BeBoP aims to better and quicker assess the behaviour in fattening system and to make welfare assessment more feasible (practical and economic) in fattening farms. It's a project which is developping Artificial Inteligence technologies to analyse the behaviour of bulls in fattening systems in order to better calculated behavioural indicators of welfare. BeBoP is also developping a specific simplified protocol to assess the welfare of fattening bulls to make the welfare evaluation feasible in all French fattening farms. BeBoP has already produced a factsheet to explain to farmers and farm technicians the behaviour of cattle and behavioural adaptation in fattening units.

Bennefits of the project are the improvement and facilitation for the evaluation of welfare. A pilot of the automated video analysis is currently implemented in 2 experimental farms. (Simplified welfare protocol : implementation in 10 commercial farms to begin in 2022).

The challenge of artificial intelligence for routine video analysis was to correctly identify bulls behaviour in fattening systems (high proximity of very similar cattle: same colour and body size). Stress behaviour (steretypies) identification is the main challenge and the current bottleneck. The seond part of the project aims to simplify the welfare assessment: the challenge is now to calibrate easy to observe/to score indicators without any loss of scientific relevance.

Video analysis is carried on by a specialised company which has long time expertise in animal video analysis (fish automated counting, automated video control analysis in cattle slaughterhouses). The system they develop for BeBoP (still as pilot) is a cost efficient system, base on on-farm video cameras to be used with several consecutive bull groups. Video setting of the cameras needs special expertise in fattening farms to insure the good visibility of all animals. Automated video analysis needs good internet connection and rather recent/efficient computer hardware equipement. 

This research innovation has an impact on:

  • Socio-economic resilience: Welfare assessment contributes to improve the welfare of bulls at fattening, and then ulitmately contributes to improve the social image of cattle fattening.
  • Animal health and welfare: Automated video analysis will improve the evaluation of welfare of bulls at fattening. This will help farmers to improve farming practices and housing conditions of bulls and ultimately to prevent or to limit health troubles (respiratory diseases and lameness). Also, behaviour is a useful indicator of heath trouble, especially when combined with temperature. So this video system may also contribute to quicker and better identify sick animals, and make it possible to treat them as early as possible, and then to prevent for the dissemination of the disease in the whole group. 
  • Product efficiency and meat quality: Automated video analysis of the behaviour of young bulls could help the fermers to better understand feeding efficiency based on individual feeding activity.