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1126
Management and genetic components of fertility indicators in dairy cattle

Wednesday, July 20, 2016: 3:45 PM
151 G (Salt Palace Convention Center)
T.M. Goncalves , University of Illinois, Champaign-Urbana, IL
D. Gonzalez-Pena , Zoetis, Kalamazoo, MI
H. Jeong , University of Illinois, Champaign-Urbana, IL
P. J. Pinedo , Colorado State University, Fort Collins, CO
J. E.P. Santos , University of Florida, Gainesville, FL
G. M. Schuenemann , Department of Veterinary Preventive Medicine, The Ohio State University, Columbus, OH
G. J.M. Rosa , University of Wisconsin - Madison, Madison, WI
R.O. Gilbert , Cornell University College of Veterinary Medicine, Department of Clinical Sciences, Ithaca, NY
R. C Bicalho , Cornell University, Ithaca, NY
R. Chebel , University of Florida, Gainesville, FL
K. N. Galvão , Department of Large Animal Clinical Sciences; University of Florida, Gainesville, FL
C. M Seabury , Texas A&M University, College Station, TX
W. W. Thatcher , Department of Animal Sciences, University of Florida, Gainesville, FL
S. L. Rodriguez Zas , University of Illinois, Urbana, IL
Abstract Text:

Management and genetic strategies are employed to attain high fertility rates in dairy farms. These high rates in turn enable higher profits from higher milk production, higher replacement rates, higher genetic progress, and lower expenses compared to those in systems with lower fertility efficiency. The goal of this study was to characterize the joint effect of management and genetic variation on fertility indicators that are linked to the cost-effectiveness of diary production systems. Fertility, disease, production, environment, and pedigree records from over 6,000 Holstein cows across the U.S Pacific, Southeast, Midwest and Southwest regions were analyzed. Binary fertility variables included pregnancy at first and second artificial insemination (AI), pregnancy loss after first and second AI, ovarian cyclicity status, and open status +100 d after calving. Explanatory variables included AI method, farm, lactation number, season, body condition score at 35 d post-calving, milk yield during the first three test-days, retained placenta, twin calving, dystocia, ovarian cyclicity status, open status +100 d after calving, pregnancy at first AI, and pregnancy loss after first AI. Sire of the cow was the random effect in the models. First lactation cows had significantly higher odds of pregnancy at first AI, higher odds of +100 d open status, lower odds of cyclicity than later lactation cows. The odds of pregnancy loss after first and second AI tended to be lower in first lactation cows relative to higher lactation cows. Cyclicity was significant and negatively associated with the odds of pregnancy loss at second AI and was positively correlated with pregnancy loss at first AI, albeit not significant. Calving of twins significantly reduced the odds of cyclicicty. Retained placenta and timed AI were associated with significantly higher odds of +100 d open status than estrus-guided AI and not retained placenta, respectively. Higher body condition score was positively and significantly associated with odds of cyclicity. The odds of pregnancy after first and second AI were lower among cows calving during summer relative to winter; likewise, the odds of pregnancy loss after first and second AI were higher during the summer. Heritability estimates for the fertility variables studied ranged from 0.03 (pregnancy at first AI) to 0.12 (pregnancy loss at first AI). These results highlight availability of genetic variation and the major relevance of non-genetic component on fertility indicators. These findings contribute to a long-term multistate project database (USDA-NIFA-AFRI-003542) for direct measures of fertility.

Keywords: reproduction, pregnancy, milk