The use of behavioural biometrics, 3D kinematics and infrared thermography to assess affective and biological states in livestock

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As a result of the move away from the Five Freedoms paradigm of welfare assessment, towards a Five Domains model, the field of ethology is challenged to develop valid, reliable, and feasible ways to evaluate a variety of affects experienced by animals. Livestock species are at the forefront of this development as an integral part of the global food system. Since 2016, studies have identified changes in facial action units through the use of grimace scales in animals to measure negative affects, however there are limitations to the use of grimace scales in livestock. For example, individual expression and magnitude of pain can vary between animals, which grimace scales have difficulty differentiating. For these and other reasons, grimace scales for pain assessment in some livestock species, such as pigs, have not been fully validated. My research program is unique as the only program investigating micro-behaviour biometrics in livestock as part of automated technology platforms for use in precision agriculture. The overall aim of my research program has been to better understand how qualitative and quantitative differences in livestock micro-behaviour biometrics can be incorporated into automated systems and combined with machine learning for a variety of research and on-farm applications. In addition to the use of automated infrared thermography platforms to detect micro-behaviour biometrics alongside thermal profiles as part of early disease detection, my research has also used 3D kinematic motion capture technology to better understand the biomechanics of micro-behaviours. For example, the kinematics of micro-behaviours exhibited during estrus, which confirmed micro-movements are better at detecting changes in biological functioning. However, an area that has not been explored is the use of micro-behaviour biometrics to assess affective states and facial expressions in livestock. The focus of the proposed research is to answer an emerging question in animal welfare: Are micro-facial expressions and other micro-behaviour biometrics an epiphenomenon for pain or other affective states in livestock? If so, what are the underlying physiological mechanisms? The short-term objectives of this research are: 1) to characterize the micro-facial expressions associated with positive and negative affective states, and 2) to ascertain the physiological mechanisms (pathway) underlying micro-facial expressions as affective biometrics using 3D kinematic analysis, thermal imaging, and genomic analysis. The proposed research will clarify the role physiology plays in driving micro-facial expressions in response to different types of stimuli experienced by pigs and not only strives to find a solution to current problems with the use of pain grimace scales, but also suggests it can be done using automation integrating machine learning as the Canadian agriculture sector moves towards greater inclusion of precision systems.