Activities per year
Project Details
Description
The overall objective of this project is to develop an on-farm system for the pig industry which provides a decision-support system to farmers, vets and advisors based on real-time monitoring of pig growth, health and welfare using 3D cameras to monitor growth and behaviour, and sensors to measure gases such as VOCs.
SRUC scientists' role in the project is to plan and run farm studies to collect VOCs and 3D behavioural data at our research farm and also at commercial farms (Wayland / Cranswick).
Also, we will advise on analysis and interpretation of study data, particularly the association between behaviour and health. Innovent's machine vision system uses 3D cameras to detect pigs and determine their weight, and monitor behavioural metrics such as activity, location inthe pen (feeder and drinker visits), group clustering, various body postures and appendage (e.g. tail) postures. SRUC's role will be to bring our knowledge of animal production and behaviour to aid interpretation of any changes in growth rate and behavioural metrics which may correspond to disturbances in behaviour resulting from ill health or other undesirable behaviour (such as aggression, tail, ear or flank biting).
We will collaborate in the data analysis and interpretation with the University of Surrey (vHive), Zoetis vets and other project partners. SRUC's research farm will be used to collect 3D camera, gas sample, and gas sensor data under controlled conditions. Pigs between 4 and 12 weeks of age will be used. Healthy pigs will be compared with:
1) Pigs undergoing various stressors which mimic production changes and are expected to stimulate behavioural changes(adding enrichment items, removing bedding/enrichment, overnight fasting)
2) Pigs undergoing vaccine challenges (Lawsonia and Circovirus) these are expected to create an immune response, modelling a minor health challenge. Vaccinations are known to induce temporary 'sickness' behaviour and are alsoexpected to affect VOCs.
SRUC scientists' role in the project is to plan and run farm studies to collect VOCs and 3D behavioural data at our research farm and also at commercial farms (Wayland / Cranswick).
Also, we will advise on analysis and interpretation of study data, particularly the association between behaviour and health. Innovent's machine vision system uses 3D cameras to detect pigs and determine their weight, and monitor behavioural metrics such as activity, location inthe pen (feeder and drinker visits), group clustering, various body postures and appendage (e.g. tail) postures. SRUC's role will be to bring our knowledge of animal production and behaviour to aid interpretation of any changes in growth rate and behavioural metrics which may correspond to disturbances in behaviour resulting from ill health or other undesirable behaviour (such as aggression, tail, ear or flank biting).
We will collaborate in the data analysis and interpretation with the University of Surrey (vHive), Zoetis vets and other project partners. SRUC's research farm will be used to collect 3D camera, gas sample, and gas sensor data under controlled conditions. Pigs between 4 and 12 weeks of age will be used. Healthy pigs will be compared with:
1) Pigs undergoing various stressors which mimic production changes and are expected to stimulate behavioural changes(adding enrichment items, removing bedding/enrichment, overnight fasting)
2) Pigs undergoing vaccine challenges (Lawsonia and Circovirus) these are expected to create an immune response, modelling a minor health challenge. Vaccinations are known to induce temporary 'sickness' behaviour and are alsoexpected to affect VOCs.
Short title | Farm Sense |
---|---|
Status | Finished |
Effective start/end date | 1/06/22 → 31/05/24 |
Funding
- Innovate UK
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
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Activities
- 1 Invited talk
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Large animal automated behaviour scoring using machine vision and 3D cameras
D'Eath, R. (Speaker)
19 Sept 2022Activity: Talk, evidence or presentation types › Invited talk