Stable trials within SLU Gigacow

Stable trials are used to investigate new findings and hypotheses under conditions that are as close to practice as possible. SLU's cow data infrastructure, Gigacow, is part of the Nordic Testbed Network and continuously collects data from the privately owned dairy herds that are part of the network.

Through barn trials, it is possible to test new technologies and methods while SLU Gigacow evaluates how new data sources can contribute to profitable and sustainable agriculture. A dairy cow lives for a long time and it is therefore valuable to collect data over long time series before, during and after the practical trials conducted. By building this holistic picture with daily data collection from dairy farms, we can better plan trials, quickly identify farms where trials can be conducted and facilitate the trials.

What happens when there is an experiment?

The trials that SLU Gigacow supports can either be research motivated or part of innovation support activities. For research-motivated barn trials, we work with researchers and the industry to secure funding for projects. SLU Gigacow can then take responsibility for building the technical infrastructure required for data collection and contribute to knowledge transfer while researchers utilize the data in several research projects.

Thanks to funding from the Knowledge Hub for Agricultural Digitization, SLU Gigacow also has the opportunity to facilitate a number of on-farm trials to support the development of new innovations and methods in agriculture.

If you are interested in using SLU Gigacow for research or farm trials, please contact our coordinator Tomas Klingström via our functional email gigacow@slu.se.

Examples of barn trials at SLU Gigacow

The Global Methane Genetics initiative is an international breeding effort to reduce methane gas emissions from ruminant animals. In Sweden, Dr. Elisenda Rius-Vilarrasa from Växa Sverige is leading the work where so-called sniffers are installed in milking robots to measure cross methane emissions and data is collected from the farms with the help of SLU Gigacow. Växa Sverige is leading the project, which is being carried out with funding from the Swedish Board of Agriculture, the Swedish Agricultural Research Foundation and the Global Methane Hub, as well as support for knowledge transfer via the Knowledge Hub for Agricultural Digitization.

From sensitive to robust athlete is a research project to evaluate whether genomic selection can help dairy cows face warmer temperatures. SLU Gigacow assists with data collection of weather data, code data and the possibility to test temperature logs on farms to measure weather impact both inside and outside. In this way, in addition to the breeding issue, the project can contribute to improved stable environments and new methods for measuring heat stress. The research project is funded by Formas and additional funds for stable experiments have been provided by the Knowledge Hub for Agricultural Digitization and the European Partnership on Animal Health and Welfare.

Anicare activity meters are developed to follow game and reindeer over large distances. SLU Gigacow has, through the Nordic Testbed Network, facilitated barn trials with Anicare's meters on dairy cows in a project funded by EIT Food and assists with data collection so that Anicare Oy can adapt the sensor for grazing cows. Read more about the trial here (link will be posted later).

Cow Social Interaction and Desease Transmission is a project conducted under the leadership of Professor Lars Rönnegård (SLU/Högskolan i dalarna). The experiment used, among other things, positioning data from dairy farms. To prepare for future research in this area, the Beijer Laboratory for Animal Research and the research group for quantitative genetics have co-financed the installation of Växa Control's system for positioning on a dairy farm in SLU Gigacow. 

Advanced light analysis in agricultural environments is a collaboration between Agtech Sweden, the non-profit association Ljusinitiativet, Vreta utbildningscentrum and researchers at SLU, Stockholm University and Linköping University. The light measurements contribute to an increased understanding of the dimension of light in good stable environments. The work is also important to better prepare future work on installing video equipment for the development of AI models for monitoring in the stable environment. Work is currently underway to plan and organize a Deeptech initiative at SLU to systematically collect video data within SLU Gigacow and make this available for various research projects where automated video analysis is used.