Evaluation of infrared thermography for predicting ovulation time in dairy cows

The development and application of an algorithm to assess the ability of infrared thermography (IRT) device to determine the occurrence of ovulation in dairy cows was investigated. Twenty cows were synchronized using a controlled internal drug release (CIDR) and prostaglandinF2α. Vulva and muzzle temperatures were measured every 12 h from CIDR insertion to 32 h post PGF2α injection (to develop baseline temperatures) and then every 4 h until ovulation occurred or 128 h after PGF2α injection. Thermal images obtained with a FLIR T620 series infrared camera were analysed using ThermaCAM Researcher Professional 2.9 software. Cows were also monitored for behavioural signs of oestrus and colour changes of OestrotectTM Heat Detector devices applied to the tail head of each cow 36 h after PGF2α injection. Algorithms were developed by adjusting the vulva temperature (for ambient temperature and humidity) of individual animals during each observation period and were expressed as a deviation (D, oC) from the baseline temperature. Out of the 20 cows enrolled in this study 12 (60%) ovulated. An IRT oestrus alert was defined using different thresholds (D = 1oC, 1.25oC, and 1.5oC). Rates of detection accuracy and error rate depended upon the chosen threshold level. At a threshold D = 1oC, the highest percentage (92%, n = 11) of sensitivity and the lowest specificity (28%) was observed. On the other hand, D = 1.4oC resulted in sensitivity = 75%, specificity = 57% and positive predictive values = 69%. The mean (±SD) intervals between onset and end of IRT oestrus alert to ovulation were 30.7 ± 8.2 and 13.3 ± 7.7 h respectively. Ovulation occurred 24-48 h after the onset of the IRT oestrus alert for 8 out of the 11 ovulated cows (73%). Although the sensitivities of the IRT alert were higher than visual observation (67%) and oestrotect activation (67%), the specificities and positive predictive value were lower than these two aids (i.e. the IRT over-predicted the incidence of ovulation). Further studies are required with a larger sample size and sampling throughout different seasons to determine the true potential of IRT as a tool for ovulation prediction.

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2013 Spatially Enabled Livestock Management Symposium

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