Abstract

Abstract Fetal aging (FA) is an assisted reproductive technique in which fetal measurements collected via transrectal ultrasonography are used to estimate the day of gestation of a fetus. These estimations can then be used to generate calving date predictions, which allow producers to capitalize on the management of both pregnant and non-pregnant females to improve reproductive efficiency and profitability. Previous literature supports the accuracy of calving date predictions when fetometry is used to generate fetal age. However, there is little published research validating the accuracy of fetal aging based on technician evaluation of the fetus at the time of ultrasound. The objectives of this study were to evaluate the accuracy of calving dates predicted with subjective FA compared with the accuracy of calving dates predicted using estrus detection methods (ED). Breeding cows (n = 130) ranging in both breed composition and parity were observed for visual signs of estrus twice daily from December 2021 through February 2022. Cattle were bred via natural service, and all observed signs of estrus and copulation were recorded and used to generate calving date predictions. Cattle were palpated for pregnancy via transrectal ultrasound in April 2022, at which time subjective estimations of fetal age were recorded by ultrasound technicians and used to generate calving date predictions. Data were analyzed using SAS version 9.4 with prediction method serving as the fixed effect. Of the cattle enrolled in this study, calving date predictions were generated from 91 cows using ED and 130 cows using FA. Data analysis indicated a strong positive correlation (Spearman) between FA calving date predictions compared with reported calving dates (r = 0.79, P ≤ 0.01), as compared with a moderately positive correlation between ED calving date predictions and reported calving dates (r = 0.59, P ≤ 0.01). When stratified according to estimated fetal age, analysis indicated a moderately positive correlation between FA calving date predictions and reported calving dates for short- (r = 0.58, P = 0.01) and mid- (r = 0.60, P ≤ 0.01) bred groups, and a weak positive correlation for the long-bred group (r = 0.17, P = 0.16). Data in this study indicates that FA calving date predictions were more accurate than ED calving date predictions. Further analysis will be conducted to quantify the economic value of FA as a method of calving date prediction for producers.

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