162 Detection of ovulation disorders and normal ovulation using wireless sensors of ventral tail surface temperature and neck acceleration data in Japanese Black cows

Abstract

The present study aimed to clarify the possibility of detection of ovulation disorders and normal ovulation in Japanese Black cows using wearable wireless sensors based on continuous measurements of body surface temperature (ST) and neck acceleration data. For cows with normal ovulation (n = 19, 8.5 years old, 476.2 kg), controlled internal drug release (CIDR) and gonadotrophin-releasing hormone were administered on arbitrary days of the oestrous cycle (Day −10), and oestrus was induced by CIDR removal and prostaglandin F_2α administration (Day −3). Ovulation (Day 0) was induced by gonadotrophin-releasing hormone administration on estimated oestrus day (Day −1) and was detected based on the disappearance of ≥8 mm follicles using ultrasonography at 1- to 2-h intervals. For cows with spontaneous ovarian cysts (n = 11, 8.6 years old, 471.2 kg), oestrus and the next day were defined as Days −1 and 0, respectively. Plasma concentrations of progesterone (P4) and oestradiol-17β (E2) were measured on Days −9, −6, −2, −1, 0, 1, 5, and 8. The body ST sensor was attached to the ventral tail base (Day −16), and ST was measured every 10 min for 24 days. For analysis of ST, after extracting hourly maximum ST values, the values were expressed as residual ST (RST; ST − mean ST for the same hour on the previous 3 days) for removal of circadian rhythm (Miura et al. 2017 Anim. Reprod. Sci. 180, 50-57; https://doi.org/10.1016/j.anireprosci.2017.03). The acceleration sensor (Farmnote Color, Farmnote Inc.) was attached to the neck (Day −16). Hourly oestrus level (amount of oestrus activity) was obtained from the amount of activity; the difference between the residual oestrus level (REL; same calculation as RST) and measured values of each day was used. To identify RST and REL of cows with normal ovulation and cows with ovarian cysts, the mean values and standard deviations for the same hours for 3-7 days before oestrus were calculated. Mean RST and REL for 3-7 days before oestrus were assumed according to the normal distribution. The 95% confidence range was determined using × 1 standard deviation of all hours. Values over the 95% confidence range for ≥5 h were considered to be different from the mean 4 days and the 5% level. For RST, no difference was found in both groups due to the large influence of environment, particularly low temperature. However, for REL, a difference was indicated for oestrus in all cows (P < 0.05). A large peak of REL appeared once on oestrus (>14.4 REL for 20 h) in normal cows, and three peaks occurred in <21 days (>16.2 REL for 21, 15, and 15 h) in cows with ovulation disorders (P < 0.05). The REL rapidly increased following peaking E2 and decreasing P4 to oestrus (Day −1) in normal cows. In cows with an ovulation disorder, REL increased on oestrus; however, E2 and P4 remained high and low stable to oestrus, respectively. In conclusion, oestrus activity and the characteristics of normal cows and those with an ovulation disorder can be detected by the neck acceleration sensor using the correction value.

This research was supported by The Research Project for the Future Agriculture Production Utilising Artificial Intelligence.