Twin pregnancies are highly undesirable in dairy cattle; they compromise the health and wellbeing of a cow and dramatically impair the farm economy. Recently, a genomic prediction for twin pregnancies has been developed. The objective of this study was to assess environmental and management risk factors affecting the incidence of twin pregnancies in high-producing dairy cows in their first lactation, with a special emphasis placed on the genomic prediction values of twin pregnancy. Our study population of primiparous cows proved valuable in identifying factors other than genomic predictive values that influence twin pregnancy rates. The odds ratio for twin pregnancies was 0.85 (p < 0.0001) for each unit of a prediction value increase, 3.5 (p = 0.023) for cows becoming pregnant during the negative photoperiod, and 0.33 (p = 0.016) for cows producing ≥42 kg of milk at AI, compared with the remaining cows who produced <42 kg of milk. As a general conclusion, the practical implication of our findings is that genomic prediction values can identify the risk of twin pregnancy at a herd level. Given the cumulative effect of genomic selection, selecting animals with a reduced genetic risk of twin pregnancies can contribute to reducing the incidence of twin pregnancies in dairy herds.
Keywords: breeding strategy; dark–light cycles; dead co-twin; early fetal loss; selection index; spontaneous twin reduction; standardized transmitting ability.