dry effects. Journal of Dairy Science. 88(4):1499-1508.

Interpretive Summary: Unbiased estimates of days dry effects were obtained using field data and designed trials with 10 or fewer cows/group were shown have an unacceptable high probability of erroneous conclusions. A considerable advantage of estimates from field data, compared to designed trials, is that they have the potential for much higher precision due to large sample sizes. Since many producers rely on their own farm data for management decisions, this study provides them with confidence in their data.

Technical Abstract: The primary objective of this research was to demonstrate that, with appropriate methodology, unbiased estimates of days dry (DD) effects can be obtained from field data, even when higher producing cows receive shorter dry periods than lower producing cows. Another objective was to ascertain relevant sampling properties of designed trials for estimation of DD effects. Simulated records were used to determine bias when previous lactation milk yield is correlated with DD. Along with a model with no adjustments for cow effects, alternative models including 1) previous lactational milk yield, 2) a prior adjustment for cow effects estimated from an animal model, and 3) a combination of 1 and 2, were tested. A simulation of designed experiments was also studied. Estimates from the unadjusted model were biased downward; however, all 3 alternative analyses provided estimates of DD effects that were essentially unbiased, with a prior adjustment for cow effects and previous milk yield in the model providing the best results in terms of elimination of bias. Therefore, DD effects can be estimated from field data without bias from cow effects. The idea that studies based on field data are biased is mistaken and unfortunate since it could erroneously erode producer confidence in results based on their data. A designed trial with 2 groups and 10 or fewer cows/group is non-informative and has an unacceptably high probability of leading to invalid conclusions. Although the use of 20 cows/group reduces this probability somewhat, a minimum of 30 cows/group is considerably better and should be used whenever possible. Even with 30 cows/group, however, the power of the test is low unless the difference between DD groups for yield is at least 1130 kg. Prior correction of 305-d, mature equivalent records for cow effects, using predicted producing abilities computed by Animal Improvement Programs Laboratory, could be done in designed trials to improve power of tests and accuracy of estimates.