GrASTech - Precision Livestock Farming (PLF) Technologies to Reduce Greenhouse Gas (GHG) Emissions Intensity of Pasture-based Cattle Systems

Aim of the project:

To develop an animal-mounted sensor platform for methane measurement in grazing cattle and validate using established techniques (Respiration chambers, LaserGun and Greenfeed).

Introduction

To what extent can we use sensors and precision farming techniques to determine the methane emission from grazing cows, and then reduce it by management interventions? Those are the two big questions of the Grastech research project.

In the highly controllable (feed and management) conditions of a modern dairy herd, methane emissions have already been determined and some climate strategies investigated. Under grazing, however, the parameters vary. Still, the researchers wish to develop solutions for the climate impact of dairy farming. The bovine enteric emissions in Flanders must be reduced by 2030 by 19% reduction compared to 2005, in France by 20% by 2025 compared to 2015 and in Scotland by 9% by 2032 compared to 2018).

What: Herd productivity, which has a major impact on GHG emission intensity (per kg product), will be improved using a wide range of precision livestock farming technologies. All strategies will be evaluated using life cycle assessment in order to find net positive effects. GrASTech will provide important advances towards achieving the challenging goals of the climate action plan.

Why: European cattle farmers are facing increased demand for pasture-based and environmentally friendly products. Although feeding strategies to reduce Greenhouse Gas (GHG) emissions have been studied intensively, strategies for grazing systems are under-researched. The lack of easy-to-implement technologies for methane measurement with grazing cattle complicates the necessary large-scale studies.

Where: The research is been done in five leading research institutes located in Belgium, UK, and France.

Main project activities:

This project investigates the possibilities of grazing management within the agreements for “pasture milk”. The aim is to choose the optimal number of grazing hours and to adjust the ration in the barn, possibly with use of methane-reducing feed additives. In addition, there is a strong focus on the selection and implementation of existing and recently developed precision livestock farming technologies with the aim of improving production efficiency in those systems.

Concept and approach:

In December 2019 GrASTech partners started exploring to what extent precision livestock farming (PLF) technologies can be used to map methane emissions of grazing cows and reduce those emissions by management interventions.

University of Strathclyde is developing a non-intrusive methane concentration measurement system for grazing ruminants. SRUC is reviewing literature to assess how PLF technologies impact technical efficiency/productivity of housed animals and how this can be translated to grazing animals. Implications on methane outputs of these PLF technologies are being investigated and modelled. ILVO has ran its first grazing experiment in which enteric methane emission related to three feeding/grazing strategies wascompared and is analysing the first results. At INRAE, unfortunately, the grazing experiment had to be postponed due to COVID-19 restrictions. However, all methodologies and protocols are in place to be picked up next spring. At IDELE, a laser methane detector is being validated to ensure accurate measurements in grazing situations later on.

Project consortium:

Coordinated by: Dr. Leen Vandaele, Institute for Agricultural and Fisheries Research, ILVO, (Belgium)

  • FRANCE: Institut de l'elevage, IDELE, French National Institute for Agricultural Research and the Environment, INRAE
  • UK: Dairy Research Centre, SRUC and Department of Electronic and Electrical Engineering, Strath

More information: 

  • The GrASTech project started on 1 Januari 2020 and runs until 31 December 2022. 
  • Twitter: #GrASTech

Presentations and posters:

Research articles: