DairyCare ‘blueprint for action’: husbandry for wellbeing

Author:

Knight Christopher H.

Abstract

AbstractKeep calm and carry on’ was a wartime message to the British public that has achieved renewed fame in the last few years. The strategy was simple: in times of extreme difficulty a cool head combined with stoicism is an appropriate response to ensure a successful outcome. The latest major challenge to society (COVID-19) met with a very different response, and only history will reveal whether ‘Stay home and worry’ will be equally effective. In devising blueprints or strategies it is extremely important to have a clear idea of what you are trying to achieve, whether it be maintaining world freedom or stopping a pandemic. In the case of livestock agriculture, it is helping to feed a rapidly growing global population in harmony with the needs of current and future generations. I hope that I have stated this clearly, and calmly. If so, I ask you to picture a scene. We are on a Calm Farm. Dairy animals go about their daily lives contented, unhurried and focused on the simple feeding and socialising activities that are so important to them. Unstressed, their productive capacities and abilities to avoid and, when necessary, cope with physiological and pathological challenges are maximised. They are not alone: the exact same characteristics also apply to the farmer and husbandry staff that we meet. How is this calm farming approach relevant to the aspirations we had when we established the EU COST Action DairyCare? Our objective was to harness the power of computing technologies to assist our management of dairy livestock. A simple rearrangement leads us to Computing Assisted Livestock Management, CALM. In this short Research Reflection I shall assess how far we have come towards the achievement of sensible goals related to technological assessment of dairy animal wellbeing, and speculate on what more things both can and need to be done to finish the job. It is a personal account. DairyCare was a major collaboration involving several hundred active researchers. To involve them all would be impossible, and I do not pretend to speak for them all. As will become evident, the wide skills base that was assembled was so successful in its primary objectives that different skills, chiefly in economics, are now needed to exploit all of the technological advance that has been achieved. DairyCare succeeded in a second direction. Whilst the focus was technology development, by assembling a large cohort of biologists with animal welfare interests, it soon became apparent that technology should run alongside and help to enable improved management practices. This Special Issue is, therefore, in two sections. The first is dedicated to technology development and the second to a novel management practice that has the potential to significantly improve the wellbeing of cows and calves: cow-calf contact rearing. That section is introduced by my DairyCare colleague, Sigrid Agenäs.

Publisher

Cambridge University Press (CUP)

Subject

Animal Science and Zoology,General Medicine,Food Science

Reference30 articles.

1. Review: Sensor techniques in ruminants: more than fitness trackers

2. Afimilk (2020) Cow monitoring solutions. https://www.afimilk.com/cow-monitoring/ (Accessed May 2020).

3. NMR (2020) Automated heat detection and health monitoring. https://www.nmr.co.uk/health/heat-detection-and-health-monitoring (Accessed May 2020).

4. Recent advancement in biosensors technology for animal and livestock health management;Neethirajan;Biosensors and Bioelectronics,2017

5. Systems for evaluation of welfare on dairy farms;Krueger;Journal of Dairy Research,2020

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