Towards a Sustainable Meat Production with Precision Livestock Farming

In future years, modern farmers will be under greater pressure to care for a large number of animals in order to remain economically viable. There is a growing global awareness of welfare conditions in animal production and a tendency towards more intensive production, resulting in a need for better genetics and a more precise way to monitor them. The challenge and the success of intensive farming will lie in how precisely we can steer the animals towards their genetic potential. Sensors have the potential to replace the eyes, ears and nose of the farmer by continuously assessing different key indicators throughout the production process, 24 hours a day and 7 days a week. The continuous automated monitoring of varying needs of individual living farm animals at every moment and anywhere is called Precision Livestock Farming (PLF). The aim of this paper is to describe how PLF-systems are used within the EU-PLF project to work towards an automated assessment of sustainability on farm level, by continuous monitoring of animal behaviour. The roadmap towards a sustainable meat production, viewed from a technologist’s point of view, is described hereafter in four steps. This phase comprises an implementation of PLF tools, where the basic inputs are measured and monitored in function of time. In a next step, a more complete control of the production process is pursued. In this step, the animal is used as a sensor to gather evidence on the animals’ bio response to its environment and management by the farmer. The final step towards the management of the meat production is through the monitoring of emissions and resource efficiency. PLF-technology and continuous monitoring of animal bio responses will improve the understanding of the production process. This will allow the farmer to manage his process by exception. Production data collection and sharing will enhance the transparency throughout the production chain and help the consumer make educated decisions.