Abstract
Length of the menstrual cycle was positively associated with antral follicle number in women. If this pattern is consistent in cattle, a value-added benefit to using automated activity monitors to determine estrous status could be the ability to predict antral follicle count (AFC). We, therefore, hypothesized that as inter-estrous interval increased ultrasonographic AFC would be greater in crossbred beef heifers. Over 3 yr, crossbred beef heifers (n = 1,394) were fitted with automated activity monitors for 81 d. From days 42 to 46, heifers were submitted for ultrasonographic examination to determine AFC. From days 60 to 81, heifers were visually observed twice daily for 45 min for signs of behavioral estrus. Heifers that had a behavioral estrus that coincided with a sensor-based estrus and had a previous sensor-based estrus between 15 and 26 d earlier were used for the analysis (n = 850). A combination of regression analyses and correlation analyses were applied to understand the association between data collected by sensors and follicle number determined by ultrasonographic examination. Antral follicle count was analyzed using the GLM procedure of SAS with estrous cycle length (15 to 26 d) as a fixed effect. Estrus was more likely to initiate in the early morning hours and peak activity was greater (P < 0.0001) when estrus initiated between 0200 and 0800 hours then when estrus initiated at other times of the day. Antral follicle count did not differ due to length of the estrous cycle (P = 0.87). Thus, length of the estrous cycle obtained from three-axis accelerometers cannot be used to predict follicle number in crossbred beef heifers; however, machine learning approaches that combine multiple features could be used to integrate parameters of activity with other relevant environmental and management data to quantify AFC and improve reproductive management in beef cows.