AgriSearch are co-funding an exciting new PhD project which is seeking to understand dairy cow behaviour to improve production and welfare in robotic milking systems. 

This project will be supervised by Dr Gareth Arnott of Queen’s University School of Biological Sciences, Dr Stephanie Buijs of the Agri-Food and Biosciences Institute, Jason Rankin of AgriSearch, and Dr Deborah McConnell of the Agri-Food and Biosciences Institute.

Increasing herd sizes and reductions in the agricultural workforce have increased the pressure on labour both nationally and internationally. In response there has been increasing uptake of robotic milking systems making use of state-of-the-art technology, whereby a cow voluntarily visits an automatic milking machine. This technology has the potential to improve dairy cow welfare and enhance farm labour efficiency. However, despite the recent uptake of robotic milking in NI, with estimates that 10% of the national herd is milked by robots (with numbers expected to continue increasing), there is little independent information regarding the management of these systems. In particular, there is a lack of knowledge regarding cow behaviour and milking frequency with robotic milking, with some cows not transitioning well to these systems and requiring prolonged training. This can have negative effects on cow welfare and production. The success of robotic milking depends on the cows’ voluntary behaviour, yet this remains to be fully understood. Understanding and influencing this behaviour is key to the successful implementation of robotic milking.

Dr Gareth Arnott, IGFS, Queen's University Belfast

Objectives:

The overall project aim is to improve cow welfare and productivity in robotic milking systems by optimizing the visit frequency to the robot.

More specifically using three experiments, this project will address the following five objectives:

  1. Assess the effects of changes in concentrate feed allocation on dairy cow behaviour and welfare in robotic milking systems.
  2. Use relevant learning theory to investigate training strategies to increase regular voluntary milking visits to the robot.
  3. Investigate training strategies to deter ‘loitering’ (cows remaining in the robot area unnecessarily thereby blocking other cows’ access).
  4. Evaluate strategies to encourage voluntary visits in animals that are lame and/or have a low social ranking.
  5. Evaluate the effect of the developed strategies on dairy cow welfare.

Queen’s University are currently recruiting a PhD student to undertake this project.  Further details can be found here.

The closing date for applications is Thursday 30th April 2020.