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Abstract: Current Canadian estrus detection rates (< 40%) need to increase to reach optimal reproduction management and economic dairy production sustainability. Therefore, the general objectives of this thesis were to evaluate the use of infrared thermography (IRT) and behaviour biometrics as an estrus detection method and compare its accuracy levels with other estrus detection aids. The initial study was designed to characterize IRT and behaviour biometrics of pregnant (Control) and cyclic synchronized (Synch) Holstein cows at 45 days in milk 5 min before, during and 5 min after milking times and to evaluate the accuracy of IRT and behaviour biometrics as estrus indicators in cyclic multiparous cows housed in a tie-stall system. Compared to baseline (i.e. luteal phase) measures, 7 different anatomical locations had increased infrared temperatures 48 and 24 h before ovulation. Additionally, behaviour biometrics change between treatments, specifically the stepping activity (treading) per day. However, Tail movement was the only behaviour that increased in frequency of movement as ovulation approached in Synch cows. Measuring thermal outputs, tail and treading behaviour can differentiate between estrus and non-estrus cows and differed between Control and Synch groups in multiparous cows. The second study’s objective was to evaluate the combined use of IRT and behaviour biometrics as an estrus alert in naturally cycling primiparous dairy cows in a tie-stall system. Radiated temperature of the vulva increased 2 days before ovulation, and changes in frequency of small hip movements 1 day before ovulation improved the accuracy of estrus detection compared to individual thermal and behavioural biometrics. Using multiple estrus detection methods reduces the error rate by increasing the specificity (Sp; true negatives) and reducing false positive alerts. The third study aimed to characterize the biomechanics of pelvic movements, foot strikes, and tail movement using 3D-kinematics analysis in naturally cycling primiparous cows in tie-stall housed cows during the proestrus–ovulation period. In addition, changes in pelvic, foot strikes, and tail movement were observed before ovulation and during the luteal phase. Pelvic, foot and tail movements were useful indicators of ovulation 48 to 24 hours when cows are housed in confinement, such as tie-stalls, that prevent locomotory movement. The fourth study’s objectives were to develop a fully automated IRT and behaviour biometrics platform on a free-stall commercial dairy herd to demonstrate the application of estrus detection on-farm. In addition, to assess the IRT platform accuracy with other estrus detection methods already used in voluntary milking systems such as in-line milk progesterone (P4) and accelerometer sensors tags. Skin temperature changes were associated with a decreased milk P4 concentration at d 0 compared to d -14 and d 4. The occurrence of tail movement per IRT frame was higher at d 0 than d -14 and d 4. The sensitivity (Se) of the IRT platform was compared with the accelerometer sensors at the different time windows, Same-day, ±24 h, ±48 h, and ±72 h. Estrus alerts achieved the highest IRT accuracy in a ±48 h window relative to in-line milk progesterone estrus alerts. The accuracy of the IRT platform resulted in higher estrus detection rates compared to accelerometers but lower compared to in-line milk P4 estrus alerts. The fifth study was designed to identify the partial budget business analysis of IRT, Visual observation, and Ovsynch as breeding alternatives in Alberta dairy production. The secondary objective was to determine the farm profit of different estrus detection rates and evaluate IRT's prospective performance compared to Visual observation and Ovsynch as an estrus detection aid. The most cost-efficient estrus detection method was Visual observation followed by IRT, however, Ovsynch had higher economic returns in feeding cost per conception service. The return to equity increased due to the low production cost, specifically the feeding cost of an efficient calving interval. Further, the more significant return to equity was directly associated with the highest accuracy of estrus detection using IRT. This thesis concludes that the practical implementation of infrared thermography and behaviour biometrics to detect estrus in dairy cows is possible. The development of an infrared thermography platform provides valuable fundamental information to commercialize a novel method of estrus detection and to provide producers with an additional decision-making tool to optimize reproductive management in the context of estrus detection.