DETECTION OF ESTRUS IN NELORE COWS USING INFRARED THERMOGRAPHY TECHNIQUE
DOI:
https://doi.org/10.56238/arev7n9-175Keywords:
Reproductive Biotechnology, Beef Cattle, Thermal Monitoring, Reproductive Efficiency, Infrared ThermographyAbstract
Detection of estrus in cattle is the most important factor for achieving satisfactory reproductive efficiency, requiring the development of strategies to improve its accuracy. Infrared thermography is a non-invasive, highly sensitive, simple, and effective method for detecting changes in skin surface temperature. The objective of this study was to validate infrared thermography as a tool for detecting estrus based on vulvar surface temperature in cattle. A total of 51 Nelore cows from the Nova Alta Paulista region, São Paulo, Brazil, were subjected to a fixed-time artificial insemination program. Vulvar and perivulvar temperatures were measured twice in the morning: on day 8 (D8; removal of the progesterone implant) and on day 10 (D10; 48 h later, corresponding to the day of artificial insemination). The effect of evaluation day (D8/D10) considered the animal as a random effect and the mean ambient temperature as a covariate. An interaction was observed between vulvar temperature and collection time (D8/D10), suggesting that the influence of ambient temperature on vulvar temperature differed between collection days. Estimated marginal means corrected for the covariate (ambient temperature) and standard errors in the different groups were as follows: vulvar temperature at D8 = 39.2 ± 0.24 °C, D10 = 39.5 ± 0.24 °C; perivulvar region at D8 = 38.7 ± 0.24 °C, D10 = 38.9 ± 0.24 °C. Although the experiment revealed a statistically significant difference in vulvar temperature during estrus, the results required correction for the covariate ambient temperature. The thermographic camera was able to detect an increase in vulvar temperature during the estrogenic phase; however, it did not prove to be a reliable diagnostic tool under field conditions for estrus detection in cattle, given the influence of multiple variables, particularly ambient temperature.
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