1:00 pm - 2:00 pm
A graduate exam seminar is a presentation of the student’s final research project for their degree.
This is an ALES PhD Final Exam Seminar by Hector Perez Marquez. This seminar is open to the general public to attend.
Meeting ID: 967 8049 3101
Thesis Topic: The Use of Infrared Thermography and Behavioural Biometrics for Estrus Detection in Dairy Cattle
PhD with Dr. Clover Bench
Seminar Abstract: Current Canadian estrus detection rates (< 50 %) need to increase in order to maintain the sustainability and social acceptance by using non-invasive technologies. Therefore, the general objective of this thesis dissertation was to evaluate the use of infrared thermography (IRT) and behaviour biometrics as an estrus detection method and to evaluate the use of infrared thermography and behaviour biometrics to different milking systems and compare accuracy levels with other estrus detection aids.
The initial study was designed to characterize IRT and behaviour biometrics of pregnant (Control) and cyclic (Synch) Holstein cows around milking times (AM and PM milking) and to evaluate the accuracy of IRT and behaviour biometrics as estrus indicators in cyclic multiparous cows in a tie-stall housing. The overall radiated temperature was higher in Synch compared to Control cows. Seven different anatomical locations (Eye, Cheek, Neck, Rump, Flank, Wither, and Vulva are) increased their radiated temperature outputs (+0.30 to 1.2 °C) at 48 and 24 h before ovulation (expected estrus period) was confirmed compared with the luteal phase. Additionally, behaviour biometrics change between treatments (i.e. Control – Synch) specifically the treading activity per day. However, Tail movement was the only behaviour that changed the frequency of movement as ovulation approach in Synch cows. Measuring thermal outputs, tail and treading behaviour can differentiate between pregnant and cyclic cows using non-invasive estrus alerts in multiparous cows in a tie-stall housing.
The second study’s objective was to evaluate the combine use of IRT and behaviour biometrics as estrus alert for naturally cycling primiparous dairy cows in a tie-stall system. The significant increased radiated temperature from vulva 2 days before ovulation and the increase in frequency of small hip movements one day prior ovulation improve the accuracy of estrus detection compare to individual thermal and behavioral biometrics in primiparous cows during milking in a tie-stall housing. Using multiple estrus detection methods reduce the error rate by increasing the specificity (true negatives) and reducing the false positive alerts (26.6 compared to single parameters; 3.87 diagnostic odds ratio [DOR]).
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 at intensive housing systems (tie-stalls) during the proestrus – ovulation period. In addition, the pelvic, foot, and tail movements were evaluated as potential estrus alerts. Changes (Events/5 min) in pelvic (20.26 ± 13.64), foot strikes (9.86 ± 1.98), and tail movement (7.30 ± 3.62) were observed before ovulation was confirmed in contrast with the luteal phase (pelvic; 3.71 ± 2.52, foot strikes; 14.44 ± 2.78, and tail movement; 14.57 ± 7.23). The pelvic, foot, and tail movement resulted useful as indicators of ovulation 48 to 24 hours in advance in absence of large locomotory movements in a tie-stall housing.
The fourth study was designed to identify the partial budget business analysis of IRT, visual observation, and ovsynch, as a breeding alternatives in Alberta dairy production. The secondary objective was to determine the farm profit of different estrus detection rates and to evaluate the prospective performance of IRT compared to visual observation and ovsynch as an estrus detection aid. The most efficient estrus detection cost was visual observation ($115.78 CAD) followed by IRT ($127.69 CAD), and ovsynch ($138.99 CAD). The return to equity increase due to the low production cost specifically the feeding cost by reducing the calving interval. Further, the higher cost benefit was directly associated to the highest accuracy of estrus detection (60% estrus detection rate for IRT and visual observation, 65% conception rate for ovsynch).
The fifth study objectives were to develop a fully automated IRT and behaviour biometrics estrus detection platform on a commercial dairy herd to demonstrate on-farm proof of concept and to assess its estrus alerts accuracy with estrus detection methods already used in voluntary milking systems such as in-line milk progesterone (P4) and 3 axis accelerometers sensors tags. Skin temperature changes were associated with decrease in milk P4 concentrations at d 0 (estrus alert day) compared to and d 4. The occurrence of tail movement per IRT frame was higher at d 0 compared to d -14 and d 4. The sensitivity of IRT platform was compared with the accelerometer sensors at ±24 h, ±48 h, and ±72 h time-windows around estrus. The highest IRT accuracy was achieved by estrus alerts in a ±48 h window relative to HN estrus alerts. The accuracy of the IRT platform (58%) resulted in higher estrus detection rates compared to accelerometers (44%) but lower compared to in-line milk P4 estrus alerts (study standard).
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 additional decision-making tool to optimize reproductive management in the context of estrus detection.